Abstract
Abstract. Billions of people in the world depend on rice as a staple food and as an income-generating crop. Asia is the leader in rice cultivation and it is necessary to maintain an up-to-date rice-related database to ensure food security as well as economic development. This study investigates general applicability of high temporal resolution Moderate Resolution Imaging Spectroradiometer (MODIS) 250m gridded vegetation product for monitoring rice crop growth, mapping rice crop acreage and analyzing crop yield, at the province-level. The MODIS 250m Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) time series data, field data and crop calendar information were utilized in this research in Sa Kaeo Province, Thailand. The following methodology was used: (1) data pre-processing and rice plant growth analysis using Vegetation Indices (VI) (2) extraction of rice acreage and start-of-season dates from VI time series data (3) accuracy assessment, and (4) yield analysis with MODIS VI. The results show a direct relationship between rice plant height and MODIS VI. The crop calendar information and the smoothed NDVI time series with Whittaker Smoother gave high rice acreage estimation (with 86% area accuracy and 75% classification accuracy). Point level yield analysis showed that the MODIS EVI is highly correlated with rice yield and yield prediction using maximum EVI in the rice cycle predicted yield with an average prediction error 4.2%. This study shows the immense potential of MODIS gridded vegetation product for keeping an up-to-date Geographic Information System of rice cultivation.
Highlights
1.1 BackgroundRice is the second most harvested staple food in the world and the leading staple food in Asia
The results obtained by this research confirm that there is an observable relationship with rice plant growth and Vegetation Indices (VI) changes in rice paddy land cover
Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) rice paddy acreage mapping gives a minimum of 86% area accuracy and 75% classification accuracy
Summary
Rice is the second most harvested staple food in the world and the leading staple food in Asia. 60% of the global population and 90% of the world rice production is derived from the Asian continent (Claessens, 2013). Rice monitoring and mapping are very important for optimizing food security, environmental sustainability, water security, greenhouse gas emission reduction and general economic prosperity. Most countries in the Asian region use limited survey methods to collect rice paddy data from community level to national level. These data sources do not meet the needs of science and policy researchers, who need geo-spatial databases of rice agriculture with updated spatial and temporal resolution (Xiao et al, 2006)
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