The Austrian node of the Natural Resources Satellite Remote Sensing Cloud Service Platform was established in 2016 through a cooperation agreement between the Land Satellite Remote Sensing Application Center(LASAC),Mi...The Austrian node of the Natural Resources Satellite Remote Sensing Cloud Service Platform was established in 2016 through a cooperation agreement between the Land Satellite Remote Sensing Application Center(LASAC),Ministry of Natural Resources of the Peoples Republic of China and the University of Vienna,Austria.Under this agreement panchromatic and multi-spectral data of the Chinese ZY-3 satellite are pushed to the server at the University of Vienna for use in education and research.So far,nearly 500 GB of data have been uploaded to the server.This technical note briefly introduces the ZY-3 system and illustrates the implementation of the agreement by the first China-Sat Workshop and several case studies.Some of them are already completed,others are still ongoing.They include a geometric accuracy validation of ZY-3 data,an animated visualization of image quick views on a spherical display to demonstrate the time series of the image coverage for Austria and Laos,and the use of ZY-3 data to study the spread of bark beetle in the province of Lower Austria.An accuracy study of DTMs from ZY-3 stereo data,as well as a land cover analysis and comparison of Austria with ZY-3 and other sensors are still ongoing.展开更多
The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and...The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.展开更多
With the accelerating effects of global warming,changes in Arctic sea ice extent(SIE)have become a focal point of research.However,due to its spatial heterogeneity and the complexity of its evolution,understanding the...With the accelerating effects of global warming,changes in Arctic sea ice extent(SIE)have become a focal point of research.However,due to its spatial heterogeneity and the complexity of its evolution,understanding the mechanisms driving sea ice remains a significant challenge.This study systematically examines the spatiotemporal variability of Arctic SIE and its coupling mechanisms with atmospheric-oceanic dynamic processes based on passive microwave satellite observations and atmospheric reanalysis datasets.The findings show that during the period from 1979 to 2022(44 a),the SIE exhibited an annual change rate of(−4.36±0.30)×10^(4)km^(2).The most significant decline was observed in summer[(−7.39±0.48)×10^(4)km^(2)/a].In contrast,the decrease in winter sea ice concentration(SIC)was primarily observed in the Barents Sea and Kara Sea.Meanwhile,persistent SIC retreat was observed across most of the Arctic during spring,summer and autumn.To quantify the contributions of environmental factors,the study employs multiple approaches,which reveal that sea surface temperature is the most influential factor.Furthermore,meteorological statistical methods are used to investigate how climate patterns regulate SIC by influencing Arctic atmospheric circulation.These findings highlight the intricate interactions among Arctic atmosphere,ocean,SIE and climate patterns,providing a theoretical framework and scientific basis for understanding the evolution of SIE.展开更多
China has implemented large-scale hydraulic engineering projects in arid regions where water resources are severely scarce to efficiently maximize limited water resources for production and domestic needs.The processe...China has implemented large-scale hydraulic engineering projects in arid regions where water resources are severely scarce to efficiently maximize limited water resources for production and domestic needs.The processes and consequences of how the change of hydrological factors affects vegetation distribution remain unclear.This study employed multi-source remote sensing data to investigate the impact of hydrological factors on vegetation distribution in the Shiyang River Basin(SRB)in the arid region in Northwestern China.The results indicate that:(1)The NDVI values in the SRB showed a fluctuating upward trend of(0.0014/yr),with vegetation increase occurring in 62.71%of the area while vegetation degradation was observed in only 6.44%of the area.(2)The Surface Water Storage Anomaly(SWSA)shows an increasing trend of(0.112 mm/month),while Terrestrial Water Storage Anomaly(TWSA)and Groundwater Storage Anomaly(GWSA)exhibit significant declines at rates of-0.124 mm/month and-0.236 mm/month,respectively.(3)Vegetation growth on agricultural land and in planted forests has shown significant growth,in contrast to the general degradation of natural vegetation that is dependent on groundwater.In addition,surface water inputs directly catalyze vegetation growth dynamics.However,the complex mechanisms linking vegetation increase and decreasing terrestrial water reserves in arid regions still need to be studied in depth.The potential negative ecological impacts that may result from the continuous decline of terrestrial and groundwater reserves should not be taken lightly.展开更多
Rapid building damage assessment following an earthquake is important for humanitarian relief and disaster emergency responses.In February 2023,two magnitude-7.8 earthquakes struck Turkey in quick succession,impacting...Rapid building damage assessment following an earthquake is important for humanitarian relief and disaster emergency responses.In February 2023,two magnitude-7.8 earthquakes struck Turkey in quick succession,impacting over 30 major cities across nearly 300 km.A quick and comprehensive understanding of the distribution of building damage is essential for e fficiently deploying rescue forces during critical rescue periods.This article presents the training of a two-stage convolutional neural network called BDANet that integrated image features captured before and after the disaster to evaluate the extent of building damage in Islahiye.Based on high-resolution remote sensing data from WorldView2,BDANet used predisaster imagery to extract building outlines;the image features before and after the disaster were then combined to conduct building damage assessment.We optimized these results to improve the accuracy of building edges and analyzed the damage to each building,and used population distribution information to estimate the population count and urgency of rescue at different disaster levels.The results indicate that the building area in the Islahiye region was 156.92 ha,with an affected area of 26.60 ha.Severely damaged buildings accounted for 15.67%of the total building area in the affected areas.WorldPop population distribution data indicated approximately 253,297,and 1,246 people in the collapsed,severely damaged,and lightly damaged areas,respectively.Accuracy verification showed that the BDANet model exhibited good performance in handling high-resolution images and can be used to directly assess building damage and provide rapid information for rescue operations in future disasters using model weights.展开更多
The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and ...The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and western China as a whole.This paper introduces the gravity center model used to analyze the spatial-temporal variation patterns of vegetation Net Primary Productivity(NPP)from 2000 to 2015,which were determined by the use of MOD17 A3 NPP products.Additionally,the dominant driving factors of the spatial–temporal changes of vegetation NPP of the Hengduan Mountain area were quantitatively determined with a geographical detector over 2000-2015.The results revealed that:(1)From 2000 to 2015,there was an increasing trend of vegetation NPP in the Hengduan mountain area.Throughout the whole study region,the vegetation NPP with a mean value of 611.37 gC·m^(-2)·a^(-1) indicated a decreasing trend from southeast to northwest in terms of spatial distribution.(2)The gravity centers of vegetation NPP in 2000-2015 were mainly concentrated in Zhongdian County.During the study period,the gravity center of vegetation NPP moved northward,which indicated that the increment and increasing rate of vegetation NPP in the northern parts were greater than that of the southern areas.(3)The vegetation NPP showed a moderately positive correlation with temperature,accumulated temperature(>10℃),and sunshine,while there was an overall negative relationship between NPP and precipitation.(4)The dominant factors and interactive dominant factors changed in different subregions over different segments of the study period.The dominant factors of most sub-regions in Hengduan mountain were natural factors,and the climate change factors played an increasingly greater role over the 16 years of the study period.展开更多
How to deal with geometric distortion is an open problem when using the massive amount of satellite images at a national or global scale, especially for multi-temporal image analysis. In this paper, an algorithm is pr...How to deal with geometric distortion is an open problem when using the massive amount of satellite images at a national or global scale, especially for multi-temporal image analysis. In this paper, an algorithm is proposed to automatically rectify the geometric distortion of time-series CCD multi- spectral data of small constellation for environmental and disaster mitigation （HJ-1A/B） which was launched by China in 2008. In this algorithm, the area-based matching method was used to automatically search tie points firstly, and then the polynomial function was introduced to correct the systematic errors caused by the satellite motion along the roll, pitch and yaw direction. The improved orthorectification method was finally used to correct pixel displacement caused by off-nadir viewing of topography, which are random errors in the images and cannot be corrected by the polynomial equation. Nine scenes of level 2 HJ CCD images from one path/row were taken as the warp images to test the algorithm. The test result showed that the overall accuracy of the proposed algorithm was within 2 pixels （the average residuals were 37.8 m, and standard deviations were 19.8 m）. The accuracies of 45.96% validation points （VPs） were within 1 pixel and 90.33% VPs were within 2 pixels. The discussion showed that three main factors including the distortion patterns of HJ CCD images, pereent of cloud cover and the varying altitude of the satellite orbit may affect the search of tie points and the accuracy of results. Although the influence of varying altitude of the satellite orbits is less than the other factors, it is noted that detailed satellite altitude information should be given in the future to get a more precise result. The proposed algorithm should be an efficient tool for the geo-correction of HJ CCD multi-spectral images.展开更多
Grassland fires results in carbon emissions,which directly affects the carbon cycle of ecosystems and the carbon balance.The grassland area of Inner Mongolia accounts for 22%of the total grassland area in China,and ma...Grassland fires results in carbon emissions,which directly affects the carbon cycle of ecosystems and the carbon balance.The grassland area of Inner Mongolia accounts for 22%of the total grassland area in China,and many fires occur in the area every year.However,there are few models for estimation of carbon emissions from grassland fires.Accurate estimation of direct carbon emissions from grassland fires is critical to quantifying the contribution of grassland fires to the regional balance of atmospheric carbon.In this study,the regression equations for aboveground biomass(AGB)of grassland in growing season and MODIS NDVI(Normalized Difference Vegetation Index)were established through field experiments,then AGB during Nov.–Apr.were retrieved based on that in Oct.and decline rate,finally surface fuel load was obtained for whole year.Based on controlled combustion experiments of different grassland types in Inner Mongolia,the carbon emission rate of grassland fires for each grassland type were determined,then carbon emission was estimated using proposed method and carbon emission rate.Results revealed that annual average surface fuel load of grasslands in Inner Mongolia during 2000–2016 was approximately 1.1978×1012 kg.The total area of grassland which was burned in the Inner Mongolia region over the 17-year period was 5298.75 km2,with the annual average area of 311.69 km2.The spatial distribution of grassland surface fuel loads is characterized by decreasing from northeast to southwest in Inner Mongolia.The total carbon emissions from grassland fires amounted to 2.24×107 kg with an annual average of 1.32×106 for the study area.The areas with most carbon emissions were mainly concentrated in Old Barag Banner and New Barag Right Banner and on the right side of the Oroqin Autonomous Banner.The spatial characteristics of carbon emission depend on the location of grassland fire,mainly in the northeast of Inner Mongolia include Hulunbuir City,Hinggan League,Xilin Gol League and Ulanqab City.The area and spatial location of grassland fires can directly affect the total amount and spatial distribution of carbon emissions.This study provides a reference for estimating carbon emissions from steppe fires.The model and framework for estimation of carbon emissions from grassland fires established can provide a reference value for estimation of carbon emissions from grassland fires in other regions.展开更多
The origin and movement of groundwater are the fundamental questions that address both the temporal and spatial aspects of ground water run and water supply related issues in hydrological systems.As groundwater flows ...The origin and movement of groundwater are the fundamental questions that address both the temporal and spatial aspects of ground water run and water supply related issues in hydrological systems.As groundwater flows through an aquifer,its composition and temperature may variation dependent on the aquifer condition through which it flows.Thus,hydrologic investigations can also provide useful information about the subsurface geology of a region.But because such studies investigate processes that follow under the Earth's shallow,obtaining the information necessary to answer these questions is not continuously easy.Springs,which discharge groundwater table directly,afford to study subsurface hydrogeological processes.The present study of estimation of aquifer factors such as transmissivity(T)and storativity(S)are vital for the evaluation of groundwater resources.There are several methods to estimate the accurate aquifer parameters(i.e.hydrograph analysis,pumping test,etc.).In initial days,these parameters are projected either by means of in-situ test or execution test on aquifer well samples carried in the laboratory.The simultaneous information on the hydraulic behavior of the well(borehole)that provides on this method,the reservoir and the reservoir boundaries,are important for efficient aquifer and well data management and analysis.The most common in-situ test is pumping test performed on wells,which involves the measurement of the fall and increase of groundwater level with respect to time.The alteration in groundwater level(drawdown/recovery)is caused due to pumping of water from the well.Theis(1935)was first to propose method to evaluate aquifer parameters from the pumping test on a bore well in a confined aquifer.It is essential to know the transmissivity(T=Kb,where b is the aquifer thickness;pumping flow rate,Q=TW(dh/dl)flow through an aquifer)and storativity(confined aquifer:S=bS_s,unconfined:S=S_y),for the characterization of the aquifer parameters in an unknown area so as to predict the rate of drawdown of the groundwater table/potentiometric surface throughout the pumping test of an aquifer.The determination of aquifer's parameters is an important basis for groundwater resources evaluation,numerical simulation,development and protection as well as scientific management.For determining aquifer's parameters,pumping test is a main method.A case study shows that these techniques have been fast speed and high correctness.The results of parameter's determination are optimized so that it has important applied value for scientific research and geology engineering preparation.展开更多
The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and i...The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.展开更多
Land surface emissivity is one of the important parameters in temperature inversion from thermal infrared remote sensing. Using MOD11C3 of Terra-MODIS L3 level products, spatio-temporal data sets of land surface emiss...Land surface emissivity is one of the important parameters in temperature inversion from thermal infrared remote sensing. Using MOD11C3 of Terra-MODIS L3 level products, spatio-temporal data sets of land surface emissivity in China for 10 years from 2001 to 2010 are obtained. The results show that the land surface emissivity in the northwest desert region is the lowest in China, with little seasonal variations. In contrast, there are significant seasonal variations in land surface emissivity in northeast China and northern Xinjiang, the Qinghai-Tibet Plateau, the Yangtze River Valley and the eastern and southern China. In winter, the land surface emissivity in the northeast China and northern Xinjiang is relatively high. The land surface emissivity of the Qinghai-Tibet Plateau region is maintained at low value from November to March, while it becomes higher in other months. The land surface emissivity of the Yangtze River Valley, eastern and southern China, and Sichuan Basin varies from July to October, and peaks in August. Land surface emissivity values could be divided into five levels low emissivity （0.6163-0.9638）, moderate-low emissivity （0.9639-0.9709）, moderate emissivity （0.9710-0.9724）, moderate-high emissivity （0.9725-0.9738）, and high emissivity （0.9739-0.9999）. The percentages of areas with low emissivity, moderate-low emissivity and moderate emissivity are, respectively, about 20%, 10% and 20%. The moderate-high emissivity region makes up 40%-50% of China＇s land surface area. The inter-annual variation of moderate-high emissivity region is also very clear, with two peaks （in spring and autumn） and two troughs （in summer and winter）. The inter-annual variation of the high emissivity region is very significant, with a peak in winter （10%）, while only 1% or 2% in other seasons. There is a clear association between the spatio-temporal distribution of China＇s land surface emissivity and temperature： the higher the emissivity, the lower the temperature, and vice versa. Emissivity is an inherent property of any object, but the precise value of its emissivity depends very much on its surrounding environmental factors.展开更多
Water resources are one of the key factors restricting the development of arid areas,and cloud water resources is an important part of water resources.The arid region of central Asia is the core region of the current ...Water resources are one of the key factors restricting the development of arid areas,and cloud water resources is an important part of water resources.The arid region of central Asia is the core region of the current national green silk road construction,and is the largest arid region in the world.Based on cloud cover data of ECMWF,the current study analyzed temporal and spatial characteristics of cloud properties in arid regions of Central Asia between 1980 and 2019.Our findings show that:(1)From the point of view of spatial distribution,total cloudiness in arid regions of Central Asia was low in the south and high in the north.The distribution of high cloud frequency and medium cloud frequency was higher in the south and lower in the north,while low cloud frequency distribution was low in the south and high in the north.(2)In terms of time,the variation of cloud cover and cloud type frequency had obvious seasonal characteristics.From winter to spring,cloud cover increased,and the change of cloud type frequency increased.From spring to summer,cloud cover continued to increase and the change of cloud type frequency increased further.Cloud cover began to decrease from summer to autumn,and the change of cloud type frequency also decreased.(3)Generally,average total cloud cover decreased in most of central Asia,and high and medium cloud cover increased while low cloud cover decreased.This study provides a reference for the rational development of cloud resources in the region.展开更多
The influence of the single photon laser altimeter range-gate width on the detection probability and ranging accuracy is discussed and analyzed,according to the LiDAR equation,single photon detection equation and the ...The influence of the single photon laser altimeter range-gate width on the detection probability and ranging accuracy is discussed and analyzed,according to the LiDAR equation,single photon detection equation and the Monte Carlo method to simulate the experiment.The simulated results show that the probability of detection is not affected by the range gate,while the probability of false alarm is relative to the gate width.When the gate width is 100 ns,the ranging accuracy can accord with the requirements of satellite laser altimeter.But when the range gate width exceeds 400 ns,ranging accuracy will decline sharply.The noise ratio will be more as long as the range gate to get larger,so the refined filtering algorithm during the data processing is important to extract the useful photons effectively.In order to ensure repeated observation of the same point for 25 times,we deduce the quantitative relation between the footprint size,footprint,and frequency repetition according to the parameters of ICESat-2.The related conclusions can provide some references for the design and the development of the domestic single photon laser altimetry satellite.展开更多
The determination of the calibration parameters of the gravity gradiometer play an important role in the GOCE gravity gradient data processing.In this paper,the temporal signals and outliers in the GOCE gravity gradie...The determination of the calibration parameters of the gravity gradiometer play an important role in the GOCE gravity gradient data processing.In this paper,the temporal signals and outliers in the GOCE gravity gradient observations are analyzed.Based on the different global gravity field models,the scale factors and biases are determined in all the components of GOCE gravity gradients.And then the accuracy of the calibration results is validated.The results indicated that the effect of the ocean tide is at mE magnitude in the measurement band,which is equivalent to the precision of the gravity gradiometer,while the effect of the non-tide temporal signals,such as terrestrial water is in the order of 10-4 E,is slightly less than that of the ocean tide.The outliers in all the gravity gradient components are larger than 0.2%.And after the calibration using global gravity field models except EGM96,the stability of scale factors in the V xx、V yy、V zz、V yz components reaches 10-4 magnitude,and the V xz component reaches 10-5 while that of the V xy component is about 10-2,which are in accordance with the accuracy differences of the gradient components.展开更多
With the improvements in the density and quality of satellite altimetry data,a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculat...With the improvements in the density and quality of satellite altimetry data,a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculated from long-time series multi-satellite altimeter data.Therefore,in this study,a method was proposed for determining marine gravity anomalies from a mean sea surface model.Taking the Gulf of Mexico(15°–32°N,80°–100°W)as the study area and using a removal-recovery method,the residual gridded deflections of the vertical(DOVs)are calculated by combining the mean sea surface,mean dynamic topography,and XGM2019e_2159 geoid,and then using the inverse Vening-Meinesz method to determine the residual marine gravity anomalies from the residual gridded DOVs.Finally,residual gravity anomalies are added to the XGM2019e_2159 gravity anomalies to derive marine gravity anomaly models.In this study,the marine gravity anomalies were estimated with mean sea surface models CNES_CLS15MSS,DTU21MSS,and SDUST2020MSS and the mean dynamic topography models CNES_CLS18MDT and DTU22MDT.The accuracy of the marine gravity anomalies derived by the mean sea surface model was assessed based on ship-borne gravity data.The results show that the difference between the gravity anomalies derived by DTU21MSS and CNES_CLS18MDT and those of the ship-borne gravity data is optimal.With an increase in the distance from the coast,the difference between the gravity anomalies derived by mean sea surface models and ship-borne gravity data gradually decreases.The accuracy of the difference between the gravity anomalies derived by mean sea surface models and those from ship-borne gravity data are optimal at a depth of 3–4 km.The accuracy of the gravity anomalies derived by the mean sea surface model is high.展开更多
Forest is the largest carbon reservoir and carbon absorber on earth.Thus,mapping forest cover change accurately is of great significance to achieving the global carbon neutrality goal.Accurate forest change informatio...Forest is the largest carbon reservoir and carbon absorber on earth.Thus,mapping forest cover change accurately is of great significance to achieving the global carbon neutrality goal.Accurate forest change information could be acquired by deep learning methods using high-resolution remote sensing images.However,deforestation detection based on deep learning on a large-scale region with high-resolution images required huge computational resources.Therefore,there was an urgent need for a fast and accurate deforestation detection model.In this study,we proposed an interesting but effective re-parameterization deforestation detection model,named RepDDNet.Unlike other existing models designed for deforestation detection,the main feature of RepDDNet was its decoupling feature,which means that it allowed the multi-branch structure in the training stages to be converted into a plain structure in the inference stage,thus the computation efficiency can be significantly improved in the inference stage while maintaining the accuracy unchanged.A large-scale experiment was carried out in Ankang city with 2-meter high-resolution remote sensing images(the total area of it was over 20,000 square kilometers),and the result indicated that the model computation efficiency could be improved by nearly 30%compared with the model without re-parameterization.Additionally,compared with other lightweight models,RepDDNet also displayed a trade-off between accuracy and computation efficiency.展开更多
Climate change is the dominant factor affecting the hydrological process,it is of great significance to simulate and predict its influence on water resources management,socio-economic activities,and sustainable develo...Climate change is the dominant factor affecting the hydrological process,it is of great significance to simulate and predict its influence on water resources management,socio-economic activities,and sustainable development in the future.In this paper,the Xiying River Basin was taken as the study area,China Atmospheric Assimilation Driven Data Set(CMADS)and observation data from the Jiutiaoling station were used to simulate runoff of the SWAT model and calibrate and verify model parameters.On this basis,runoff change of the basin under the future climate scenario of CMIP6 was predicted.Our research shows that:(1)The contribution rates of climate change and human activities to runoff increase of the Xiying River are 89.17%and 10.83%,respectively.Climate change is the most important factor affecting runoff change of the Xiying River.(2)In these three different emission scenarios of SSP1-2.6,SSP2-4.5 and SSP5-8.5 in CMIP6 climate model,the average temperature increased by0.61,1.09 and 1.74 C,respectively,in the Xiying River Basin from 2017 to 2050.Average precipitation increased by 14.36,66.88,and 142.73 mm,respectively,and runoff increased by 15,24,and 35 million m3,respectively.The effect of climate change on runoff will continue to deepen in the future.展开更多
Hydrological monitoring and seasonal forecasting is an active research field because of its potential applications in hydrological risk assessment,preparedness and mitigation.In recent decades,developments in ground a...Hydrological monitoring and seasonal forecasting is an active research field because of its potential applications in hydrological risk assessment,preparedness and mitigation.In recent decades,developments in ground and satellite measurements have made the hydrometeorological information readily available,and advances in information technology have facilitated the data analysis in a real-time manner.New progress in climate research and modeling has enabled the prediction of seasonal climate with reasonable accuracy and increased resolution.These emerging techniques and advances have enabled more timely acquisition of accurate hydrological fluxes and status,and earlier warning of extreme hydrological events such as droughts and floods.This paper gives current state-of-the-art understanding of the uncertainties in hydrological monitoring and forecasting,reviews the efforts and progress in operational hydrological monitoring system assisted by observations from various sources and experimental seasonal hydrological forecasting,and briefly introduces the current monitoring and forecasting practices in China.The grand challenges and perspectives for the near future are also discussed,including acquiring and extracting reliable information for monitoring and forecasting,predicting realistic hydrological fluxes and states in the river basin being significantly altered by human activity,and filling the gap between numerical models and the end user.We highlight the importance of understanding the needs of the operational water management and the priority to transfer research knowledge to decision-makers.展开更多
Landslides are destructive geohazards to people and infrastructure,resulting in hundreds of deaths and billions of dollars of damage every year.Therefore,mapping the rate of deformation of such geohazards and understa...Landslides are destructive geohazards to people and infrastructure,resulting in hundreds of deaths and billions of dollars of damage every year.Therefore,mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks.In this paper,the main outcomes relevant to the joint European Space Agency(ESA)and the Chinese Ministry of Science and Technology(MOST)Dragon-5 initiative cooperation project ID 59,339“Earth observation for seismic hazard assessment and landslide early warning system”are reported.The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks,detect potential landslides in wide regions,and demonstrate EO-based landslide early warning system over selected landslides.This work only focuses on the landslide hazard content of the project,and thus,in order to achieve these objectives,the following tasks were developed up to now:a)a procedure for phase unwrapping errors and tropospheric delay correction;b)an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements;c)the application of polarimetric SAR interferometry(PolInSAR)to increase the number and quality of monitoring points in landslide-prone areas;d)the semiautomatic mapping and preliminary classification of active displacement areas on wide regions;e)the modeling and identification of landslides in order to identify triggering factors or predict future displacements;and f)the application of an InSAR-based landslide early warning system on a selected site.The achieved results,which mainly focus on specific sensitive regions,provide essential assets for planning present and future scientific activities devoted to identifying,mapping,characterizing,monitoring and predicting landslides,as well as for the implementation of early warning systems.展开更多
Greenway is a green linear corridor connecting scenic spots, residential areas, nature reserves, road traffic, etc. Rational greenway route selection can not only attract tourists to increase the income of local villa...Greenway is a green linear corridor connecting scenic spots, residential areas, nature reserves, road traffic, etc. Rational greenway route selection can not only attract tourists to increase the income of local villages, but also arouse people’s awareness of the protection of traditional villages. This paper took Xingtai County, Hebei Province, China as an example to practice greenway route selection in the county territory. Eight factors were selected for greenway route planning, namely elevation, water body, mountain, ecological protection redline, cultural relics protection units, population density, road traffic network, and important transportation hub. These eight factors were assigned in the GIS platform, and the suitability evaluation system of each factor was constructed. The analytic hierarchy process (AHP) and entropy weight method were combined to calculate the weight of these eight factors. The raster calculator was used to weight and overlay the suitability evaluation system of each factor, and the comprehensive suitability evaluation map of greenway route selection was obtained. Based on an important transport hub, along with the water body and the road traffic, the final selection greenway route of traditional villages in Xingtai county was formed. The results of the research can provide a certain reference for the greenway route selection at the county scale.展开更多
基金This work was supported by the National Key R&D Program of China for Strategic International Cooperation in Science and Technology Innovation(Grant No.2016YFE0205300)as well as a grant under the Eurasia Pacific UNINET program of the Austrian Federal Ministry of Education,Science and Research to the University of Vienna(Grant No.EPU 32/2017).
文摘The Austrian node of the Natural Resources Satellite Remote Sensing Cloud Service Platform was established in 2016 through a cooperation agreement between the Land Satellite Remote Sensing Application Center(LASAC),Ministry of Natural Resources of the Peoples Republic of China and the University of Vienna,Austria.Under this agreement panchromatic and multi-spectral data of the Chinese ZY-3 satellite are pushed to the server at the University of Vienna for use in education and research.So far,nearly 500 GB of data have been uploaded to the server.This technical note briefly introduces the ZY-3 system and illustrates the implementation of the agreement by the first China-Sat Workshop and several case studies.Some of them are already completed,others are still ongoing.They include a geometric accuracy validation of ZY-3 data,an animated visualization of image quick views on a spherical display to demonstrate the time series of the image coverage for Austria and Laos,and the use of ZY-3 data to study the spread of bark beetle in the province of Lower Austria.An accuracy study of DTMs from ZY-3 stereo data,as well as a land cover analysis and comparison of Austria with ZY-3 and other sensors are still ongoing.
基金Under the auspices of National Natural Science Foundation of China(No.42201374,42071359)。
文摘The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.
基金The National Natural Science Foundation of China under contract Nos 42430101,42274006,42192535 and 42104084.
文摘With the accelerating effects of global warming,changes in Arctic sea ice extent(SIE)have become a focal point of research.However,due to its spatial heterogeneity and the complexity of its evolution,understanding the mechanisms driving sea ice remains a significant challenge.This study systematically examines the spatiotemporal variability of Arctic SIE and its coupling mechanisms with atmospheric-oceanic dynamic processes based on passive microwave satellite observations and atmospheric reanalysis datasets.The findings show that during the period from 1979 to 2022(44 a),the SIE exhibited an annual change rate of(−4.36±0.30)×10^(4)km^(2).The most significant decline was observed in summer[(−7.39±0.48)×10^(4)km^(2)/a].In contrast,the decrease in winter sea ice concentration(SIC)was primarily observed in the Barents Sea and Kara Sea.Meanwhile,persistent SIC retreat was observed across most of the Arctic during spring,summer and autumn.To quantify the contributions of environmental factors,the study employs multiple approaches,which reveal that sea surface temperature is the most influential factor.Furthermore,meteorological statistical methods are used to investigate how climate patterns regulate SIC by influencing Arctic atmospheric circulation.These findings highlight the intricate interactions among Arctic atmosphere,ocean,SIE and climate patterns,providing a theoretical framework and scientific basis for understanding the evolution of SIE.
基金financially supported by the National Natural Science Foundation of China(42371040,41971036)Key Natural Science Foundation of Gansu Province(23JRRA698)+2 种基金Key Research and Development Program of Gansu Province(22YF7NA122)Cultivation Program of Major key projects of Northwest Normal University(NWNU-LKZD-202302)Oasis Scientific Research achievements Breakthrough Action Plan Project of Northwest normal University(NWNU-LZKX-202303).
文摘China has implemented large-scale hydraulic engineering projects in arid regions where water resources are severely scarce to efficiently maximize limited water resources for production and domestic needs.The processes and consequences of how the change of hydrological factors affects vegetation distribution remain unclear.This study employed multi-source remote sensing data to investigate the impact of hydrological factors on vegetation distribution in the Shiyang River Basin(SRB)in the arid region in Northwestern China.The results indicate that:(1)The NDVI values in the SRB showed a fluctuating upward trend of(0.0014/yr),with vegetation increase occurring in 62.71%of the area while vegetation degradation was observed in only 6.44%of the area.(2)The Surface Water Storage Anomaly(SWSA)shows an increasing trend of(0.112 mm/month),while Terrestrial Water Storage Anomaly(TWSA)and Groundwater Storage Anomaly(GWSA)exhibit significant declines at rates of-0.124 mm/month and-0.236 mm/month,respectively.(3)Vegetation growth on agricultural land and in planted forests has shown significant growth,in contrast to the general degradation of natural vegetation that is dependent on groundwater.In addition,surface water inputs directly catalyze vegetation growth dynamics.However,the complex mechanisms linking vegetation increase and decreasing terrestrial water reserves in arid regions still need to be studied in depth.The potential negative ecological impacts that may result from the continuous decline of terrestrial and groundwater reserves should not be taken lightly.
基金supported by the Third Xinjiang Scientific Expedition Program(Grant 2022xjkk0600)。
文摘Rapid building damage assessment following an earthquake is important for humanitarian relief and disaster emergency responses.In February 2023,two magnitude-7.8 earthquakes struck Turkey in quick succession,impacting over 30 major cities across nearly 300 km.A quick and comprehensive understanding of the distribution of building damage is essential for e fficiently deploying rescue forces during critical rescue periods.This article presents the training of a two-stage convolutional neural network called BDANet that integrated image features captured before and after the disaster to evaluate the extent of building damage in Islahiye.Based on high-resolution remote sensing data from WorldView2,BDANet used predisaster imagery to extract building outlines;the image features before and after the disaster were then combined to conduct building damage assessment.We optimized these results to improve the accuracy of building edges and analyzed the damage to each building,and used population distribution information to estimate the population count and urgency of rescue at different disaster levels.The results indicate that the building area in the Islahiye region was 156.92 ha,with an affected area of 26.60 ha.Severely damaged buildings accounted for 15.67%of the total building area in the affected areas.WorldPop population distribution data indicated approximately 253,297,and 1,246 people in the collapsed,severely damaged,and lightly damaged areas,respectively.Accuracy verification showed that the BDANet model exhibited good performance in handling high-resolution images and can be used to directly assess building damage and provide rapid information for rescue operations in future disasters using model weights.
基金supported by the Open fund of Key Laboratory of National Geographic Census and Monitoring,MNR(grant no.2020NGCM02)Open Research Fund of the Key Laboratory of Digital Earth Science,Chinese Academy of Sciences(grant no.2019LDE006)+8 种基金the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources(grant no.KF-2020-05001)Open fund of Key Laboratory of Land use,Ministry of Natural Resources(grant no.20201511835)Open Fund of Key Laboratory for Digital Land and Resources of Jiangxi Province,East China University of Technology(grant no.DLLJ202002)Open foundation of MOE Key Laboratory of Western China’s Environmental Systems,Lanzhou University and the fundamental Research funds for the Central Universities(grant no.lzujbky-2020-kb01)University-Industry Collaborative Education Program(grant no.201902208005)Open Fund of Key Laboratory of Meteorology and Ecological Environment of Hebei Province(grant no.Z202001H)Open Fund of Key Laboratory of Geomatics and Digital Technology of Shandong ProvinceOpen Fund of Key Laboratory of Geomatics Technology and Application Key Laboratory of Qinghai Province(grant no.QHDX-2019-04)Natural Science Foundation of Shandong Province(grant no.ZR2018BD001)。
文摘The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and western China as a whole.This paper introduces the gravity center model used to analyze the spatial-temporal variation patterns of vegetation Net Primary Productivity(NPP)from 2000 to 2015,which were determined by the use of MOD17 A3 NPP products.Additionally,the dominant driving factors of the spatial–temporal changes of vegetation NPP of the Hengduan Mountain area were quantitatively determined with a geographical detector over 2000-2015.The results revealed that:(1)From 2000 to 2015,there was an increasing trend of vegetation NPP in the Hengduan mountain area.Throughout the whole study region,the vegetation NPP with a mean value of 611.37 gC·m^(-2)·a^(-1) indicated a decreasing trend from southeast to northwest in terms of spatial distribution.(2)The gravity centers of vegetation NPP in 2000-2015 were mainly concentrated in Zhongdian County.During the study period,the gravity center of vegetation NPP moved northward,which indicated that the increment and increasing rate of vegetation NPP in the northern parts were greater than that of the southern areas.(3)The vegetation NPP showed a moderately positive correlation with temperature,accumulated temperature(>10℃),and sunshine,while there was an overall negative relationship between NPP and precipitation.(4)The dominant factors and interactive dominant factors changed in different subregions over different segments of the study period.The dominant factors of most sub-regions in Hengduan mountain were natural factors,and the climate change factors played an increasingly greater role over the 16 years of the study period.
基金funded jointly by the "Hundred Talents" Project of Chinese Academy of Sciences (CAS)the Hundred Talent Program of Sichuan Province, International Cooperation Partner Program of Innovative Team, CAS (Grant No. KZZD-EW-TZ-06)+1 种基金the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-QN313)the Strategic Priority Research Program-Climate Change: Carbon Budget and Related Issues (Grant No. XDA05050105)
文摘How to deal with geometric distortion is an open problem when using the massive amount of satellite images at a national or global scale, especially for multi-temporal image analysis. In this paper, an algorithm is proposed to automatically rectify the geometric distortion of time-series CCD multi- spectral data of small constellation for environmental and disaster mitigation （HJ-1A/B） which was launched by China in 2008. In this algorithm, the area-based matching method was used to automatically search tie points firstly, and then the polynomial function was introduced to correct the systematic errors caused by the satellite motion along the roll, pitch and yaw direction. The improved orthorectification method was finally used to correct pixel displacement caused by off-nadir viewing of topography, which are random errors in the images and cannot be corrected by the polynomial equation. Nine scenes of level 2 HJ CCD images from one path/row were taken as the warp images to test the algorithm. The test result showed that the overall accuracy of the proposed algorithm was within 2 pixels （the average residuals were 37.8 m, and standard deviations were 19.8 m）. The accuracies of 45.96% validation points （VPs） were within 1 pixel and 90.33% VPs were within 2 pixels. The discussion showed that three main factors including the distortion patterns of HJ CCD images, pereent of cloud cover and the varying altitude of the satellite orbit may affect the search of tie points and the accuracy of results. Although the influence of varying altitude of the satellite orbits is less than the other factors, it is noted that detailed satellite altitude information should be given in the future to get a more precise result. The proposed algorithm should be an efficient tool for the geo-correction of HJ CCD multi-spectral images.
基金Under the auspices of National Natural Science Foundation of China (No. 4176110141771450+2 种基金41871330)National Natural Science Foundation of Inner Mongolia (No. 2017MS0409)Fundamental Research Funds for the Central Universities (No. 2412019BJ001)
文摘Grassland fires results in carbon emissions,which directly affects the carbon cycle of ecosystems and the carbon balance.The grassland area of Inner Mongolia accounts for 22%of the total grassland area in China,and many fires occur in the area every year.However,there are few models for estimation of carbon emissions from grassland fires.Accurate estimation of direct carbon emissions from grassland fires is critical to quantifying the contribution of grassland fires to the regional balance of atmospheric carbon.In this study,the regression equations for aboveground biomass(AGB)of grassland in growing season and MODIS NDVI(Normalized Difference Vegetation Index)were established through field experiments,then AGB during Nov.–Apr.were retrieved based on that in Oct.and decline rate,finally surface fuel load was obtained for whole year.Based on controlled combustion experiments of different grassland types in Inner Mongolia,the carbon emission rate of grassland fires for each grassland type were determined,then carbon emission was estimated using proposed method and carbon emission rate.Results revealed that annual average surface fuel load of grasslands in Inner Mongolia during 2000–2016 was approximately 1.1978×1012 kg.The total area of grassland which was burned in the Inner Mongolia region over the 17-year period was 5298.75 km2,with the annual average area of 311.69 km2.The spatial distribution of grassland surface fuel loads is characterized by decreasing from northeast to southwest in Inner Mongolia.The total carbon emissions from grassland fires amounted to 2.24×107 kg with an annual average of 1.32×106 for the study area.The areas with most carbon emissions were mainly concentrated in Old Barag Banner and New Barag Right Banner and on the right side of the Oroqin Autonomous Banner.The spatial characteristics of carbon emission depend on the location of grassland fire,mainly in the northeast of Inner Mongolia include Hulunbuir City,Hinggan League,Xilin Gol League and Ulanqab City.The area and spatial location of grassland fires can directly affect the total amount and spatial distribution of carbon emissions.This study provides a reference for estimating carbon emissions from steppe fires.The model and framework for estimation of carbon emissions from grassland fires established can provide a reference value for estimation of carbon emissions from grassland fires in other regions.
文摘The origin and movement of groundwater are the fundamental questions that address both the temporal and spatial aspects of ground water run and water supply related issues in hydrological systems.As groundwater flows through an aquifer,its composition and temperature may variation dependent on the aquifer condition through which it flows.Thus,hydrologic investigations can also provide useful information about the subsurface geology of a region.But because such studies investigate processes that follow under the Earth's shallow,obtaining the information necessary to answer these questions is not continuously easy.Springs,which discharge groundwater table directly,afford to study subsurface hydrogeological processes.The present study of estimation of aquifer factors such as transmissivity(T)and storativity(S)are vital for the evaluation of groundwater resources.There are several methods to estimate the accurate aquifer parameters(i.e.hydrograph analysis,pumping test,etc.).In initial days,these parameters are projected either by means of in-situ test or execution test on aquifer well samples carried in the laboratory.The simultaneous information on the hydraulic behavior of the well(borehole)that provides on this method,the reservoir and the reservoir boundaries,are important for efficient aquifer and well data management and analysis.The most common in-situ test is pumping test performed on wells,which involves the measurement of the fall and increase of groundwater level with respect to time.The alteration in groundwater level(drawdown/recovery)is caused due to pumping of water from the well.Theis(1935)was first to propose method to evaluate aquifer parameters from the pumping test on a bore well in a confined aquifer.It is essential to know the transmissivity(T=Kb,where b is the aquifer thickness;pumping flow rate,Q=TW(dh/dl)flow through an aquifer)and storativity(confined aquifer:S=bS_s,unconfined:S=S_y),for the characterization of the aquifer parameters in an unknown area so as to predict the rate of drawdown of the groundwater table/potentiometric surface throughout the pumping test of an aquifer.The determination of aquifer's parameters is an important basis for groundwater resources evaluation,numerical simulation,development and protection as well as scientific management.For determining aquifer's parameters,pumping test is a main method.A case study shows that these techniques have been fast speed and high correctness.The results of parameter's determination are optimized so that it has important applied value for scientific research and geology engineering preparation.
基金supported by the National Natural Science Foundation of China (71991484,42271471,72088101,and 41830645)Danish Agency for Higher Education and Science (International Network Project,0192-00056B)the Fundamental Research Funds for the Central Universities (Peking University).
文摘The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.
基金China Global Change Research Program, No.2010CB950902 National Natural Science Foundation of China, No.41071240
文摘Land surface emissivity is one of the important parameters in temperature inversion from thermal infrared remote sensing. Using MOD11C3 of Terra-MODIS L3 level products, spatio-temporal data sets of land surface emissivity in China for 10 years from 2001 to 2010 are obtained. The results show that the land surface emissivity in the northwest desert region is the lowest in China, with little seasonal variations. In contrast, there are significant seasonal variations in land surface emissivity in northeast China and northern Xinjiang, the Qinghai-Tibet Plateau, the Yangtze River Valley and the eastern and southern China. In winter, the land surface emissivity in the northeast China and northern Xinjiang is relatively high. The land surface emissivity of the Qinghai-Tibet Plateau region is maintained at low value from November to March, while it becomes higher in other months. The land surface emissivity of the Yangtze River Valley, eastern and southern China, and Sichuan Basin varies from July to October, and peaks in August. Land surface emissivity values could be divided into five levels low emissivity （0.6163-0.9638）, moderate-low emissivity （0.9639-0.9709）, moderate emissivity （0.9710-0.9724）, moderate-high emissivity （0.9725-0.9738）, and high emissivity （0.9739-0.9999）. The percentages of areas with low emissivity, moderate-low emissivity and moderate emissivity are, respectively, about 20%, 10% and 20%. The moderate-high emissivity region makes up 40%-50% of China＇s land surface area. The inter-annual variation of moderate-high emissivity region is also very clear, with two peaks （in spring and autumn） and two troughs （in summer and winter）. The inter-annual variation of the high emissivity region is very significant, with a peak in winter （10%）, while only 1% or 2% in other seasons. There is a clear association between the spatio-temporal distribution of China＇s land surface emissivity and temperature： the higher the emissivity, the lower the temperature, and vice versa. Emissivity is an inherent property of any object, but the precise value of its emissivity depends very much on its surrounding environmental factors.
基金financially supported by the National Natural Science Foundation of China (41867030, 41971036)the National Natural Science Foundation innovation research group science foundation of China (41421061)
文摘Water resources are one of the key factors restricting the development of arid areas,and cloud water resources is an important part of water resources.The arid region of central Asia is the core region of the current national green silk road construction,and is the largest arid region in the world.Based on cloud cover data of ECMWF,the current study analyzed temporal and spatial characteristics of cloud properties in arid regions of Central Asia between 1980 and 2019.Our findings show that:(1)From the point of view of spatial distribution,total cloudiness in arid regions of Central Asia was low in the south and high in the north.The distribution of high cloud frequency and medium cloud frequency was higher in the south and lower in the north,while low cloud frequency distribution was low in the south and high in the north.(2)In terms of time,the variation of cloud cover and cloud type frequency had obvious seasonal characteristics.From winter to spring,cloud cover increased,and the change of cloud type frequency increased.From spring to summer,cloud cover continued to increase and the change of cloud type frequency increased further.Cloud cover began to decrease from summer to autumn,and the change of cloud type frequency also decreased.(3)Generally,average total cloud cover decreased in most of central Asia,and high and medium cloud cover increased while low cloud cover decreased.This study provides a reference for the rational development of cloud resources in the region.
基金National Natural Science Foundation of China(No.41871382)Open Foundation of the Key Laboratory of Space Active Opto-electronics Technologyand Chinese Academy of Sciences(No.2018-ZDKF-1)。
文摘The influence of the single photon laser altimeter range-gate width on the detection probability and ranging accuracy is discussed and analyzed,according to the LiDAR equation,single photon detection equation and the Monte Carlo method to simulate the experiment.The simulated results show that the probability of detection is not affected by the range gate,while the probability of false alarm is relative to the gate width.When the gate width is 100 ns,the ranging accuracy can accord with the requirements of satellite laser altimeter.But when the range gate width exceeds 400 ns,ranging accuracy will decline sharply.The noise ratio will be more as long as the range gate to get larger,so the refined filtering algorithm during the data processing is important to extract the useful photons effectively.In order to ensure repeated observation of the same point for 25 times,we deduce the quantitative relation between the footprint size,footprint,and frequency repetition according to the parameters of ICESat-2.The related conclusions can provide some references for the design and the development of the domestic single photon laser altimetry satellite.
文摘The determination of the calibration parameters of the gravity gradiometer play an important role in the GOCE gravity gradient data processing.In this paper,the temporal signals and outliers in the GOCE gravity gradient observations are analyzed.Based on the different global gravity field models,the scale factors and biases are determined in all the components of GOCE gravity gradients.And then the accuracy of the calibration results is validated.The results indicated that the effect of the ocean tide is at mE magnitude in the measurement band,which is equivalent to the precision of the gravity gradiometer,while the effect of the non-tide temporal signals,such as terrestrial water is in the order of 10-4 E,is slightly less than that of the ocean tide.The outliers in all the gravity gradient components are larger than 0.2%.And after the calibration using global gravity field models except EGM96,the stability of scale factors in the V xx、V yy、V zz、V yz components reaches 10-4 magnitude,and the V xz component reaches 10-5 while that of the V xy component is about 10-2,which are in accordance with the accuracy differences of the gradient components.
基金The National Natural Science Foundation of China under contract Nos 42274006,42174041,41774001the Research Fund of University of Science and Technology under contract No.2014TDJH101.
文摘With the improvements in the density and quality of satellite altimetry data,a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculated from long-time series multi-satellite altimeter data.Therefore,in this study,a method was proposed for determining marine gravity anomalies from a mean sea surface model.Taking the Gulf of Mexico(15°–32°N,80°–100°W)as the study area and using a removal-recovery method,the residual gridded deflections of the vertical(DOVs)are calculated by combining the mean sea surface,mean dynamic topography,and XGM2019e_2159 geoid,and then using the inverse Vening-Meinesz method to determine the residual marine gravity anomalies from the residual gridded DOVs.Finally,residual gravity anomalies are added to the XGM2019e_2159 gravity anomalies to derive marine gravity anomaly models.In this study,the marine gravity anomalies were estimated with mean sea surface models CNES_CLS15MSS,DTU21MSS,and SDUST2020MSS and the mean dynamic topography models CNES_CLS18MDT and DTU22MDT.The accuracy of the marine gravity anomalies derived by the mean sea surface model was assessed based on ship-borne gravity data.The results show that the difference between the gravity anomalies derived by DTU21MSS and CNES_CLS18MDT and those of the ship-borne gravity data is optimal.With an increase in the distance from the coast,the difference between the gravity anomalies derived by mean sea surface models and ship-borne gravity data gradually decreases.The accuracy of the difference between the gravity anomalies derived by mean sea surface models and those from ship-borne gravity data are optimal at a depth of 3–4 km.The accuracy of the gravity anomalies derived by the mean sea surface model is high.
基金supported by the Shenzhen Science and Technology Innovation Project(No.ZDSYS20210623091808026)supported in part by the National Natural Science Foundation of China(General Program,No.42071351)+1 种基金the National Key Research and Development Program of China(No.2020YFA0608501)the Chongqing Science and Technology Bureau technology innovation and application development special(cstc2021jscx-gksb0116).
文摘Forest is the largest carbon reservoir and carbon absorber on earth.Thus,mapping forest cover change accurately is of great significance to achieving the global carbon neutrality goal.Accurate forest change information could be acquired by deep learning methods using high-resolution remote sensing images.However,deforestation detection based on deep learning on a large-scale region with high-resolution images required huge computational resources.Therefore,there was an urgent need for a fast and accurate deforestation detection model.In this study,we proposed an interesting but effective re-parameterization deforestation detection model,named RepDDNet.Unlike other existing models designed for deforestation detection,the main feature of RepDDNet was its decoupling feature,which means that it allowed the multi-branch structure in the training stages to be converted into a plain structure in the inference stage,thus the computation efficiency can be significantly improved in the inference stage while maintaining the accuracy unchanged.A large-scale experiment was carried out in Ankang city with 2-meter high-resolution remote sensing images(the total area of it was over 20,000 square kilometers),and the result indicated that the model computation efficiency could be improved by nearly 30%compared with the model without re-parameterization.Additionally,compared with other lightweight models,RepDDNet also displayed a trade-off between accuracy and computation efficiency.
基金the National Natural Science Foundation of China(41867030,41971036)the key Natural Science Foundation of Gansu Province(23JRRA698)+2 种基金the key Research and Development Program of Gansu Province(22YF7NA122)the Oasis Scientific Research achievements Breakthrough Action Plan Project of Northwest normal University(NWNU-LZKX-202302)the cultivation Plan Project of the Major(key)Project of Northwest normal University.
文摘Climate change is the dominant factor affecting the hydrological process,it is of great significance to simulate and predict its influence on water resources management,socio-economic activities,and sustainable development in the future.In this paper,the Xiying River Basin was taken as the study area,China Atmospheric Assimilation Driven Data Set(CMADS)and observation data from the Jiutiaoling station were used to simulate runoff of the SWAT model and calibrate and verify model parameters.On this basis,runoff change of the basin under the future climate scenario of CMIP6 was predicted.Our research shows that:(1)The contribution rates of climate change and human activities to runoff increase of the Xiying River are 89.17%and 10.83%,respectively.Climate change is the most important factor affecting runoff change of the Xiying River.(2)In these three different emission scenarios of SSP1-2.6,SSP2-4.5 and SSP5-8.5 in CMIP6 climate model,the average temperature increased by0.61,1.09 and 1.74 C,respectively,in the Xiying River Basin from 2017 to 2050.Average precipitation increased by 14.36,66.88,and 142.73 mm,respectively,and runoff increased by 15,24,and 35 million m3,respectively.The effect of climate change on runoff will continue to deepen in the future.
基金National Natural Science Foundation of China,No.41425002National Basic Research Program of China,No.2012CB955403+2 种基金National Youth Topnotch Talent Support Program in ChinaChina Special Fund for Meteorological Research in the Public Interest(Major projects),No.GYHY201506001-7The Beijing Science and Technology Plan Project,No.Z141100003614052
文摘Hydrological monitoring and seasonal forecasting is an active research field because of its potential applications in hydrological risk assessment,preparedness and mitigation.In recent decades,developments in ground and satellite measurements have made the hydrometeorological information readily available,and advances in information technology have facilitated the data analysis in a real-time manner.New progress in climate research and modeling has enabled the prediction of seasonal climate with reasonable accuracy and increased resolution.These emerging techniques and advances have enabled more timely acquisition of accurate hydrological fluxes and status,and earlier warning of extreme hydrological events such as droughts and floods.This paper gives current state-of-the-art understanding of the uncertainties in hydrological monitoring and forecasting,reviews the efforts and progress in operational hydrological monitoring system assisted by observations from various sources and experimental seasonal hydrological forecasting,and briefly introduces the current monitoring and forecasting practices in China.The grand challenges and perspectives for the near future are also discussed,including acquiring and extracting reliable information for monitoring and forecasting,predicting realistic hydrological fluxes and states in the river basin being significantly altered by human activity,and filling the gap between numerical models and the end user.We highlight the importance of understanding the needs of the operational water management and the priority to transfer research knowledge to decision-makers.
基金supported by the ESA-MOST China DRAGON-5 project with ref.59339,by the Spanish Ministry of Science and Innovation,the State Agency of Research(AEI)the European Funds for Regional Development under grant[grant number PID2020-117303GB-C22]+5 种基金by the Conselleria de Innovación,Universidades,Ciencia y Sociedad Digital in the framework of the project CIAICO/2021/335by the Natural Science Foundation of China[grant numbers 41874005 and 41929001]the Fundamental Research Funds for the Central University[grant numbers 300102269712 and 300102269303]China Geological Survey Project[grant numbers DD20190637 and DD20190647]Xiaojie Liu and Liuru Hu have been funded by Chinese Scholarship Council Grants Ref.[grant number 202006560031][grant number 202004180062],respectively.
文摘Landslides are destructive geohazards to people and infrastructure,resulting in hundreds of deaths and billions of dollars of damage every year.Therefore,mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks.In this paper,the main outcomes relevant to the joint European Space Agency(ESA)and the Chinese Ministry of Science and Technology(MOST)Dragon-5 initiative cooperation project ID 59,339“Earth observation for seismic hazard assessment and landslide early warning system”are reported.The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks,detect potential landslides in wide regions,and demonstrate EO-based landslide early warning system over selected landslides.This work only focuses on the landslide hazard content of the project,and thus,in order to achieve these objectives,the following tasks were developed up to now:a)a procedure for phase unwrapping errors and tropospheric delay correction;b)an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements;c)the application of polarimetric SAR interferometry(PolInSAR)to increase the number and quality of monitoring points in landslide-prone areas;d)the semiautomatic mapping and preliminary classification of active displacement areas on wide regions;e)the modeling and identification of landslides in order to identify triggering factors or predict future displacements;and f)the application of an InSAR-based landslide early warning system on a selected site.The achieved results,which mainly focus on specific sensitive regions,provide essential assets for planning present and future scientific activities devoted to identifying,mapping,characterizing,monitoring and predicting landslides,as well as for the implementation of early warning systems.
文摘Greenway is a green linear corridor connecting scenic spots, residential areas, nature reserves, road traffic, etc. Rational greenway route selection can not only attract tourists to increase the income of local villages, but also arouse people’s awareness of the protection of traditional villages. This paper took Xingtai County, Hebei Province, China as an example to practice greenway route selection in the county territory. Eight factors were selected for greenway route planning, namely elevation, water body, mountain, ecological protection redline, cultural relics protection units, population density, road traffic network, and important transportation hub. These eight factors were assigned in the GIS platform, and the suitability evaluation system of each factor was constructed. The analytic hierarchy process (AHP) and entropy weight method were combined to calculate the weight of these eight factors. The raster calculator was used to weight and overlay the suitability evaluation system of each factor, and the comprehensive suitability evaluation map of greenway route selection was obtained. Based on an important transport hub, along with the water body and the road traffic, the final selection greenway route of traditional villages in Xingtai county was formed. The results of the research can provide a certain reference for the greenway route selection at the county scale.
