Spatiotemporal Land Use Land Cover change analysis and erosion risk mapping of Azad Jammu and Kashmir, Pakistan

被引:95
作者
Iqbal, Muhammad Farooq [1 ]
Khan, Iftikhar Ahmad [2 ]
机构
[1] COMSATS Inst Informat Technol CIIT, Dept Meteorol, Islamabad 44000, Pakistan
[2] Forest Dept, Muzaffarabad, Ajk, Pakistan
关键词
LUCL; Erosion risk mapping; Change detection; Landsat; Soil erodibility; Remote sensing;
D O I
10.1016/j.ejrs.2014.09.004
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land Use Land Cover (LULC) change analysis assists decision makers to ensure sustainable development and to understand the dynamics of our changing environment. During the past 15 years the study area has undergone many LULC changes due to rapid urban growth, poorly planned infrastructural development and a devastating earthquake event. This study was proposed to detect LULC changes and to investigate the major factors that have caused these changes. Steep topography, shallow soils and monsoonal climatic conditions tend to accelerate soil erosion that causes heavy sedimentation downstream. Therefore, erosion risk mapping was performed to prioritize the vulnerable areas for conservation efforts. For LULC change detection and analysis temporal Landsat satellite data captured by Thematic Mapper (TM) were employed. Maximum Likelihood (MLH) supervised classification algorithm was applied to classify the study area, whereas, Post Classification Comparison (PCC) approach was adopted to analyze the LULC changes. Soil erosion risk map was generated using four erosion controlling factors including rainfall, topography, soil erodibility and LULC. Results revealed that over a period of 11 years, a decrease has taken place in forest and low vegetation cover at a change rate of -02.70% and -02.60% respectively. On the other hand, built up and bare soil have increased at a rate of 01.00% and 04.20% respectively. The resultant erosion risk map shows that 59% of the area lies under low risk zone whereas 24%, 5% and 12% of the total area fall in medium, high and very high risk categories respectively. (C) 2014 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
引用
收藏
页码:209 / 229
页数:21
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