[Objective] To study the remote sensing information extraction technology for the impervious surface of Erhai basin with the aim to develop dynamic simulation platform for the formation of water pollution. [Method] Li...[Objective] To study the remote sensing information extraction technology for the impervious surface of Erhai basin with the aim to develop dynamic simulation platform for the formation of water pollution. [Method] Linear spectral separation technology was used to achieve Vd-S model solution, extracting remote sensing in- formation of the impervious surface of Erhai basin from the TM data of Landsat5 in 2009. The linear combination of 4 kinds of endmember spectra, namely vegetation, high anti-illumination, low anti-illumination and bare soil, were used to simulate the TM spectral characteristics, and its distribution and spatial characteristics were ana- lyzed. [Result] Middle-resolution image is suitable for the basin-scaled impervious surface extraction with reliable results and satisfactory accuracy. [Conclusion] This study provided basis for deciding the relationship between the regulation strategy on the non-point source pollution of Erhai Lake, coordinated economic development and environmental protection.展开更多
Because of the developed economy and lush vegetation in southern China, the following obstacles or difficulties exist in remote sensing land surface classification: 1) Diverse surface composition types;2) Undulating t...Because of the developed economy and lush vegetation in southern China, the following obstacles or difficulties exist in remote sensing land surface classification: 1) Diverse surface composition types;2) Undulating terrains;3) Small fragmented land;4) Indistinguishable shadows of surface objects. It is our top priority to clarify how to use the concept of big data (Data mining technology) and various new technologies and methods to make complex surface remote sensing information extraction technology develop in the direction of automation, refinement and intelligence. In order to achieve the above research objectives, the paper takes the Gaofen-2 satellite data produced in China as the data source, and takes the complex surface remote sensing information extraction technology as the research object, and intelligently analyzes the remote sensing information of complex surface on the basis of completing the data collection and preprocessing. The specific extraction methods are as follows: 1) extraction research on fractal texture features of Brownian motion;2) extraction research on color features;3) extraction research on vegetation index;4) research on vectors and corresponding classification. In this paper, fractal texture features, color features, vegetation features and spectral features of remote sensing images are combined to form a combination feature vector, which improves the dimension of features, and the feature vector improves the difference of remote sensing features, and it is more conducive to the classification of remote sensing features, and thus it improves the classification accuracy of remote sensing images. It is suitable for remote sensing information extraction of complex surface in southern China. This method can be extended to complex surface area in the future.展开更多
Spatial and temporal informationon urban infrastructure is essential and requires various land-cover/land-use planning and management applications.Besides,a change in infrastructure has a direct impact on other land-c...Spatial and temporal informationon urban infrastructure is essential and requires various land-cover/land-use planning and management applications.Besides,a change in infrastructure has a direct impact on other land-cover and climatic conditions.This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature(LST)during the years 1996 and 2019.For this purpose,firstly,satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper)plus and OLI(Operational Land Imager)of 30 m resolution were taken.Secondly,for classification and image processing,remote sensing(RS)applications ENVI(Environment for Visualising Images)and GIS(Geographic Information System)were used.Thirdly,for better visualization and more in-depth analysis of land sat images,pre-processing techniques were employed.For Land use and Land cover(LU/LC)four types of land cover areas were identified-vegetation area,water cover,urbanized area,and infertile land for the years under research.The composition of red,green,and near infra-red bands was used for supervised classification.Classified images were extracted for analyzing the relative infrastructure change.A comparative analysis for the classification of images is performed for SVM(Support Vector Machine)and ANN(Artificial Neural Network).Based on analyzing these images,the result shows the rise in the average temperature from 30.04℃ to 45.25℃.This only possible reason is the increase in the built-up area from 78.73 to 332.78 Area km^(2) from 1996 to 2019.It has also been witnessed that the city’s sides are hotter than the city’s center due to the barren land on the borders.展开更多
Remote sensing technique plays an important role in geological prospecting in Altay because of the remote location and steep terrain with mountains.Pegmatite has important implications for metallogenic prospecting as ...Remote sensing technique plays an important role in geological prospecting in Altay because of the remote location and steep terrain with mountains.Pegmatite has important implications for metallogenic prospecting as most of rare metals occurs in it.Pegmatite information from optical and radar images was extracted,and the spatial distribution and scale of pegmatite were generalized in Azubai,Altay.Three mining targets,that is,Halon-Azubai,Kuermutu-Tuyibaguo and Zhuolute-Akuoyige,were delineated based on the analysis of pegmatite information,structure interpretation and other geological data.展开更多
In this paper,I propose a personal view on the general contents of remote sensing science and technology,which includes sensor research and manufacturing,remotely sensed data acquisition,data processing,information ex...In this paper,I propose a personal view on the general contents of remote sensing science and technology,which includes sensor research and manufacturing,remotely sensed data acquisition,data processing,information extraction and remote sensing applications.Serving as the basis for all these components is radiative transfer process modeling and inversion.Also of importance is the effective visualization of remotely sensed data and their efficient distribution to end users.In all these areas,there are critical research questions.In particular,I consider 4 fundamental areas for improved application of remote sensing.These include the scale and angular issues in remote sensing,removal of topographic effects on the radiance and geometry of remotely sensed imagery and the related question of multisource and multitemporal data registration,integrating knowledge and remotely sensed data into effective information extraction,and four dimensional data assimilation techniques.Strategies of information extraction can be broadly divided into manual visual analysis and computer-based analysis.The computer based information analysis include radiative transfer model inversion,image classification,regression analysis,three dimensional information extraction,shape analysis and change detection.Successful information extraction is the key to the success of remote sensing.There are many important issues that need to be solved including how to make better use of the spatial and temporal data present in remotely sensed data in information extraction.How to effectively combine the strength of both computer analysis and human interpretation?Finally,4D data assimilation is the new direction that allows for the integration of instantaneous observation with process-based climate,hydrological and ecological models.Further work along this direction will enhance the contribution of remote sensing in global change studies.In return,the quality of remotely sensed parameters can be improved.展开更多
Change Detection(CD)provides a research basis for environmental monitoring,urban expansion and reconstruction as well as disaster assessment,by identifying the changes of ground objects in different time periods.Tradi...Change Detection(CD)provides a research basis for environmental monitoring,urban expansion and reconstruction as well as disaster assessment,by identifying the changes of ground objects in different time periods.Traditional CD focused on the Binary Change Detection(BCD),focusing solely on the change and no-change regions.Due to the dynamic progress of earth observation satellite techniques,the spatial resolution of remote sensing images continues to increase,Multi-class Change Detection(MCD)which can reflect more detailed land change has become a hot research direction in the field of CD.Although many scholars have reviewed change detection at present,most of the work still focuses on BCD.This paper focuses on the recent progress in MCD,which includes five major aspects:challenges,datasets,methods,applications and future research direction.Specifically,the background of MCD is first introduced.Then,the major difficulties and challenges in MCD are discussed and delineated.The benchmark datasets for MCD are described,and the available open datasets are listed.Moreover,MCD is further divided into three categories and the specific techniques are described,respectively.Subsequently,the common applications of MCD are described.Finally,the relevant literature in the main journals of remote sensing in the past five years are analyzed and the development and future research direction of MCD are discussed.This review will help researchers understand this field and provide a reference for the subsequent development of MCD.Our collections of MCD benchmark datasets are available at:https://zenodo.org/record/6809804#.YsfvxXZByUk.展开更多
Accurate estimation of soil lead pollution degree is one of the key steps in controlling soil lead pollution;vegetable hyperspectral features research provided a new approach to discovering and monitoring soil heavy m...Accurate estimation of soil lead pollution degree is one of the key steps in controlling soil lead pollution;vegetable hyperspectral features research provided a new approach to discovering and monitoring soil heavy metal pollution.Spectral reflectance implies information of pollution impacts on vegetation;estimation of lead pollution degree based on the spectral reflectance is equivalent to extraction of weak information.展开更多
Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse de...Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.展开更多
基金Supported by the Special Program for Pilot Study of the National Basic Research Program(973Program)(2010CB434803)~~
文摘[Objective] To study the remote sensing information extraction technology for the impervious surface of Erhai basin with the aim to develop dynamic simulation platform for the formation of water pollution. [Method] Linear spectral separation technology was used to achieve Vd-S model solution, extracting remote sensing in- formation of the impervious surface of Erhai basin from the TM data of Landsat5 in 2009. The linear combination of 4 kinds of endmember spectra, namely vegetation, high anti-illumination, low anti-illumination and bare soil, were used to simulate the TM spectral characteristics, and its distribution and spatial characteristics were ana- lyzed. [Result] Middle-resolution image is suitable for the basin-scaled impervious surface extraction with reliable results and satisfactory accuracy. [Conclusion] This study provided basis for deciding the relationship between the regulation strategy on the non-point source pollution of Erhai Lake, coordinated economic development and environmental protection.
文摘Because of the developed economy and lush vegetation in southern China, the following obstacles or difficulties exist in remote sensing land surface classification: 1) Diverse surface composition types;2) Undulating terrains;3) Small fragmented land;4) Indistinguishable shadows of surface objects. It is our top priority to clarify how to use the concept of big data (Data mining technology) and various new technologies and methods to make complex surface remote sensing information extraction technology develop in the direction of automation, refinement and intelligence. In order to achieve the above research objectives, the paper takes the Gaofen-2 satellite data produced in China as the data source, and takes the complex surface remote sensing information extraction technology as the research object, and intelligently analyzes the remote sensing information of complex surface on the basis of completing the data collection and preprocessing. The specific extraction methods are as follows: 1) extraction research on fractal texture features of Brownian motion;2) extraction research on color features;3) extraction research on vegetation index;4) research on vectors and corresponding classification. In this paper, fractal texture features, color features, vegetation features and spectral features of remote sensing images are combined to form a combination feature vector, which improves the dimension of features, and the feature vector improves the difference of remote sensing features, and it is more conducive to the classification of remote sensing features, and thus it improves the classification accuracy of remote sensing images. It is suitable for remote sensing information extraction of complex surface in southern China. This method can be extended to complex surface area in the future.
文摘Spatial and temporal informationon urban infrastructure is essential and requires various land-cover/land-use planning and management applications.Besides,a change in infrastructure has a direct impact on other land-cover and climatic conditions.This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature(LST)during the years 1996 and 2019.For this purpose,firstly,satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper)plus and OLI(Operational Land Imager)of 30 m resolution were taken.Secondly,for classification and image processing,remote sensing(RS)applications ENVI(Environment for Visualising Images)and GIS(Geographic Information System)were used.Thirdly,for better visualization and more in-depth analysis of land sat images,pre-processing techniques were employed.For Land use and Land cover(LU/LC)four types of land cover areas were identified-vegetation area,water cover,urbanized area,and infertile land for the years under research.The composition of red,green,and near infra-red bands was used for supervised classification.Classified images were extracted for analyzing the relative infrastructure change.A comparative analysis for the classification of images is performed for SVM(Support Vector Machine)and ANN(Artificial Neural Network).Based on analyzing these images,the result shows the rise in the average temperature from 30.04℃ to 45.25℃.This only possible reason is the increase in the built-up area from 78.73 to 332.78 Area km^(2) from 1996 to 2019.It has also been witnessed that the city’s sides are hotter than the city’s center due to the barren land on the borders.
基金Project(11JJ6029)supported by Natural Science Foundation of Hunan Province,ChinaProject(2011QNZT006)supported by Fundamental Research Funds for the Central Universities,China
文摘Remote sensing technique plays an important role in geological prospecting in Altay because of the remote location and steep terrain with mountains.Pegmatite has important implications for metallogenic prospecting as most of rare metals occurs in it.Pegmatite information from optical and radar images was extracted,and the spatial distribution and scale of pegmatite were generalized in Azubai,Altay.Three mining targets,that is,Halon-Azubai,Kuermutu-Tuyibaguo and Zhuolute-Akuoyige,were delineated based on the analysis of pegmatite information,structure interpretation and other geological data.
基金National Natural Science Foundation of China(30590370)National High-Tech Program(2006AA12Z112)National Scientific Support program(2006BAJ01B02)
文摘In this paper,I propose a personal view on the general contents of remote sensing science and technology,which includes sensor research and manufacturing,remotely sensed data acquisition,data processing,information extraction and remote sensing applications.Serving as the basis for all these components is radiative transfer process modeling and inversion.Also of importance is the effective visualization of remotely sensed data and their efficient distribution to end users.In all these areas,there are critical research questions.In particular,I consider 4 fundamental areas for improved application of remote sensing.These include the scale and angular issues in remote sensing,removal of topographic effects on the radiance and geometry of remotely sensed imagery and the related question of multisource and multitemporal data registration,integrating knowledge and remotely sensed data into effective information extraction,and four dimensional data assimilation techniques.Strategies of information extraction can be broadly divided into manual visual analysis and computer-based analysis.The computer based information analysis include radiative transfer model inversion,image classification,regression analysis,three dimensional information extraction,shape analysis and change detection.Successful information extraction is the key to the success of remote sensing.There are many important issues that need to be solved including how to make better use of the spatial and temporal data present in remotely sensed data in information extraction.How to effectively combine the strength of both computer analysis and human interpretation?Finally,4D data assimilation is the new direction that allows for the integration of instantaneous observation with process-based climate,hydrological and ecological models.Further work along this direction will enhance the contribution of remote sensing in global change studies.In return,the quality of remotely sensed parameters can be improved.
基金supported by the National Natural Science Foundation of China[grant number 41901306]the Key Lab of Spatial Data Mining&Information Sharing of Ministry of Education[grant number 2022LSDMIS09].
文摘Change Detection(CD)provides a research basis for environmental monitoring,urban expansion and reconstruction as well as disaster assessment,by identifying the changes of ground objects in different time periods.Traditional CD focused on the Binary Change Detection(BCD),focusing solely on the change and no-change regions.Due to the dynamic progress of earth observation satellite techniques,the spatial resolution of remote sensing images continues to increase,Multi-class Change Detection(MCD)which can reflect more detailed land change has become a hot research direction in the field of CD.Although many scholars have reviewed change detection at present,most of the work still focuses on BCD.This paper focuses on the recent progress in MCD,which includes five major aspects:challenges,datasets,methods,applications and future research direction.Specifically,the background of MCD is first introduced.Then,the major difficulties and challenges in MCD are discussed and delineated.The benchmark datasets for MCD are described,and the available open datasets are listed.Moreover,MCD is further divided into three categories and the specific techniques are described,respectively.Subsequently,the common applications of MCD are described.Finally,the relevant literature in the main journals of remote sensing in the past five years are analyzed and the development and future research direction of MCD are discussed.This review will help researchers understand this field and provide a reference for the subsequent development of MCD.Our collections of MCD benchmark datasets are available at:https://zenodo.org/record/6809804#.YsfvxXZByUk.
文摘Accurate estimation of soil lead pollution degree is one of the key steps in controlling soil lead pollution;vegetable hyperspectral features research provided a new approach to discovering and monitoring soil heavy metal pollution.Spectral reflectance implies information of pollution impacts on vegetation;estimation of lead pollution degree based on the spectral reflectance is equivalent to extraction of weak information.
基金supported by the National Natural Science Foundation of China(Nos.61906168,62202429 and 62272267)the Zhejiang Provincial Natural Science Foundation of China(No.LY23F020023)the Construction of Hubei Provincial Key Laboratory for Intelligent Visual Monitoring of Hydropower Projects(No.2022SDSJ01)。
文摘Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.
