To evaluate the quantitative effect of the topographic conditions on the spatial distribution of land use, the Shanxi Province is taken as the research area， to study four topographic factors (the elevation, the relief, the slope and the aspect) obtained from the DEM dataset, representing the digital topographic characteristics, and the spatial distribution of the land use is interpreted based on the remote sensing images, finally to analyze the spatial stratified heterogeneity, the spatial correlation and the interaction effect of the four digital topographic factors on the spatial distribution of the land use. It is shown that: (1) the relief and slope factors have the most remarkable spatial stratified heterogeneity effect (p<0.01); (2) the relief factor has the strongest spatial correlation effect (q=0.012), followed by the slope (q=0.010); (3) any two kinds of digital terrain indicators have a significant interaction enhancement; the interaction between the altitude and the relief has the strongest effect with the highest statistic value q of 0.034. Hence, the relief factor is the most important single factor affecting the spatial distribution of the land use, which plays an important role in the spatial distribution of the land use by combining the elevation factor.
[1] Kiran G, Joshi U. Estimation of variables explaining urbanization concomitant with land-use change:A spatial approach[J]. International Journal of Remote Sensing, 2013, 34(3):824-847.
[2] 鲁春阳, 杨庆媛, 田永中, 等. 基于主成分法的区域土地利用变化驱动力分析[J]. 安徽农业科学, 2006, 34(21):5627-5628.
[3] 陈利顶, 杨爽, 冯晓明. 土地利用变化的地形梯度特征与空间扩展[J]. 地理研究, 2008, 27(6):1225-1235.
[4] 何维灿, 赵尚民, 程维明. 山西省不同地貌形态类型区土地覆被变化的GIS分析[J]. 地球信息科学学报, 2016, 18(2):210-219.
[5] Dwivedi R, Sreenivas K, Ramana K. Land-use/land cover change analysis in part of Ethiopia using Landsat Thematic Mapper data[J]. International Journal of Remote Sensing, 2005, 26(7):1285-1287.
[6] 毛蒋兴, 李志刚, 闫小培, 等. 深圳土地利用时空变化与地形因子的关系研究[J]. 地理与地理信息科学, 2008, 24(2):71-76.
[7] 国巧真, 宁晓平, 王志恒, 等. 地形地貌对半山区土地利用动态变化影响分析[J]. 国土资源遥感, 2015, 27(1):153-159.
[8] 李京京, 吕哲敏, 石小平, 等. 基于地形梯度的汾河流域土地利用时空变化分析[J]. 农业工程学报, 2016, 32(7):230-236.
[9] 周成虎, 程维明, 钱金凯. 数字地貌遥感解析与制图[M]. 北京:科学出版社, 2009.
[10] 黄贤金. 城乡土地市场一体化对土地利用/覆被变化的影响研究综述[J]. 地理科学, 2017, 37(2):200-208.
[11] 张丽娟, 于洋, 粟练灵, 等. 1960-2010年黑龙江省土地利用变化对气温的影响[J]. 地理科学, 2017, 37(6):952-959.
[12] 梁发超, 刘黎明. 基于地形梯度的土地利用类型分布特征分析[J]. 资源科学, 2010, 32(11):2138-2144.
[13] 王琳, 武虹. 基于DEM的遗址域定量算法及可获取耕地统计[J]. 遥感技术与应用, 2017, 32(2):274-281.
[14] 于佳, 刘吉平. 基于地理探测器的东北地区气温变化影响因素定量分析[J]. 湖北农业科学, 2015, 54(19):4682-4687.
[15] 刘军, 张正福, 胡燕凌. 应用DEM数据进行耕地坡度分级量算方法研究[J]. 遥感技术与应用, 2009, 24(5):691-697.
[16] Wang J F, Li X, Christakos G, et al. Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region, China[J]. International Journal of Geographical Information Science, 2010, 24(1):107-127.
[17] Wang J F, Hu Y. Environmental health risk detection with GeogDetector[J]. Environmental Modelling & Software, 2012(33):114-115.
[18] Cao F, Ge Y, Wang J F. Optimal discretization for geographical detectors-based risk assessment[J]. GIScience & Remote Sensing, 2013, 50(1):78-92.
[19] 王劲峰, 徐成东. 地理探测器:原理与展望[J]. 地理学报, 2017, 72(1):116-134.
[20] 徐成东, 王劲峰. 基于地理探测器的手足口病风险因子分析[C]. 中国地理学会2012年学术年会, 2012:150.
[21] 刘彦随, 杨忍. 中国县域城镇化的空间特征与形成机理[J]. 地理学报, 2012, 67(8):1011-1020.
[22] Luo W, Jasiewicz J, Stepinski T, et al. Spatial association between dissection density and environmental factors over the entire conterminous United States[J]. Geophysical Research Letters, 2016(43):692-700.
[23] 杨忍, 刘彦随, 龙花楼, 等. 基于格网的农村居民点用地时空特征及空间指向性的地理要素识别——以环渤海地区为例[J]. 地理研究, 2015, 34(6):1077-1087.
[24] 湛东升, 张文忠, 余建辉, 等. 基于地理探测器的北京市居民宜居满意度影响机理[J]. 地理科学进展, 2015, 34(8):966-975.
[25] 谷晓天, 高小红, 马慧娟, 等. 复杂地形区土地利用/土地覆被分类机器学习方法比较研究[J]. 遥感技术与应用, 2019, 34(1):57-67.
[26] 杨叶涛, 龚健雅, 王迎迎, 等. 基于格网划分的城市区域土地利用景观格局[J]. 遥感技术与应用, 2010, 25(4):480-485.
[27] Wang J, Zhang T, Fu B J. A measure of spatial stratified heterogeneity[J]. Ecological Indicators, 2016(67):250-256.
