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Land Applications of Radar Remote Sensing || Combining Moderate-Resolution Time-Series RS Data from SAR and Optical Sources for Rice Crop Characterisation: Examples from Bangladesh

DOI:10.5772/57443 出版年份:2014 更新时间:2025-09-10 09:29:36
摘要: Operational monitoring of agricultural extent and production is part of several national and international efforts to provide transparent, rapid and accurate information related to food security and food markets. Initiatives such as the G20 Agricultural Market Information System (AMIS), the European Commission’s Monitoring Agricultural Resources mission (MARS), the Global Agricultural Monitoring (GEOGLAM) component of GEO, and the United States Department of Agriculture’s Global Agricultural Monitoring Foreign Agricultural Service (GLAMFAS), are just some examples of operational services that do, or will require remote-sensing–based information on crop status in almost any part of the world. Of the thousands of edible plants, just three—rice, wheat, and maize —provide 60% of the global population’s food energy intake, and the top 15 crops amount to 90% [1]. Seasonal or monthly estimates of production and availability of these staples form a part of many agricultural bulletins and agricultural outlook reports. These reports are used for decision-making and policies on imports, exports, subsidies, and investments, which, in turn, affect prices. Food security is fundamentally about availability and price; such reports, and the responses to these reports, affect both. International events, such as the food price crisis of 2008, are the unintended outcome of national and international policy decisions that can detrimentally affect millions of people. More accurate and timely information to better inform policymakers is one way to reduce the likelihood of similar events in the future.
作者: Andrew Nelson,Mirco Boschetti,Giacinto Manfron,Franceco Holecz,Francesco Collivignarelli,Luca Gatti,Massimo Barbieri,Lorena Villano,Parvesh Chandna,Tri Setiyono
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To demonstrate how a combination of hypertemporal synthetic-aperture radar (SAR) and optical remote sensing (RS) data can be combined to generate both baseline map information and near–real-time monitoring information on crop extent and crop seasonality in Bangladesh.

The study demonstrates the joint use of active and passive data as a smart method, based on the strengths of both sensors, to produce rice extent information (from multi-year ASAR analysis) and seasonal monitoring (from MODIS analysis). Crop monitoring systems should rely on a range of remote-sensing information sources in order to obtain the best possible information and smart combinations.

The study acknowledges the challenges of using moderate-resolution data in regions characterized by pervasive cloud cover, small fields, and complex cropping systems. The conservative nature of the phenological detection with moderate-resolution data suggests that pixel-level interpretation and pixel counting for area estimation should be avoided as they are likely to be unreliable estimates of crop system characteristics.

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