PlanetScope遥感土壤电导率与地面实测数据在小麦和甜菜产量中的比较

U. Avdan, Gordana Kaplan, Zehra Yiğit Avdan, Dilek Küçük Matcı, F. Erdem, Ece Tuğba Mızık, Ilknur Demirtas
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引用次数: 2

摘要

土壤盐碱化是对可持续农业和粮食供应的连续性以及土壤结构恶化的主要威胁。在这种背景下,确定、减少和管理土壤盐分对于创造可持续的现代农业非常重要。测定土壤盐度通常在实验室环境中进行,并在地块上使用设备。遥感是精确估算和测绘盐度的重要方法之一。利用遥感技术,可以以低成本、低努力获得大面积的土壤盐度图。本研究旨在比较PlanetScope遥感土壤电导率与土耳其Alpu农业区小麦和甜菜田的地面测量数据。因此,在小麦和甜菜田的几个点使用原位测量测量电导率,并与当天获得的PlanetScope图像中的各种土壤盐度指数进行比较。通过线性回归分析,将电导率数据与其对应的土壤盐度光谱指标值进行相关性分析。结果表明,稻田土壤盐分与部分指标呈高度相关(R2 = 0.84)。该研究加强了利用遥感技术可以快速准确地获得大面积土壤盐度图的想法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Remote Sensing Soil Electrical Conductivity from PlanetScope and Ground Measured Data in Wheat and Beet Yields
Soil salinity is a major threat to the continuity of sustainable agriculture and food provision and the soil structure deterioration. In this context, determining, reducing and managing soil salinity is very important for creating sustainable modern agriculture. Determining soil salinity is generally carried out in the laboratory environment and devices used in land plots. Remote sensing is one of the important methods used for precise estimation and mapping of salinity. With remote sensing technology, soil salinity maps for large areas can be obtained with low cost and low effort. This study aims to compare remote sensing soil electrical conductivity from PlanetScope and ground measured data in wheat and beet fields in the farming areas of Alpu, Turkey. For that reason, electrical conductivity was measured at several points in wheat and beet fields using in-situ measurements and compared with various soil salinity indices from PlanetScope imagery acquired on the same day. Linear regression analysis was carried out to correlate the electrical conductivity data with their corresponding soil salinity spectral index values. The results show a high correlation (R2 = 0.84) between soil salinity in wheat fields and some of the used indices. This study strengthens the idea that soil salinity maps can be obtained fast and accurately for large areas using remote sensing technology.
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