Measuring Rice Yield from Space: The Case of Thai Binh Province, Vietnam
Guan, Kaiyu; Hien, Ngo The; Li, Zhan; Rao, Lakshman Nagraj | March 2018
Despite a growing interest in using satellite data to estimate paddy rice yield in Southeast Asia, significant cloud coverage has led to a scarcity of usable optical data for such analysis. In this paper, we study the feasibility of using two alternative sources of satellite data—(i) surface reflectance fusion data which integrates Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) images, and (ii) L-band radar backscatter data from the Advanced Land Observing Satellite 2 (ALOS-2) PALSAR-2 sensors—to circumvent the cloud cover problem and estimate yield in Thai Binh Province, Viet Nam during the second growing season of 2015. Our findings indicate that although Landsat–MODIS fusion data are not necessarily beneficial for paddy rice mapping when compared with only using Landsat data, fusion data allows us to estimate the peak value of various vegetation indexes and derive the best empirical relationship between these indexes and yield data from the field. We also find that the L-band radar data not only has a lower performance in paddy rice mapping when compared with optical data, but also contributes little to rice yield estimation.
CitationGuan, Kaiyu; Hien, Ngo The; Li, Zhan; Rao, Lakshman Nagraj. 2018. Measuring Rice Yield from Space: The Case of Thai Binh Province, Vietnam. © Asian Development Bank. http://hdl.handle.net/11540/8126. License: CC BY 3.0 IGO.
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