The study of land use change has great theoretical and practical significance for the effective and rational utilization of regional land resources and the governance of ecological environment. Take Jinan City as the study area, and the landsat8 OLI images in 2013, 2017 and 2020 as the data source, use ENVI software to preprocess the images (radiometric calibration, atmospheric correction, splicing and clipping), then use the maximum likelihood method in supervised classification to extract the land use type area and distribution information in the study area in three years, and finally compare the image classification results in three years, so as to realize the dynamic monitoring of land use change in this area. Through the analysis of the research results, it is found that in the three periods, the area of forest land, construction land and water body increase, the area of cultivated land decreases and then increases, and the area of bare land increases first and then decreases, which can provide a theoretical basis for the development planning of land use in the next step.
{"title":"Remote Sensing Monitoring of Land Use Change in Jinan","authors":"Rui-Feng Wang, Huan Wang, Wenlong Yu, Rubing Huang","doi":"10.1109/ICGMRS55602.2022.9849253","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849253","url":null,"abstract":"The study of land use change has great theoretical and practical significance for the effective and rational utilization of regional land resources and the governance of ecological environment. Take Jinan City as the study area, and the landsat8 OLI images in 2013, 2017 and 2020 as the data source, use ENVI software to preprocess the images (radiometric calibration, atmospheric correction, splicing and clipping), then use the maximum likelihood method in supervised classification to extract the land use type area and distribution information in the study area in three years, and finally compare the image classification results in three years, so as to realize the dynamic monitoring of land use change in this area. Through the analysis of the research results, it is found that in the three periods, the area of forest land, construction land and water body increase, the area of cultivated land decreases and then increases, and the area of bare land increases first and then decreases, which can provide a theoretical basis for the development planning of land use in the next step.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115840715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849234
Jinku Huang, Ping Li, Y. Lou, Yingru Pei
China Geological Survey (CGS) has accumulated a large number of geological data in its geological survey activities, but the relevant geological data exists in a variety of forms and data formats, with low utilization and difficulty in sharing, which is not conducive to the rapid inquiry and mining and utilization of geological data. Relying on different types of geological data produced by CGS, this paper uses ArcGIS Server, Web Service, Ajax, Memcached, and other computers and GIS technologies to complete the digitization, integration and includes standardized management of different types of geological data such as article reports, geological maps, geological vector data and geological remote sensing image data. In this paper, a WebGIS-based geological data management and display platform is developed to achieve a one-stop service for geological data collection, storage, query and visualization, which can quickly respond to scientific researchers to view geological data and multidimensional statistical analysis needs. The experiment proves that the platform can effectively improve the information technology level of geological data management and the working efficiency of researchers.
{"title":"Design and Implementation of Geological Data Management Platform based on WebGIS","authors":"Jinku Huang, Ping Li, Y. Lou, Yingru Pei","doi":"10.1109/ICGMRS55602.2022.9849234","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849234","url":null,"abstract":"China Geological Survey (CGS) has accumulated a large number of geological data in its geological survey activities, but the relevant geological data exists in a variety of forms and data formats, with low utilization and difficulty in sharing, which is not conducive to the rapid inquiry and mining and utilization of geological data. Relying on different types of geological data produced by CGS, this paper uses ArcGIS Server, Web Service, Ajax, Memcached, and other computers and GIS technologies to complete the digitization, integration and includes standardized management of different types of geological data such as article reports, geological maps, geological vector data and geological remote sensing image data. In this paper, a WebGIS-based geological data management and display platform is developed to achieve a one-stop service for geological data collection, storage, query and visualization, which can quickly respond to scientific researchers to view geological data and multidimensional statistical analysis needs. The experiment proves that the platform can effectively improve the information technology level of geological data management and the working efficiency of researchers.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116131049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849228
Haiwei Bai, Jian Chen, Q. Wang, Changtao He
Semantic labeling of high-resolution remote sensing images is a challenging task, requiring the models to effectively distinguish different classes of ground objects while learning advanced feature representations. First of all, we propose a dual-decoder semantic labeling neural network based on the atrous spatial pyramid pooling module and attention mechanism to achieve the high-precision classification of different ground objects. The main idea is to enhance the high-level feature representation by using the complementary relationship that may exist between different decoders. Furthermore, based on this network structure, a decision calibration auxiliary loss is proposed to improve the models’s ability to classify examples of highly ambiguous output by different decoders. Finally, we conduct experimental verification on the ISPRS Vaihingen and Potsdam datasets, and the results show that the auxiliary loss can effectively improve the classification accuracy of the model.
{"title":"Decision Calibration Network for Semantic Labeling of High-Resolution Remote Sensing Images","authors":"Haiwei Bai, Jian Chen, Q. Wang, Changtao He","doi":"10.1109/ICGMRS55602.2022.9849228","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849228","url":null,"abstract":"Semantic labeling of high-resolution remote sensing images is a challenging task, requiring the models to effectively distinguish different classes of ground objects while learning advanced feature representations. First of all, we propose a dual-decoder semantic labeling neural network based on the atrous spatial pyramid pooling module and attention mechanism to achieve the high-precision classification of different ground objects. The main idea is to enhance the high-level feature representation by using the complementary relationship that may exist between different decoders. Furthermore, based on this network structure, a decision calibration auxiliary loss is proposed to improve the models’s ability to classify examples of highly ambiguous output by different decoders. Finally, we conduct experimental verification on the ISPRS Vaihingen and Potsdam datasets, and the results show that the auxiliary loss can effectively improve the classification accuracy of the model.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115529328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849358
Fangda Li, Zhenwei Guo, Bochen Wang, Longyun Hu
Ocean carbon storage is one of the effective ways to achieve emission peak and carbon neutrality. It requires detailed characterization of the seabed reservoir. Seismic exploration is a method of using artificially excited seismic waves to identify subsurface structures. It is widely applied in hydrocarbon exploration and geological engineering, such as reservoir prediction, structural interpretation and subsurface cavity investigation. Currently, researchers investigate the application of the method to carbon storage. Stratum velocity is the key result of seismic data processing and imaging, which determines the accuracy and resolution of the stacked profile. It ultimately affects the results of geological structure identification. This paper proposed a new deep learning velocity inversion method with the convolutional network structure and mix loss function. The results illustrated that our inversion method has better accuracy and resolution than traditional convolutional networks, and is more suitable for velocity inversion.
{"title":"Deep learning pre-stacked seismic velocity inversion using Res-Unet network","authors":"Fangda Li, Zhenwei Guo, Bochen Wang, Longyun Hu","doi":"10.1109/ICGMRS55602.2022.9849358","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849358","url":null,"abstract":"Ocean carbon storage is one of the effective ways to achieve emission peak and carbon neutrality. It requires detailed characterization of the seabed reservoir. Seismic exploration is a method of using artificially excited seismic waves to identify subsurface structures. It is widely applied in hydrocarbon exploration and geological engineering, such as reservoir prediction, structural interpretation and subsurface cavity investigation. Currently, researchers investigate the application of the method to carbon storage. Stratum velocity is the key result of seismic data processing and imaging, which determines the accuracy and resolution of the stacked profile. It ultimately affects the results of geological structure identification. This paper proposed a new deep learning velocity inversion method with the convolutional network structure and mix loss function. The results illustrated that our inversion method has better accuracy and resolution than traditional convolutional networks, and is more suitable for velocity inversion.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114604080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849354
Xian Zhang, Li Chen, Wei Li, Yu Li
Remote sensing technology has great advantages in timely and rapid monitoring of open-pit mining conditions. Based on Worldview-2 multi-spectral satellite remote sensing images, we took a typical lateritic nickel deposit in Indonesia as an example, and 9 types elements which are mining area, dump, collection sump, tailings pond, buildings, roads, smelter, vegetation and bare soil in mining active areas were extracted. Firstly, a deep learning method based on TensorFlow framework was used to extract the main roads and mining areas from the pre-processed images to obtain vector data. Secondly, according to the vector data, our study area can be divided into two areas, center and outskirts, by FNEA coarse segmentation, and the local variance change rates of the two areas are calculated, so as to select appropriate segmentation scales for each factor type and establish a bottom-up multi-scale segmentation hierarchy. Thirdly, the spectral difference index (SDI) and PCA-based GLCM texture features were proposed to expand the feature base. The FSO algorithm and SEaTH algorithm were combined to select the optimal features and separation thresholds. At last, the multi-element extraction of laterite nickel ore area was completed hierarchically. The overall accuracy reached 90.12%. Our results indicated that the proposed method takes into account the spatial differences of various elements, ensuring the accuracy of segmentation and element extraction. Furthermore, method of selecting scales and thresholds avoids multiple experiments and reduces the time and labor cost of trial and error, which ensures objectivity and improves the selection efficiency. In addition, the PCA-based texture features can shorten the feature calculation time from 6.25 min to 14 s, reducing the operation time of the algorithm and greatly saving the operation time while ensuring the correlation effectively.
{"title":"Multi-element quantitative extraction of mining area of laterite nickel mine combined deep learning with object-oriented method","authors":"Xian Zhang, Li Chen, Wei Li, Yu Li","doi":"10.1109/ICGMRS55602.2022.9849354","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849354","url":null,"abstract":"Remote sensing technology has great advantages in timely and rapid monitoring of open-pit mining conditions. Based on Worldview-2 multi-spectral satellite remote sensing images, we took a typical lateritic nickel deposit in Indonesia as an example, and 9 types elements which are mining area, dump, collection sump, tailings pond, buildings, roads, smelter, vegetation and bare soil in mining active areas were extracted. Firstly, a deep learning method based on TensorFlow framework was used to extract the main roads and mining areas from the pre-processed images to obtain vector data. Secondly, according to the vector data, our study area can be divided into two areas, center and outskirts, by FNEA coarse segmentation, and the local variance change rates of the two areas are calculated, so as to select appropriate segmentation scales for each factor type and establish a bottom-up multi-scale segmentation hierarchy. Thirdly, the spectral difference index (SDI) and PCA-based GLCM texture features were proposed to expand the feature base. The FSO algorithm and SEaTH algorithm were combined to select the optimal features and separation thresholds. At last, the multi-element extraction of laterite nickel ore area was completed hierarchically. The overall accuracy reached 90.12%. Our results indicated that the proposed method takes into account the spatial differences of various elements, ensuring the accuracy of segmentation and element extraction. Furthermore, method of selecting scales and thresholds avoids multiple experiments and reduces the time and labor cost of trial and error, which ensures objectivity and improves the selection efficiency. In addition, the PCA-based texture features can shorten the feature calculation time from 6.25 min to 14 s, reducing the operation time of the algorithm and greatly saving the operation time while ensuring the correlation effectively.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"5 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125968735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849357
Youmei Han, Shuai Zhou, Panrui Xia, Qun Zhao
Based on the principle of oblique photogrammetry, it used DJI phantom 4 PRO, one kind of light UAV photogrammetry system, to collect the oblique photogrammetry image data of tall buildings, and then produced real scene 3D model by the oblique photogrammetry modeling software. While the real scene 3D model results show much distortion and deformation. In order to improve 3D model results, it designed four side elevation flight and data processing schemes based on the photogrammetry principle. In addition to the above oblique photogrammetry images, four side elevations images of the tall building are collected separately by DJI phantom 4 Pro with certain overlaps. Meanwhile it surveyed some image control points and test points to grantee the results precision and texture authenticity. During the data processing, the four side elevation images and the oblique photogrammetry images are combined to perform the Aerial triangulation (AT) calculation. Then it produced a new scene 3D model. The results showed that the new model has significantly been improved both in accuracy and texture authenticity. This method satisfies the need of fine realistic 3D modeling of tall buildings and provides strong support for fine 3D modeling of smart cities.
{"title":"Research on fine 3D modeling technology of tall buildings based on UAV Photogrammetry","authors":"Youmei Han, Shuai Zhou, Panrui Xia, Qun Zhao","doi":"10.1109/ICGMRS55602.2022.9849357","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849357","url":null,"abstract":"Based on the principle of oblique photogrammetry, it used DJI phantom 4 PRO, one kind of light UAV photogrammetry system, to collect the oblique photogrammetry image data of tall buildings, and then produced real scene 3D model by the oblique photogrammetry modeling software. While the real scene 3D model results show much distortion and deformation. In order to improve 3D model results, it designed four side elevation flight and data processing schemes based on the photogrammetry principle. In addition to the above oblique photogrammetry images, four side elevations images of the tall building are collected separately by DJI phantom 4 Pro with certain overlaps. Meanwhile it surveyed some image control points and test points to grantee the results precision and texture authenticity. During the data processing, the four side elevation images and the oblique photogrammetry images are combined to perform the Aerial triangulation (AT) calculation. Then it produced a new scene 3D model. The results showed that the new model has significantly been improved both in accuracy and texture authenticity. This method satisfies the need of fine realistic 3D modeling of tall buildings and provides strong support for fine 3D modeling of smart cities.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128153140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849374
Shouchao Hu, Yaguang Zhu
As the first civilian high resolution stereo mapping satellite in China, the ZY-3 satellite can obtain high-precision terrain data efficiently and quickly, which has broad application prospects. In order to verify the application effect of the ZY-3 data in electric power engineering survey, this paper selects a transmission line project and a wind farm topographic mapping project as the experimental areas. The elevation accuracy of the ZY-3 satellite products is evaluated. Compared with the accuracy of STRM DEM, the results show that the accuracy of ZY-3 satellite data is better than STRM DEM, which can play a good auxiliary role in the electric power engineering survey and design stage.
{"title":"Accuracy Assessment of ZY-3 Stereo Images in Electric Power Engineering Survey","authors":"Shouchao Hu, Yaguang Zhu","doi":"10.1109/ICGMRS55602.2022.9849374","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849374","url":null,"abstract":"As the first civilian high resolution stereo mapping satellite in China, the ZY-3 satellite can obtain high-precision terrain data efficiently and quickly, which has broad application prospects. In order to verify the application effect of the ZY-3 data in electric power engineering survey, this paper selects a transmission line project and a wind farm topographic mapping project as the experimental areas. The elevation accuracy of the ZY-3 satellite products is evaluated. Compared with the accuracy of STRM DEM, the results show that the accuracy of ZY-3 satellite data is better than STRM DEM, which can play a good auxiliary role in the electric power engineering survey and design stage.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124264489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849386
Xiaoman Li, Xuejie Bi, Hongyun Chen, Hongyu Lu
The marine environment parameters can be estimated by analyzing the received sound signal. In shallow water waveguide with high-speed bottom, the transmission loss of sound signal can be obtained by the bottom reflection phase shift, which consists of the bottom parameters. A fast inversion method of the marine environment parameters based on bottom reflection phase shift is presented in this paper. Bayesian inversion theory is the theoretical framework for the application of this method. The signal obtained from the measured data is the input function, and the replica can be calculated by the bottom reflection shift parameter and other parameters in water column quickly. The propagation range and depth, and some geoacoustic parameters were estimated accurately by the posterior probability density without the prior knowledge of the marine environment information. This method can be applied to most shallow water waveguides, and is also applicable to acoustic signals with different bandwidths. The accuracy and validity of the inversion results are verified by the experimental data.
{"title":"A fast inversion method of marine environment parameters based on bottom reflection phase shift","authors":"Xiaoman Li, Xuejie Bi, Hongyun Chen, Hongyu Lu","doi":"10.1109/ICGMRS55602.2022.9849386","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849386","url":null,"abstract":"The marine environment parameters can be estimated by analyzing the received sound signal. In shallow water waveguide with high-speed bottom, the transmission loss of sound signal can be obtained by the bottom reflection phase shift, which consists of the bottom parameters. A fast inversion method of the marine environment parameters based on bottom reflection phase shift is presented in this paper. Bayesian inversion theory is the theoretical framework for the application of this method. The signal obtained from the measured data is the input function, and the replica can be calculated by the bottom reflection shift parameter and other parameters in water column quickly. The propagation range and depth, and some geoacoustic parameters were estimated accurately by the posterior probability density without the prior knowledge of the marine environment information. This method can be applied to most shallow water waveguides, and is also applicable to acoustic signals with different bandwidths. The accuracy and validity of the inversion results are verified by the experimental data.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122531004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849345
Kailei Xu, Y. Wan, Jun Chen, Jianhua Qiang
With the rapid development of social economy in Guanzhong urban agglomeration, the living standards of the people has been greatly improved. Because of the extensive mode of development, environmental problems have also become the cost of economic development in Guanzhong urban agglomeration. Urban agglomeration is facing a series of environmental problems, such as ecological destruction, atmospheric pollution, water shortage and so on. Focusing on these issues, multi-source remote sensing data and auxiliary data are integrated to build a comprehensive and regional eco-environmental quality assessment model. The evaluation model is established based on the combination of Fuzzy Analytical Hierarchy Process, Principal Component Analysis and Lagrange Multiplier. The results show that the quality of ecological environment in Guanzhong urban agglomeration shows a downward trend in general. The area of the eco-environmental quality index between 0.4-0.6 performs an upward trend, which transformed from other levels. The quality of ecological environment in Guanzhong urban agglomeration has gradually improved from north to south. The southern part of Guanzhong urban agglomeration is Qinling Nature Reserve, which Contains a lot of woodland and has high ecological environment quality.
{"title":"Comprehensive Evaluation of Eco-environmental Quality in Guanzhong Urban Agglomeration Based on Multi-source Remote Sensing Data","authors":"Kailei Xu, Y. Wan, Jun Chen, Jianhua Qiang","doi":"10.1109/ICGMRS55602.2022.9849345","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849345","url":null,"abstract":"With the rapid development of social economy in Guanzhong urban agglomeration, the living standards of the people has been greatly improved. Because of the extensive mode of development, environmental problems have also become the cost of economic development in Guanzhong urban agglomeration. Urban agglomeration is facing a series of environmental problems, such as ecological destruction, atmospheric pollution, water shortage and so on. Focusing on these issues, multi-source remote sensing data and auxiliary data are integrated to build a comprehensive and regional eco-environmental quality assessment model. The evaluation model is established based on the combination of Fuzzy Analytical Hierarchy Process, Principal Component Analysis and Lagrange Multiplier. The results show that the quality of ecological environment in Guanzhong urban agglomeration shows a downward trend in general. The area of the eco-environmental quality index between 0.4-0.6 performs an upward trend, which transformed from other levels. The quality of ecological environment in Guanzhong urban agglomeration has gradually improved from north to south. The southern part of Guanzhong urban agglomeration is Qinling Nature Reserve, which Contains a lot of woodland and has high ecological environment quality.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123543166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-22DOI: 10.1109/ICGMRS55602.2022.9849315
W. Zhang, Yilin Dong
In order to scientifically manage flood disasters in flood storage areas and effectively reduce economic losses, the Mengwa flood storage area in Anhui Province was taken as the research area, and Sentinel 1, 2 and Gaofen series satellite images were selected as data sources, and the regional growth algorithm was used to quickly extract floods. Inundation area, draw the monitoring map of water body changes before and after the flood disaster, combined with the land use type coverage map of Mengwa flood storage area, and use GIS technology to analyze the disaster situation and total land use type of Mengwa flood storage area during the flood in July and August 2020. Spatial and temporal variation characteristics of regional disasters. The regional growth algorithm combined with multi-source remote sensing data can quickly and accurately extract the flood range and realize the timeliness and high-frequency monitoring of flood information. The severely affected areas of Mengwa flood storage area are mainly concentrated in the central and northeastern regions, and the southwestern region is less affected; farmland and breeding ponds are the most severely affected, and Baozhuangwei and Zhuangtai are the least affected. The temporal change of the affected area in the Mengwa flood storage area has a strong correlation with the flood storage measures, but a weak correlation with the local precipitation.
{"title":"Research on flood remote sensing monitoring based on multi-source remote sensing data","authors":"W. Zhang, Yilin Dong","doi":"10.1109/ICGMRS55602.2022.9849315","DOIUrl":"https://doi.org/10.1109/ICGMRS55602.2022.9849315","url":null,"abstract":"In order to scientifically manage flood disasters in flood storage areas and effectively reduce economic losses, the Mengwa flood storage area in Anhui Province was taken as the research area, and Sentinel 1, 2 and Gaofen series satellite images were selected as data sources, and the regional growth algorithm was used to quickly extract floods. Inundation area, draw the monitoring map of water body changes before and after the flood disaster, combined with the land use type coverage map of Mengwa flood storage area, and use GIS technology to analyze the disaster situation and total land use type of Mengwa flood storage area during the flood in July and August 2020. Spatial and temporal variation characteristics of regional disasters. The regional growth algorithm combined with multi-source remote sensing data can quickly and accurately extract the flood range and realize the timeliness and high-frequency monitoring of flood information. The severely affected areas of Mengwa flood storage area are mainly concentrated in the central and northeastern regions, and the southwestern region is less affected; farmland and breeding ponds are the most severely affected, and Baozhuangwei and Zhuangtai are the least affected. The temporal change of the affected area in the Mengwa flood storage area has a strong correlation with the flood storage measures, but a weak correlation with the local precipitation.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126482548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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