近30年来黄河三角洲耕地轨迹转化及驱动力研究
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摘要
黄河三角洲是山东省乃至全国重要的土地增长区和耕地资源储备区,耕地是研究区最重要的景观类型之一。通过Landsat TM/OLI遥感影像解译,获取黄河三角洲1986、1992、1998、2004、2010和2016年6个时期用地类型分布,使用轨迹分析法分析耕地轨迹的时空变化。借助斑块占景观面积比例指数(PLAND)、散布与并列指数(IJI)、面积加权平均斑块分维指数(FREAC-AM),分析不同耕地转化类型的景观格局。选择自然环境、社会经济和区位因素3大类共13个影响因子,利用Logistic回归模型对耕地转化进行驱动力分析。结果表明:①1986—2004年黄河三角洲耕地面积由1 390. 16 km~2,增长至2 184 km~2,2016年减少至2 138. 88 km~2,1986—2016年间研究区耕地和耕地占三角洲总面积比例呈先增长后下降趋势。30年间未利用地向耕地转入322. 46 km~2,是耕地增加的主要来源,耕地向建设用地输出107. 82 km~2,是耕地转出的主要去向。恒定非耕地主要分布在河口区和垦利区,间歇性耕地主要分布在河口区,转入耕地主要分布在垦利区,恒定耕地与转出耕地在各县区均有分布。②耕地是黄河三角洲最重要的景观类型之一,耕地轨迹占研究区总面积的62. 75%。间歇性耕地和恒定耕地的IJI指数分别为89. 84%和78. 20%,表明间歇性耕地和恒定耕地周边的耕地变化复杂,相邻景观类型最多。同时,间歇性耕地FREAC-AM指数为1. 22,还是研究区耕地转化轨迹中形状最复杂的类型。③Logistic分析表明,地理区位是黄河三角洲耕地转化的主要驱动因素,距海岸线距离(贡献率1 832. 730)、距黄河距离(贡献率589. 109)、人口密度差(贡献率408. 403)、距乡镇距离(贡献率398. 933)是耕地转入的主要驱动因子。距海岸线距离(贡献率1 914. 205)、距乡镇距离(贡献率763. 96)、距黄河距离(贡献率142. 210)是耕地转出的主要驱动因子。
The Yellow River Delta is a vital area of land growth and cultivated land reserve in Shandong Province and even in China.Cultivated land is one of the most important landscape types in study area. By interpreting Landsat TM/OLI images,the land use/cover information of the Yellow River Delta in 1986,1992,1998,2004,2010 and 2016 was extracted. The trajectory analysis method was used to analyze the temporal and spatial variation of cultivated land trajectory. Index( PLAND),Dispersion and Parallel Index( IJI),Area Weighted Average Patch Fractal Dimension Index( FREAC-AM) were used to analyze the landscape pattern of different types of cultivated land conversion. 13 factors were selected from three categories: natural environment,socio-economic and location factors and logistic regression model was used to analyze the driving force of cultivated land conversion. The results showed that: ①The cultivated land increased from 1 390. 16 km~2 to 2 184 km~2 from 1986 to 2004. However,the area decreased to 2 138. 88 km~2 in 2016. Thus,the cultivated land and its ratio of the whole delta showed a trend of increase in 1986 to 2004,and decreased from 2004 to 2016. Over the past 30 years,322. 46 km~2 unutilized land was transferred to the cultivated land,which was the main source of the increased cultivated land. The cultivated land of 107. 82 km~2 changed to construction land was the main source. The constant non-cultivated land was mainly distributed in Hekou and Kenli Districts. The intermittent cultivated land was mainly distributed in Hekou District. The converted cultivated land was mainly distributed in Kenli District. The constant cultivated land and the transferred cultivated land were distributed in all counties and districts. ②Cultivated land was one of the most important types of landscapes in the Yellow River Delta.The cultivated land trajectory accounted for 62. 75% of the study area. The IJI indexes of intermittent cultivated land and constant cultivated land were 89. 84% and 78. 20% respectively,indicating that the cultivated land around intermittent cultivated land and constant cultivated land was complex,and the adjacent landscape types were the most. At the same time,the FREAC-AM index of intermittent arable land was 1. 22,which was the most complex type of arable land conversion trajectory in the study area. ③Logistic analysis showed that the geographical location was the main driving factor for the conversion of cultivated land in the Yellow River Delta. The main driving factors for the conversion of cultivated land were distance from the coastline( contribution rate 1 832. 730),distance from the Yellow River( contribution rate 589. 109),population density difference( contribution rate 408. 403),and distance from township( contribution rate 398. 933). Distance from the coastline( contribution rate 1 914. 205),distance from township( contribution rate 763. 96),distance from the Yellow River( contribution rate 142. 210) were the main driving factors for the conversion of cultivated land.
The Yellow River Delta is a vital area of land growth and cultivated land reserve in Shandong Province and even in China.Cultivated land is one of the most important landscape types in study area. By interpreting Landsat TM/OLI images,the land use/cover information of the Yellow River Delta in 1986,1992,1998,2004,2010 and 2016 was extracted. The trajectory analysis method was used to analyze the temporal and spatial variation of cultivated land trajectory. Index( PLAND),Dispersion and Parallel Index( IJI),Area Weighted Average Patch Fractal Dimension Index( FREAC-AM) were used to analyze the landscape pattern of different types of cultivated land conversion. 13 factors were selected from three categories: natural environment,socio-economic and location factors and logistic regression model was used to analyze the driving force of cultivated land conversion. The results showed that: ①The cultivated land increased from 1 390. 16 km~2 to 2 184 km~2 from 1986 to 2004. However,the area decreased to 2 138. 88 km~2 in 2016. Thus,the cultivated land and its ratio of the whole delta showed a trend of increase in 1986 to 2004,and decreased from 2004 to 2016. Over the past 30 years,322. 46 km~2 unutilized land was transferred to the cultivated land,which was the main source of the increased cultivated land. The cultivated land of 107. 82 km~2 changed to construction land was the main source. The constant non-cultivated land was mainly distributed in Hekou and Kenli Districts. The intermittent cultivated land was mainly distributed in Hekou District. The converted cultivated land was mainly distributed in Kenli District. The constant cultivated land and the transferred cultivated land were distributed in all counties and districts. ②Cultivated land was one of the most important types of landscapes in the Yellow River Delta.The cultivated land trajectory accounted for 62. 75% of the study area. The IJI indexes of intermittent cultivated land and constant cultivated land were 89. 84% and 78. 20% respectively,indicating that the cultivated land around intermittent cultivated land and constant cultivated land was complex,and the adjacent landscape types were the most. At the same time,the FREAC-AM index of intermittent arable land was 1. 22,which was the most complex type of arable land conversion trajectory in the study area. ③Logistic analysis showed that the geographical location was the main driving factor for the conversion of cultivated land in the Yellow River Delta. The main driving factors for the conversion of cultivated land were distance from the coastline( contribution rate 1 832. 730),distance from the Yellow River( contribution rate 589. 109),population density difference( contribution rate 408. 403),and distance from township( contribution rate 398. 933). Distance from the coastline( contribution rate 1 914. 205),distance from township( contribution rate 763. 96),distance from the Yellow River( contribution rate 142. 210) were the main driving factors for the conversion of cultivated land.
引文
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[14]石晓丽，史文娇．气候变化和人类活动对耕地格局变化的贡献归因综述[J]．地理学报，2015,70(9):1463-1476．
[15]曾凌红，王钧，王红亚．基于GIS和Logistic回归模型的北京山区耕地变化分析与模拟[J]．北京大学学报(自然科学版)，2009,45(1):165-170．
[16]赵锐锋，王福红，张丽华，等．黑河中游地区耕地景观演变及社会经济驱动力分析[J]．地理科学，2017,37(6):920-928．
[17]张绪良，肖滋民，徐宗军，等．黄河三角洲滨海湿地的生物多样性特征及保护策略[J]．湿地科学，2011,9(2):125-131．
[18]SHI T,QI S,MENG F,et al.Land use change and landscape response in the Yellow River Delta of China:a case of Dongying City[J].Environmental earth sciences,2016,75(7):547．
[19]BAO L,ZHANG L,YIN S M,et al.Assessment on characteristics of LUCC process based on complex network in Modern Yellow River Delta,Shandong Province of China[J].Earth science informatics,2016,9(1):83-93．
[20]栗云召，于君宝，韩广轩，等．黄河三角洲自然湿地动态演变及其驱动因子[J]．生态学杂志，2011,30(7):1535-1541．
[21]SHU Y,HU Y M.Analysis of land use and land cover change in Yellow River Delta[J].Journal of soil and water conservation,2006,20(5):158-161．
[22]曹文．黄河三角洲地区耕地资源的可持续利用研究[J]．中国人口·资源与环境，2001,11(51):26-27．
[23]周文佐．近10 a黄河三角洲LUCC及其驱动因素分析[J]．农业工程学报，2010,26(1):341-345．
[24]汪小钦，王钦敏，刘高焕，等．黄河三角洲土地利用/土地覆被区域分异[J]．自然资源学报，2006,21(2):165-171．
[25]赵志杰，张成扬．黄河三角洲土地利用/覆盖时空变化研究[J]．应用基础与工程科学学报，2016,24(4):731-740．
[26]吴美琼，陈秀贵．基于主成分分析法的钦州市耕地面积变化及其驱动力分析[J]．地理科学，2014,34(1):54-59．
[27]刘超，霍永伟，许月卿，等．生态退耕前后张家口市耕地变化及影响因素识别[J]．自然资源学报，2018,33(10):134-148．
[28]赵宇东，刘嵘，刘延龄，等．多元Logistic回归的共线性分析[J]．中国卫生统计，2000,17(5):259-261．
[29]斯科特·梅纳德．应用Logistic回归分析[M]．第2版．李俊秀，译．上海:上海人民出版社，2012．
[30]姚荣江，杨劲松，刘广明，等．黄河三角洲地区典型地块土壤盐分空间变异特征研究[J]．农业工程学报，2006,22(6):61-66．
[31]杨劲松，姚荣江．黄河三角洲地区土壤水盐空间变异特征研究[J]．地理科学，2007,27(3):348-353．
[32]曹康琳，廖金凤．珠江三角洲耕地资源变化区域差异及对策[J]．中国人口·资源与环境，2000,10(2):75-78．
[33]董文福．珠江三角洲耕地变化及驱动力研究[C]//土地变化科学与生态建设学术研讨会．2005．
[34]黄贤金，方鹏．长江三角洲地区农地流转的土地利用变化机理及驱动力模型研究[C]//全国青年管理科学与系统科学学术会议．2005．
[35]陈肖飞，姚士谋，张落成．1990年以来长江三角洲耕地资源变化及驱动因子研究[J]．长江流域资源与环境，2015,24(9):1521-1527．
[36]王凌，李秀珍，郭笃发．辽河三角洲土地利用变化及其影响[J]．山东师范大学学报(自然科学版)，2003,18(3):43-47．
[37]谢花林，李波．基于logistic回归模型的农牧交错区土地利用变化驱动力分析---以内蒙古翁牛特旗为例[J]．地理研究，2008,27(2):294-304.
[2]KLEIJIN D,KOHLER F,BLDI A,et al.On the relationship between farmland biodiversity and land-use intensity in Europe[J].Proceedings of the royal society B:biological sciences,2008,1658:903-909．
[3]王迪，聂锐，王胜洲．耕地保护外部性及其经济补偿研究进展[J]．中国人口·资源与环境，2012,22(10):131-136．
[4]ESTEL S,KUEMMERLE T,ALCNTAR A,et al.Mapping farmland abandonment and recultivation across Europe using MODISNDVI time series[J].Remote sensing of environment,2015,163:312-325．
[5]田光进，庄大方，刘明亮．近10年中国耕地资源时空变化特征[J]．地球科学进展，2003,18(1):30-36．
[6]谭永忠，何巨，岳文泽，等．全国第二次土地调查前后中国耕地面积变化的空间格局[J]．自然资源学报，2017,32(2):12-23．
[7]宋戈，梁海鸥，林佳，等．黑龙江省垦区耕地利用综合效益评价及驱动力分析[J]．经济地理，2010,30(5):835-840．
[8]傅泽强，蔡运龙，杨友孝，等．中国粮食安全与耕地资源变化的相关分析[J]．自然资源学报，2001,16(4):313-319．
[9]李景刚，何春阳，史培军，等．近20年中国北方13省的耕地变化与驱动力[J]．地理学报，2004,59(2):274-282．
[10]李秀彬．中国近20年来耕地面积的变化及其政策启示[J]．自然资源学报，1999,14(4):329-333．
[11]赵晓丽，张增祥，汪潇，等．中国近30 a耕地变化时空特征及其主要原因分析[J]．农业工程学报，2014,30(3):1-11．
[12]李均力，姜亮亮，包安明，等．1962-2010年玛纳斯流域耕地景观的时空变化分析[J]．农业工程学报，2015,31(4):277-285．
[13]邓楚雄，李晓青，向云波，等．长株潭城市群地区耕地数量时空变化及其驱动力分析[J]．经济地理，2013,33(6):142-147．
[14]石晓丽，史文娇．气候变化和人类活动对耕地格局变化的贡献归因综述[J]．地理学报，2015,70(9):1463-1476．
[15]曾凌红，王钧，王红亚．基于GIS和Logistic回归模型的北京山区耕地变化分析与模拟[J]．北京大学学报(自然科学版)，2009,45(1):165-170．
[16]赵锐锋，王福红，张丽华，等．黑河中游地区耕地景观演变及社会经济驱动力分析[J]．地理科学，2017,37(6):920-928．
[17]张绪良，肖滋民，徐宗军，等．黄河三角洲滨海湿地的生物多样性特征及保护策略[J]．湿地科学，2011,9(2):125-131．
[18]SHI T,QI S,MENG F,et al.Land use change and landscape response in the Yellow River Delta of China:a case of Dongying City[J].Environmental earth sciences,2016,75(7):547．
[19]BAO L,ZHANG L,YIN S M,et al.Assessment on characteristics of LUCC process based on complex network in Modern Yellow River Delta,Shandong Province of China[J].Earth science informatics,2016,9(1):83-93．
[20]栗云召，于君宝，韩广轩，等．黄河三角洲自然湿地动态演变及其驱动因子[J]．生态学杂志，2011,30(7):1535-1541．
[21]SHU Y,HU Y M.Analysis of land use and land cover change in Yellow River Delta[J].Journal of soil and water conservation,2006,20(5):158-161．
[22]曹文．黄河三角洲地区耕地资源的可持续利用研究[J]．中国人口·资源与环境，2001,11(51):26-27．
[23]周文佐．近10 a黄河三角洲LUCC及其驱动因素分析[J]．农业工程学报，2010,26(1):341-345．
[24]汪小钦，王钦敏，刘高焕，等．黄河三角洲土地利用/土地覆被区域分异[J]．自然资源学报，2006,21(2):165-171．
[25]赵志杰，张成扬．黄河三角洲土地利用/覆盖时空变化研究[J]．应用基础与工程科学学报，2016,24(4):731-740．
[26]吴美琼，陈秀贵．基于主成分分析法的钦州市耕地面积变化及其驱动力分析[J]．地理科学，2014,34(1):54-59．
[27]刘超，霍永伟，许月卿，等．生态退耕前后张家口市耕地变化及影响因素识别[J]．自然资源学报，2018,33(10):134-148．
[28]赵宇东，刘嵘，刘延龄，等．多元Logistic回归的共线性分析[J]．中国卫生统计，2000,17(5):259-261．
[29]斯科特·梅纳德．应用Logistic回归分析[M]．第2版．李俊秀，译．上海:上海人民出版社，2012．
[30]姚荣江，杨劲松，刘广明，等．黄河三角洲地区典型地块土壤盐分空间变异特征研究[J]．农业工程学报，2006,22(6):61-66．
[31]杨劲松，姚荣江．黄河三角洲地区土壤水盐空间变异特征研究[J]．地理科学，2007,27(3):348-353．
[32]曹康琳，廖金凤．珠江三角洲耕地资源变化区域差异及对策[J]．中国人口·资源与环境，2000,10(2):75-78．
[33]董文福．珠江三角洲耕地变化及驱动力研究[C]//土地变化科学与生态建设学术研讨会．2005．
[34]黄贤金，方鹏．长江三角洲地区农地流转的土地利用变化机理及驱动力模型研究[C]//全国青年管理科学与系统科学学术会议．2005．
[35]陈肖飞，姚士谋，张落成．1990年以来长江三角洲耕地资源变化及驱动因子研究[J]．长江流域资源与环境，2015,24(9):1521-1527．
[36]王凌，李秀珍，郭笃发．辽河三角洲土地利用变化及其影响[J]．山东师范大学学报(自然科学版)，2003,18(3):43-47．
[37]谢花林，李波．基于logistic回归模型的农牧交错区土地利用变化驱动力分析---以内蒙古翁牛特旗为例[J]．地理研究，2008,27(2):294-304.
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