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Study of land use/land cover dynamics through classification algorithms for Harangi catchment area, Karnataka State, INDIA

机译:印度卡纳塔克邦喀纳塔卡州喀纳塔卡州地区土地利用/陆地覆盖动力学研究

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Industrialization and urbanization are mainly responsible for the conversion of significant amount of vegetation rich lands such as forests and wetlands into agricultural lands and human settlements. This land use and land cover change in turn has influence on various hydrological processes such as soil erosion rate, sediment deposition in rivers and dams and also stream flow pattern in a catchment. Qualitative and quantitative analysis of Land use and Land cover (LU/LC) changes is necessary to assess the impacts of change in the pattern of natural vegetation on the earth's environment. Satellite images can provide useful information regarding spatial and temporal variation of LU/LC in an area. The purpose of this paper is to analyse the dynamics of LU/LC changes using LISS-III data for the years 2007, 2010 and 2013 of Harangi catchment, Coorg District, Karnataka State, India. Also, study compares three classification techniques such as Parallelepiped Algorithm, Minimum Distance to Mean Algorithm and Maximum Likelihood Algorithm based on the value of overall accuracy and kappa coefficient to check the reliability of the methods in classifying images. The overall accuracy and kappa coefficient obtained by using Parellelepiped, Minimum distance to mean and Maximum likelihood algorithm for the year 2013 are 81.47% & 0.71, 78.67 & 0.68 and 89.36% & 0.81 respectively. Based on these results, it can be concluded that, among all the three techniques, the Maximum Likelihood Algorithm gave higher accuracy with high kappa coefficient and Minimum Distance to Mean Algorithm gave lower accuracy. The LU/LC change detection results between years 2007 and 2013 indicated a drastic change in forest area, plantation and waste land among all other classes. The forest area decreased dramatically from 183.12 sq. km to 131.02 sq. km. Also, fallow land and water body are decreased from 68.89 sq. km to 42.63 sq. km and 6.71 sq. km to 3.82 sq. km respectively. In contrast, the plantation and waterlogged area are observed to have an increasing trend of about 56.07 sq. km to 146.55 sq. km and 17.99 sq. km to 23.81 sq. km. The urban area has been increased from 13.06 sq. km to 13.72 sq. km. The urbanization and agricultural activities are the major reasons for increase in plantation and urban area in an expense of decrease in forest area.
机译:工业化和城市化主要负责将大量植被的植被转换为森林和湿地等森林和湿地进入农业土地和人类住区。该土地使用和陆地覆盖变化依次对各种水文过程产生影响,如土壤侵蚀率,河流和水坝中的泥泥沉积以及集水区中的流动模式。有必要对土地利用和陆地覆盖(LU / LC)进行定性和定量分析,以评估地球环境上的自然植被模式的影响。卫星图像可以提供关于一个区域中LU / LC的空间和时间变化的有用信息。本文的目的在于分析LU / LC的动态使用LISS-III的数据为2007年,2010年和Harangi流域的2013年,库格区,卡纳塔克邦,印度的变化。此外,研究比较了三种分类技术,例如并行六面体算法,最小距离到基于总体精度和κ系数的值和κ系数的基于总体精度和κ系数的最大似然算法,以检查分类图像中的方法的可靠性。通过使用镶嵌和2013年的均值和最大似然算法获得的总体精度和κ系数分别为81.47%和0.71,78.67&0.68和89.36%和0.81。基于这些结果,可以得出结论,在所有三种技术中,最大似然算法具有高κ系数的准确性,并且与平均算法的最小距离产生较低的精度。 LU / LC改变检测结果2007年和2013年之间表明,所有其他课程中的森林面积,种植园和废物土地的激烈变化。从183.12平方公里划分为131.02平方公里,森林面积急剧下降。此外,休耕土地和水体从68.89平方公里减少到42.63平方公里,分别为3.71平方公里。km至3.82平方公里..km。相比之下,观察到种植园和涝渍区域的趋势增加约56.07平方公里至146.55平方公里.km和17.99平方公里。km到23.81平方公里。市区从13.06平方公里增加到13.72平方公里。城市化和农业活动是森林地区减少种植园和城市地区的主要原因。

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