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https://doi.org/10.1016/j.catena.2016.05.023

has been cited by the following article:

• TITLE: The Estimation of Soil Organic Matter Variation in Arid and Semi-Arid Lands Using Remote Sensing Data

  AUTHORS: Majed Ibrahim, Fatima Ghanem, Afnan Al-Salameen, Abdallah Al-Fawwaz

  KEYWORDS: Soil Organic Matter, Remote Sensing, NDVI, SAVI, BSI, Arid and Semi-Arid

  JOURNAL NAME: International Journal of Geosciences, Vol.10 No.5, May 22, 2019

  ABSTRACT: Soil organic matter (SOM) is an important term to realize soil productivity and quality that is extremely influential on soil physical, chemical and biological processes; SOM is one of the key soil properties controlling nutrient budgets in agricultural production systems and is an important index of soil productivity. Remote sensing (RS) and Geographic Information System (GIS) techniques were used to assess organic matter in soil and determine the relationship between measures SOM in field and digital data to calculate or obtain the correlation coefficients applied to evaluate the strength and direction of the linear relationships. In this study Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Bare Soil Index (BSI) were used. The results show that the relationship between vegetation indices (NDVI, SAVI) and SOM in whole study area was (R2 = 0.19, p 2 = 0.01, p 2 = 0.13, p 2 = 0.11, p