Title: The use of remote sensing to characterise geomorphometry and soil properties at watershed scale

Authors: Turgay Dindaroglu; Vesna Tunguz; Emre Babur; Hiba M. Alkharabsheh; Mahmoud F. Seleiman; Rana Roy; Elina Zakharchenko

Addresses: Department of Forest Engineering, Faculty of Forestry, Karadeniz Technical University, 61080 Trabzon, Turkey ' Faculty of Agriculture, University of East Sarajevo, Bosnia and Herzegovina ' Department of Forest Engineering, Faculty of Forestry, Kahramanmaras Sutcu Imam University, 46100 Kahramanmaras, Turkey ' Department of Water Resources and Environment, Faculty of Agricultural Technology, Al Balqa Applied University, Salt 19117, Jordan ' Plant Production Department, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia; Department of Crop Sciences, Faculty of Agriculture, Menoufia University, Shibin El-Kom 32514, Egypt ' Department of Agroforestry and Environmental Science, Sylhet Agricultural University, Sylhet 3100, Bangladesh ' Department of Agrotechnologies and Soil Science, Faculty of Agrotechnologies and Natural Resource Management, Sumy National Agrarian University, H. Kondratieva, 160, Sumy 40021, Ukraine

Abstract: This study aims to investigate the complex ecological interactions between geomorphometry, spectral indices, and soil properties to develop a watershed management plan that can mitigate the effects of global warming. In this study, Sentinel-2 multi-spectral instrument data was used to map some spectral indices. The digital elevation model was used to map transportation capacity index (TCI), stream power index (SPI), compound topographic index (CTI), and curvature. Some soil properties were analysed using 128 top-soils. According to the results, a strong correlation (p < 0.05) was found between CTI and NDVI (0.358), NDWI (-0.336), NDMI (0.372), SBI (-0.298), pH (-0.165), and phosphorus (0.164). The highest correlation (p < 0.01) was found between SPI and phosphorus (0.301). The CTI model of the watershed, which was developed using geomorphometric data, can increase the success of forestry activities. Spectral indices have the potential to be used in the evaluation of soil properties and geomorphometric characteristics.

Keywords: geomorphometry; geographic information system; GIS; remote sensing; soil ecology; watershed; environmental modelling; land use; topsoil; spatial analyses.

DOI: 10.1504/IJGW.2022.10049112

International Journal of Global Warming, 2022 Vol.27 No.4, pp.402 - 421

Received: 14 Sep 2021
Accepted: 07 Jan 2022

Published online: 29 Jul 2022 *

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