Deforestation modeling and investigation on related physiographic and human factors using satellite images and GIS (Case study: Armerdeh forests of Baneh) | ||
| تحقیقات جنگل و صنوبر ایران | ||
| Article 9, Volume 16, Issue 3 - Serial Number 33, December 2008, Pages 443-431 PDF (666.96 K) | ||
| Document Type: Research article | ||
| Authors | ||
| Mohammad Rashid Amini* 1; Sha'ban Shataee Joybari2; Mohammad Hadi Moaieri3; Hedayatollah Ghazanfari4 | ||
| 1M.Sc. of forestry, Gorgan University | ||
| 2Associate Prof. of forestry, Gorgan University | ||
| 3Assistant Prof. of forestry, Gorgan University | ||
| 4Assistant Prof. of forestry, Kurdistan University | ||
| Abstract | ||
| In order to investigate on deforestation modeling and correlation between deforestation and physiographic parameters, man made settlements and roads parameters in Zagros forests using remote sensing and GIS, a case study was accomplished at the Armerdeh forests, Baneh, Iran. The Landsat 7 ETM+, IRS-1C images and aerial photos were used for forest extent mapping and obtaining forest extent changes from 1955 to 2002. The forest extent map in 1955 was produced from digitizing of a digital photo mosaic of aerial photos. The ETM+ and IRS-1C images were used to generate the forest extent map in 2002. The images were geo referenced using GCPs points and digital elevation model in some steps. In addition to main spectral bands, some arithmetic bands such as some rationing transformations, vegetation indices, tasseled cap transformation, and principal components analysis were used for classification processes. Moreover, the panchromatic images of ETM+ and IRS-1D with multi spectral bands were merged using IHS and automatic statistical PANSHARP techniques. After selecting some pixels as training area for forest and non forest classes, the best set bands for classification were chosen using severability indices. The images were classified with supervised classification to forest and non forest by maximum likelihood algorithm. Results showed that using the best selected ETM+ bands could better classified forest and non forest areas than other images by maximum likelihood algorithm with 81.3% overall accuracy and 0.64 Kappa coefficient. The result of forest change detection using forest maps of 1955 and 2002 showed that 4853 ha of the forest area have been reduced and 953 ha increased in this period. The Spearman test correlation and logistic regression model were used to investigate correlation between changed forests and the mentioned parameters. The result showed that there is inverse relationship between deforestation and distance from roads. Minimum and maximum deforestation were happened at north and east aspects, respectively. The result of applying logistic regression model indicated that distance from road is more effective than other parameters on deforestation in the study area. Because of irregular scattering of deforested area and low impact of other parameters, this model could not predicted deforested area, accurately. | ||
| Keywords | ||
| forest extent mapping; satellite data; aerial photos; modeling; regression logistic; GIS | ||
| References | ||
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