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INTER-COMPARISON OF SATELLITE BASED VEGETATION INDICES TO ESTIMATE CROP YIELD IN IRRIGATED AREAS OF INDUS BASIN

机译:基于卫星的植被指数在印度洋盆地灌溉区域的产量估算之间的比较

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Crop yield prediction is of significant importance to ensure food security and making efficient food management plans. The information on crop yield well before harvesting is required to prepare future plans. Traditionally in Pakistan crop yield estimation is being carried out by manual surveys and Village Master Sampling (VMS) which is laborious and time consuming. Initially, a comparison was performed between various satellite based indices e.g. Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), Modified Soil Adjusted Vegetation Index (MSAVI) to evaluate most appropriate vegetation index that performs better in irrigated areas of Indus Basin. Two Canal Commands i.e. Lower Chenab (LCC) and Muzaffargarh Canal (MZG) were selected for this purpose. A stepwise regression based model was developed for Wheat crop yield using MODIS and Landsat 8 vegetation products. Landuse and Land cover map was prepared by Supervised Classification and expert knowledge. Landsat 8 SAVI performed better than other indices of both Landsat 8 and MODIS with R~2 of 0.6 between SAVI and insitu crop yield. The relation between observed yield and predicted for Landsat 8 using SAVI based regression model was better than other indices with R2, Pearson correlation and Nash Scuffle Efficiency estimated at 0.70, 0.83 and 0.617 respectively. The maps thus generated will help concerned authorities to prepare security plan and reciprocate measures will be suggested for improvement.
机译:预测作物产量对于确保粮食安全和制定有效的粮食管理计划至关重要。在准备收获计划之前,需要在收割之前提供有关作物单产的信息。巴基斯坦传统上是通过人工调查和乡村主抽样(VMS)来进行农作物产量估算的,这既费力又费时。最初,在各种基于卫星的索引之间进行比较,例如归一化植被指数(NDVI),增强植被指数(EVI),土壤调整植被指数(SAVI),改良土壤调整植被指数(MSAVI)可以评估最合适的植被指数,这些指数在印度河流域灌区表现更好。为此,选择了两个运河指挥部,即下切纳布(LCC)和穆扎法尔加尔运河(MZG)。使用MODIS和Landsat 8植被产品开发了基于逐步回归的小麦作物产量模型。土地利用和土地覆盖图是根据监督分类和专家知识制作的。 Landsat 8 SAVI的表现优于Landsat 8和MODIS的其他指标,SAVI和原位作物产量之间的R〜2为0.6。使用基于SAVI的回归模型对Landsat 8的观察到的产量与预测之间的关系要好于其他指数,R2,Pearson相关性和Nash混合效率分别估计为0.70、0.83和0.617。这样生成的地图将帮助有关当局制定安全计划,并提出相应的对策以加以改进。

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