Measuring Rice Yield from Space: The Case of Thai Binh Province, Viet Nam

Kaiyu Guan,Zhan Li,Lakshman Nagraj Rao,Ngo The Hien

doi:10.2139/ssrn.3188560

Abstract

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.

Highlights

Rice is an important staple crop grown in Southeast Asia, accounting for nearly 25% of the total rice area planted in the world and more than 22% of global rice production (FAO 2016)
The objective of this paper is to build a prototype to map paddy rice fields and estimate crop yield in Thai Binh, using multiple satellite data sources: Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Land Observing Satellite 2 (ALOS-2)/PALSAR-2; and field data collected through crop cutting activities during the rainy season of 2015
Measuring Rice Yield from Space: The Case of Thai Binh Province, Viet Nam | 15 We find that the ALOS-2 backscatter bears little information for paddy rice yield prediction over this study region (Figure 7)

Summary

Introduction

Rice is an important staple crop grown in Southeast Asia, accounting for nearly 25% of the total rice area planted in the world and more than 22% of global rice production (FAO 2016). Crop area and yield are estimated using administrative data, whereby government agricultural extension officers observe harvests, interview village heads and/or farmers in their assigned localities, and report the estimates to their level of bureaucracy, until the summary statistics reach the national government. While this data collection approach is inexpensive, estimates derived can be prone to large measurement errors (ADB 2016). Administrative reporting often does not usually include a validation process that could improve the quality of estimates (ADB 2016)

Objectives

Results

Conclusion