近30a瀛湖流域土地利用时空变化的遥感分析

发布时间：2018-02-21 18:32

本文关键词： 土地利用遥感时空变化瀛湖南水北调水源区　出处：《人民长江》2017年13期 　论文类型：期刊论文

【摘要】：为揭示1988~2014年南水北调中线工程水源区瀛湖流域土地利用变化规律,以Landsat TM/ETM+和ALOS遥感影像为数据源,采用监督分类与目视解译相结合的分类方法,提取瀛湖流域1988~2014年5期土地利用信息,分析了土地利用时空变化特征。精度分析表明:监督分类与人工目视解译相结合方法,能够快速、准确地完成土地利用空间分布信息提取,ALOS影像总体分类精度达98%以上;但是Landsat TM/ETM+等中低分辨率遥感影像难以识别山区较分散的农村居民用地等建设用地,导致建设用地解译结果偏低。土地分类结果表明:受山谷型地貌特点影响,瀛湖流域土地利用类型呈斑块状交错分布,建设用地多呈条带状分布;目前土地利用类型以草地、耕地和林地为主,分别约占流域面积的51%,29%和18%;1988年以来建设用地的年变化率最大,高达22%,新增量来源主要是耕地,其贡献比例高达87%。
[Abstract]:In order to reveal the law of land use change in Yinghu watershed in the middle route project of South-to-North Water transfer Project from 1988 to 2014, the Landsat TM/ETM and ALOS remote sensing images were used as data sources, and the classification method combined with supervised classification and visual interpretation was adopted. The land use information of Yinghu Basin from 1988 to 2014 was extracted, and the temporal and spatial changes of land use were analyzed. The precision analysis showed that the combination of supervised classification and artificial visual interpretation could be used quickly. The overall classification accuracy of land use spatial distribution information extraction is more than 98%, but the low resolution remote sensing images such as Landsat TM/ETM are difficult to identify the construction land such as scattered rural land in mountainous areas. The results of land classification show that the land use types of Yinghu Lake basin are patch like interlaced distribution, and most of the construction land is banded distribution, and the current land use type is grassland, the results of land classification show that the land use types in Yinghu Lake basin are plaques and interlaced distribution, and the current land use types are grassland. Cultivated land and woodland mainly account for 51% and 18% of the basin area, respectively. Since 1988, the annual change rate of construction land is the largest, up to 22%, the main source of increase is cultivated land, and its contribution ratio is as high as 87%.
【作者单位】：陕西省环境科学研究院;安康市汉滨区环保局;
【基金】：陕西省社会发展科技攻关项目(2015SF293)
【分类号】：F301.2;P237

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