Spatial modeling of SPAD values for different type of crops using LISS-IV satellite imagery

2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE) Pub Date : 2015-12-01 DOI:10.1109/ICMOCE.2015.7489728

D. Gupta, R. Prasad, Pradeep Kumar, V. Mishra, A. K. Vishwakarma, R. S. Singh, V. Srivastava

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引用次数: 1

Abstract

The aim of present study is to assess the feasibility of Linear Imaging Self Scanning (LISS-IV) sensor data for the spatial modeling of SPAD (Soil-Plant Analysis Development) values to monitor the spatial distribution of chlorophyll contents in the agricultural areas. Six crop fields and ten different GPS locations in each crop field were selected for the measurement of SPAD values. The DN (digital number) values of each pixel of LISS-IV satellite image were converted into their top of atmospheric (TOA) reflectance values. The measurement of SPAD values were carried out at the same time of satellite passes over the study area. Two band algorithms was developed using cubic polynomial regression analysis between spectral coefficients and SPAD values. The performance of the two band algorithm was evaluated by using statistical performance indices like %Bias, root mean squared error (RMSE) and Nash-Sutcliffe efficiency (NSE). The values of %Bias, RMSE and NSE were found -0.04, 3.99 and 0.95 respectively.

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基于LISS-IV卫星影像的不同作物SPAD值空间建模

本研究的目的是评估线性成像自扫描(LISS-IV)传感器数据用于SPAD(土壤-植物分析发展)值空间建模以监测农区叶绿素含量空间分布的可行性。选取6块作物田和每个作物田10个不同的GPS位置测量SPAD值。将LISS-IV卫星影像各像元的DN (digital number)值转换为其大气顶反射率(TOA)值。SPAD值的测量是在卫星经过研究区域的同时进行的。利用光谱系数与SPAD值之间的三次多项式回归分析，提出了两种波段算法。采用%Bias、均方根误差(RMSE)和Nash-Sutcliffe效率(NSE)等统计性能指标评价两波段算法的性能。%Bias、RMSE和NSE分别为-0.04、3.99和0.95。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE)

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