Rapid and simultaneous estimation of certain soil physico-chemical properties by regression modelling using the hyperspectral signature of agricultural soils

S. Arunageetha, S. Rajendran, P. S Senthil Kumar, R. Kumaraperumal, S. Raja, P. Kannan

Research output: Contribution to journalArticle

Abstract

Application of remote sensing in crop production has gained its popularity in recent times due to an increased concern on issues like land degradation, soil pollution, etc. caused by imbalanced fertilization of agricultural lands. Past research in this area has focused primarily on the use of spectral signature of crops as an indirect indicator and as a response factor to the nutrient management systems imposed in soil. Spectral features of various soil properties have not been fully evaluated, especially, concerning the studies on soil fertility evaluation. In this study, spectral evaluation on selected soils was done to determine wavelengths and /or combinations of wavelengths that are indicative of certain soil properties (pH, EC, OC, available phosphorus, available sulphur and available potassium). Further, based on the reference spectral points and reflectance inflection difference (RID) values, various prediction models were developed using simple linear regression (SLR) and multiple linear regression (MLR) approaches and were evaluated as a foundation towards the establishment of functional spectral library' for the coastal soils of Tamil Nadu. The results revealed that certain spectral reflectance at specific wavelengths and RID value based spectral regions have been proved to exhibit significant relationships with specific soil properties. The MLR based models were found to provide better estimates of the soil attributes than SLR ones and the models involving RID values were highly effective for quantifying the soil attributes than the individual spectral reflectance values of the soil. Laboratory spectral reflectance (SR) yielded high correlations with traditional laboratory analyses using MLR equations with R2 values > 0.70 for all the soil attributes studied. Therefore, for various soil fertility evaluation studies, soil properties can be predicted directly, better with VNIR reflectance spectroscopy than the conventional approach involving the indirect laboratory methods.

Original languageEnglish
Pages (from-to)339-344
Number of pages6
JournalResearch on Crops
Volume11
Issue number2
Publication statusPublished - Aug 2010

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Keywords

  • Hyperspectral
  • Reflectance spectroscopy
  • Remote sensing
  • Soil nutrients
  • Soil testing

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Soil Science

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