基于二元逻辑斯蒂模型的桐梓河流域土地利用变化及模拟
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摘要
为探明典型喀斯特流域土地利用时空变化过程,揭示流域土地利用变化主控因素,以桐梓河流域1980、1990、2000、2010、2015年五期的遥感影像解译数据以及研究区的自然社会经济等数据为基础,综合运用土地利用转移概率矩阵以及二元逻辑斯蒂回归模型对流域的土地利用格局进行了最佳模拟尺度选择,在此基础上构建了流域不同土地利用类型空间分布概率图。研究结果表明:桐梓河流域的景观类型异质性较强,土地利用类型在研究期间内转移过程比较复杂,各种土地类型流转中"转出与转入"现象普遍存在;桐梓河流域土地利用分析及其模拟的最佳空间模拟尺度为120 m×120 m;喀斯特流域林地与灌木林地的发生概率与降水量的大小并没有直接关系,降水量越大的地方流域林地分布概率不一定越高,其发生概率一般与气温正相关,温度越高,林地和灌木林地的出现概率越大;喀斯特流域草地的分布与岩性有极大的关系,草地发生概率一般出现在喀斯特地区以及降水量高的地区,而气温越高的地区草地出现的概率越低;从逐点对比的精度来看,建设用地的模拟准确率最高(89. 62%),水体次之(86. 15%),而草地的模拟准确率最低,仅为62. 68%。由此可见在对喀斯特流域土地利用时空数据变化及其驱动力识别时,二元逻辑斯蒂回归模型具有很好的模拟能力。
In order to explore the temporal and spatial change process of land use in typical karst basins and reveal the main controlling factors of land use change in the basins,the probability matrix of land use transfer and the binary logistic logistic regression model was combined to select the optimal simulation scale for the land use pattern based on the remote sensing image interpretation data from 1980,1990,2000,2010,2015 and the natural and socioeconomic data in the Tongzi river basin,and then a probability map of spatial distribution of different land types in the basin was constructed. The results show that the heterogeneity of landscape type in the basin is strong,and the transfer process of the land use type is complex during the study period. The phenomenon of "turning out and transferring"is common in the study area. The best spatial simulation scale for land use analysis and land use simulation is 120 m × 120 m in Tongzi river basin. The probability of the occurrence of woodland and shrub land in Karst is not directly related to amount of precipitation,and the probability of distribution of woodland and shrub land in watershed with higher precipitation is not necessarily higher. The occurrence probability of woodland and shrub land is generally positively correlated with temperature. The higher the temperature,the greater the probability of occurrence of woodland and shrub land. There is a great relationship between the distribution of grassland and the lithology in Karst.The grassland usually appears in the Karst region and the region with high precipitation,and the higher the temperature. From the raster of point by point,the accuracy of the construction land is the highest( 89. 62%) and the water body is in second( 86. 15%),while the simulation accuracy of the grassland is the lowest,and its value is only62. 68%. It is concluded that the binary logistic regression model has a good simulation ability when identifying the spatial and temporal data changes and driving forces of land use in the karst basin.
In order to explore the temporal and spatial change process of land use in typical karst basins and reveal the main controlling factors of land use change in the basins,the probability matrix of land use transfer and the binary logistic logistic regression model was combined to select the optimal simulation scale for the land use pattern based on the remote sensing image interpretation data from 1980,1990,2000,2010,2015 and the natural and socioeconomic data in the Tongzi river basin,and then a probability map of spatial distribution of different land types in the basin was constructed. The results show that the heterogeneity of landscape type in the basin is strong,and the transfer process of the land use type is complex during the study period. The phenomenon of "turning out and transferring"is common in the study area. The best spatial simulation scale for land use analysis and land use simulation is 120 m × 120 m in Tongzi river basin. The probability of the occurrence of woodland and shrub land in Karst is not directly related to amount of precipitation,and the probability of distribution of woodland and shrub land in watershed with higher precipitation is not necessarily higher. The occurrence probability of woodland and shrub land is generally positively correlated with temperature. The higher the temperature,the greater the probability of occurrence of woodland and shrub land. There is a great relationship between the distribution of grassland and the lithology in Karst.The grassland usually appears in the Karst region and the region with high precipitation,and the higher the temperature. From the raster of point by point,the accuracy of the construction land is the highest( 89. 62%) and the water body is in second( 86. 15%),while the simulation accuracy of the grassland is the lowest,and its value is only62. 68%. It is concluded that the binary logistic regression model has a good simulation ability when identifying the spatial and temporal data changes and driving forces of land use in the karst basin.
引文
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15田义超,任志远.基于CLUE-S模型的黄土台塬区土地利用变化模拟---以陕西省咸阳台塬区为例[J].地理科学进展,2012,31(9):1224-1234Tian Yichao,Ren Zhiyuan.Land use change simulations in loess hilly areas based on CLUE-S Model:A case study in Xianyang Loess Tableland areas of Shaanxi Province[J].Progress in Geography,2012,31(9):1224-1234
16 Manno A.CART:Classification and regression trees[J].Wiley Interdisciplinary Reviews Data Mining&Knowledge Discovery,2011,1(1):14-23
17徐岚,赵羿.利用马尔柯夫过程预测东陵区土地利用格局的变化[J].应用生态学报,1993,4(3):272-277Xu Lan,Zhao Yi.Forecast of land use pattern change in Dongling District of Shenyang:An application of Markov process[J].Chinese Journal of Applied Ecology,1993,4(3):272-277
18邓华,邵景安,王金亮,等.多因素耦合下三峡库区土地利用未来情景模拟[J].地理学报,2016,71(11):1979-1997Deng Hua,Shao Jin'gan,Wang Jinliang,et al.Land use driving forces and its future scenario simulation in the Three Gorges Reservoir Area using CLUE-S model[J].Acta Geographica Sinica,2016,71(11):1979-1997
19闫效莺,康磊.基于回归模型的网络排序算法预测药物靶点关系[J].科学技术与工程,2016,16(22):36-40Yan Xiaoying,Kang Lei.A regression-based network ranking prediction model for drug-target interaction[J].Science Technology and Engineering,2016,16(22):36-40
20王祺,蒙吉军,毛熙彦.基于邻域相关的漓江流域土地利用多情景模拟与景观格局变化[J].地理研究,2014,33(6):1073-1084Wang Qi,Meng Jijun,Mao Xiyan.Scenario simulation and landscape pattern assessment of land use change based on neighborhood analysis and auto-logistic model:A case study of Lijiang river basin[J].Geographical Research,2014,33(6):1073-1084
21田义超,陈志坤,梁铭忠,等.土地利用最佳模拟尺度选择及空间格局模拟[J].计算机工程与应用,2014,50(24):244-249Tian Yichao,Chen Zhikun,Liang Mingzhong,et al.Selection of land use best simulation scale and patterns of spatial simulation[J].Computer Engineering and Applications,2014,50(24):244-249
2 Li D,Huang Y,Qiao B,et al.The research on land-use change and ecological environment effect of urban landscape in China[J].International Journal of Geosciences,2016,7(7):956-961
3保家有,王海华.亦庄新城地区土地利用时空动态变化及其驱动因素分析[J].科学技术与工程,2008,8(6):1522-1529Bao Jiayou,Wang Haihua.Land use temporal-spatial dynamic change and driving factor analysis of Yizhuang New City Area[J].Science Technology and Engineering,2008,8(6):1522-1529
4 Hunter M C.Emerging landscapes:Using ecological theory to guide urban planting design:An adaptation strategy for climate change[J].Landscape Journal,2011,30(2):173-193
5吴莉,侯西勇,徐新良,等.山东沿海地区土地利用和景观格局变化[J].农业工程学报,2013,29(5):207-216Wu Li,Hou Xiyong,Xu Xinliang,et al.Land use and landscape pattern changes in coastal areas of Shandong Province,China[J].Transactions of the Chinese Society of Agricultural Engineering,2013,29(5):207-216
6 Turner B L I,Skole D L,Sanderson S,et al.Land-use and landcover change.Science/research plan[J].Global Change Report,1995,43(1995):669-679
7 Bormann H,Breuer L,Grff T,et al.Analysing the effects of soil properties changes associated with land use changes on the simulated water balance:A comparison of three hydrological catchment models for scenario analysis[J].Ecological Modelling:2007,209:29-40
8蔺卿,罗格平,陈曦,等.LUCC驱动力模型研究综述[J].地理科学进展,2005,24(5):79-87Lin Qing,Luo Geping,Chen Xi,et al.Review of land-use model[J].Progress in Geography,2005,24(5):79-87
9张永民,赵士洞.CLUE-S模型及其在奈曼旗土地利用时空动态变化模拟中的应用[J].自然资源学报,2003,18(3):310-318Zhang Yongmin,Zhao Shidong.CLUE-S and its application for simulating temporal and spatial change of land use in Naiman Banner[J].Journal of Natural Resources,2003,18(3):310-318
10 Verburg P H,Schot P P,Dijst M J,et al.Land use change modelling:Current practice and research priorities[J].Geojournal,2004,61(4):309-324
11王海军,孔祥冬,张勃.空间统计模型在土地利用与覆被变化模拟与预测中的应用---以Logistic-CA-Markov模型为例[J].科学技术与工程,2016,16(15):139-143Wang Haijun,Kong Xiangdong,Zhang Bo.Application of spatial statistical model in LUCC simulation and forecast-Taking the Logistic-CA-Markov model as an example[J].Science Technology and Engineering,2016,16(15):139-143
12赵庚星,尚建业.黄河三角洲垦利用土地利用的系统动力仿真模拟研究[J].浙江大学学报:农业与生命科学版,1998,24(2):141-147Zhao Gengxing,Shang Jianye.Study on land use system dynamics simulation of Kenli County,Yellow river delta[J].Journal of Zhejiang Agricultural University:Agriculture and Life Sciences,1998,24(2):141-147
13赵何丹,金凤君,周璟.基于Logistic-CA-Markov的土地利用景观格局变化---以京津冀都市圈为例[J].地理科学,2011,31(8):903-910Zhao Hedan,Jin Fengjun,Zhou Jing.The changes of land use and landscape pattern based on Logistic-CA-Markov model-A case Study of Beijing-Tianjin-Hebei metropolitan region[J].Scientia Geographica Sinica,2011,31(8):903-910
14赵李闻.基于CLUE-S模型的土地利用模拟研究[D].南京:南京师范大学,2011Zhao Liwen.Simulation of land use based on CLUE-S model[D].Nanjing:Nanjing Normal University,2011
15田义超,任志远.基于CLUE-S模型的黄土台塬区土地利用变化模拟---以陕西省咸阳台塬区为例[J].地理科学进展,2012,31(9):1224-1234Tian Yichao,Ren Zhiyuan.Land use change simulations in loess hilly areas based on CLUE-S Model:A case study in Xianyang Loess Tableland areas of Shaanxi Province[J].Progress in Geography,2012,31(9):1224-1234
16 Manno A.CART:Classification and regression trees[J].Wiley Interdisciplinary Reviews Data Mining&Knowledge Discovery,2011,1(1):14-23
17徐岚,赵羿.利用马尔柯夫过程预测东陵区土地利用格局的变化[J].应用生态学报,1993,4(3):272-277Xu Lan,Zhao Yi.Forecast of land use pattern change in Dongling District of Shenyang:An application of Markov process[J].Chinese Journal of Applied Ecology,1993,4(3):272-277
18邓华,邵景安,王金亮,等.多因素耦合下三峡库区土地利用未来情景模拟[J].地理学报,2016,71(11):1979-1997Deng Hua,Shao Jin'gan,Wang Jinliang,et al.Land use driving forces and its future scenario simulation in the Three Gorges Reservoir Area using CLUE-S model[J].Acta Geographica Sinica,2016,71(11):1979-1997
19闫效莺,康磊.基于回归模型的网络排序算法预测药物靶点关系[J].科学技术与工程,2016,16(22):36-40Yan Xiaoying,Kang Lei.A regression-based network ranking prediction model for drug-target interaction[J].Science Technology and Engineering,2016,16(22):36-40
20王祺,蒙吉军,毛熙彦.基于邻域相关的漓江流域土地利用多情景模拟与景观格局变化[J].地理研究,2014,33(6):1073-1084Wang Qi,Meng Jijun,Mao Xiyan.Scenario simulation and landscape pattern assessment of land use change based on neighborhood analysis and auto-logistic model:A case study of Lijiang river basin[J].Geographical Research,2014,33(6):1073-1084
21田义超,陈志坤,梁铭忠,等.土地利用最佳模拟尺度选择及空间格局模拟[J].计算机工程与应用,2014,50(24):244-249Tian Yichao,Chen Zhikun,Liang Mingzhong,et al.Selection of land use best simulation scale and patterns of spatial simulation[J].Computer Engineering and Applications,2014,50(24):244-249