Unveiling Spatial Variation in Salt Affected Soil of Gautam Buddha Nagar District Based on Remote Sensing Indicators

Somvanshi, Shivangi S.; Kunwar, Phool; De Vries, Walter Timo; Kumari, Maya; Zubair, Syed

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Unveiling Spatial Variation in Salt Affected Soil of Gautam Buddha Nagar District Based on Remote Sensing Indicators

Shivangi S. Somvanshi

Somvanshi, Shivangi S.

,

Phool Kunwar

Kunwar, Phool

,

Walter Timo De Vries

De Vries, Walter Timo

,

y

26 may 2020

Journal of Landscape Ecology

Volumen 13 (2020): Edición 1 (Mayo 2020)

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Publicado en línea: 26 may 2020

Páginas: 61 - 84

Recibido: 09 ene 2020

Aceptado: 02 abr 2020

DOI: https://doi.org/10.2478/jlecol-2020-0005

Palabras clave
Soil quality parameters, Landsat OLI & TIRS, Correlation, Artificial Neural Network (ANN), Multiple Linear Regression (MLR), Analytical Hierarchy Process (AHP) and Weighted Index Overlay (WIO)

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Somvanshi, Shivangi S.

Amity Institute of Environmental Sciences, Amity UniversityNoida, India

Kunwar, Phool

Remote Sensing Application Centre – Uttar PradeshLucknow, India

De Vries, Walter Timo

Department of Civil, Geo and Environmental Engineering, Technische Universitat MunchenGermany

Kumari, Maya

Amity School of Natural Resources and Sustainable Development, Amity UniversityNoida, India

Zubair, Syed

Department of Civil Engineering, Amity School of Engineering and Technology, Amity UniversityNoida, India

Idioma:: Inglés

Calendario de la edición:: 4 veces al año
Temas de la revista:: Geociencias, Geociencias, otros, Ciencias de la vida, Ecología

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Unveiling Spatial Variation in Salt Affected Soil of Gautam Buddha Nagar District Based on Remote Sensing Indicators

Shivangi S. Somvanshi

Phool Kunwar

Walter Timo De Vries

Maya Kumari

Syed Zubair

Publicado en línea: 26 may 2020

Páginas: 61 - 84

Recibido: 09 ene 2020

Aceptado: 02 abr 2020

DOI: https://doi.org/10.2478/jlecol-2020-0005

Palabras claveSoil quality parameters, Landsat OLI & TIRS, Correlation, Artificial Neural Network (ANN), Multiple Linear Regression (MLR), Analytical Hierarchy Process (AHP) and Weighted Index Overlay (WIO)

© 2020 Shivangi S. Somvanshi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
Soil quality parameters, Landsat OLI & TIRS, Correlation, Artificial Neural Network (ANN), Multiple Linear Regression (MLR), Analytical Hierarchy Process (AHP) and Weighted Index Overlay (WIO)