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Titlebook: Geoinformatics in Sustainable Ecosystem and Society; 7th International Co Yichun Xie,Yong Li,Yingbin Deng Conference proceedings 2020 Sprin

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楼主: Capricious
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https://doi.org/10.1007/978-3-322-98946-8ta analysis. The data quality of Jason-3 satellites was evaluated by data screening and analysis of two satellite data, comparative analysis of geophysical parameters, analysis of sea level height discrepancy at crossover points, and analysis of along-trace sea level anomaly. The results show that t
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Einleitung, Patientengut und Methode,a-1 compared to VIIRS images, we employed road network analysis to compare the two kinds of images in Los Angeles, United States. In the road network analysis, we calculated the correlation coefficients between the distance to the primary road and the image radiance in 228 neighborhood areas, and we
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https://doi.org/10.1007/978-3-662-26271-9ge negative impact on the maintenance of China’s marine right. In lack of marine functional zoning of the NSS and natural/social considerations in suitability evaluation of oil and gas zoning, this paper constructed a suitability evaluation model that involves resource conditions, topographic condit
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Sorry, daran ist die Mathematik schuld,timations are divided into two categories: optical-based and SAR-based (synthetic aperture radar) methods. By analyzing and discussing on the advantages and disadvantages of various methods. The following points can be summarized: First, the accuracy of optical remote sensing water depth detection m
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Die farbigen Dämmerungserscheinungento reflect the level of urban development and predict the potential of urban development. Based on the Landsat 8 images, by using the way of spectral signature analysis, the study selected four indices, Modified Normalized Difference Built-up Index (MNDBI), Normalized Difference Vegetation Index (ND
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,Gullfoss-Kerid (Kerið)-Reykjavík,rtance to explore the cause effect of climatic shifts on vegetation. Based on the long-term satellite NDVI dataset during 1982–2012, we analysed the causal relationship of vegetation greenness with temperature and precipitation by using the Granger causality test at monthly and seasonal temporal sca
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