A massive amount of plastic waste has presented an immense management challenge.This escalating ecological damage,coupled with the detrimental effects of plastics infiltrating the marine food web,poses a significant t...A massive amount of plastic waste has presented an immense management challenge.This escalating ecological damage,coupled with the detrimental effects of plastics infiltrating the marine food web,poses a significant threat to human livelihoods.To combat this,there is a call for the development of plastic detection algorithms using remote sensing data.Here we tested a new index,referred to index_(MP),to detect clusters of floating macro plastics in the ocean using satellite imagery.The index_(MP)was applied to convolution high-pass filtered(3×3)Sentinel 2 Level 1 C images,showing the potential to reduce atmospheric interference and enhance the object edges,thereby improving the clarity of detection.In the analysis,we used three scatter plots to identify and assess plastic pixels.To differentiate the common features of plastic from non-plastic objects,the Sentinel 2 bands 5,8,and 9 were plotted against index_(MP)calculated and convolution high-pass filtered Level 1 C(CHPIC)images.The plastic pixels,clustering in the three scatter plots,showed positive‘X’,i.e.,CHPIC image value and‘Y’,i.e.,each band 5,8,and 9 reflectance values,along with a CHPIC image value exceeding 0.05.Using the index_(MP)and scatter plot analysis,we identified plastic pixels containing 14%or more plastic bottles.Detection of other types of plastics,such as fishing nets and plastic bags,required pixel proportions greater than 50%.Hence,plastic bottles were notably responsive even at a low pixel fraction.We further explored the classification of plastic and non-plastic objects by analyzing reed(plant)pixels;the differentiation between plastic and reed was conducted in the band 5 and 9 scatter plots.展开更多
This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery,based on principal component analysis(PCA) and intensity-hue-saturation(IHS) transformations.The PCA and the IHS trans...This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery,based on principal component analysis(PCA) and intensity-hue-saturation(IHS) transformations.The PCA and the IHS transformations are used to separate the spatial information of the multi-spectral image into the first principal component and the intensity component,respectively.The enhanced image is obtained by replacing the intensity component of the IHS transformation with the first principal component of the PCA transformation,and undertaking the inverse IHS transformation.The objective of the proposed method is to make greater use of the spatial and spectral information contained in the original multi-spectral image.On the basis of the visual and statistical analysis results of the experimental study,we can conclude that the proposed method is an ideal new way for multi-spectral image quality enhancement with little color distortion.It has potential advantages in image mapping optimization,object recognition,and weak information sharpening.展开更多
It is important to explore active faults in urban areas and their surroundings for earth- quake disaster mitigation. Satellite remote sensing techniques can play an important role in such active fault exploration. It ...It is important to explore active faults in urban areas and their surroundings for earth- quake disaster mitigation. Satellite remote sensing techniques can play an important role in such active fault exploration. It can not only reveal the pattern of active faults and active tectonics on a macroscop- ic scale, but also monitor the occurrence, development and rules of temporal-spatial evolution of active faults. In this paper, we use the Hangzhou area as an example to introduce methods of extracting de- tailed active fault information when covered by thick unconsolidated Quaternary sediment, using im- age enhancement and image fusion etc. to improve the definition and precision of satellite images and presenting a three-dimensional （3D） image to illustrate tectono-geomorphic features along the relevant faults. We have also collected aeromagnetic anomaly data, shallow seismic exploration data and dating data, and carried out field surveys to validate the characteristics of active faults based on remote sens- ing images. The results revealed about the faults showed a high consistency with traditional geological knowledge, and demonstrate that it is feasible to explore active faults in a weakly active tectonic area by using satellite remote sensing techniques and contribute to large engineering projects and research on neotectonics.展开更多
Based on the 16 scenes GF-1 satellite multi-spectral remote sensing images,through the adoption of data processing methods including orthorectification,geometric rectification,data fusion and image mosaic,integrated w...Based on the 16 scenes GF-1 satellite multi-spectral remote sensing images,through the adoption of data processing methods including orthorectification,geometric rectification,data fusion and image mosaic,integrated with field surveys,the remote sensing interpretation signs for the inland wetland types have been built,and the remote sensing survey of inland wetlands in Yadong region has been initiated,with six types of inland wetlands recognized in Yadong region,namely permanent rivers,seasonal rivers,lakes,salt lakes,alpine meadows,and inundated land.The spatial distribution characteristics and the spreading rules of these wetlands have also been revealed.Based on full understanding of the overall characteristics of the inland wetlands in the Yadong region,using the three phases of TM images acquired in 1989,2003 and 2008 as well as the PMS2 data gathered by GF-1 in 2014,and the wide-range data(WFV3)gathered by GF-1 in 2020.As to the typical salt lakes,a long-time salt lakes transition study was carried out.The results show that the typical salt lakes in Yadong have been shrinking in the past three decades.The average annual shrinkage of Duoqing Co(Co means lake in Tibetan)was stronger than that of Gala Co,which are respective 87.30 hectares(usually short as ha;1 ha equals to 0.01 km^(2))/a and 24.20 ha/a;the shrinkage degree of Gala Co was higher than that of Duoqing Co,shrank by 59.27%and 35.73%respectively.Based on the remote sensing survey results and an integrated analysis of the predecessors’researchers,the reason for the shrinkage of the salt lakes is more inclined to geological factors.Geological process is manifested by a series of extensional faults at the bottom of the lake basin generated from tectonic activities,providing fluid infiltration channels,and inducing the eventual leakage of lake water to the lower strata.The result provides an important instance for understanding the evolution characteristics of wetlands and salt lakes in specific environment of the Tibetan Plateau.展开更多
The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia,from which the global climate change can be underst...The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia,from which the global climate change can be understood on a large scale,especially the climate change in the Mongolian Plateau.This study extracted the information on the wetlands from three stages of remote sensing images(also referred to as RS images)of the study area,including Enhanced Thematic Mapper Plus(ETM+)images of 2000,TM images of 2010,and Landsat 8 Operational Land Imager(OLI)images of 2018.As indicated by the extraction results,the area of wetlands decreased from 796.90 km^(2) of 2000 to 666.24 km^(2) of 2018 at a rate of 7.26 km^(2)/a.The reduced area is 130.66 km^(2),which is about 16.4%reduction.And the patch number of wetlands decreased from 731 of 2000 to 316 of 2018 in the study area,approximately 56.8%reduction(415 patches),and the decrease in the area of the wetlands mainly occurred in the northwest endorheic region.In terms of wetland types,the change of the wetlands was dominated by the decrease of lacustrine wetlands,of which the area and patch number decreased by 106.2 km^(2) and 242,respectively.Furthermore,the area of the lacustrine wetlands decreased at the highest rate of 8.70 km^(2)/a in 2010‒2018.From the perspective of spatial distribution,the wetlands in the western part shrunk more notably than those in the eastern part as a whole in the study area.According to local meteorological data,the precipitation gently decreased and the temperature increased(about 1.7℃)from 1975-2018.Overall,the decrease in the area of the wetlands and the temperature rises in the study area were mainly driven by the Mongolian monsoon climate,reduction in precipitation,and human activities.展开更多
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
With the rapid development of China＇s economy, coal resources are increasingly in great demand. As a result, the remaining coal reserves diminish gradually with large-scale exploitation of coal resources. Easily-foun...With the rapid development of China＇s economy, coal resources are increasingly in great demand. As a result, the remaining coal reserves diminish gradually with large-scale exploitation of coal resources. Easily-found mines which used to be identified from outcrops or were buried under shallow overburden are decreasing, especially in the prosperous eastern regions of China, which experience coal shortages. Currently the main targets of coal prospecting are concealed and unidentified underground coal bodies, making it more and more difficult for coal prospecting. It is therefore important to explore coal prospecting by taking advantage of modern remote sensing and geographic information system technologies. Given a theoretical basis for coal prospecting by remote sensing, we demonstrate the methodologies and existing problems systematically by summarizing past practices of coal prospecting with remote sensing. We propose a new theory of coal prospecting with remote sensing. In uncovered areas, coal resources can be prospected for by direct interpretation. In coal beating strata of developed areas covered by thin Quaternary strata or vegetation, prospecting for coal can be carried out by indirect interpretation of geomorphology and vegetation. For deeply buried underground deposits, coal prospecting can rely on tectonic structures, interpretation and analysis of new tectonic clues and regularity of coal formation and preservation controlled by tectonic structures. By applying newly hyper-spectral, multi-polarization, multi-angle, multi-temporal and multi-resolution remote sensing data and carrying out integrated analysis of geographic attributes, ground attributes, geophysical exploration results, geochemical exploration results, geological drilling results and remote sensing data by GIS tools, coal geology resources and mineralogical regularities can be explored and coal resource information can be acquired with some confidence.展开更多
Rift Valley Fever (RVF) is an emerging, mosquito-borne disease with serious economical and negative implications on human and animal health. This study was conducted to verify the factors which influenced the spatial ...Rift Valley Fever (RVF) is an emerging, mosquito-borne disease with serious economical and negative implications on human and animal health. This study was conducted to verify the factors which influenced the spatial pattern of Rift Valley Fever occurrence and identified the high risk areas for the occurrence of the disease at Sinner State, Sudan. The normalized difference vegetation index (NDVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and rainfall data in addition to the point data of RVF clinical cases in humans were used in this study. In order to identify the RVF high risk areas, remote sensing data and rainfall data were integrated in a GIS with other information including, soil type, water body, DEM (Digital Elevation Model), and animal routes and analyzed using Spatial Analysis tools. The information on clinical cases was used for verification. The Normalized Difference Vegetation Index (NDVI) was used to describe vegetation patterns of the study area by calculating the mean NDVI. The results of the study showed that, RVF risk increased with the increase in vegetation cover (high NDVI values), and increase in rainfall, which both provided suitable conditions for disease vectors breeding and a good indicator for RVF epizootics. The study concluded that, identification of high risk area for RVF disease improved the understanding of the spatial distribution of the disease and helped in locating the areas where disease was likely to be endemic and therefore preparedness measures should be taken. The identification represents the first step of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation. Further detailed studies are recommended in this domain.展开更多
1 Introduction Potassium is listed as one of the shortage of mineral resources in china.Geophysical and remote sensing technology plays an important role in prospecting for potash ressources.
GIS and RS techniques have been applied to interpret satellite data in 1992, 2000 and 2010. Further, the ecological environment factors of these three periods and the data for various types of land use have been obtai...GIS and RS techniques have been applied to interpret satellite data in 1992, 2000 and 2010. Further, the ecological environment factors of these three periods and the data for various types of land use have been obtained. LUDI in the Amur River Basin from 1992 to 2010 has been quantitatively analyzed by using the land use dynamic(LUDI) model and of land use transfer matrix model. The results indicated that from 1992 to 2010 the LUDI of land desertification is greatest, and is the most dramatic change. The comprehensive land use dynamic in the study area is 15.25, hence the land type is characterized by rapid change. In addition the area of woodland and farmland continues to increase, which has been mainly transformed from the mixture of forestland and grassland, marsh and wetland, this is an outcome of the production of shelter-forest plantation in North China, Northeast China and Northwest China. In the ten years period of the study, the area of desertified land has increased, changing mainly from a mixture of woodland and grassland. This study can rovide data for eco-geological environment management.展开更多
The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achiev...The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achieve using satellite remote sensing.Considering the convenient,facilitative,and flexible characteristics of UAV(unmanned air vehicle)remote sensing tech-nology,this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral data.Using professional software,including Context Capture,ENVI,and ArcGIS,a 3D(three-dimensional)campus model,a digital orthophoto map,and multi-spectral remote sensing map drawing are realized,and the geometric accuracy of typical feature selection is evaluated.Based on a quantitative remote sensing model,the campus ecological environment assessment is performed from the perspectives of vegetation and water body.The results presented in this study could be of great significance to the scientific management and sustainable development of regional natural resources.展开更多
Uncertainty is the most important factor affecting the quality of the remote sensing image classification.Aiming at the characteristics ofboth the random and the fuzzy uncertainties in the process of the remote sensin...Uncertainty is the most important factor affecting the quality of the remote sensing image classification.Aiming at the characteristics ofboth the random and the fuzzy uncertainties in the process of the remote sensing image classification,a method based on the mixed entropy model is proposed to measure these two uncertainties comprehensively,and a multi-scale evaluation index is established.Based on the analysis of the basic principles of the mixed entropy model,a method of using the statistical data of the feature space and the fuzzy classifier to establish the information entropy,the fuzzy entropy and the mixed entropy is proposed.At the same time,on the scale of the pixel and the category,the index of the mixed entropy of the pixel and the mixed entropy of the category are established to evaluate the uncertainty of the classification.展开更多
regional hydrogeological survey is groundwork for regional water resource development and utilization. In order to promote working efficiency and work cycle of traditional general survey, remote sensing technology is ...regional hydrogeological survey is groundwork for regional water resource development and utilization. In order to promote working efficiency and work cycle of traditional general survey, remote sensing technology is used to obtain the information of the region surveyed, such as landscape, Quaternary geology, geological disasters, geologic structure, hydrographic features, etc, thus building diagrams, such as regional remote sensing interpretation geomorphologic map, Quaternary geological map, hydrogeologic map, tectonic map, etc. This paper takes application of remote sensing in hydrogeological general survey(revision) of 1:200 000 mountain region in Hebei Province as an example, to systematically introduce technical route and technical method of remote sensing applied in regional hydrogeological survey as well as main content of interpretation. The paper also combines the latest remote sensing technological development to look far ahead into application of remote sensing in regional hydrogeological survey and introduces a new direction.展开更多
Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general contr...Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.展开更多
Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiote...Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.展开更多
Accurate calibration of China's new generation ground-based polarimetric radar(GR) network is crucial yet challenging. Although application of the Dual-frequency Precipitation Radar(DPR) of the Global Precipitatio...Accurate calibration of China's new generation ground-based polarimetric radar(GR) network is crucial yet challenging. Although application of the Dual-frequency Precipitation Radar(DPR) of the Global Precipitation Measurement Core Observatory for GR assessment is well-established, current methodologies are inherently limited. Focusing on three GRs in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)—strategically selected for their high overlapping coverage(>65%) and distinct from single GR or less dense coverage studies—this work introduces key refinements by integrating innovative enhancements into the volume-matching method(VMM), reflecting a systematic approach to mitigating potential error sources. Specifically, we integrate: 1) a novel frequency correction method that adapts to DPR-observed precipitation phase and type, replacing assumption-based polynomial fitting;and 2) a precise beam time-difference matching approach(accuracy < 1 s) to minimize temporal mismatch errors, which improves upon coarser time averaging methods. Furthermore, we developed statistically robust, optimized threshold criteria based on systematic sensitivity analyses using 11 quality control factors, including precipitation type, bright band effects, and attenuation correction limitations. These criteria establish an enhanced protocol designed to minimize errors arising from instrumental, frequency, and scanning differences. Application of this enhanced methodology to the GBA GRs(2021–2023) yielded a significantly improved matching accuracy(correlation coefficient, CC: 0.90–0.95;standard deviation,STD: 1.2–1.6 dB). A unique contribution of this work is the quantitative estimation of historical calibration errors and operational stability, which was achieved by linking VMM results with operational GR calibration and maintenance records. This analysis revealed decreasing STD trends and identified specific calibration-related events, such as an underestimation of approximately 2.43 dB for the Shenzhen radar following calibration in 2023. Consequently, the refined methodology provides a robust framework for ongoing GR network monitoring and offers a validated pathway for authenticating China's Fengyun-3G(FY-3G) satellite precipitation measurement radar(PMR) data.展开更多
The ASTER (Advanced Space-borne Thermal Emission and Reflection radiometer) data, including all the 3 parts: VNIR (Visible and Near-Infrared), SWIR (Short Wave Infrared), TIR (Thermal Infrared), were applied for extra...The ASTER (Advanced Space-borne Thermal Emission and Reflection radiometer) data, including all the 3 parts: VNIR (Visible and Near-Infrared), SWIR (Short Wave Infrared), TIR (Thermal Infrared), were applied for extraction of mineral deposits, such as the Ni-Cu deposit in eastern Tianshan, the gypsum in western Tianshan, and the borax in Tibetan. This paper discusses the extraction methodology using the ASTER remote sensing data and reveals the good extraction results. This paper bravely represents the summary of the main achievement for this field by the scientists in other countries and gives a comparison with the works by others. The new achievements, described in this paper, comprise the extraction of anomalies for Ni-Cu deposit, gypsum, and borax.展开更多
Arctic sea-ice extent reaches its minimum each year in September. On 11 September 2023 the minimum was 4.969 million square kilometers(mill.km^(2)). This was not a record low, which occurred in 2012, when the minimum ...Arctic sea-ice extent reaches its minimum each year in September. On 11 September 2023 the minimum was 4.969 million square kilometers(mill.km^(2)). This was not a record low, which occurred in 2012, when the minimum was 4.175 mill.km^(2), 0.794 mill.km^(2) less than the minimum in 2023. However, the ice extent had decreased by 0.432 mill.km^(2) compared with 2022. Nevertheless, the summer melting in 2023 was remarkably less than expected when considering the strong heat waves in the atmosphere and ocean, with record temperatures set around the world. In general, there is a high correlation between the long-term decrease in sea-ice extent and the increasing CO_(2) in the atmosphere, where the increase of CO_(2) in recent decades explains about 80% of the decrease in sea ice in September, while the remainder is caused by natural variability.展开更多
In current neural network algorithms for nuclide identification in high-background,poor-resolution detectors,traditional network paradigms including back-propagation networks,convolutional neural networks,recurrent ne...In current neural network algorithms for nuclide identification in high-background,poor-resolution detectors,traditional network paradigms including back-propagation networks,convolutional neural networks,recurrent neural networks,etc.,have been limited in research on γ spectrum analysis because of their inherent mathematical mechanisms.It is difficult to make progress in terms of training data requirements and prediction accuracy.In contrast to traditional network paradigms,network models based on the transformer structure have the characteristics of parallel computing,position encoding,and deep stacking,which have enabled good performance in natural language processing tasks in recent years.Therefore,in this paper,a transformer-based neural network (TBNN) model is proposed to achieve nuclide identification for the first time.First,the Geant4 program was used to generate the basic single-nuclide energy spectrum through Monte Carlo simulations.A multi-nuclide energy spectrum database was established for neural network training using random matrices of γ-ray energy,activity,and noise.Based on the encoder–decoder structure,a network topology based on the transformer was built,transforming the 1024-channel energy spectrum data into a 32×32 energy spectrum sequence as the model input.Through experiments and adjustments of model parameters,including the learning rate of the TBNN model,number of attention heads,and number of network stacking layers,the overall recognition rate reached 98.7%.Additionally,this database was used for training AI models such as back-propagation networks,convolutional neural networks,residual networks,and long shortterm memory neural networks,with overall recognition rates of 92.8%,95.3%,96.3%,and 96.6%,respectively.This indicates that the TBNN model exhibited better nuclide identification among these AI models,providing an important reference and theoretical basis for the practical application of transformers in the qualitative and quantitative analysis of the γ spectrum.展开更多
In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw ...In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw attitude changes most dramatically and corresponds best to the magnetic data anomaly interval.Based on this finding,we solved the compensation model using least squares fitting and Huber's parametric fitting.By comparison,we found that the Huber parametric fit not only eliminates the interference introduced by attitude changes but also retains richer anomaly source information and therefore obtains a higher signal-to-noise ratio.The experimental results show that the quality of the magnetometry data obtained by using the compensation method proposed in this paper has been significantly improved,and the mean value of its improvement ratio can reach 118.93.展开更多
基金Supported by the Guangdong Special Support Program for Key Talents Team Program(No.2019BT02H594)the PI Project of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(No.GML2021GD0810)the Major Project of National Social Science Foundation of China(No.21ZDA097)。
文摘A massive amount of plastic waste has presented an immense management challenge.This escalating ecological damage,coupled with the detrimental effects of plastics infiltrating the marine food web,poses a significant threat to human livelihoods.To combat this,there is a call for the development of plastic detection algorithms using remote sensing data.Here we tested a new index,referred to index_(MP),to detect clusters of floating macro plastics in the ocean using satellite imagery.The index_(MP)was applied to convolution high-pass filtered(3×3)Sentinel 2 Level 1 C images,showing the potential to reduce atmospheric interference and enhance the object edges,thereby improving the clarity of detection.In the analysis,we used three scatter plots to identify and assess plastic pixels.To differentiate the common features of plastic from non-plastic objects,the Sentinel 2 bands 5,8,and 9 were plotted against index_(MP)calculated and convolution high-pass filtered Level 1 C(CHPIC)images.The plastic pixels,clustering in the three scatter plots,showed positive‘X’,i.e.,CHPIC image value and‘Y’,i.e.,each band 5,8,and 9 reflectance values,along with a CHPIC image value exceeding 0.05.Using the index_(MP)and scatter plot analysis,we identified plastic pixels containing 14%or more plastic bottles.Detection of other types of plastics,such as fishing nets and plastic bags,required pixel proportions greater than 50%.Hence,plastic bottles were notably responsive even at a low pixel fraction.We further explored the classification of plastic and non-plastic objects by analyzing reed(plant)pixels;the differentiation between plastic and reed was conducted in the band 5 and 9 scatter plots.
文摘This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery,based on principal component analysis(PCA) and intensity-hue-saturation(IHS) transformations.The PCA and the IHS transformations are used to separate the spatial information of the multi-spectral image into the first principal component and the intensity component,respectively.The enhanced image is obtained by replacing the intensity component of the IHS transformation with the first principal component of the PCA transformation,and undertaking the inverse IHS transformation.The objective of the proposed method is to make greater use of the spatial and spectral information contained in the original multi-spectral image.On the basis of the visual and statistical analysis results of the experimental study,we can conclude that the proposed method is an ideal new way for multi-spectral image quality enhancement with little color distortion.It has potential advantages in image mapping optimization,object recognition,and weak information sharpening.
基金supported by the Major Research Project of the Ministry of Land and Resources,China(No.1212011120887)
文摘It is important to explore active faults in urban areas and their surroundings for earth- quake disaster mitigation. Satellite remote sensing techniques can play an important role in such active fault exploration. It can not only reveal the pattern of active faults and active tectonics on a macroscop- ic scale, but also monitor the occurrence, development and rules of temporal-spatial evolution of active faults. In this paper, we use the Hangzhou area as an example to introduce methods of extracting de- tailed active fault information when covered by thick unconsolidated Quaternary sediment, using im- age enhancement and image fusion etc. to improve the definition and precision of satellite images and presenting a three-dimensional （3D） image to illustrate tectono-geomorphic features along the relevant faults. We have also collected aeromagnetic anomaly data, shallow seismic exploration data and dating data, and carried out field surveys to validate the characteristics of active faults based on remote sens- ing images. The results revealed about the faults showed a high consistency with traditional geological knowledge, and demonstrate that it is feasible to explore active faults in a weakly active tectonic area by using satellite remote sensing techniques and contribute to large engineering projects and research on neotectonics.
基金funded by the China Geological Survey Project(DD20190545 and DD20221824).
文摘Based on the 16 scenes GF-1 satellite multi-spectral remote sensing images,through the adoption of data processing methods including orthorectification,geometric rectification,data fusion and image mosaic,integrated with field surveys,the remote sensing interpretation signs for the inland wetland types have been built,and the remote sensing survey of inland wetlands in Yadong region has been initiated,with six types of inland wetlands recognized in Yadong region,namely permanent rivers,seasonal rivers,lakes,salt lakes,alpine meadows,and inundated land.The spatial distribution characteristics and the spreading rules of these wetlands have also been revealed.Based on full understanding of the overall characteristics of the inland wetlands in the Yadong region,using the three phases of TM images acquired in 1989,2003 and 2008 as well as the PMS2 data gathered by GF-1 in 2014,and the wide-range data(WFV3)gathered by GF-1 in 2020.As to the typical salt lakes,a long-time salt lakes transition study was carried out.The results show that the typical salt lakes in Yadong have been shrinking in the past three decades.The average annual shrinkage of Duoqing Co(Co means lake in Tibetan)was stronger than that of Gala Co,which are respective 87.30 hectares(usually short as ha;1 ha equals to 0.01 km^(2))/a and 24.20 ha/a;the shrinkage degree of Gala Co was higher than that of Duoqing Co,shrank by 59.27%and 35.73%respectively.Based on the remote sensing survey results and an integrated analysis of the predecessors’researchers,the reason for the shrinkage of the salt lakes is more inclined to geological factors.Geological process is manifested by a series of extensional faults at the bottom of the lake basin generated from tectonic activities,providing fluid infiltration channels,and inducing the eventual leakage of lake water to the lower strata.The result provides an important instance for understanding the evolution characteristics of wetlands and salt lakes in specific environment of the Tibetan Plateau.
基金This study was funded by the project initiated by the China Geological Survey entitled “Remote Sensing Geological Survey of National Key Earth Zones”(DD20190536).
文摘The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia,from which the global climate change can be understood on a large scale,especially the climate change in the Mongolian Plateau.This study extracted the information on the wetlands from three stages of remote sensing images(also referred to as RS images)of the study area,including Enhanced Thematic Mapper Plus(ETM+)images of 2000,TM images of 2010,and Landsat 8 Operational Land Imager(OLI)images of 2018.As indicated by the extraction results,the area of wetlands decreased from 796.90 km^(2) of 2000 to 666.24 km^(2) of 2018 at a rate of 7.26 km^(2)/a.The reduced area is 130.66 km^(2),which is about 16.4%reduction.And the patch number of wetlands decreased from 731 of 2000 to 316 of 2018 in the study area,approximately 56.8%reduction(415 patches),and the decrease in the area of the wetlands mainly occurred in the northwest endorheic region.In terms of wetland types,the change of the wetlands was dominated by the decrease of lacustrine wetlands,of which the area and patch number decreased by 106.2 km^(2) and 242,respectively.Furthermore,the area of the lacustrine wetlands decreased at the highest rate of 8.70 km^(2)/a in 2010‒2018.From the perspective of spatial distribution,the wetlands in the western part shrunk more notably than those in the eastern part as a whole in the study area.According to local meteorological data,the precipitation gently decreased and the temperature increased(about 1.7℃)from 1975-2018.Overall,the decrease in the area of the wetlands and the temperature rises in the study area were mainly driven by the Mongolian monsoon climate,reduction in precipitation,and human activities.
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Projects 1212010733809 and 1212010534601 supported by the National Geological Prospecting Foundation of China
文摘With the rapid development of China＇s economy, coal resources are increasingly in great demand. As a result, the remaining coal reserves diminish gradually with large-scale exploitation of coal resources. Easily-found mines which used to be identified from outcrops or were buried under shallow overburden are decreasing, especially in the prosperous eastern regions of China, which experience coal shortages. Currently the main targets of coal prospecting are concealed and unidentified underground coal bodies, making it more and more difficult for coal prospecting. It is therefore important to explore coal prospecting by taking advantage of modern remote sensing and geographic information system technologies. Given a theoretical basis for coal prospecting by remote sensing, we demonstrate the methodologies and existing problems systematically by summarizing past practices of coal prospecting with remote sensing. We propose a new theory of coal prospecting with remote sensing. In uncovered areas, coal resources can be prospected for by direct interpretation. In coal beating strata of developed areas covered by thin Quaternary strata or vegetation, prospecting for coal can be carried out by indirect interpretation of geomorphology and vegetation. For deeply buried underground deposits, coal prospecting can rely on tectonic structures, interpretation and analysis of new tectonic clues and regularity of coal formation and preservation controlled by tectonic structures. By applying newly hyper-spectral, multi-polarization, multi-angle, multi-temporal and multi-resolution remote sensing data and carrying out integrated analysis of geographic attributes, ground attributes, geophysical exploration results, geochemical exploration results, geological drilling results and remote sensing data by GIS tools, coal geology resources and mineralogical regularities can be explored and coal resource information can be acquired with some confidence.
文摘Rift Valley Fever (RVF) is an emerging, mosquito-borne disease with serious economical and negative implications on human and animal health. This study was conducted to verify the factors which influenced the spatial pattern of Rift Valley Fever occurrence and identified the high risk areas for the occurrence of the disease at Sinner State, Sudan. The normalized difference vegetation index (NDVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and rainfall data in addition to the point data of RVF clinical cases in humans were used in this study. In order to identify the RVF high risk areas, remote sensing data and rainfall data were integrated in a GIS with other information including, soil type, water body, DEM (Digital Elevation Model), and animal routes and analyzed using Spatial Analysis tools. The information on clinical cases was used for verification. The Normalized Difference Vegetation Index (NDVI) was used to describe vegetation patterns of the study area by calculating the mean NDVI. The results of the study showed that, RVF risk increased with the increase in vegetation cover (high NDVI values), and increase in rainfall, which both provided suitable conditions for disease vectors breeding and a good indicator for RVF epizootics. The study concluded that, identification of high risk area for RVF disease improved the understanding of the spatial distribution of the disease and helped in locating the areas where disease was likely to be endemic and therefore preparedness measures should be taken. The identification represents the first step of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation. Further detailed studies are recommended in this domain.
基金financially supported by projects of 2006AA06A208, 2013AA0639, 1212011120188 and 12120113099000
文摘1 Introduction Potassium is listed as one of the shortage of mineral resources in china.Geophysical and remote sensing technology plays an important role in prospecting for potash ressources.
文摘GIS and RS techniques have been applied to interpret satellite data in 1992, 2000 and 2010. Further, the ecological environment factors of these three periods and the data for various types of land use have been obtained. LUDI in the Amur River Basin from 1992 to 2010 has been quantitatively analyzed by using the land use dynamic(LUDI) model and of land use transfer matrix model. The results indicated that from 1992 to 2010 the LUDI of land desertification is greatest, and is the most dramatic change. The comprehensive land use dynamic in the study area is 15.25, hence the land type is characterized by rapid change. In addition the area of woodland and farmland continues to increase, which has been mainly transformed from the mixture of forestland and grassland, marsh and wetland, this is an outcome of the production of shelter-forest plantation in North China, Northeast China and Northwest China. In the ten years period of the study, the area of desertified land has increased, changing mainly from a mixture of woodland and grassland. This study can rovide data for eco-geological environment management.
基金supported by the National Natural Science Foundation of China (Grant No.42171311)the Open Fund of State Key Laboratory of Remote Sensing Science (Grant No.OFSLRSS202218)+1 种基金the Key Research and Development Program of the Hainan Province,China (Grant No.ZDYF2021SHFZ105)the Training Program of Excellent Master Thesis of Zhejiang Ocean University.
文摘The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achieve using satellite remote sensing.Considering the convenient,facilitative,and flexible characteristics of UAV(unmanned air vehicle)remote sensing tech-nology,this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral data.Using professional software,including Context Capture,ENVI,and ArcGIS,a 3D(three-dimensional)campus model,a digital orthophoto map,and multi-spectral remote sensing map drawing are realized,and the geometric accuracy of typical feature selection is evaluated.Based on a quantitative remote sensing model,the campus ecological environment assessment is performed from the perspectives of vegetation and water body.The results presented in this study could be of great significance to the scientific management and sustainable development of regional natural resources.
文摘Uncertainty is the most important factor affecting the quality of the remote sensing image classification.Aiming at the characteristics ofboth the random and the fuzzy uncertainties in the process of the remote sensing image classification,a method based on the mixed entropy model is proposed to measure these two uncertainties comprehensively,and a multi-scale evaluation index is established.Based on the analysis of the basic principles of the mixed entropy model,a method of using the statistical data of the feature space and the fuzzy classifier to establish the information entropy,the fuzzy entropy and the mixed entropy is proposed.At the same time,on the scale of the pixel and the category,the index of the mixed entropy of the pixel and the mixed entropy of the category are established to evaluate the uncertainty of the classification.
文摘regional hydrogeological survey is groundwork for regional water resource development and utilization. In order to promote working efficiency and work cycle of traditional general survey, remote sensing technology is used to obtain the information of the region surveyed, such as landscape, Quaternary geology, geological disasters, geologic structure, hydrographic features, etc, thus building diagrams, such as regional remote sensing interpretation geomorphologic map, Quaternary geological map, hydrogeologic map, tectonic map, etc. This paper takes application of remote sensing in hydrogeological general survey(revision) of 1:200 000 mountain region in Hebei Province as an example, to systematically introduce technical route and technical method of remote sensing applied in regional hydrogeological survey as well as main content of interpretation. The paper also combines the latest remote sensing technological development to look far ahead into application of remote sensing in regional hydrogeological survey and introduces a new direction.
基金supported by the National Natural Science Foundation of China(grant numbers 42171085)and the National Key R&D Program of China(Grant No.2024YFF1307801,2024YFF1307804).
文摘Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.
基金supported by the National Key Research and Development Program of China[grant number 2022YFE0106800]an Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 311024001]+3 种基金a project supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number SML2023SP209]a Research Council of Norway funded project(MAPARC)[grant number 328943]a Nansen Center´s basic institutional funding[grant number 342624]the high-performance computing support from the School of Atmospheric Science at Sun Yat-sen University。
文摘Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.
基金National Key Research and Development Program of China (2023YFB3905801)。
文摘Accurate calibration of China's new generation ground-based polarimetric radar(GR) network is crucial yet challenging. Although application of the Dual-frequency Precipitation Radar(DPR) of the Global Precipitation Measurement Core Observatory for GR assessment is well-established, current methodologies are inherently limited. Focusing on three GRs in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)—strategically selected for their high overlapping coverage(>65%) and distinct from single GR or less dense coverage studies—this work introduces key refinements by integrating innovative enhancements into the volume-matching method(VMM), reflecting a systematic approach to mitigating potential error sources. Specifically, we integrate: 1) a novel frequency correction method that adapts to DPR-observed precipitation phase and type, replacing assumption-based polynomial fitting;and 2) a precise beam time-difference matching approach(accuracy < 1 s) to minimize temporal mismatch errors, which improves upon coarser time averaging methods. Furthermore, we developed statistically robust, optimized threshold criteria based on systematic sensitivity analyses using 11 quality control factors, including precipitation type, bright band effects, and attenuation correction limitations. These criteria establish an enhanced protocol designed to minimize errors arising from instrumental, frequency, and scanning differences. Application of this enhanced methodology to the GBA GRs(2021–2023) yielded a significantly improved matching accuracy(correlation coefficient, CC: 0.90–0.95;standard deviation,STD: 1.2–1.6 dB). A unique contribution of this work is the quantitative estimation of historical calibration errors and operational stability, which was achieved by linking VMM results with operational GR calibration and maintenance records. This analysis revealed decreasing STD trends and identified specific calibration-related events, such as an underestimation of approximately 2.43 dB for the Shenzhen radar following calibration in 2023. Consequently, the refined methodology provides a robust framework for ongoing GR network monitoring and offers a validated pathway for authenticating China's Fengyun-3G(FY-3G) satellite precipitation measurement radar(PMR) data.
文摘The ASTER (Advanced Space-borne Thermal Emission and Reflection radiometer) data, including all the 3 parts: VNIR (Visible and Near-Infrared), SWIR (Short Wave Infrared), TIR (Thermal Infrared), were applied for extraction of mineral deposits, such as the Ni-Cu deposit in eastern Tianshan, the gypsum in western Tianshan, and the borax in Tibetan. This paper discusses the extraction methodology using the ASTER remote sensing data and reveals the good extraction results. This paper bravely represents the summary of the main achievement for this field by the scientists in other countries and gives a comparison with the works by others. The new achievements, described in this paper, comprise the extraction of anomalies for Ni-Cu deposit, gypsum, and borax.
文摘Arctic sea-ice extent reaches its minimum each year in September. On 11 September 2023 the minimum was 4.969 million square kilometers(mill.km^(2)). This was not a record low, which occurred in 2012, when the minimum was 4.175 mill.km^(2), 0.794 mill.km^(2) less than the minimum in 2023. However, the ice extent had decreased by 0.432 mill.km^(2) compared with 2022. Nevertheless, the summer melting in 2023 was remarkably less than expected when considering the strong heat waves in the atmosphere and ocean, with record temperatures set around the world. In general, there is a high correlation between the long-term decrease in sea-ice extent and the increasing CO_(2) in the atmosphere, where the increase of CO_(2) in recent decades explains about 80% of the decrease in sea ice in September, while the remainder is caused by natural variability.
基金supported by the National Natural Science Foundation of China(No.42127807)Natural Science Foundation of Sichuan Province(Nos.2024NSFSC0422,23NSFSCC0116)Nuclear Energy Development Project(No.[2021]-88).
文摘In current neural network algorithms for nuclide identification in high-background,poor-resolution detectors,traditional network paradigms including back-propagation networks,convolutional neural networks,recurrent neural networks,etc.,have been limited in research on γ spectrum analysis because of their inherent mathematical mechanisms.It is difficult to make progress in terms of training data requirements and prediction accuracy.In contrast to traditional network paradigms,network models based on the transformer structure have the characteristics of parallel computing,position encoding,and deep stacking,which have enabled good performance in natural language processing tasks in recent years.Therefore,in this paper,a transformer-based neural network (TBNN) model is proposed to achieve nuclide identification for the first time.First,the Geant4 program was used to generate the basic single-nuclide energy spectrum through Monte Carlo simulations.A multi-nuclide energy spectrum database was established for neural network training using random matrices of γ-ray energy,activity,and noise.Based on the encoder–decoder structure,a network topology based on the transformer was built,transforming the 1024-channel energy spectrum data into a 32×32 energy spectrum sequence as the model input.Through experiments and adjustments of model parameters,including the learning rate of the TBNN model,number of attention heads,and number of network stacking layers,the overall recognition rate reached 98.7%.Additionally,this database was used for training AI models such as back-propagation networks,convolutional neural networks,residual networks,and long shortterm memory neural networks,with overall recognition rates of 92.8%,95.3%,96.3%,and 96.6%,respectively.This indicates that the TBNN model exhibited better nuclide identification among these AI models,providing an important reference and theoretical basis for the practical application of transformers in the qualitative and quantitative analysis of the γ spectrum.
基金Earth Observation and Navigation Special,Research on Low Temperature Superconducting Aeromagnetic Vector Gradient Observation Technology(2021YFB3900201)projectState Key Laboratory of Remote Sensing Science project.
文摘In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw attitude changes most dramatically and corresponds best to the magnetic data anomaly interval.Based on this finding,we solved the compensation model using least squares fitting and Huber's parametric fitting.By comparison,we found that the Huber parametric fit not only eliminates the interference introduced by attitude changes but also retains richer anomaly source information and therefore obtains a higher signal-to-noise ratio.The experimental results show that the quality of the magnetometry data obtained by using the compensation method proposed in this paper has been significantly improved,and the mean value of its improvement ratio can reach 118.93.
