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Assessment of spatial variation of soil moisture during Maize growthcycle using SAR observations

机译:使用SAR观察评估玉米生长血糖过程中土壤水分的空间变化

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Spatial Information about Soil moisture over agricultural crops are required for efficient irrigation which in turn helps in saving water and increases crop yield. Soil moisture also useful in prediction of flooded and drought regions. However field measurement of soil moisture is not a practical approach. The main objective of the study is to track soil moisture variation all along the maize growth period in a Semi-Arid region. There are only few studies carried out on soil moisture variation considering whole maize growing period. During the crop growing period soil moisture field investigation are conducted in synchronization with Satellite pass. Sentinel-la Synthetic Aperture RADAR (SAR) satellite, Interferometric wide swath dual polarized datawith 5.405 GHz frequency and central incidence angle of 23° with repeat period of 12 days was used in this study. All in all during growth period 6 satellite pass scenes are acquired and processed by standard procedure using Sentinel Application Platform (SNAP) software. An attempt was made to redeem surface soil moisture for the whole maize growing crop cycle using water cloud model. The whole period of maize crop was divided into 3 parts like seedling, growing and harvesting period and soil moistureis retrieved for each period. The estimated soil moisture was validated with 30 field measured soil moisture samplings. The correlation coefficient of retrieved and actual soil moisture of seedling, growing and harvesting periods are 0.77, 0.72 and 0.6 respectively. The output of this study will be helpful in formulating strategies for irrigation water management.
机译:有关农业农作物土壤水分的空间信息是有效的灌溉所需的,这反过来有助于节约用水并提高作物产量。土壤湿度也可用于预测洪水和干旱地区。然而,土壤水分的田间测量不是一种实用的方法。该研究的主要目的是在半干旱地区沿着玉米生长期追踪土壤湿度变化。考虑到整个玉米生长期,只有很少的研究进行了土壤湿度变化。在作物生长期间,土壤水分实地研究与卫星通过同步进行。 Sentinel-La合成孔径雷达(SAR)卫星,干涉宽的SWATH双极化DataWith 5.405 GHz频率和中央入射角23°,在本研究中使用了12天的重复期。所有在增长期间,通过使用Sentinel应用程序平台(SNAP)软件,通过标准过程获取和处理卫星通行证场景。试图使用水云模型兑换整个玉米生长作物周期的地表土壤水分。玉米作物的整个时期分为3个零件,如幼苗,生长和收获时期和每个时期检索的土壤湿润。估计土壤水分验证了30个田间测量的土壤水分叠片。幼苗的检索和实际土壤水分的相关系数分别为0.77,0.72和0.6。本研究的产出将有助于制定灌溉水管理的策略。

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