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Pushing the Boundaries of Sustainability:Advances in Hyperspectral Remote Sensing for Ecosystem and Natural Resource Management 认领 引用
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作者 Yongfei Han Hailin Zhang +2 位作者 Xiushan Sun Ning Luo Dengbiao Ma 《Journal of Environmental & Earth Sciences》 CAS 2026年第1期324-353,共30页
Also known as imaging spectroscopy,hyperspectral remote sensing is becoming a key technology for ecosystem and natural resource management sustainability.Hyperspectral observations can be used to measure tens to hundr... Also known as imaging spectroscopy,hyperspectral remote sensing is becoming a key technology for ecosystem and natural resource management sustainability.Hyperspectral observations can be used to measure tens to hundreds of narrow bands of reflected radiation to resolve diagnostic absorption bands and spectral shape variations associated with vegetation pigments,water status of the canopy,biochemical composition,mineralogies,and organic matter of the soil,and water quality constituents of aquatic water.These abilities allow one to make a transition between the descriptive mapping and the functional monitoring,the anticipation of stress and disturbance early,and the more accurate attribution of environmental change.This summary encompasses improvements on the entire sensor-to-product pipeline,including field and UAV(Unmanned Aerial Vehicle)system platform developments,airborne campaign and spaceborne mission developments,calibration and analysis-ready preprocessing improvements,empirical learning methodology improvements,radiative transfer-based inversion method,spectral unmixing,deep learning,and hybrid physics-machine learning.We underline the increased importance of the combination of data with LiDAR(Light Detection and Ranging),SAR(Synthetic Aperture Radar),and thermal features aimed at decreasing the level of ambiguity and enhancing operational resilience.Applications based on decision are evaluated in terms of biodiversity and habitat evaluation,vegetation functionality and restoration,stress and disturbance,sustainable agricultural production,inland water quality and coastal water quality,land degradation and soil status,and environmental impact assessment.Inhibiting factors to operational adoption have always been perceived to be domain shift by region,season,and sensor,ground truth and validation,mixed pixels and scale mismatch,preprocessing sensitivities,and desirable uncertainty quantification and product output that is interpretable.We conclude with the scalability,sustainability,service priorities,such as harmonization standards,representative benchmarking,uncertainty-aware delivery,and co-design of stakeholders. 展开更多
关键词 Hyperspectral Remote Sensing Imaging Spectroscopy Ecosystem Monitoring Data Fusion Uncertainty Quantification
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River Surface Change Detection Using a Graph Structure-Aware Transformer with Multi-Temporal Spectral Remote Sensing Data 认领 引用 被引量：1
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作者 SU Yuanchao HU Chenduo +4 位作者 YAN Lin JIANG Mengying GAO Jianjian FENG Xiaohua TIAN Yuansheng 《Journal of Geodesy and Geoinformation Science》 CSCD 2025年第4期83-101,共19页
River surface change detection is a vital technology for watershed monitoring,enabling real-time identification of dynamic hydrological variations through remote sensing image analysis.This technology facilitates the ... River surface change detection is a vital technology for watershed monitoring,enabling real-time identification of dynamic hydrological variations through remote sensing image analysis.This technology facilitates the precise assessment of water resource utilization and ecological environmental changes,which are essential for sustainable water management.However,accurately identifying river surfaces remains a challenge,as it requires simultaneously considering both local and global information within the river area.Recently,we developed a Graph Generative Structure-aware Transformer(GraphGST)for hyperspectral image classification.Specifically,we employ the GraphGST as a component of the new approach,leveraging it to capture local-global correlations by feature representation,thereby facilitating river surface change detection in both multispectral and hyperspectral images.This approach is referred to as GraphGST-river.This paper adopts three hyperspectral and multispectral image datasets from GF-5 and Jilin-I GF-02B satellites to validate the effectiveness of the new GraphGST-river.In these confirmatory experiments,our method achieved average accuracies of 99.81%,99.91%,and 99.72%,surpassing existing state-of-the-art approaches.These results demonstrate the superiority of our approach in refining water body contour recognition and enhancing overall change detection performance. 展开更多
关键词 remote sensing river surface change detection transformer deep learning multi-temporal image processing
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Bayesian and Geostatistical Approaches to Combining Categorical Data Derived from Visual and Digital Processing of Remotely Sensed Images 认领 引用 被引量：1
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作者 ZHANG Jingxiong LI Deren 《Geo-Spatial Information Science》 EI 2005年第2期90-97,137,共8页
This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification.By experiment with aerial photographs and Landsat TM data,accuracy o... This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification.By experiment with aerial photographs and Landsat TM data,accuracy of spectral,spatial,and combined classification results was evaluated.It was confirmed that the incorporation of spatial information in spectral classification increases accuracy significantly.Secondly,through test with a 5-class and a 3-class classification schemes,it was revealed that setting a proper semantic framework for classification is fundamental to any endeavors of categorical mapping and the most important factor affecting accuracy.Lastly,this paper promotes non-parametric methods for both definition of class membership profiling based on band-specific histograms of image intensities and derivation of spatial probability via indicator kriging,a non-parametric geostatistical technique. 展开更多
关键词 Bayesian remote sensing image visual and digital processing
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Review of large scale crop remote sensing monitoring based on MODIS data 认领 引用 被引量：1
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作者 刘丹 杨风暴 +2 位作者 李大威 梁若飞 冯裴裴 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2016年第2期193-204,共12页
China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this pap... China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this paper,by selecting moderateresolution imaging spectroradiometer(MODIS)data as the main information source,on the basis of spectral and biological characteristics mechanism of the crop,and using the freely available advantage of hyperspectral temporal MODIS data,conduct large scale agricultural remote sensing monitoring research,develop applicable model and algorithm,which can achieve large scale remote sensing extraction and yield estimation of major crop type information,and improve the accuracy of crop quantitative remote sensing.Moreover,the present situation of global crop remote sensing monitoring based on MODIS data is analyzed.Meanwhile,the climate and environment grid agriculture information system using large-scale agricultural condition remote sensing monitoring has been attempted preliminary. 展开更多
关键词 moderate-resolution imaging spectroradiometer(MODIS)data remote sensing monitoring crops
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A RBF classification method of remote sensing image based on genetic algorithm 认领 引用 被引量：1
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作者 万鲁河 张思冲 +1 位作者 刘万宇 臧淑英 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2006年第6期711-714,共4页
The remote sensing image classification has stimulated considerable interest as an effective method for better retrieving information from the rapidly increasing large volume, complex and distributed satellite remote ... The remote sensing image classification has stimulated considerable interest as an effective method for better retrieving information from the rapidly increasing large volume, complex and distributed satellite remote imaging data of large scale and cross-time, due to the increase of remote image quantities and image resolutions. In the paper, the genetic algorithms were employed to solve the weighting of the radial basis faction networks in order to improve the precision of remote sensing image classification. The remote sensing image classification was also introduced for the GIS spatial analysis and the spatial online analytical processing (OLAP), and the resulted effectiveness was demonstrated in the analysis of land utilization variation of Daqing city. 展开更多
关键词 genetic algorithm radial basis function networks remote sensing image classification spatial online analytical processing GIS
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Application of PCA Numalgorithm in Remote Sensing Image Processing 认领 引用
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作者 Hong Dai 《Modern Electronic Technology》 2023年第1期17-21,共5页
A numerical algorithm of principal component analysis (PCA) is proposed and its application in remote sensing image processing is introduced: (1) Multispectral image compression;(2) Multi-spectral image noise cancella... A numerical algorithm of principal component analysis (PCA) is proposed and its application in remote sensing image processing is introduced: (1) Multispectral image compression;(2) Multi-spectral image noise cancellation;(3) Information fusion of multi-spectral images and spot panchromatic images. The software experiments verify and evaluate the effectiveness and accuracy of the proposed algorithm. 展开更多
关键词 PCA numerical algorithm Remote sensing image processing Multi-spectral image
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A method of remote sensing image water segmentation based on adaptive morphological elliptical structuring elements 认领 引用 被引量：1
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作者 WEN Hao-tian WANG Xiao-peng 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2020年第3期236-243,共8页
The use of visible and infrared remote sensing images to calculate the water area is an effective means to grasp the basic situation of water resources,and water segmentation is the premise of statistics.Generally,the... The use of visible and infrared remote sensing images to calculate the water area is an effective means to grasp the basic situation of water resources,and water segmentation is the premise of statistics.Generally,the edge features of the water in the remote sensing images are complex.When the traditional morphology is used for image segmentation,it is easy to change the image edge and affect the accuracy of image segmentation because the fixed structuring elements are used to perform morphological operations on the image.To segment water in the remote sensing image accurately,a remote sensing image water segmentation method based on adaptive morphological elliptical structuring elements is proposed.Firstly,the eigenvalue and eigenvector of the image are estimated by linear structure tensor,and the elliptical structuring elements are constructed by the eigenvalue and eigenvector.Then adaptive morphological operations are defined,combining the close operation to eliminate the influence of dark detail noise on water without overstretching the water edge,so that the water edge can be maintained more accurately.Finally,on this basis,the water area can be segmented by gray slice.The experimental results show that the proposed method has higher segmentation accuracy and the average segmentation error is less than 1.43%. 展开更多
关键词 image processing adaptive morphology elliptical structuring elements remote sensing images water segmentation gray slice
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Framework of SAGI Agriculture Remote Sensing and Its Perspectives in Supporting National Food Security 认领 引用 被引量：17
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作者 SHI Yun JI Shun-ping +5 位作者 SHAO Xiao-wei TANG Hua-jun WU Wen-bin YANG Peng ZHANG Yong-jun Shibasaki Ryosuke 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2014年第7期1443-1450,共8页
Remote sensing, in particular satellite imagery, has been widely used to map cropland, analyze cropping systems, monitor crop changes, and estimate yield and production. However, although satellite imagery is useful w... Remote sensing, in particular satellite imagery, has been widely used to map cropland, analyze cropping systems, monitor crop changes, and estimate yield and production. However, although satellite imagery is useful within large scale agriculture applications （such as on a national or provincial scale）, it may not supply sufifcient information with adequate resolution, accurate geo-referencing, and specialized biological parameters for use in relation to the rapid developments being made in modern agriculture. Information that is more sophisticated and accurate is required to support reliable decision-making, thereby guaranteeing agricultural sustainability and national food security. To achieve this, strong integration of information is needed from multi-sources, multi-sensors, and multi-scales. In this paper, we propose a new framework of satellite, aerial, and ground-integrated （SAGI） agricultural remote sensing for use in comprehensive agricultural monitoring, modeling, and management. The prototypes of SAGI agriculture remote sensing are ifrst described, followed by a discussion of the key techniques used in joint data processing, image sequence registration and data assimilation. Finally, the possible applications of the SAGI system in supporting national food security are discussed. 展开更多
关键词 SAGI agriculture remote sensing multi-platform data processing food security
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Technical progress of China’s national remote sensing mapping:from mapping western China to national dynamic mapping 认领 引用 被引量：6
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作者 Jixian Zhang Haiyan Gu +1 位作者 Wei Hou Chunquan Cheng 《Geo-Spatial Information Science》 SCIE EI CSCD 2021年第1期121-133,I0013,共13页
Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system ... Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system has been established.In this project,many problems have been solved through technological innovation,such as block adjustment with scarce control points,large-scale aerial/satellite image mapping,and intelligent interpretation of multi-source images.Several softwares were developed,e.g.PixelGrid for aerial/satellite image mapping in a large area,FeatureStation for the integration of multi-source data in the complex terrain areas,and an airborne multi-band and multi-polarization interferometric data acquisition system for SAR mapping.For the first time,full coverage of 1:50,000 topographic data of China’s land territory has been produced,which means the geospatial framework of digital China is basically completed.With the implementation of other key national plans and projects(i.e.national geographic conditions monitoring and national remote sensing mapping),the focus has changed from MWC to national dynamic mapping.Accordingly,a dynamic mapping system is established.The data acquisition capability has developed from a single source to multiple sources and multiple modalities.The mapping capability has developed into dynamic mapping,and the capability for database update shows the characteristics of collaboration.The national geographic condition monitoring creates a multi-scale index system for statistical analysis for various needs.A multi-level and multi-dimensional technical system for statistical computing and decision-making service is developed for the transformation from dynamic monitoring to information service.In this paper,we give a brief introduction about the recent development of remote sensing mapping in China with respect to data acquisition,map production,and information service.The purpose of this paper is to motivate the establishment of theory and method for remote sensing mapping,technical and equipment in the smart mapping era,to improve the capability of perceiving,analyzing,mining,and applying geographic data,and to promote the intelligent development of geographic surveying and mapping. 展开更多
关键词 Remote sensing mapping mapping western China national dynamic monitoring data acquisition image interpretation information service
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Sub-pixel change detection for urban land-cover analysis via multi-temporal remote sensing images 认领 引用 被引量：6
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作者 Peijun DU Sicong LIU +2 位作者 Pei LIU Kun TAN Liang CHENG 《Geo-Spatial Information Science》 EI 2014年第1期26-38,共13页
Conventional change detection approaches are mainly based on per-pixel processing,which ignore the sub-pixel spectral variation resulted from spectral mixture.Especially for medium-resolution remote sensing images use... Conventional change detection approaches are mainly based on per-pixel processing,which ignore the sub-pixel spectral variation resulted from spectral mixture.Especially for medium-resolution remote sensing images used in urban landcover change monitoring,land use/cover components within a single pixel are usually complicated and heterogeneous due to the limitation of the spatial resolution.Thus,traditional hard detection methods based on pure pixel assumption may lead to a high level of omission and commission errors inevitably,degrading the overall accuracy of change detection.In order to address this issue and find a possible way to exploit the spectral variation in a sub-pixel level,a novel change detection scheme is designed based on the spectral mixture analysis and decision-level fusion.Nonlinear spectral mixture model is selected for spectral unmixing,and change detection is implemented in a sub-pixel level by investigating the inner-pixel subtle changes and combining multiple composition evidences.The proposed method is tested on multi-temporal Landsat Thematic Mapper and China–Brazil Earth Resources Satellite remote sensing images for the land-cover change detection over urban areas.The effectiveness of the proposed approach is confirmed in terms of several accuracy indices in contrast with two pixel-based change detection methods(i.e.change vector analysis and principal component analysis-based method).In particular,the proposed sub-pixel change detection approach not only provides the binary change information,but also obtains the characterization about change direction and intensity,which greatly extends the semantic meaning of the detected change targets. 展开更多
关键词 change detection sub-pixel level processing multi-temporal images spectral mixture model back propagation neural network remote sensing
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Digital Watermarking Secure Scheme for Remote Sensing Image Protection 认领 引用 被引量：10
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作者 Guanghui Yuan Qi Hao 《China Communications》 SCIE CSCD 2020年第4期88-98,共11页
As a means of copyright protection for multimedia data, digital watermarking technology has attracted more and more attention in various research fields. Researchers have begun to explore the feasibility of applying i... As a means of copyright protection for multimedia data, digital watermarking technology has attracted more and more attention in various research fields. Researchers have begun to explore the feasibility of applying it to remote sensing data recently. Because of the particularity of remote sensing image, higher requirements are put forward for its security and management, especially for the copyright protection, illegal use and authenticity identification of remote sensing image data. Therefore, this paper proposes to use image watermarking technology to achieve comprehensive security protection of remote sensing image data, while the use of cryptography technology increases the applicability and security of watermarking technology. The experimental results show that the scheme of remote sensing image digital watermarking technology has good performance in the imperceptibility and robustness of watermarking. 展开更多
关键词 data security watermark remote sensing image protection
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Salient Object Detection from Multi-spectral Remote Sensing Images with Deep Residual Network 认领 引用 被引量：18
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作者 Yuchao DAI Jing ZHANG +2 位作者 Mingyi HE Fatih PORIKLI Bowen LIU 《Journal of Geodesy and Geoinformation Science》 2019年第2期101-110,共10页
alient object detection aims at identifying the visually interesting object regions that are consistent with human perception. Multispectral remote sensing images provide rich radiometric information in revealing the ... alient object detection aims at identifying the visually interesting object regions that are consistent with human perception. Multispectral remote sensing images provide rich radiometric information in revealing the physical properties of the observed objects, which leads to great potential to perform salient object detection for remote sensing images. Conventional salient object detection methods often employ handcrafted features to predict saliency by evaluating the pixel-wise or superpixel-wise contrast. With the recent use of deep learning framework, in particular, fully convolutional neural networks, there has been profound progress in visual saliency detection. However, this success has not been extended to multispectral remote sensing images, and existing multispectral salient object detection methods are still mainly based on handcrafted features, essentially due to the difficulties in image acquisition and labeling. In this paper, we propose a novel deep residual network based on a top-down model, which is trained in an end-to-end manner to tackle the above issues in multispectral salient object detection. Our model effectively exploits the saliency cues at different levels of the deep residual network. To overcome the limited availability of remote sensing images in training of our deep residual network, we also introduce a new spectral image reconstruction model that can generate multispectral images from RGB images. Our extensive experimental results using both multispectral and RGB salient object detection datasets demonstrate a significant performance improvement of more than 10% improvement compared with the state-of-the-art methods. 展开更多
关键词 deep residual network salient object detection top-down model remote sensing image processing
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Extraction of Desertification Information in Hulun Buir Based on MODIS Image Data 认领 引用 被引量：4
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作者 孟翔冲 姜琦刚 +4 位作者 齐霞 王斌 吴阳春 李根军 杨佳佳 《Agricultural Science & Technology》 CAS 2012年第1期233-237,共5页
[Objective] To extract desertification information of Hulun Buir region based on MODIS image data. [Method] Based on MODIS image data with the spatial res- olution of 1 km, 5 indicators which could reflect different d... [Objective] To extract desertification information of Hulun Buir region based on MODIS image data. [Method] Based on MODIS image data with the spatial res- olution of 1 km, 5 indicators which could reflect different desertification features were selected to conduct inversion. The desertification information of Hulun Buir region was extracted by decision tree classification. [Result] The desertification area of Hu- lun Buir region is 33 862 km2, accounting for 24% of the total area, and it is mainly dominated by sandiness desertification. Though field verification and mining point validation of high-resolution interpretation data, the overall accuracy of this evaluation is above 89%. [Conclusion] Evaluation method used in this study is not only effectively for large scale regional desertification monitoring but also has a better evaluation performance. 展开更多
关键词 Desertification MODiS image data Remote sensing, Decision tree,Inversion
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A new integrated 3D modeling method based on multisource heterogeneous geological data and its application 认领 引用
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作者 Zhao-yang Ma Sen Zhang +3 位作者 Jie Li Ya-kai Qiao Hua-feng Sun Fateh Bouchaala 《China Geology》 CAS CSCD 2026年第2期383-399,共17页
With continuous advancement in geological studies,three-dimensional(3D)geological modeling technology based on big data and artificial intelligence(AI)has become a prominent focus in the interdisciplinary field of ear... With continuous advancement in geological studies,three-dimensional(3D)geological modeling technology based on big data and artificial intelligence(AI)has become a prominent focus in the interdisciplinary field of earth and information sciences.Through the analysis and comparison of existing 3D modeling methods,this study introduces a high-precision 3D geological modeling approach.The new method leverages advanced computing technologies,including multisource heterogeneous data processing,integrated model databases,seamless splicing of local models,and cluster analysis.Furthermore,it enables unified 3D visualization of subsurface and surface conditions,providing new insights into disaster prevention,mitigation,and intelligent mineral exploration.To validate its practicality,this study conducts 3D geological modeling of the X area within the Sichuan Basin,China.The data sources include remote sensing images,geological maps,geophysical data,borehole data,and X-ray fluorescence(XRF)spectroscopy data.Preliminary exploration in the X area has successfully identified new mineralization belts,verifying the feasibility and effectiveness of the new 3D geological modeling method that integrates big data processing and intelligent techniques. 展开更多
关键词 Big data Artificial intelligence Geological modeling Multisource heterogeneous data Intelligent mineral exploration Remote sensing images Geological maps Geophysical data 3D visualization
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AN IMPROVED ALGORITHM FOR SUPERVISED FUZZY C-MEANS CLUSTERING OF REMOTELY SENSED DATA 认领 引用 被引量：1
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作者 ZHANG Jingxiong Roger P Kirby 《Geo-Spatial Information Science》 2000年第1期39-44,共6页
This paper describes an improved algorithm for fuzzy c-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is de- creased as comparing with that by a conventional... This paper describes an improved algorithm for fuzzy c-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is de- creased as comparing with that by a conventional algorithm: that is, the classification accura- cy is increased. This is achieved by incorporating covariance matrices at the level of individual classes rather than assuming a global one. Empirical results from a fuzzy classification of an Edinburgh suburban land cover confirmed the improved performance of the new algorithm for fuzzy c-means clustering, in particular when fuzziness is also accommodated in the assumed reference data. 展开更多
关键词 remotely sensed data (images) classification fuzzyc-means clustering fuzzy membership values (FMVs) Mahalanobis distances covariance matrix
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THE APPLICATION OF REMOTE SENSING TECHNIQUE ON GEOLOGICAL INVESTIGATION OF PLACER DEPOSIT 认领 引用
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作者 万恩璞 溥立群 +2 位作者 王野乔 陈春 刘殿伟 《Chinese Geographical Science》 SCIE EI 1991年第2期72-84,共13页
The practice has proved that it is an economic and effective method to investigate placer gold deposit by using multi-level information sources of remote sensing and multi-variate analysis methods, especially for the ... The practice has proved that it is an economic and effective method to investigate placer gold deposit by using multi-level information sources of remote sensing and multi-variate analysis methods, especially for the area with a sparse population and difficult condition like the Da Hinggan Mountains, China.The information sources used in our work includes Landsat TM, aerial infrared photography and their mosaic image maps and enlarged photos with different scales. According to statistic data, in the study area the gold-bearing rocks are mainly granite, alaskite, granodiorite and some old metamorphic rocks. On gold-bearing geological structures, the fault zones in the four directions (NE, NNE, NW and EW) are obvious, in which NNE and EW are the most key fault zones. On fluvial geomorphology the flow courses stored placer are in the tributaries of the 4th and 5th levels, especially in straight or slight curve reaches. On the basis of analysis the interpretative signs were set up, and the interpretative 展开更多
关键词 remote sensing Nenjiang River placer gold deposit image processing interpretative signs perspective effect
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Delineation of groundwater potential zones using remote sensing and Geographic Information Systems(GIS)in Kadaladi region,Southern India 认领 引用 被引量：1
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作者 Stephen Pitchaimani V Narayanan MSS +2 位作者 Abishek RS Aswin SK Jerin Joe RJ 《Journal of Groundwater Science and Engineering》 2024年第2期147-160,共14页
The primary objective of this research is to delineate potential groundwater recharge zones in the Kadaladi taluk of Ramanathapuram,Tamil Nadu,India,using a combination of remote sensing and Geographic Information Sys... The primary objective of this research is to delineate potential groundwater recharge zones in the Kadaladi taluk of Ramanathapuram,Tamil Nadu,India,using a combination of remote sensing and Geographic Information Systems(GIS)with the Analytical Hierarchical Process(AHP).Various factors such as geology,geomorphology,soil,drainage,density,lineament density,slope,rainfall were analyzed at a specific scale.Thematic layers were evaluated for quality and relevance using Saaty's scale,and then inte-grated using the weighted linear combination technique.The weights assigned to each layer and features were standardized using AHP and the Eigen vector technique,resulting in the final groundwater potential zone map.The AHP method was used to normalize the scores following the assignment of weights to each criterion or factor based on Saaty's 9-point scale.Pair-wise matrix analysis was utilized to calculate the geometric mean and normalized weight for various parameters.The groundwater recharge potential zone map was created by mathematically overlaying the normalized weighted layers.Thematic layers indicating major elements influencing groundwater occurrence and recharge were derived from satellite images.2 Results indicate that approximately 21.8 km of the total area exhibits high potential for groundwater recharge.Groundwater recharge is viable in areas with moderate slopes,particularly in the central and southeastern regions. 展开更多
关键词 Groundwater Satellite image Remote sensing GIS techniques Analytical Hierarchy Process(AHP)
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Identification of groundwater potential in hard rock aquifer systems using Remote Sensing, GIS and Magnetic Survey in Veppanthattai, Perambalur, Tamilnadu 认领 引用 被引量：1
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作者 Muthamilselvan A Anamika Sekar Emmanuel Ignatius 《Journal of Groundwater Science and Engineering》 2022年第4期367-380,共14页
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
关键词 Groundwater exploration Remote Sensing and GIS Magnetic data Hard rock terrain Analytical hierarchy process Radially averaged power spectrum
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Computationally Efficient Gradient-Aware Hyperspectral Image Denoising Using Center-Difference Convolutional Networks 认领 引用
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作者 Mahmood Ashraf Nuha Zamzami +4 位作者 Shtwai Alsubai Raed Alharthi Muhammad Umer Yunyoung Nam Yongwon Cho 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第6期1173-1207,共35页
Hyperspectral image(HSI)denoising is a crucial preprocessing step that significantly enhances the performance of downstream applications,such as object detection and classification.Whereas deep neural networks have ac... Hyperspectral image(HSI)denoising is a crucial preprocessing step that significantly enhances the performance of downstream applications,such as object detection and classification.Whereas deep neural networks have achieved remarkable performance in HSI denoising,many existing models rely mostly on vanilla convolutions,which often fail to capture fine-grained noise patterns and structural details in real-time HSIs.To address these limitations,we propose a novel Center-Difference Convolutional Network(CDCN)designed to effectively suppress various noise types while preserving the inherent structure of HSIs.By leveraging center-difference convolution(CDC),our model captures both gradient and intensity information in the spatial domain,enabling better discrimination of subtle noise characteristics.The CDCN architecture processes 3D HSI cubes through separable 3D convolutions,efficiently extracting spatial-spectral features with minimal computational overhead.Additionally,a spatial-spectral attention mechanism is integrated to further refine feature representation.We evaluate the proposed method on one simulated dataset(Kennedy Space Center)and two real-world datasets(Pavia Center and Houston-2018).Experimental results demonstrate that CDCN consistently outperforms existing state-of-the-art approaches,achieving superior denoising performance while maintaining spectral-spatial information.Ablation studies also validate the effectiveness of CDC and attention mechanisms in enhancing denoising capability over standard convolutional baselines. 展开更多
关键词 Attention mechanism center difference network image denoising real-time image processing hyperspectral imaging remote sensing edge-preserving filtering
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A Review of Satellite Remote Sensing Monitoring Methods for Sea Surface Oil Spill 认领 引用 被引量：1
20
作者 WANG Xinsheng WANG Chenxu +3 位作者 ZHAO Yinan LUO Qinghua LIU Zhiyong ZHU Zhiquan 《Aerospace China》 2018年第3期11-16,共6页
Using satellite remote sensing to monitor oil spill on the sea is an advanced means of oil spill monitoring, and it has the characteristics of wide coverage, speediness and real time, synchronization, continuity, and ... Using satellite remote sensing to monitor oil spill on the sea is an advanced means of oil spill monitoring, and it has the characteristics of wide coverage, speediness and real time, synchronization, continuity, and low cost. Hence, accelerating the research on this technology and establishing a satellite remote sensing monitoring mechanism suitable for oil spill emergency situations is of great significance to improve China's oil spill monitoring capability and prevent or reduce the pollution damage caused by oil spill in the marine environment.This paper analyzes and studies the current situation using satellite remote sensing to monitor oil spills at home and abroad. Based on the basic principle of satellite remote sensing, this paper systematically studies the satellite remote sensing monitoring oil spill principles, satellite data processing methods and oil spill information identification, and summarizes an oil spill identification system that can realize oil spill information reproduction. This system provides an important means of support for the handling of oil spill accidents. 展开更多
关键词 satellite remote sensing oil spill radar satellite spectral satellite image processing
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