China Symposium on Remote Sensing最新文献_第2页

Comparison of three empirical methods for water depth mapping with case study of Pratas Island 三种经验水深制图方法的比较——以普拉塔斯岛为例

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204945

Ailian Chen, Boqin Zhu

引用次数: 2

Temporal and spatial analysis of global GOSAT XCO2 variations characteristics 全球GOSAT XCO2变化特征的时空分析

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204827

Qian Wang, L. Lei, Da Liu, Min Liu, Xiuchun Qin, B. Sun

{"title":"Temporal and spatial analysis of global GOSAT XCO2 variations characteristics","authors":"Qian Wang, L. Lei, Da Liu, Min Liu, Xiuchun Qin, B. Sun","doi":"10.1117/12.2204827","DOIUrl":"https://doi.org/10.1117/12.2204827","url":null,"abstract":"CO2 is one of the most important greenhouse gases due to its selective absorption of long wave radiation from the Earth’s surface. In this paper, we use the column average dry air mole fraction of CO2 (XCO2) data from the Japanese GOSAT satellite to conduct a comprehensive and systematic analysis of temporal and spatial distribution of XCO2. This includes: (1) analysis of seasonal change characteristics of XCO2 data; and (2) comparative analysis of the northern and southern hemispheres carbon dioxide concentration at different latitudes. The results show that (1) from 2010 to 2013, atmospheric XCO2 significantly increased each year. The southern hemisphere's annual averages of XCO2 from 2010 to 2012 were 385.2 ppm, 387.3 ppm, and 389.1 ppm, while the average annual values for the northern hemisphere from 2010 to 2012 were 387.8 ppm, 390.0 ppm, and 391.7 ppm. The annual XCO2 in northern and southern hemispheres exhibited growth rates of 1-2 ppm per year. (2) The results show seasonal change trends: winter months displayed higher XCO2. Regarding the global spatial distribution of XCO2, the results show that the total XCO2 in the northern hemisphere is higher than that in the southern hemisphere. (3) The growth of global XCO2 in 2011 and 2012 was 1.9 ppm/yr and 2.1 ppm/yr. These values are in accordance with the growth rates of 1.9 ppm/yr and 2.2 ppm/yr reported in the World Meteorological Organization's greenhouse gas bulletin.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114854341","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}

引用次数: 1

Monitoring soil moisture through assimilation of active microwave remote sensing observation into a hydrologic model 通过将主动微波遥感观测数据同化到水文模型中监测土壤湿度

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204954

Qiang Liu, Yingshi Zhao

{"title":"Monitoring soil moisture through assimilation of active microwave remote sensing observation into a hydrologic model","authors":"Qiang Liu, Yingshi Zhao","doi":"10.1117/12.2204954","DOIUrl":"https://doi.org/10.1117/12.2204954","url":null,"abstract":"Soil moisture can be estimated from point measurements, hydrologic models, and remote sensing. Many researches indicated that the most promising approach for soil moisture is the integration of remote sensing surface soil moisture data and computational modeling. Although many researches were conducted using passive microwave remote sensing data in soil moisture assimilation with coarse spatial resolution, few researches were carried out using active microwave remote sensing observation. This research developed and tested an operational approach of assimilation for soil moisture prediction using active microwave remote sensing data ASAR (Advanced Synthetic Aperture Radar) in Heihe Watershed. The assimilation was based on ensemble Kalman filter (EnKF), a forward radiative transfer model and the Distributed Hydrology Soil Vegetation Model (DHSVM). The forward radiative transfer model, as a semi-empirical backscattering model, was used to eliminate the effect of surface roughness and vegetation cover on the backscatter coefficient. The impact of topography on soil water movement and the vertical and lateral exchange of soil water were considered. We conducted experiments to assimilate active microwave remote sensing data (ASAR) observation into a hydrologic model at two field sites, which had different underlying conditions. The soil moisture ground-truth data were collected through the field Time Domain Reflectometry (TDR) tools, and were used to assess the assimilation method. The temporal evolution of soil moisture measured at point-based monitoring locations were compared with EnKF based model predictions. The results indicated that the estimate of soil moisture was improved through assimilation with ASAR observation and the soil moisture based on data assimilation can be monitored in moderate spatial resolution.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683546","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}

引用次数: 0

Maize recognition and accuracy evaluation with GF-1 WFV sensor data GF-1 WFV传感器数据的玉米识别及精度评价

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204722

Y. Guo, S. Li, X. Wu, Yuan Cheng, L. Wang, T. Liu, G. Zheng

{"title":"Maize recognition and accuracy evaluation with GF-1 WFV sensor data","authors":"Y. Guo, S. Li, X. Wu, Yuan Cheng, L. Wang, T. Liu, G. Zheng","doi":"10.1117/12.2204722","DOIUrl":"https://doi.org/10.1117/12.2204722","url":null,"abstract":"As part of the \"High-Resolution Earth Observation System,\" many major projects are being implemented. The first optical satellite (GF-1) in the high-resolution satellite series has completed in-orbit tests and entered the stage of data acquisition. GF-1 owns high resolution and information of wide field view sensor (WFV sensor) and the panchromatic and multispectral sensor (PMS sensor). In this study, GF-1 WFV sensor data with a resolution of 16 m, integrated with Landsat-8 and RapidEye data were selected to recognize maize in Xuchang using Support Vector Machine (SVM) and Spectral Angle Mapper (SAM) method. The results showed that the precision of classification varies greatly among WFV sensors. In particular, WFV3 was of the highest accuracy to identify crops and planting area with accuracy higher than Landsat-8 and close to RapidEye. With regard to WFV1 and WFV4, the application effect was worse and less viable to identify species of complex autumn crops. In brief, the classification accuracy of SVM classifier is better than SAM classifier. It can be also concluded that SVM is more suitable for the identification of crops and planting area of extraction in the study area.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121950622","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}

引用次数: 0

A study on monitoring land use/cover change of mining area based on ticket-voting SVM classification 基于票选SVM分类的矿区土地利用/覆被变化监测研究

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204811

Yi Lin, Jie Yu, Min Ying, M. Shen

{"title":"A study on monitoring land use/cover change of mining area based on ticket-voting SVM classification","authors":"Yi Lin, Jie Yu, Min Ying, M. Shen","doi":"10.1117/12.2204811","DOIUrl":"https://doi.org/10.1117/12.2204811","url":null,"abstract":"Based on the development of classification algorithm applied in monitoring spatio-temporal dynamic changes of coal-- mining areas, several improvements were made on feature space and classification model in this paper. There were two innovations in our study: 1) During building the feature spaces, a new index for extracting information about mining area was created, which can classify mining area and settlements efficiently; 2) a special ticket-voting SVM algorithm with wavelet kernel function was proposed, which provides higher classification accuracy than other traditional classifiers via the secondary classification. Here we took the northeast plain of Pei county in Xuzhou city as a studying region, applying the proposed method to implement the classification by using the image of multi-temporal TM/ETM from the year of 1987 to 2013. How to carry on deep analysis combined with various non-spatial data is much more significant. Then we studied the rules of dynamic changes of land use/cover and further analyzed their driving factors by combining RS interpretation with GIS spatial analysis techniques. In this study, image recognition technology was applied to the problems of environmental change in coal mining area. These explanations provide some valuable supports for human to recognize and deal with the conflicts between economic development and environmental protection in coal mining areas.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"28 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128274335","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}

引用次数: 0

Framework design for remote sensing monitoring and data service system of regional river basins 区域流域遥感监测与数据服务系统框架设计

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204860

J. Fu, Jingxuan Lu, Z. Pang

{"title":"Framework design for remote sensing monitoring and data service system of regional river basins","authors":"J. Fu, Jingxuan Lu, Z. Pang","doi":"10.1117/12.2204860","DOIUrl":"https://doi.org/10.1117/12.2204860","url":null,"abstract":"Regional river basins, transboundary rivers in particular, are shared water resources among multiple users. The tempo-spatial distribution and utilization potentials of water resources in these river basins have a great influence on the economic layout and the social development of all the interested parties in these basins. However, due to the characteristics of cross borders and multi-users in these regions, especially across border regions, basic data is relatively scarce and inconsistent, which bring difficulties in basin water resources management. Facing the basic data requirements in regional river management, the overall technical framework for remote sensing monitoring and data service system in China’s regional river basins was designed in the paper, with a remote sensing driven distributed basin hydrologic model developed and integrated within the frame. This prototype system is able to extract most of the model required land surface data by multi-sources and multi-temporal remote sensing images, to run a distributed basin hydrological simulation model, to carry out various scenario analysis, and to provide data services to decision makers.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127054108","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}

引用次数: 0

Geometric simulation analysis of multi-band mosaic imaging from the same orbit by agile satellites 敏捷卫星同轨多波段拼接成像几何仿真分析

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204808

Yue Xu, Jinwei Chen, Yue-ting Chen, Zhi-hai Xu, H. Feng, Qi Li

引用次数: 1

Effectiveness analysis of ACOS-Xco2 bias correction method with GEOS-Chem model results 利用GEOS-Chem模型结果分析ACOS-Xco2偏置校正方法的有效性

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204821

Da Liu, L. Lei, Min Liu, Lijie Guo, Qian Wang, Nian Bie

引用次数: 0

Remote sensing monitoring of the 2012 Beijing extreme rainstorm event 2012年北京特大暴雨事件遥感监测

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204720

Ping Huang, Jingxuan Lu, Delong Li, W. Song, W. Qu

引用次数: 1

A rapid extraction of landslide disaster information research based on GF-1 image 基于GF-1图像的滑坡灾害信息快速提取研究

China Symposium on Remote Sensing Pub Date : 2015-08-06 DOI: 10.1117/12.2204784

Sai Wang, Suning Xu, Li Peng, Zhiyi Wang, Na Wang

{"title":"A rapid extraction of landslide disaster information research based on GF-1 image","authors":"Sai Wang, Suning Xu, Li Peng, Zhiyi Wang, Na Wang","doi":"10.1117/12.2204784","DOIUrl":"https://doi.org/10.1117/12.2204784","url":null,"abstract":"In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 ㎡.Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128753619","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}

引用次数: 3