The informativeness of coefficients a and b of the soil line for the analysis of remote sensing materials
- Autores: Rukhovich D.1, Rukhovich A.2, Rukhovich D.2, Simakova M.1, Kulyanitsa A.3, Bryzzhev A.1, Koroleva P.1
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Afiliações:
- Dokuchaev Soil Science Institute
- Lomonosov Moscow State University
- National University of Science and Technology MISiS
- Edição: Volume 49, Nº 8 (2016)
- Páginas: 831-845
- Seção: Genesis and Geography of Soils
- URL: https://journals.rcsi.science/1064-2293/article/view/223454
- DOI: https://doi.org/10.1134/S1064229316080123
- ID: 223454
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Resumo
The coefficients of the soil line are often taken into account in calculations of vegetation indices. These coefficients are usually calculated for the entire satellite image, or are taken as constants without any calculations. In both cases, the informativeness of these coefficients is low and insufficient for the needs of soil mapping. In our study, we calculated soil line coefficients at 8000 lattice points for the territory of Plavsk, Arsen’evsk, and Chern districts of Tula oblast on the basis of 34 Landsat 5, 7, and 8 images obtained in 1985–2014. In order to distinguish between the soil line calculated for a given image and the soil line calculated for lattice points on the basis of dozens of multitemporal images, we suggest that the latter can be referred to as the temporal soil line. The temporal soil line is described by a classical equation: NIR = RED a + b, where a is its slope relative to the horizontal axis (RED), and b is the Y-axis (NIR) intercept. Both coefficients were used to create soil maps. The verification of the maps was performed with the use of data on 1985 soil pits. The informativeness of these coefficients appeared to be sufficient for delineation of eight groups of soils of different taxonomic levels: soddy moderately podzolic soils, soddy slightly podzolic soils, soddy-podzolic soils, light gray forest soils, gray forest soils, dark gray forest soils, podzolized chernozems, and leached chernozems. The b coefficient proved to be more informative, as it allowed us to create the soil map precisely on its basis. In order to create the soil map on the basis of the a coefficient, we had to apply some threshold values of the b coefficient. The bare soil on each of Landsat scenes was separated with the help of the mask of agricultural fields and the notion of the spectral neighborhood of soil line (SNSL).
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Sobre autores
D. Rukhovich
Dokuchaev Soil Science Institute
Autor responsável pela correspondência
Email: landmap@yandex.ru
Rússia, per. Pyzhevskii 7, Moscow, 119017
A. Rukhovich
Lomonosov Moscow State University
Email: landmap@yandex.ru
Rússia, Moscow, 119991
D. Rukhovich
Lomonosov Moscow State University
Email: landmap@yandex.ru
Rússia, Moscow, 119991
M. Simakova
Dokuchaev Soil Science Institute
Email: landmap@yandex.ru
Rússia, per. Pyzhevskii 7, Moscow, 119017
A. Kulyanitsa
National University of Science and Technology MISiS
Email: landmap@yandex.ru
Rússia, Leninskii pr. 4, Moscow, 119049
A. Bryzzhev
Dokuchaev Soil Science Institute
Email: landmap@yandex.ru
Rússia, per. Pyzhevskii 7, Moscow, 119017
P. Koroleva
Dokuchaev Soil Science Institute
Email: landmap@yandex.ru
Rússia, per. Pyzhevskii 7, Moscow, 119017