巴基斯坦吉尔吉特伊什科曼流域山区人为原因引起的土地覆盖变化评估

Komal Nabi, K. Ali, M. Ashraf, A. Imran, N. Ahmad
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引用次数: 0

摘要

遥感(RS)提供了监测时间变化和了解土地利用动态的最佳方法。当社区对变化的主要驱动因素的认识得到整合时,遥感分析可以进一步加强。本研究旨在评价吉泽尔地区伊什科曼流域土地利用和土地覆被的变化。该研究利用Landsat-5和Landsat-8图像来评估1998年至2018年的LULC动态,并使用问卷调查来了解社区对过去20年LULC变化的看法。利用监督分类技术监测1998年至2018年间的变化,并利用最大似然技术将像元分为6类:植被/林区、裸岩、水体、冰川/雪区、河流、水和农业。在问卷调查中,建立了自变量(人口、开垦土地类型、新增家庭成员所需额外土地)与因变量(土地利用动态因素和社会经济变量)之间的相关矩阵和回归模型。结果表明,1998-2018年间,所有6个土地覆盖类别都出现了时间变化,其中森林和牧场的变化最为显著(从18.7%降至5.9%)。同样,1998年至2018年间,冰川、水、河流和农业分别从13.1、6.5、9.3、1.5变化为15.8、4.0、11.32、3.1。裸露岩石的变化最大,从50.2%增加到60.06%。此外,时间NDVI分析显示,1998-2018年期间植被覆盖减少(转化为裸岩)。调查结果显示,人口增长与农作物产量下降的相关性最高(R2 = -0.348),而人口增长与公交站点的相关性最低(R2 = -0.167)。同样,道路和市场的可及性(R2 = 0.349)与因变量(土地清理类型)之间的相关性最高,而水资源的可及性最低(R2 = -0.021)。该研究得出结论,1998年至2018年,Ishkoman流域的土地利用和土地覆盖发生了显著变化。该研究建议进行更深入的研究,通过使用高分辨率卫星图像,在更精细的尺度上检查土地利用和土地覆盖的变化,并对土地利用动态的潜在人为原因进行详细调查。
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ASSESSMENT OF LAND COVER CHANGES DUE TO ANTHROPOGENIC CAUSES IN THE MOUNTAINOUS AREA OF ISHKOMAN WATERSHED, GILGIT, PAKISTAN
Remote Sensing (RS) provides the best ways to monitor temporal changes and to understand land use dynamics. Remote sensing analysis can be further enhanced when community perception regarding major drivers of change is integrated. The present study was an attempt to assess the land use land cover changes in the Ishkoman watershed in the Ghizer district. The study explored Landsat-5 and Landsat-8 images to assess the LULC dynamics from 1998 to 2018, and also used questionnaires for community perception regarding LULC changes in the past two decades. Supervised classification was used to monitor changes between 1998 and 2018 and the maximum likelihood technique was used to categorize the pixels into six classes: vegetation/forest area, bare rocks, water bodies, glaciers/snow area, rivers, water, and agriculture. Regarding the questionnaires, the correlation matrix and regression models were developed between independent variables (population, land type cleared, and extra land required for new family members) and dependent variables (land use dynamics factors and socio-economic variables). The results showed that all six land cover classes have shown temporal changes between 1998-2018 and the most significant change was observed in forests and pastures (which decreased from 18.7% to 5.9 %). Similarly, glaciers, water, rivers, and agriculture have changed from 13.1, 6.5, 9.3, 1.5 to 15.8, 4.0, 11.32, 3.1, respectively between 1998-2018. The largest change was observed in bare rocks which increased from 50.2 % to 60.06%. Moreover, temporal NDVI analysis showed a decrease in vegetation cover (conversion to bare rocks) between 1998-2018. The questionnaire results revealed that the highest correlation was shown between population increase and decrease in crop production (R2 = -0.348), whereas the lowest correlation was found in population increase and population access to bus stops (R2 = -0.167). Similarly, the highest correlation was found between access to roads and markets (R2 = 0.349) and dependent variable (land type cleared), whereas the lowest correlobserved in access to water resources (R2 = -0.021). The study concluded that land use land cover has been significantly changed from 1998 to 2018 in the Ishkoman Watershed. The study suggested more in-depth research to examine land use land cover changes at finer scales by using high resolution satellite imagery, and conducting details surveys regarding the underlying anthropogenic causes of land use dynamics.
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