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Titlebook: Remote Sensing Time Series; Revealing Land Surfa Claudia Kuenzer,Stefan Dech,Wolfgang Wagner Book 2015 Springer International Publishing Sw

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發(fā)表于 2025-3-30 10:56:46 | 只看該作者
52#
發(fā)表于 2025-3-30 15:12:08 | 只看該作者
Monitoring Recent Urban Expansion and Urban Subsidence of Beijing Using ENVISAT/ASAR Time Series Danformation about the spatial and temporal dynamics of the characteristics of urban areas is therefore needed to support sustainable urban development. Time series earth observation data obtained using radar satellites have provided effective data sources for monitoring urban areas. This chapter firs
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發(fā)表于 2025-3-30 18:53:59 | 只看該作者
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發(fā)表于 2025-3-30 21:54:48 | 只看該作者
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發(fā)表于 2025-3-31 01:55:44 | 只看該作者
Assessing Drivers of Vegetation Changes in Drylands from Time Series of Earth Observation Data,ethodological challenges related to the use of these. Finally, teleconnections between global sea surface temperature (SST) anomalies and dryland vegetation productivity are illustrated and the associated predictive capabilities are discussed.
56#
發(fā)表于 2025-3-31 05:45:46 | 只看該作者
,Land Degradation in South Africa – A Degradation Index Derived from 10 Years of Net Primary Product(Leaf area index) and ECMWF meteorology time-series for the period of 1999–2010. The trend-analysis of model output and climatic input results in a new land degradation index (LDI) that distinguishes between climatic and human-induced reduction of vegetative productivity.
57#
發(fā)表于 2025-3-31 10:07:26 | 只看該作者
58#
發(fā)表于 2025-3-31 16:28:59 | 只看該作者
The Utility of Landsat Data for Global Long Term Terrestrial Monitoring,Specifically, it introduces the NASA (National Aeronautics and Space Administration) funded global Web Enabled Landsat Data products, and overviews Landsat time series phenology and land cover change monitoring applications and research, and prospectives for Landsat time series monitoring.
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發(fā)表于 2025-3-31 18:24:39 | 只看該作者
978-3-319-35243-5Springer International Publishing Switzerland 2015
60#
發(fā)表于 2025-4-1 00:33:44 | 只看該作者
Remote Sensing Time Series978-3-319-15967-6Series ISSN 1567-3200 Series E-ISSN 2215-1842
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