The marshes of southern Iraq are of great value due to their roles in the economy,environment,heritage,tourism,and agriculture.However,the region has witnessed remarkable transformations in land cover,influenced by hu...The marshes of southern Iraq are of great value due to their roles in the economy,environment,heritage,tourism,and agriculture.However,the region has witnessed remarkable transformations in land cover,influenced by human interventions and natural environmental factors.In this research,the Central Marshlands were selected for study and monitoring.These Marshes form the Mesopotamian Marshes,a vital part of the Tigris-Euphrates river system.This area 2 formerly covered an area of approximately 3,000 km and was once home to the lives of Marsh Arabs and their animals.The primary objective of this study was to compile a set of satellite images covering the same marshland region over several decades.The data used includes images captured by various Landsat missions:MSS(1975),TM(1983&1993),ETM+(2003),and the Operational Land Imager(OLI)from Landsat 8(2015).Satellite images were combined and pre-processed through steps such as layer stacking to create composite images from multiple bands.Several image classification methods were applied,and the classification results showed a significant and unprecedented increase in the percentage of water in the marsh,reaching 16%in 2003.This was combined with vegetation identification techniques,including the identification of vegetation boundaries to detect areas of dense vegetation.In addition,the relative depth of the water was measured to estimate marsh water levels,with the best result obtained in 2003.The normalized mean vegetation index(NDVI)calculated in this study had its best value in 1984 due to the spread of reeds and papyrus during this period.Papyrus is the raw material in the sugar industry,providing a significant economic boost.展开更多
INTRODUCTION.On May 1st,2024,around 2:10 a.m.,a catastrophic collapse occurred along the Meilong Expressway near Meizhou City,Guangdong Province,China,at coordinates 24°29′24″N and 116°40′25″E.This colla...INTRODUCTION.On May 1st,2024,around 2:10 a.m.,a catastrophic collapse occurred along the Meilong Expressway near Meizhou City,Guangdong Province,China,at coordinates 24°29′24″N and 116°40′25″E.This collapse resulted in a pavement failure of approximately 17.9 m in length and covering an area of about 184.3 m^(2)(Chinanews,2024).展开更多
The evolution of land use patterns and the emergence of urban heat islands(UHI)over time are critical issues in city development strategies.This study aims to establish a model that maps the correlation between change...The evolution of land use patterns and the emergence of urban heat islands(UHI)over time are critical issues in city development strategies.This study aims to establish a model that maps the correlation between changes in land use and land surface temperature(LST)in the Mashhad City,northeastern Iran.Employing the Google Earth Engine(GEE)platform,we calculated the LST and extracted land use maps from 1985 to 2020.The convolutional neural network(CNN)approach was utilized to deeply explore the relationship between the LST and land use.The obtained results were compared with the standard machine learning(ML)methods such as support vector machine(SVM),random forest(RF),and linear regression.The results revealed a 1.00°C–2.00°C increase in the LST across various land use categories.This variation in temperature increases across different land use types suggested that,in addition to global warming and climatic changes,temperature rise was strongly influenced by land use changes.The LST surge in built-up lands in the Mashhad City was estimated to be 1.75°C,while forest lands experienced the smallest increase of 1.19°C.The developed CNN demonstrated an overall prediction accuracy of 91.60%,significantly outperforming linear regression and standard ML methods,due to the ability to extract higher level features.Furthermore,the deep neural network(DNN)modeling indicated that the urban lands,comprising 69.57%and 71.34%of the studied area,were projected to experience extreme temperatures above 41.00°C and 42.00°C in the years 2025 and 2030,respectively.In conclusion,the LST predictioin framework,combining the GEE platform and CNN method,provided an effective approach to inform urban planning and to mitigate the impacts of UHI.展开更多
Water is an essential natural resource without which life wouldn’t exist.The study aims to identify groundwater potential areas in Vepapanthattai taluk of Perambalur district,Tamil Nadu,India,using analytic hierarchy...Water is an essential natural resource without which life wouldn’t exist.The study aims to identify groundwater potential areas in Vepapanthattai taluk of Perambalur district,Tamil Nadu,India,using analytic hierarchy process(AHP)model.Remote sensing and magnetic parameters have been used to determine the evaluation indicators for groundwater occurrence under the ArcGIS environment.Groundwater occurrence is linked to structural porosity and permeability over the predominantly hard rock terrain,making magnetic data more relevant for locating groundwater potential zones in the research area.NE-SW and NW-SE trending magnetic breaks derived from reduction to pole map are found to be more significant for groundwater exploration.The lineaments rose diagram indicates the general trend of the fracture to be in the NE-SW direction.Assigned normalised criteria weights acquired using the AHP model was used to reclassify the thematic layers.As a result,the taluk’s low,moderate,and high potential zones cover 25.08%,25.68%and 49.24%of the study area,respectively.The high potential zones exhibit characteristics favourable for groundwater infiltration and storage,with factors as gentle slope of<3°,high lineament densities,magnetic breaks,magnetic low zones as indicative of dykes and cracks,lithology as colluvial deposits and land surface with dense vegetation.The depth of the fracture zones was estimated using power spectrum and Euler Deconvolution method.The groundwater potential mapping results were validated using groundwater level data measured from the wells,which indicated that the groundwater potential zoning results are consistent with the data derived from the real world.展开更多
Watershed characteristics and land use/land cover study is necessary, for improved decision-making and for the resource management strategies. The methodology necessitates the provision of the base map from SOI toposh...Watershed characteristics and land use/land cover study is necessary, for improved decision-making and for the resource management strategies. The methodology necessitates the provision of the base map from SOI toposheet, delineation of drainage, preparation of slope and flow direction map using ASTER data and for the land use/land cover change detection, visual interpretation has been carried out using IRSP6-LISS-III data of 2005 and 2015. The land use/land cover analysis discloses several categories of land cover as well as land use present in Govindsagar variation from 2005 to 2015. The study area is mainly cramped to cultivated land and uncultivated land which show changes since last decade, there is an increase in cultivated land of about 4.86% of the geographical area where as uncultivated land (fallow land) shows a decline of 1.61% of the total geographical area, morphometric analysis reveals that area has impermeable subsurface materials and mountainous relief with dendritic drainage pattern with low surface runoff.展开更多
Remote Sensing (RS) and geographic information system (GIS) are now very essential tools for efficient planning and management and handling a range of data simultaneously in a time- and cost-efficient manner for targe...Remote Sensing (RS) and geographic information system (GIS) are now very essential tools for efficient planning and management and handling a range of data simultaneously in a time- and cost-efficient manner for targeting of groundwater, which assists in measuring, monitoring, and conserving groundwater resources. Survey of India toposheets, LISS-III and CARTOSAT DEM satellite imageries are used to prepare various thematic layers viz., geology, slope, lineament, drainage, and geomorphology, and were transformed to raster data using feature to raster conversion tool in ArcGIS spatial analysis, then we reclassify each raster map using reclassify tools. By using weight overlay analysis, each weighted thematic layer is statistically computed to get the ground water potential zones. Then, five different groundwater potential zones were identified, namely “very good”, “good”, “moderate”, “poor”, and “very poor”. The villages under poor groundwater potential zone and the villages under very good groundwater potential zone are finding out. The above study has clearly demonstrated the capabilities of Remote Sensing and GIS in demarcation of the different groundwater potential zones in hard rock terrain.展开更多
Soil color changes with water content due to chemical and physical reactions,making it a potential indicator for moisture estimation.By analyzing soil surface images and comparing color variations against laboratory-m...Soil color changes with water content due to chemical and physical reactions,making it a potential indicator for moisture estimation.By analyzing soil surface images and comparing color variations against laboratory-measured water content,a rapid and cost-effective method for moisture determination can be developed.Traditional moisture measurement techniques are time-consuming,so an imaging-based approach would be highly beneficial for quick decision-making.Soil color is also influenced by factors such as particle coarseness,which creates shadows and alters perceived darkness.This research introduces a novel method to isolate true soil color by analyzing the maximum color response in image pixels,minimizing shadow effects.Several equations were derived to correlate color changes with moisture content and were validated against lab measurements to ensure accuracy and simplicity.The most effective equation can be further adapted for satellite imagery by accounting for atmospheric light scattering differences between ground and satellite sensors,enabling large-scale moisture monitoring.The derived equations can be programmed into a software tool,allowing moisture estimation from simple soil surface images.The study involved controlled experiments where soil samples at varying moisture levels were imaged to establish an empirical color-moisture relationship.This method provides a fast,economical,and practical alternative to conventional techniques.However,the approach requires further refinement to account for different soil types globally.Future work should focus on adjusting the model with variables that adapt the color-moisture relationship for diverse soils,ensuring broader applicability.Once optimized,this could significantly improve moisture assessment in agriculture,environmental monitoring,and land management.展开更多
In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a ...In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a hierarchical classifier system that uses different feature inputs for specific classes and conducted a classification post-processing approach to improve its accuracy. From our statistical analysis of changes in urban land cover from 1987 to 2007, we conclude that built-up land areas have obviously increased, while farmland has seen in a continuous loss due to urban growth and human activities. A NDVI difference approach was used to extract information on changes in vegetation. A false change information elimination approach was developed based on prior knowledge and statistical analysis. The areas of vegetation cover have been in continuous decline over the past 20 years, although some measures have been adopted to protect and maintain urban vegetation. Given the stability of underground coal exploitation since 1990s, urban growth has become the major driving force in vegetation loss, which is different from the vegetation change driven by coal exploitation mainly before 1990.展开更多
Taking into account the demands of hyperspectral remote sensing(RS) image retrieval and processing, some encoding methods of spectral vector including direct encoding, feature-based encoding and tree-based encoding me...Taking into account the demands of hyperspectral remote sensing(RS) image retrieval and processing, some encoding methods of spectral vector including direct encoding, feature-based encoding and tree-based encoding methods are proposed and compared. In direct encoding, based on the analysis of binary encoding and quad-value encoding, decimal encoding is proposed. It is proved that quad-value encoding and decimal encoding are suitable to fast processing and retrieval. In absorption feature-based encoding method, five common metrics are compared. Because locations of reflection/absorption features are sensitive to noise, this method is not very effective in retrieval. In tree-based encoding methods, bitree, quadtree, octree and hextree are proposed and discussed. It is proved that 2-level octree and 2-level hextree are more effective than bitree and quadtree. Finally, quad-value encoding, decimal encoding, 2-level octree and 2-level hextree are proposed in spectral vectors encoding, similarity measure and hyperspectral RS image retrieval.展开更多
Crustal deformation and neotectonics are well-understood phenomena that happen almost on every part of the Earth and have some diastrophic effects on the Earth’s surface.To understand these effects,Remote Sensing(RS)...Crustal deformation and neotectonics are well-understood phenomena that happen almost on every part of the Earth and have some diastrophic effects on the Earth’s surface.To understand these effects,Remote Sensing(RS)and(GIS)have sharpened the human ability to learn about the scientiflc reasons for the Earth’s dynamic activities,including active tectonics and surface landform changes in spatially and temporally.展开更多
The land-cover dynamics has been quite conspicuous over the last three decades in Dehdez area, Iran. Therefore, the present study was undertaken in the Dehdez area to assess the trends of rangelands dynamics in the st...The land-cover dynamics has been quite conspicuous over the last three decades in Dehdez area, Iran. Therefore, the present study was undertaken in the Dehdez area to assess the trends of rangelands dynamics in the study area during the period 1990-2006. Two clear, cloud-free Landsat and one ASTER images were selected to classify the study area. All images were rectified to UTM zone 39, WGS84 using at least 25 well distributed ground control points and nearest neighbor resampling. Land-use/cover mapping is achieved through interpretation of Landsat TM satellite images of 1990, 1998 and ASTER image of 2006. Fieldwork was carried out to collect data for training and validating land-use/cover interpretation from satellite image of 2006, and for qualitative description of the characteristics of each land-use/cover class. In order to create a testing sample set, first of all, a set of testing points was selected randomly. A supervised classification technique with Maximum Likelihood Algorithm was applied based on 48 training samples for the image of 2006, and 42 samples for the images of 1990 and 1998 and the land-use/cover maps were produced. Error matrices were used to assess classification accuracy. The results showed rangeland covers about 30.8%, 36.7% and 45% of the total geographical area of the Dehdez area in 1990, 1998 and 2006, respectively. Overall accuracies of land-use/cover classification for 1990, 1998 and 2006 were 89.37%, 75.24% and 71.14%, respectively. Kappa values obtained were of 78.71%, 55.61% and 51.41% of accuracy for the 1990, 1998 and 2006, respectively. During 16 years span period (1990-2006) about 1738.4 ha, 383.7 ha, 32.8 ha and 890.1 ha of rangelands were converted to forest, agriculture, water and settlement. The total rich rangelands in the area, accounted for 38.5%, 44% and 42.2% in 1990, 1998 and 2006, respectively. The total poor rangeland in the area accounted for 61.5%, 56% and 57.8% in 1990, 1998 and 2006, respectively. Satellite Remote Sensing enabled the generation of a detailed rangeland map and the separation of grazing intensity levels in rangelands could be generated with the relatively little effort in areas that were difficult to access.展开更多
In recent years,decision support systems(DSSs)have successfully deployed ontologies in their architecture.The result of such a use is information systems that assist users and organizations in semi-structured decision...In recent years,decision support systems(DSSs)have successfully deployed ontologies in their architecture.The result of such a use is information systems that assist users and organizations in semi-structured decision-making activities.Visitors from throughout Iran travel to different cities and regions every year,and they need help making their choices.Some of these tourists are unable to visit the beautiful areas of the destination city due to a lack of awareness.In this study,we design an ontology-based spatial DSS to find entertainment and tourism centers in Arak,Iran.The objective is to provide users with recommendations appropriate for the location,time,age group,type of activity,and other factors.In this model,the demands and concerns of tourists have been managed by creating a domain Web Ontology Language(OWL)for entertainment centers as a knowledge base in the Protégéenvironment.The developed webbased DSS operates on a client-server architecture using technologies such as Werkzeug and Flask.As a result,it makes it possible to ontology reasoning based on the HermiT engine to choose the right center and conduct a semantic search on classes related to the appropriate point of interest.The main distinction between the proposed methodology and the previous studies on spatial DSS is that criteria are object properties in an ontology.Therefore,decision support relies on real-time reasoning rather than transforming criteria into geospatial layers.The evaluation results confirmed efficient interaction with this system,purposeful information retrieval,and rapid decision-making process.The results also indicated that searching for a POI(point of interest)in the study area using the developed system is at least 30%more successful than a search engine or social media.Moreover,to overcome the cold start problem,the proposed technique might be utilized in conjunction with the POI recommender systems.展开更多
Floods are among the worst natural catastrophes, devastating homes, businesses, public buildings, farms, and crops. Studies show that it’s not the flood itself that’s deadly but people’s vulnerability. This study i...Floods are among the worst natural catastrophes, devastating homes, businesses, public buildings, farms, and crops. Studies show that it’s not the flood itself that’s deadly but people’s vulnerability. This study investigates the Ala and Akure-Ofosu flood-prone zones;identifies elements that cause flooding in the study area;classifies each criterion by its effect;develops a flood risk map;estimates flood damage using Sentinel-1A SAR data;compares AHP results. Literature study and GIS-computer database georeferenced fieldwork data. Photos from the 2020 Sentinel 2A satellite have been organized. Built-up area, cropland, rock, the body of water, and forest Land use and cover, slope, rainfall, soil, Euclidean River Distance, and flow accumulation were mapped. These variables were integrated into a Multi-Criteria Analysis (MCA) using GIS tools, resulting in the creation of a flood risk map that categorizes the region into five risk zones: 5% of the area is identified as high-risk, 21% as low-risk, and 74% as moderate-risk. Copernicus SAR data from before and after the flood were processed on Google Earth Engine to map flood extent and ensured that the MCA map accurately reflected flood-prone areas. Periodic review, real-time flood susceptibility monitoring, early warning, and quick damage assessment are suggested to avoid flood danger and other environmental problems.展开更多
Urban tree species provide various essential ecosystem services in cities,such as regulating urban temperatures,reducing noise,capturing carbon,and mitigating the urban heat island effect.The quality of these services...Urban tree species provide various essential ecosystem services in cities,such as regulating urban temperatures,reducing noise,capturing carbon,and mitigating the urban heat island effect.The quality of these services is influenced by species diversity,tree health,and the distribution and the composition of trees.Traditionally,data on urban trees has been collected through field surveys and manual interpretation of remote sensing images.In this study,we evaluated the effectiveness of multispectral airborne laser scanning(ALS)data in classifying 24 common urban roadside tree species in Espoo,Finland.Tree crown structure information,intensity features,and spectral data were used for classification.Eight different machine learning algorithms were tested,with the extra trees(ET)algorithm performing the best,achieving an overall accuracy of 71.7%using multispectral LiDAR data.This result highlights that integrating structural and spectral information within a single framework can improve the classification accuracy.Future research will focus on identifying the most important features for species classification and developing algorithms with greater efficiency and accuracy.展开更多
This paper first analyzes the vibration environment at the spacecraft/launch vehicle(SC/LV)interface during the powered flight phase.Second,it proposes a method to enhance satellite panel stiffness.Satellite frequency...This paper first analyzes the vibration environment at the spacecraft/launch vehicle(SC/LV)interface during the powered flight phase.Second,it proposes a method to enhance satellite panel stiffness.Satellite frequency response analysis examines stiffness compatibility between the satellite(including its components)and the integrated launch stack.The environmental effect equivalence method then determines satellite ground verification test condi-tions.Ground test responses are compared with SC/LV coupling analysis results to ensure that ground tests envelope the coupling analysis results,confirming the adequacy of ground verification.展开更多
In order to combine feature extraction operations with specific hyperspectral remote sensing information processing objectives,two aspects of feature extraction were explored. Based on clustering and decision tree alg...In order to combine feature extraction operations with specific hyperspectral remote sensing information processing objectives,two aspects of feature extraction were explored. Based on clustering and decision tree algorithm,spectral absorption index (SAI),continuum-removal and derivative spectral analysis were employed to discover characterized spectral features of different targets,and decision trees for identifying a specific class and discriminating different classes were generated. By combining support vector machine (SVM) classifier with different feature extraction strategies including principal component analysis (PCA),minimum noise fraction (MNF),grouping PCA,and derivate spectral analysis,the performance of feature extraction approaches in classification was evaluated. The results show that feature extraction by PCA and derivate spectral analysis are effective to OMIS (operational modular imaging spectrometer) image classification using SVM,and SVM outperforms traditional SAM and MLC classifiers for OMIS data.展开更多
WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this pape...WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.展开更多
The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we ...The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we can evaluate the numerical model and dynamic degree model for calculating land-use change rates. Furthermore, the paper raises the possibility of revising the calculating analysis model of spatial information in order to predicate more precisely the dynamic changing level of all types of land uses. In the most concrete terms, the model is used mainly to understand changed area and changed rates (increasing or decreasing) of different land types from microcosmic angle and establish spatial distribution and spatio-temporal principles of the changing urban lands. And we will try to find out why the situation can take place by combining social and economic situations. The result indicates the calculating analysis model of spatial information can derive more accurate procedure of spatial transference and increase of all kinds of land from microcosmic angle. By this model and technology we can conduct the research of land-use spatio-temporal structure evolution more systematically and more deeply, and can obtain a satisfactory result. The result will benefit the rational planning and management of urban land use of developed coastal areas in China in the future.展开更多
The Subarnarekha River in east India experiences frequent high magnitude flooding in monsoon season.In this study,we present an in-depth analysis of flood hydrology and GIS-based flood susceptibility mapping of the en...The Subarnarekha River in east India experiences frequent high magnitude flooding in monsoon season.In this study,we present an in-depth analysis of flood hydrology and GIS-based flood susceptibility mapping of the entire catchment.About 40 years of annual peak discharge data,historical cross-sections of different gauging sites,and 12 flood conditioning factors were considered.Our flood susceptibility mapping followed an expert knowledge-based multi-parametric analytical hierarchy process(AHP)and optimized AHP-VIP methods.Peak hydrology data indicated more than 5 times higher discharge contrasted with the mean streamflow of the peak monsoon month in all hydro-monitoring stations that correspond to possible overbank flooding in the shallow semi-alluvial reaches of the Subarnarekha River.Widthdepth ratio revealed continuous changes on the channel cross-sections at decadal scale in all gauging sites.Predicted flood susceptibility map through optimized AHP-VIP method showed a great amount of areas(38%)have a high probability of flooding and demands earnest attention of administrative bodies.The AHP-VIP based flood susceptibility map was theoritically validated through AUC approach and it showed fairly high accuracy(AUC=0.93).Our study offers an exceptionally cost and time effective solution to the flooding issues in the Subarnarekha basin.展开更多
The study of drainage patterns in tectonically active regions is conducive to the prediction of regional geomorphology.Subtle subsurface changes can be detected by drainage conditions and manifested in the form of dra...The study of drainage patterns in tectonically active regions is conducive to the prediction of regional geomorphology.Subtle subsurface changes can be detected by drainage conditions and manifested in the form of drainage anomalies.The Satluj valley of Bilaspur,which is traversed by numerous faults in northwest Himalayan region,was selected to analyze the effect of active tectonics on drainage evolution.With the Persistent Scatterer Interferometric Synthetic Aperture Radar(PS-InSAR)technique,SENTINEL-1A data were used to estimate the active surface deformation between September 2015 and December 2020.The results show that the region between Barasar Thrust(BrT)and Main Central Thrust(MCT)is undergoing deformation of±12 mm/yr.The Stream Power Incision Model(SPIM)was used to predict deformation patterns.To validate the tectonic activity generated by the drainage network,seismic bvalues were calculated,indicating the accumulating stresses.This study shows the importance of drainage anomalies in tectonically active areas.When used in close combination with other seismotectonic parameters,drainage anomalies can be effective in delineating tectonically active regions.展开更多
文摘The marshes of southern Iraq are of great value due to their roles in the economy,environment,heritage,tourism,and agriculture.However,the region has witnessed remarkable transformations in land cover,influenced by human interventions and natural environmental factors.In this research,the Central Marshlands were selected for study and monitoring.These Marshes form the Mesopotamian Marshes,a vital part of the Tigris-Euphrates river system.This area 2 formerly covered an area of approximately 3,000 km and was once home to the lives of Marsh Arabs and their animals.The primary objective of this study was to compile a set of satellite images covering the same marshland region over several decades.The data used includes images captured by various Landsat missions:MSS(1975),TM(1983&1993),ETM+(2003),and the Operational Land Imager(OLI)from Landsat 8(2015).Satellite images were combined and pre-processed through steps such as layer stacking to create composite images from multiple bands.Several image classification methods were applied,and the classification results showed a significant and unprecedented increase in the percentage of water in the marsh,reaching 16%in 2003.This was combined with vegetation identification techniques,including the identification of vegetation boundaries to detect areas of dense vegetation.In addition,the relative depth of the water was measured to estimate marsh water levels,with the best result obtained in 2003.The normalized mean vegetation index(NDVI)calculated in this study had its best value in 1984 due to the spread of reeds and papyrus during this period.Papyrus is the raw material in the sugar industry,providing a significant economic boost.
基金supported by the National Natural Science Foundation of China(Nos.42371094,41907253)partially supported by the Interdisciplinary Cultivation Program of Xidian University(No.21103240005)the Postdoctoral Fellowship Program of CPSF(No.GZB20240589)。
文摘INTRODUCTION.On May 1st,2024,around 2:10 a.m.,a catastrophic collapse occurred along the Meilong Expressway near Meizhou City,Guangdong Province,China,at coordinates 24°29′24″N and 116°40′25″E.This collapse resulted in a pavement failure of approximately 17.9 m in length and covering an area of about 184.3 m^(2)(Chinanews,2024).
文摘The evolution of land use patterns and the emergence of urban heat islands(UHI)over time are critical issues in city development strategies.This study aims to establish a model that maps the correlation between changes in land use and land surface temperature(LST)in the Mashhad City,northeastern Iran.Employing the Google Earth Engine(GEE)platform,we calculated the LST and extracted land use maps from 1985 to 2020.The convolutional neural network(CNN)approach was utilized to deeply explore the relationship between the LST and land use.The obtained results were compared with the standard machine learning(ML)methods such as support vector machine(SVM),random forest(RF),and linear regression.The results revealed a 1.00°C–2.00°C increase in the LST across various land use categories.This variation in temperature increases across different land use types suggested that,in addition to global warming and climatic changes,temperature rise was strongly influenced by land use changes.The LST surge in built-up lands in the Mashhad City was estimated to be 1.75°C,while forest lands experienced the smallest increase of 1.19°C.The developed CNN demonstrated an overall prediction accuracy of 91.60%,significantly outperforming linear regression and standard ML methods,due to the ability to extract higher level features.Furthermore,the deep neural network(DNN)modeling indicated that the urban lands,comprising 69.57%and 71.34%of the studied area,were projected to experience extreme temperatures above 41.00°C and 42.00°C in the years 2025 and 2030,respectively.In conclusion,the LST predictioin framework,combining the GEE platform and CNN method,provided an effective approach to inform urban planning and to mitigate the impacts of UHI.
文摘Water is an essential natural resource without which life wouldn’t exist.The study aims to identify groundwater potential areas in Vepapanthattai taluk of Perambalur district,Tamil Nadu,India,using analytic hierarchy process(AHP)model.Remote sensing and magnetic parameters have been used to determine the evaluation indicators for groundwater occurrence under the ArcGIS environment.Groundwater occurrence is linked to structural porosity and permeability over the predominantly hard rock terrain,making magnetic data more relevant for locating groundwater potential zones in the research area.NE-SW and NW-SE trending magnetic breaks derived from reduction to pole map are found to be more significant for groundwater exploration.The lineaments rose diagram indicates the general trend of the fracture to be in the NE-SW direction.Assigned normalised criteria weights acquired using the AHP model was used to reclassify the thematic layers.As a result,the taluk’s low,moderate,and high potential zones cover 25.08%,25.68%and 49.24%of the study area,respectively.The high potential zones exhibit characteristics favourable for groundwater infiltration and storage,with factors as gentle slope of<3°,high lineament densities,magnetic breaks,magnetic low zones as indicative of dykes and cracks,lithology as colluvial deposits and land surface with dense vegetation.The depth of the fracture zones was estimated using power spectrum and Euler Deconvolution method.The groundwater potential mapping results were validated using groundwater level data measured from the wells,which indicated that the groundwater potential zoning results are consistent with the data derived from the real world.
文摘Watershed characteristics and land use/land cover study is necessary, for improved decision-making and for the resource management strategies. The methodology necessitates the provision of the base map from SOI toposheet, delineation of drainage, preparation of slope and flow direction map using ASTER data and for the land use/land cover change detection, visual interpretation has been carried out using IRSP6-LISS-III data of 2005 and 2015. The land use/land cover analysis discloses several categories of land cover as well as land use present in Govindsagar variation from 2005 to 2015. The study area is mainly cramped to cultivated land and uncultivated land which show changes since last decade, there is an increase in cultivated land of about 4.86% of the geographical area where as uncultivated land (fallow land) shows a decline of 1.61% of the total geographical area, morphometric analysis reveals that area has impermeable subsurface materials and mountainous relief with dendritic drainage pattern with low surface runoff.
文摘Remote Sensing (RS) and geographic information system (GIS) are now very essential tools for efficient planning and management and handling a range of data simultaneously in a time- and cost-efficient manner for targeting of groundwater, which assists in measuring, monitoring, and conserving groundwater resources. Survey of India toposheets, LISS-III and CARTOSAT DEM satellite imageries are used to prepare various thematic layers viz., geology, slope, lineament, drainage, and geomorphology, and were transformed to raster data using feature to raster conversion tool in ArcGIS spatial analysis, then we reclassify each raster map using reclassify tools. By using weight overlay analysis, each weighted thematic layer is statistically computed to get the ground water potential zones. Then, five different groundwater potential zones were identified, namely “very good”, “good”, “moderate”, “poor”, and “very poor”. The villages under poor groundwater potential zone and the villages under very good groundwater potential zone are finding out. The above study has clearly demonstrated the capabilities of Remote Sensing and GIS in demarcation of the different groundwater potential zones in hard rock terrain.
文摘Soil color changes with water content due to chemical and physical reactions,making it a potential indicator for moisture estimation.By analyzing soil surface images and comparing color variations against laboratory-measured water content,a rapid and cost-effective method for moisture determination can be developed.Traditional moisture measurement techniques are time-consuming,so an imaging-based approach would be highly beneficial for quick decision-making.Soil color is also influenced by factors such as particle coarseness,which creates shadows and alters perceived darkness.This research introduces a novel method to isolate true soil color by analyzing the maximum color response in image pixels,minimizing shadow effects.Several equations were derived to correlate color changes with moisture content and were validated against lab measurements to ensure accuracy and simplicity.The most effective equation can be further adapted for satellite imagery by accounting for atmospheric light scattering differences between ground and satellite sensors,enabling large-scale moisture monitoring.The derived equations can be programmed into a software tool,allowing moisture estimation from simple soil surface images.The study involved controlled experiments where soil samples at varying moisture levels were imaged to establish an empirical color-moisture relationship.This method provides a fast,economical,and practical alternative to conventional techniques.However,the approach requires further refinement to account for different soil types globally.Future work should focus on adjusting the model with variables that adapt the color-moisture relationship for diverse soils,ensuring broader applicability.Once optimized,this could significantly improve moisture assessment in agriculture,environmental monitoring,and land management.
基金supported by the National High Technology Research and Developmemt Program of China (No2007AA12Z162)the Program for New Century Excellent Talents in University, Ministry of Education (NoNCET-06-0476)the Jiangsu Provincial 333 Engineering for High Level Talents(No.BK2006505)
文摘In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a hierarchical classifier system that uses different feature inputs for specific classes and conducted a classification post-processing approach to improve its accuracy. From our statistical analysis of changes in urban land cover from 1987 to 2007, we conclude that built-up land areas have obviously increased, while farmland has seen in a continuous loss due to urban growth and human activities. A NDVI difference approach was used to extract information on changes in vegetation. A false change information elimination approach was developed based on prior knowledge and statistical analysis. The areas of vegetation cover have been in continuous decline over the past 20 years, although some measures have been adopted to protect and maintain urban vegetation. Given the stability of underground coal exploitation since 1990s, urban growth has become the major driving force in vegetation loss, which is different from the vegetation change driven by coal exploitation mainly before 1990.
文摘Taking into account the demands of hyperspectral remote sensing(RS) image retrieval and processing, some encoding methods of spectral vector including direct encoding, feature-based encoding and tree-based encoding methods are proposed and compared. In direct encoding, based on the analysis of binary encoding and quad-value encoding, decimal encoding is proposed. It is proved that quad-value encoding and decimal encoding are suitable to fast processing and retrieval. In absorption feature-based encoding method, five common metrics are compared. Because locations of reflection/absorption features are sensitive to noise, this method is not very effective in retrieval. In tree-based encoding methods, bitree, quadtree, octree and hextree are proposed and discussed. It is proved that 2-level octree and 2-level hextree are more effective than bitree and quadtree. Finally, quad-value encoding, decimal encoding, 2-level octree and 2-level hextree are proposed in spectral vectors encoding, similarity measure and hyperspectral RS image retrieval.
基金editorial office of Geodesy and Geodynamics,for constant support。
文摘Crustal deformation and neotectonics are well-understood phenomena that happen almost on every part of the Earth and have some diastrophic effects on the Earth’s surface.To understand these effects,Remote Sensing(RS)and(GIS)have sharpened the human ability to learn about the scientiflc reasons for the Earth’s dynamic activities,including active tectonics and surface landform changes in spatially and temporally.
文摘The land-cover dynamics has been quite conspicuous over the last three decades in Dehdez area, Iran. Therefore, the present study was undertaken in the Dehdez area to assess the trends of rangelands dynamics in the study area during the period 1990-2006. Two clear, cloud-free Landsat and one ASTER images were selected to classify the study area. All images were rectified to UTM zone 39, WGS84 using at least 25 well distributed ground control points and nearest neighbor resampling. Land-use/cover mapping is achieved through interpretation of Landsat TM satellite images of 1990, 1998 and ASTER image of 2006. Fieldwork was carried out to collect data for training and validating land-use/cover interpretation from satellite image of 2006, and for qualitative description of the characteristics of each land-use/cover class. In order to create a testing sample set, first of all, a set of testing points was selected randomly. A supervised classification technique with Maximum Likelihood Algorithm was applied based on 48 training samples for the image of 2006, and 42 samples for the images of 1990 and 1998 and the land-use/cover maps were produced. Error matrices were used to assess classification accuracy. The results showed rangeland covers about 30.8%, 36.7% and 45% of the total geographical area of the Dehdez area in 1990, 1998 and 2006, respectively. Overall accuracies of land-use/cover classification for 1990, 1998 and 2006 were 89.37%, 75.24% and 71.14%, respectively. Kappa values obtained were of 78.71%, 55.61% and 51.41% of accuracy for the 1990, 1998 and 2006, respectively. During 16 years span period (1990-2006) about 1738.4 ha, 383.7 ha, 32.8 ha and 890.1 ha of rangelands were converted to forest, agriculture, water and settlement. The total rich rangelands in the area, accounted for 38.5%, 44% and 42.2% in 1990, 1998 and 2006, respectively. The total poor rangeland in the area accounted for 61.5%, 56% and 57.8% in 1990, 1998 and 2006, respectively. Satellite Remote Sensing enabled the generation of a detailed rangeland map and the separation of grazing intensity levels in rangelands could be generated with the relatively little effort in areas that were difficult to access.
文摘In recent years,decision support systems(DSSs)have successfully deployed ontologies in their architecture.The result of such a use is information systems that assist users and organizations in semi-structured decision-making activities.Visitors from throughout Iran travel to different cities and regions every year,and they need help making their choices.Some of these tourists are unable to visit the beautiful areas of the destination city due to a lack of awareness.In this study,we design an ontology-based spatial DSS to find entertainment and tourism centers in Arak,Iran.The objective is to provide users with recommendations appropriate for the location,time,age group,type of activity,and other factors.In this model,the demands and concerns of tourists have been managed by creating a domain Web Ontology Language(OWL)for entertainment centers as a knowledge base in the Protégéenvironment.The developed webbased DSS operates on a client-server architecture using technologies such as Werkzeug and Flask.As a result,it makes it possible to ontology reasoning based on the HermiT engine to choose the right center and conduct a semantic search on classes related to the appropriate point of interest.The main distinction between the proposed methodology and the previous studies on spatial DSS is that criteria are object properties in an ontology.Therefore,decision support relies on real-time reasoning rather than transforming criteria into geospatial layers.The evaluation results confirmed efficient interaction with this system,purposeful information retrieval,and rapid decision-making process.The results also indicated that searching for a POI(point of interest)in the study area using the developed system is at least 30%more successful than a search engine or social media.Moreover,to overcome the cold start problem,the proposed technique might be utilized in conjunction with the POI recommender systems.
文摘Floods are among the worst natural catastrophes, devastating homes, businesses, public buildings, farms, and crops. Studies show that it’s not the flood itself that’s deadly but people’s vulnerability. This study investigates the Ala and Akure-Ofosu flood-prone zones;identifies elements that cause flooding in the study area;classifies each criterion by its effect;develops a flood risk map;estimates flood damage using Sentinel-1A SAR data;compares AHP results. Literature study and GIS-computer database georeferenced fieldwork data. Photos from the 2020 Sentinel 2A satellite have been organized. Built-up area, cropland, rock, the body of water, and forest Land use and cover, slope, rainfall, soil, Euclidean River Distance, and flow accumulation were mapped. These variables were integrated into a Multi-Criteria Analysis (MCA) using GIS tools, resulting in the creation of a flood risk map that categorizes the region into five risk zones: 5% of the area is identified as high-risk, 21% as low-risk, and 74% as moderate-risk. Copernicus SAR data from before and after the flood were processed on Google Earth Engine to map flood extent and ensured that the MCA map accurately reflected flood-prone areas. Periodic review, real-time flood susceptibility monitoring, early warning, and quick damage assessment are suggested to avoid flood danger and other environmental problems.
文摘Urban tree species provide various essential ecosystem services in cities,such as regulating urban temperatures,reducing noise,capturing carbon,and mitigating the urban heat island effect.The quality of these services is influenced by species diversity,tree health,and the distribution and the composition of trees.Traditionally,data on urban trees has been collected through field surveys and manual interpretation of remote sensing images.In this study,we evaluated the effectiveness of multispectral airborne laser scanning(ALS)data in classifying 24 common urban roadside tree species in Espoo,Finland.Tree crown structure information,intensity features,and spectral data were used for classification.Eight different machine learning algorithms were tested,with the extra trees(ET)algorithm performing the best,achieving an overall accuracy of 71.7%using multispectral LiDAR data.This result highlights that integrating structural and spectral information within a single framework can improve the classification accuracy.Future research will focus on identifying the most important features for species classification and developing algorithms with greater efficiency and accuracy.
文摘This paper first analyzes the vibration environment at the spacecraft/launch vehicle(SC/LV)interface during the powered flight phase.Second,it proposes a method to enhance satellite panel stiffness.Satellite frequency response analysis examines stiffness compatibility between the satellite(including its components)and the integrated launch stack.The environmental effect equivalence method then determines satellite ground verification test condi-tions.Ground test responses are compared with SC/LV coupling analysis results to ensure that ground tests envelope the coupling analysis results,confirming the adequacy of ground verification.
基金Projects 40401038 and 40871195 supported by the National Natural Science Foundation of ChinaNCET-06-0476 by the Program for New Century Excellent Talents in University20070290516 by the Specialized Research Fund for the Doctoral Program of Higher Education
文摘In order to combine feature extraction operations with specific hyperspectral remote sensing information processing objectives,two aspects of feature extraction were explored. Based on clustering and decision tree algorithm,spectral absorption index (SAI),continuum-removal and derivative spectral analysis were employed to discover characterized spectral features of different targets,and decision trees for identifying a specific class and discriminating different classes were generated. By combining support vector machine (SVM) classifier with different feature extraction strategies including principal component analysis (PCA),minimum noise fraction (MNF),grouping PCA,and derivate spectral analysis,the performance of feature extraction approaches in classification was evaluated. The results show that feature extraction by PCA and derivate spectral analysis are effective to OMIS (operational modular imaging spectrometer) image classification using SVM,and SVM outperforms traditional SAM and MLC classifiers for OMIS data.
文摘WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.
基金State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingNo.WKL((020)0302)
文摘The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we can evaluate the numerical model and dynamic degree model for calculating land-use change rates. Furthermore, the paper raises the possibility of revising the calculating analysis model of spatial information in order to predicate more precisely the dynamic changing level of all types of land uses. In the most concrete terms, the model is used mainly to understand changed area and changed rates (increasing or decreasing) of different land types from microcosmic angle and establish spatial distribution and spatio-temporal principles of the changing urban lands. And we will try to find out why the situation can take place by combining social and economic situations. The result indicates the calculating analysis model of spatial information can derive more accurate procedure of spatial transference and increase of all kinds of land from microcosmic angle. By this model and technology we can conduct the research of land-use spatio-temporal structure evolution more systematically and more deeply, and can obtain a satisfactory result. The result will benefit the rational planning and management of urban land use of developed coastal areas in China in the future.
文摘The Subarnarekha River in east India experiences frequent high magnitude flooding in monsoon season.In this study,we present an in-depth analysis of flood hydrology and GIS-based flood susceptibility mapping of the entire catchment.About 40 years of annual peak discharge data,historical cross-sections of different gauging sites,and 12 flood conditioning factors were considered.Our flood susceptibility mapping followed an expert knowledge-based multi-parametric analytical hierarchy process(AHP)and optimized AHP-VIP methods.Peak hydrology data indicated more than 5 times higher discharge contrasted with the mean streamflow of the peak monsoon month in all hydro-monitoring stations that correspond to possible overbank flooding in the shallow semi-alluvial reaches of the Subarnarekha River.Widthdepth ratio revealed continuous changes on the channel cross-sections at decadal scale in all gauging sites.Predicted flood susceptibility map through optimized AHP-VIP method showed a great amount of areas(38%)have a high probability of flooding and demands earnest attention of administrative bodies.The AHP-VIP based flood susceptibility map was theoritically validated through AUC approach and it showed fairly high accuracy(AUC=0.93).Our study offers an exceptionally cost and time effective solution to the flooding issues in the Subarnarekha basin.
基金Department of Science and Technology(DST)for financial assistance under the DST Women Scientist Scheme(reference no.SR/WOS-A/EA-20/2019(G))Department of Geology,Kumaun University,Nainital for providing work facilitiesMinistry of Earth Science for partial assistance under the AMF mapping program。
文摘The study of drainage patterns in tectonically active regions is conducive to the prediction of regional geomorphology.Subtle subsurface changes can be detected by drainage conditions and manifested in the form of drainage anomalies.The Satluj valley of Bilaspur,which is traversed by numerous faults in northwest Himalayan region,was selected to analyze the effect of active tectonics on drainage evolution.With the Persistent Scatterer Interferometric Synthetic Aperture Radar(PS-InSAR)technique,SENTINEL-1A data were used to estimate the active surface deformation between September 2015 and December 2020.The results show that the region between Barasar Thrust(BrT)and Main Central Thrust(MCT)is undergoing deformation of±12 mm/yr.The Stream Power Incision Model(SPIM)was used to predict deformation patterns.To validate the tectonic activity generated by the drainage network,seismic bvalues were calculated,indicating the accumulating stresses.This study shows the importance of drainage anomalies in tectonically active areas.When used in close combination with other seismotectonic parameters,drainage anomalies can be effective in delineating tectonically active regions.
