کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5754858 1621201 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications
چکیده انگلیسی
Crop monitoring information is essential for food security and to improve our understanding of the role of agriculture on climate change, among others. Remotely sensing optical and radar data can help to map crop types and to estimate biophysical parameters, especially with the availability of an unprecedented amount of free Sentinel data within the Copernicus programme. These datasets, whose continuity is guaranteed up to decades, offer a unique opportunity to monitor crops systematically every 5 to 10 days. Before developing operational monitoring methods, it is important to understand the temporal variations of the remote sensing signal of different crop types in a given region. In this study, we analyse the temporal trajectory of remote sensing data for a variety of winter and summer crops that are widely cultivated in the world (wheat, rapeseed, maize, soybean and sunflower). The test region is in southwest France, where Sentinel-1 data have been acquired since 2014. Because Sentinel-2 data were not available for this study, optical satellites similar to Sentinel-2 are used, mainly to derive NDVI, for a comparison between the temporal behaviors with radar data. The SAR backscatter and NDVI temporal profiles of fields with varied management practices and environmental conditions are interpreted physically. Key findings from this analysis, leading to possible applications of Sentinel-1 data, with or without the conjunction of Sentinel-2, are then described. This study points out the interest of SAR data and particularly the VH/VV ratio, which is poorly documented in previous studies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 199, 15 September 2017, Pages 415-426
نویسندگان
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