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  • 标题:The Estimation of Soil Organic Matter Variation in Arid and Semi-Arid Lands Using Remote Sensing Data
  • 本地全文:下载
  • 作者:Majed Ibrahim ; Fatima Ghanem ; Afnan Al-Salameen
  • 期刊名称:International Journal of Geosciences
  • 印刷版ISSN:2156-8359
  • 电子版ISSN:2156-8367
  • 出版年度:2019
  • 卷号:10
  • 期号:5
  • 页码:576-588
  • DOI:10.4236/ijg.2019.105033
  • 语种:English
  • 出版社:Scientific Research Pub
  • 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 < 0.05), while the relationship in arid areas was (R2 = 0.01, p < 0.05), and the relationship in semi-arid areas was (R2 = 0.13, p < 0.05). It can be concluded that the diversity in vegetation cover and humidity effects to the relationship between vegetation indices (NDVI, SAVI) and SOM, where these relationships increase rapidly in semi-arid areas more than arid areas. In the other hand about the relationship between SOM and BSI (R2 = 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 MatterRemote SensingNDVISAVIBSIArid and Semi-Arid
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