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基于多光谱与统计数据的凤台县地理国情分析方法探讨
黄慧,侯恩兵,董斌,陈春晖,张治凡,陈凌娜,王成,叶小康
0
(安徽省智慧城市与地理国情监测重点实验室,合肥 230061; 安徽农业大学理学院,合肥 230036)
摘要:
地理国情是重要的基本国情,对服务经济社会发展有着重要的意义。利用安徽省凤台县凤凰镇多光谱影像数据和安徽省第一次地理国情普查数据库,以2012年1:50 000更新数据为参照,从凤凰镇地表覆盖概况和变化情况角度分析该地区的城镇扩张变化程度与趋势,深层次地研究其内在驱动力因素并提出相应的措施。结果表明,2期数据的地表覆盖中耕地面积占比最大;地表覆盖变化面积居中,减小面积较大的是耕地和草地,增加面积较大的是房屋、道路和建筑用地;地表覆盖净增面积中,耕地、林地和水域面积有所减少,园地、草地、建筑区和道路等要素面积均有增加。总体来说,凤凰镇2012—2015年间主要地类变化为耕地转向建设用地,造成其根本驱动力表现在经济因素和人口因素。
关键词:  多光谱数据  地理国情  地表覆盖  统计分析
DOI:10.13610/j.cnki.1672-352x.20180620.020
基金项目:安徽省智慧城市与地理国情监测重点实验室开放性课题基金(2016-K-04Z), 国家自然科学基金面上项目(41571101), 安徽省国土资源厅科技项目(2013-k-10), 安徽省高校省级自然科学研究项目(KJ2012Z108)和
Geographic analysis based on the multispectral and statistical data of Fengtan county
HUANG Hui,HOU Enbing,DONG Bin,CHEN Chunhui,ZHANG Zhifan,CHEN Lingna,WANG Cheng,YE Xiaokang
(Anhui Key Laboratory of Smart City and Geographical Condition Monitoring, Hefei 230061; School of Science, Anhui Agricultural University, Hefei 230036)
Abstract:
The national geographical condition is an important basic national condition. Based on the multi-spectral image data of Fenghuang town in Fengtai county, Anhui Province and the first geographical conditions survey database in Anhui Province, we analyzed the extent and tendency of urban expansion from the perspective of surface coverage and changes with the updated data of 1: 50 000 in 2012 to further study its internal driving force and put forward the corresponding measures. These results were as follows: the agricultural acreage was the biggest part of the ground cover acreage based on the two periods of data. Regarding the change of the ground cover, the large reduction areas were the cultivated land and grassland and the large increased area were the housing land, the roads land and the buildings land. Of the net area change of the ground cover, the areas of forest land, cultivated land and waters was decreased, while the areas of garden plots, grassland, building area, road, etc. were increased. In general, the main land change was the change of the cultivated land to the buildings land in 2012-2015, which reflected the fundamental driving force of economic and population factors.
Key words:  multi-spectral data  national geographical conditions  ground mulching  statistical analysis

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