摘要
以2000年、2010年的TM遥感影像以及数字高程模型、水系、铁路、公路、降雨量、气温等数据为基础,综合运用Binary Logistic和CA-Markov模型,对陕西省咸阳台塬区的土地利用格局进行模拟,并对咸阳台塬区2020年的土地利用进行预测。结果表明:①2000—2010年,建设用地和林地呈增加趋势,而耕地、草地、水域和未利用地呈减少趋势,其中耕地减少的趋势与建设用地增加的趋势基本一致。②从土地利用转化的方向来看,草地主要转化为林地,其次流向耕地、建设用地和水域;建设用地和林地主要来源于耕地;林地和水域面积变化不太明显,而未利用地则主要是由耕地转化而来,并少量流向耕地。③对Binary Logistic回归模型的研究结果图层进行组合,并将其作为CA-Markov输入参数中的适宜性图层,可以拓展CA-Markov模型的应用范围,同时也在一定程度上提高了模拟的预测精度。④到2020年建设用地面积急剧增加,增加的区域主要集中在原有建设用地周边,扩展的趋势主要是沿着道路和铁路沿线,建设用地变化最为明显的区域主要集中在咸阳市的秦都区三原县。
Based on the remote sensing images in the years 1990 and 2000 and the data of digital elevation model, stream systems, railways, highways, precipitation and temperature, the integrated use of Binary Logistic Regression and CA-Markov model was developed to simulate the land use patterns in the loess tableland areas in Xianyang, Shaanxi Province, and the land use types there in the near future were predicted. The results are as follows： ① There was an expansion of construction land and woodland during the period from 2000 to 2010, but the area of arable land, grass- lands,waters and unused land was reduced,in which the reduction trend of arable land and the expansion trend of construction land were similar; ② Investigating from the conversion direction of land use types, grassland was mainly changed into woodlands, and then into farmland, construction land and waters; construction land and woodland was mainly from arable land; the change of area of woodland and waters was not significant, unused land was mainly from arable land ,and some unused land in small area was changed into arable land; ③Through inputting the parameters which were combined with the results of Binary Logistic Regression, the application range of CA-Markov model was expanded ,and the prediction of land use was improved to some degree ; ④ It was predicted that the area of construc- tion land in the study area in 2020 would be expanded dramatically, especially in the surrounding regions of the origi- nal construction land, along the railways and highways, and in Sanyuan County of Qindu District, Xianyang City.
出处
《干旱区研究》
CSCD
北大核心
2013年第3期563-569,共7页
Arid Zone Research
基金
基于3S技术的广西湿地资源信息系统研究(桂科能1002K008)
