This chapter provides a proof of concept for how a key staple crop can be monitored on a national scale using existing remote-sensing (RS) products that will soon be complemented and superseded by forthcoming sensors. Our exemplar crop is rice and our test country is Bangladesh (Figure 1). This region is highly suitable for a demonstration because of the triple remote-sensing challenge of pervasive cloud cover, small field size, and complex cropping patterns, which are typical of the vast and important agricultural areas of Asia, Africa, and Latin America. It is these areas where future gains in productivity must and will be made, not the agricultural areas of Europe, the US, and other developed regions where crop monitoring is substantially easier. We first briefly describe the rice environments of Bangladesh, and then demonstrate how a combination of hypertemporal synthetic-aperture radar (SAR) and optical RS data can be combined to generate both baseline map information and near-real-time monitoring infor- mation on crop extent and crop seasonality.

Combining Moderate-Resolution Time-Series RS Data from SAR and Optical Sources for Rice Crop Characterisation: Examples from Bangladesh

Mirco Boschetti;Giacinto Manfron;
2014

Abstract

This chapter provides a proof of concept for how a key staple crop can be monitored on a national scale using existing remote-sensing (RS) products that will soon be complemented and superseded by forthcoming sensors. Our exemplar crop is rice and our test country is Bangladesh (Figure 1). This region is highly suitable for a demonstration because of the triple remote-sensing challenge of pervasive cloud cover, small field size, and complex cropping patterns, which are typical of the vast and important agricultural areas of Asia, Africa, and Latin America. It is these areas where future gains in productivity must and will be made, not the agricultural areas of Europe, the US, and other developed regions where crop monitoring is substantially easier. We first briefly describe the rice environments of Bangladesh, and then demonstrate how a combination of hypertemporal synthetic-aperture radar (SAR) and optical RS data can be combined to generate both baseline map information and near-real-time monitoring infor- mation on crop extent and crop seasonality.
2014
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
978-953-51-1589-2
RADAR & optical data integration
time series
agricultural monitoring
rice
Bangladesh
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/245348
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