机构地区:[1]Geographic Information System and Remote Sensing Department, Erath and Environmental Science Institute, Al Al-Bayt Univesity, Mafraq, Jordan [2]Biology Department, Science Faculty, Al Al-Bayt University, Mafraq, Jordan
出 处:《International Journal of Geosciences》2019年第5期576-588,共13页地球科学国际期刊(英文)
摘 要: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 < 0.05), soil organic carbon increases with increasing NDVI and decreasing BSI. NDVI, SAVI and BSI were considered a useful index to detect the spatial distribution of SOM concentrations and mapping using remote sensing data.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 < 0.05), soil organic carbon increases with increasing NDVI and decreasing BSI. NDVI, SAVI and BSI were considered a useful index to detect the spatial distribution of SOM concentrations and mapping using remote sensing data.
关 键 词:Soil Organic MATTER Remote Sensing NDVI SAVI BSI ARID and SEMI-ARID
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