The application of the piecewise linear approximation to the spectral neighborhood of soil line for the analysis of the quality of normalization of remote sensing materials


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Abstract

The concept of soil line can be to describe the temporal distribution of spectral characteristics of the bare soil surface. In this case, the soil line can be referred to as the multi-temporal soil line, or simply temporal soil line (TSL). In order to create TSL for 8000 regular lattice points for the territory of three regions of Tula oblast, we used 34 Landsat images obtained in the period from 1985 to 2014 after their certain transformation. As Landsat images are the matrices of the values of spectral brightness, this transformation is the normalization of matrices. There are several methods of normalization that move, rotate, and scale the spectral plane. In our study, we applied the method of piecewise linear approximation to the spectral neighborhood of soil line in order to assess the quality of normalization mathematically. This approach allowed us to range normalization methods according to their quality as follows: classic normalization > successive application of the turn and shift > successive application of the atmospheric correction and shift > atmospheric correction > shift > turn > raw data. The normalized data allowed us to create the maps of the distribution of a and b coefficients of the TSL. The map of b coefficient is characterized by the high correlation with the ground-truth data obtained from 1899 soil pits described during the soil surveys performed by the local institute for land management (GIPROZEM).

About the authors

D. I. Rukhovich

Dokuchaev Soil Science Institute

Author for correspondence.
Email: landmap@yandex.ru
Russian Federation, per. Pyzhevskii 7, Moscow, 119017

M. S. Simakova

Dokuchaev Soil Science Institute

Email: landmap@yandex.ru
Russian Federation, per. Pyzhevskii 7, Moscow, 119017

A. L. Kulyanitsa

Natinal University of Science and Technology MISiS

Email: landmap@yandex.ru
Russian Federation, Leninskii Prosp. 4, Moscow, 119049

A. D. Rukhovich

Lomonosov Moscow State University

Email: landmap@yandex.ru
Russian Federation, Leninskie gory 1, Moscow, 119991

D. D. Rukhovich

Lomonosov Moscow State University

Email: landmap@yandex.ru
Russian Federation, Leninskie gory 1, Moscow, 119991

P. V. Koroleva

Dokuchaev Soil Science Institute

Email: landmap@yandex.ru
Russian Federation, per. Pyzhevskii 7, Moscow, 119017


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