Integration of VIS–NIR Spectroscopy and Multivariate Technique for Soils Discrimination Under Different Land Management

Mohamed S. Shokr (), Abdel-rahman A. Mustafa, Talal Alharbi, Jose Emilio Meroño de Larriva, Abdelbaset S. El-Sorogy, Khaled Al-Kahtany and Elsayed A. Abdelsamie
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Mohamed S. Shokr: Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt
Abdel-rahman A. Mustafa: Soil and Water Department, Faculty of Agriculture, Sohag University, Sohag 82524, Egypt
Talal Alharbi: Geology and Geophysics Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Jose Emilio Meroño de Larriva: Department of Graphic Engineering and Geomatics, University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain
Abdelbaset S. El-Sorogy: Geology and Geophysics Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Khaled Al-Kahtany: Geology and Geophysics Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Elsayed A. Abdelsamie: National Authority for Remote Sensing and Space Sciences, Cairo 1564, Egypt

Land, 2024, vol. 13, issue 12, 1-25

Abstract: Proximal sensing has become increasingly popular due to developments in soil observation technologies and the demands of timely information gathering through contemporary methods. By utilizing the morphological, physical, and chemical characteristics of representative pedogenetic profiles established in various soils of the Sohag governorate, Egypt, the current research addresses the characterization of surface reflectance spectra and links them with the corresponding soil classification. Three primary areas were identified: recently cultivated, old cultivated, and bare soils. For morphological analysis, a total of 25 soil profiles were chosen and made visible. In the dark room, an ASD Fieldspec portable spectroradiometer (350–2500 nm) was used to measure the spectrum. Based on how similar their surface spectra were, related soils were categorized. Ward’s method served as the basis for the grouping. Despite the fact that the VIS–NIR spectra of the surface soils from various land uses have a similar reflectance shape, it is still possible to compare the soil reflectance curves and the effects of the surface soils. As a result, three groups of soil curves representing various land uses were observed. Cluster analysis was performed on the reflectance data in four ranges (350–750, 751–1150, 1151–1850, and 1851–2500 nm). The groups derived from the soil surface ranges of 350–750 nm and 751–1150 nm were not the same as those derived from the ranges of 1151–1850 nm and 1851–2500 nm. The last two categories are strikingly comparable to various land uses with marginally similar features. Based on the ranges of 1151–1850 nm and 1851–2500 nm in surface spectral data, the dendrogram effectively separated and combined the profiles into two separate clusters. These clusters matched different land uses exactly. The results can be used to promote the widespread usage of in situ hyperspectral data sets for the investigation of various soil characteristics.

Keywords: ASD Fieldspec; Proximal sensing; clustering; land use/landcover; Sohag governorate; Egypt (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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