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RICE CROP MONITORING AND YIELD ASSESSMENT WITH MODIS 250m GRIDDED VEGETATION PRODUCT: A case study in Sa Kaeo Province, Thailand

机译:用MODIS 250M包装植被产品的稻米作物监测和产量评估:泰国SA Kaeo省的案例研究

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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.
机译:数十亿人在世界上依赖米饭作为主食,作为创收作物。亚洲是水稻种植的领导者,有必要维持最新的与水稻相关数据库,以确保粮食安全和经济发展。本研究研究了高时分辨率中度分辨率成像分光仪(MODIS)250M包装植被产品的一般适用性,用于监测稻米作物生长,绘制稻田种植面积和分析省级级别。在SA Kaeo省,泰国的这项研究中,MODIS 250M归一化差异植被指数(NDVI)和增强型植被指数(EVI)时间序列数据,现场数据和作物日历信息。使用以下方法:(1)数据预处理和水稻植物生长分析使用植被指数(vi)(2)从vi时间序列数据(3)准确评估的稻米面积和季节日期的提取, (4)MODIS VI的产量分析。结果表明了水稻植物高度和MODIS VI之间的直接关系。作物日历信息和平滑的NDVI时间序列与Whittaker Smoother提供高水稻面积估计(具有86%的区域精度和75%的分类精度)。点水平产量分析表明,Modis EVI与水稻产量和使用大米循环预测产量的最大EVI的产量预测与平均预测误差为4.2%。本研究表明,MODIS网格植被产品的巨大潜力,用于保持水稻栽培的最新地理信息系统。

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