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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:使用MODIS 250m网格植被产品进行稻米作物监测和收成评估:以泰国沙缴府为例

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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:世界上有数十亿人口依靠稻米作为主要食品和创收作物。亚洲是稻米种植的领导者,有必要维护与稻米有关的最新数据库,以确保粮食安全和经济发展。这项研究调查了省级水平的高分辨率中等分辨率成像光谱仪(MODIS)250m栅格化植被产品在水稻作物生长的监测,水稻作物种植图的绘制以及作物产量分析中的普遍适用性。泰国Sa Kaeo省的这项研究利用了MODIS 250m归一化植被指数(NDVI)和增强植被指数(EVI)的时间序列数据,田间数据和作物日历信息。使用了以下方法:(1)使用植被指数(VI)进行数据预处理和水稻植物生长分析(2)从VI时间序列数据中提取水稻种植面积和季节开始日期(3)准确性评估,以及(4)使用MODIS VI进行产量分析。结果表明稻株高与MODIS VI之间存在直接关系。作物日历信息和使用Whittaker Smoother进行的NDVI时间序列平滑处理可以估算出水稻的高种植面积(面积精度为86%,分类精度为75%)。点水平产量分析表明,MODIS EVI与水稻产量高度相关,在水稻周期预测产量中使用最大EVI预测产量,平均预测误差为4.2%。这项研究表明,MODIS网格化植被产品对于保持水稻种植的最新地理信息系统具有巨大的潜力。

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