Remote sensing and GIS application in the detection of environmental degradation indicators

The main aim of this research is to highlight the environment change indicators during the last 20 years in a representative area of the southern part of Iraq (Basrah Province was taken as a case) to understand the main causes which led to widespread environment degradation phenomena using a 1:250000 mapping scale. Remote sensing and GIS’s software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation land, sand land, urban area, unused land, and water bodies. Supervised classification and Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-up Index (NDBI), Normalized Difference Water Index (NDWI), Normalized Difference Salinity Index (NDSI), and Topsoil Grain Size Index (GSI) were adopted in this research and used respectively to retrieve its class boundary. The results showed a clear deterioration in vegetative cover (514.9 km2) and an increase of sand dune accumulations (438.6 km2), accounting for 10.1, and 10.6 percent, respectively, of the total study area. In addition, a decrease in the water bodies’ area was detected (228.9 km2). Sand area accumulations had increased in the total study area, with an annual increasing expansion rate of (33.7 km2 · yr−1) during the thirteen years covered by the study. It is therefore imperative that Iraqi government undertake a series of prudent actions now that will enable to be in the best possible position when the current environmental crisis ultimately passes.

[1]  Jabbar,et al.  Soil Loss by Wind Erosion for Three Different Textured Soils Treated with Polyacrylamide and Crude Oil, Iraq , 2001 .

[2]  D. P. Groeneveld,et al.  Broadband vegetation index performance evaluated for a low‐cover environment , 2006 .

[3]  H. Partow,et al.  The Mesopotamian Marshlands: Demise of an Ecosystem , 2002 .

[4]  Xiaoling Chen,et al.  Land degradation assessment with the aid of geo-information techniques , 2006 .

[5]  Andrew Warren,et al.  Land degradation is contextual , 2002 .

[6]  P. Raina,et al.  Mapping of soil degradation by using remote sensing on alluvial plain, Rajasthan, India , 1993 .

[7]  R. Tateishi,et al.  Relationships between percent vegetation cover and vegetation indices , 1998 .

[8]  S. K. McFeeters.  The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .

[9]  K. Z. Al-Janabi,et al.  Origin and nature of sand dunes in the alluvial plain of southern Iraq , 1988 .

[10]  David S. G. Thomas,et al.  Salinization: new perspectives on a major desertification issue , 1993 .

[11]  Feng Zhang,et al.  Eco-environmental degradation in the northeastern margin of the Qinghai–Tibetan Plateau and comprehensive ecological protection planning , 2008 .

[12]  Sun Danfeng,et al.  Landscape connectivity changes analysis for monitoring desertification of Minqin county, China , 2008, Environmental monitoring and assessment.

[13]  Herman Eerens,et al.  Sub-pixel classification of SPOT-VEGETATION time series for the assessment of regional crop areas in Belgium , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[14]  Yanjun Shen,et al.  Development of topsoil grain size index for monitoring desertification in arid land using remote sensing , 2006 .

[15]  Erik Lichtenberg,et al.  Assessing farmland protection policy in China , 2008 .

[16]  F. Sabins.  Remote Sensing: Principles and Interpretation , 1987 .

[17]  Yong Zha,et al.  A landscape approach to quantifying land cover changes in Yulin, Northwest China , 2008, Environmental monitoring and assessment.

[18]  Maria Teresa Pareschi,et al.  The Vegetation Resilience After Fire (VRAF) index: Development, implementation and an illustration from central Italy , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[19]  H. Partow,et al.  The Mesopotamian marshlands , 2009, Engineering and Technology Journal.

[20]  L. Venkataratnam,et al.  Mapping and monitoring of degraded lands in part of Jaunpur district of Uttar Pradesh using temporal spaceborne multispectral data , 2000 .

[21]  Xiaoling Chen,et al.  Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+ , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..