矿区土地利用生态风险的时空异质性
|
摘要
以微山县煤矿较集中、地面塌陷较严重的11个乡镇作为研究区,以遥感影像和土地利用现状数据为数据源,获取4期土地利用类型分布图,根据景观生态学理论构建景观意义上的土地利用生态风险指数,结合空间统计学及地统计学理论,探究2000—2016年研究区适宜尺度下土地利用生态风险的时空变化情况及空间异质性。结果表明:1 km×1 km规则网格是最佳研究尺度,在该尺度下研究区土地利用生态风险的空间分布呈集聚模式,且具有很强的空间正相关性;2000—2005年土地利用生态风险指数在小尺度上的随机变异逐渐被较大尺度上的空间结构性变异所取代,2005年生态风险总的空间变异程度较高,2005—2016年随机因素引起的空间变异程度增强;2000—2016年土地利用生态风险呈现由中高、高生态风险向中、中低生态风险转变的特征;生态风险恶化区和明显恶化区主要分布在东部矿区周边、道路沿线、地面塌陷较严重的区域,研究区西南部微山湖沿岸东西两侧,耕地的生态风险恶化程度2010—2016年较高;17年间微山湖湖区的生态风险稳定区和改善区大幅增加,生态风险明显下降。
In this study, the 11 towns with the most coal mines and serious surface collapses in Weishan County were selected as the areas of study, and remote sensor images and land use data were used as the data sources. From this information, distribution maps of land use type in 2000, 2005, 2010 and 2016 were obtained. Based on landscape ecology theory, an index of the ecological risk of land use was constructed. In this study, the theories of spatial statistics and geostatistics were used to determine an appropriate study scale. Spatial-temporal change and spatial heterogeneity of the ecological risk of land use in the research area were analyzed between 2000 and 2016. It was concluded that 1 km × 1 km regular grid was the best research scale. At this scale, the spatial distribution of the ecological risk of land use in the research area was concentrated and had a strong positive spatial correlation. The random variation of the land use ecological risk index on a small scale was gradually replaced by spatial structural variation on a larger scale between 2000 and 2005. The total spatial variability of ecological risk in 2005 was high. Between 2005 and 2016, the degree of spatial variability caused by random factors was increased. Between 2000 and 2016, the ecological risk of land use was characterized by the transition from medium-high and high ecological risk to medium and medium-low ecological risk. The ecological risk of deteriorated areas and obviously deteriorated areas was mainly distributed around the eastern mining area, roadside, and serious collapse areas. In addition, the ecological risk of deterioration of cultivated land on both sides of the east and west side of Weishan Lake was higher between 2010 and 2016. Over the past 17 years, the stable areas and improved areas of Weishan Lake increased significantly, with a clear decrease in the overall ecological risk.
In this study, the 11 towns with the most coal mines and serious surface collapses in Weishan County were selected as the areas of study, and remote sensor images and land use data were used as the data sources. From this information, distribution maps of land use type in 2000, 2005, 2010 and 2016 were obtained. Based on landscape ecology theory, an index of the ecological risk of land use was constructed. In this study, the theories of spatial statistics and geostatistics were used to determine an appropriate study scale. Spatial-temporal change and spatial heterogeneity of the ecological risk of land use in the research area were analyzed between 2000 and 2016. It was concluded that 1 km × 1 km regular grid was the best research scale. At this scale, the spatial distribution of the ecological risk of land use in the research area was concentrated and had a strong positive spatial correlation. The random variation of the land use ecological risk index on a small scale was gradually replaced by spatial structural variation on a larger scale between 2000 and 2005. The total spatial variability of ecological risk in 2005 was high. Between 2005 and 2016, the degree of spatial variability caused by random factors was increased. Between 2000 and 2016, the ecological risk of land use was characterized by the transition from medium-high and high ecological risk to medium and medium-low ecological risk. The ecological risk of deteriorated areas and obviously deteriorated areas was mainly distributed around the eastern mining area, roadside, and serious collapse areas. In addition, the ecological risk of deterioration of cultivated land on both sides of the east and west side of Weishan Lake was higher between 2010 and 2016. Over the past 17 years, the stable areas and improved areas of Weishan Lake increased significantly, with a clear decrease in the overall ecological risk.
引文
[1] 卢宏玮,曾光明,谢更新,张硕辅,黄国和,金相灿,刘鸿亮.洞庭湖流域区域生态风险评价.生态学报,2003,23(12):2520- 2530.
[2] U.S.Environmental Protection Agency.Framework for Ecological Risk Assessment.Washington,DC:Risk Assessment Forum,1992:1- 2.
[3] 付在毅,许学工.区域生态风险评价.地球科学进展,2001,16(2):267- 271.
[4] 邬建国.景观生态学:格局、过程、尺度与等级(第二版).北京:高等教育出版社,2007:19- 19,126- 136.
[5] 付在毅,许学工,林辉平,王宪礼.辽河三角洲湿地区域生态风险评价.生态学报,2001,21(3):365- 373.
[6] 许学工,林辉平,付在毅,布仁仓.黄河三角洲湿地区域生态风险评价.北京大学学报:自然科学版,2001,37(1):111- 120.
[7] 王春梅,王金达,刘景双,张学林,严登华.东北地区森林资源生态风险评价研究.应用生态学报,2003,14(6):863- 866.
[8] 程建龙,陆兆华,范英宏.露天煤矿区生态风险评价方法.生态学报,2004,24(12):2945- 2950.
[9] 陈辉,李双成,郑度.基于人工神经网络的青藏公路铁路沿线生态系统风险研究.北京大学学报:自然科学版,2005,41(4):586- 593.
[10] Breyta R,Black R,Kaufman J,Kurath G.Spatial and temporal heterogeneity of infectious hematopoietic necrosis virus in Pacific Northwest salmonids.Infection,Genetics and Evolution,2016,45:347- 358.
[11] 李谢辉,王磊,李景宜.基于GIS的渭河下游河流沿线区域生态风险评价.生态学报,2009,29(10):5523- 5534.
[12] 常青,邱瑶,谢苗苗,彭建.基于土地破坏的矿区生态风险评价:理论与方法.生态学报,2012,32(16):5164- 5174.
[13] 许妍,高俊峰,郭建科.太湖流域生态风险评价.生态学报,2013,33(9):2896- 2906.
[14] 张雅洲,谢小平.基于RS和GIS的南四湖生态风险评价.生态学报,2015,35(5):1371- 1377.
[15] 肖武,李素萃,王铮,杨耀淇,王涛.高潜水位煤矿区生态风险识别与评价.生态学报,2016,36(17):5611- 5619.
[16] 巫丽芸,何东进,游巍斌,邓西鹏,谭勇,纪志荣.福建东山岛灾害生态风险的时空演化.生态学报,2016,36(16):5027- 5037.
[17] 吴健生,乔娜,彭建,黄秀兰,刘建政,潘雅婧.露天矿区景观生态风险空间分异.生态学报,2013,33(12):3816- 3824.
[18] 李保杰.矿区土地景观格局演变及其生态效应研究——以徐州市贾汪矿区为例[D].徐州:中国矿业大学,2014.
[19] 胡金龙,周志翔,滕明君,罗楠.基于土地利用变化的典型喀斯特流域生态风险评估——以漓江流域为例.应用生态学报,2017,28(6):2003- 2012.
[20] 孙洪波,杨桂山,苏伟忠,朱天明,万荣荣.沿江地区土地利用生态风险评价——以长江三角洲南京地区为例.生态学报,2010,30(20):5616- 5625.
[21] 王国杰,廖善刚.土地利用强度变化的空间异质性研究.应用生态学报,2006,17(4):611- 614.
[22] 曾勇.区域生态风险评价——以呼和浩特市区为例.生态学报,2010,30(3):668- 673.
[23] 谢花林.基于景观结构和空间统计学的区域生态风险分析.生态学报,2008,28(10):5020- 5026.
[24] 谢花林.基于景观结构的土地利用生态风险空间特征分析——以江西兴国县为例.中国环境科学,2011,31(4):688- 695.
[25] 肖琳,田光进.天津市土地利用生态风险评价.生态学杂志,2014,33(2):469- 476.
[26] 赵丽红.南昌市景观格局时空变化及其驱动力研究[D].南昌:江西农业大学,2016.
[27] 于化龙,陈青锋,田超,张杰,陈亚恒.基于景观结构的土地利用生态空间特征及风险评估——以怀来县为例.水土保持研究,2016,23(3):155- 163.
[28] 卿凤婷,彭羽.基于景观结构的北京市顺义区生态风险时空特征.应用生态学报,2016,27(5):1585- 1593.
[29] 王鹏,王亚娟,刘小鹏,陈晓,孔福星.基于景观结构的生态移民安置区生态风险评价——以宁夏红寺堡区为例.生态学报,2018,38(8):2672- 2682.
[30] 胡明星,李建.空间信息技术在城镇体系规划中的应用研究.南京:东南大学出版社,2009:80- 80,82- 94.
[31] 冯益明.空间统计学理论及其在林业中的应用.北京:中国林业出版社,2008:1- 4.
[32] 闫庆武.空间数据分析方法在人口数据空间化中的应用.南京:东南大学出版社,2011:68- 74,97- 114.
[33] 刘湘南,黄方,王平.GIS空间分析原理与方法(第二版).北京:科学出版社,2008:189- 206.
[34] 吴剑,陈鹏,文超祥,傅世锋,陈庆辉.基于探索性空间数据分析的海坛岛土地利用生态风险评价.应用生态学报,2014,25(7):2056- 2062.
[35] 徐建华.计量地理学(第二版).北京:高等教育出版社,2014:158- 181.
[36] 李哈滨,王政权,王庆成.空间异质性定量研究理论与方法.应用生态学报,1998,9(6):651- 657.
[37] 邓敏,樊子德,刘启亮.空间分析实验教程.北京:测绘出版社,2015:66- 70.
[38] 岳文泽,徐建华,徐丽华,谈文琦,梅安新.不同尺度下城市景观综合指数的空间变异特征研究.应用生态学报,2005,16(11):2053- 2059.
[2] U.S.Environmental Protection Agency.Framework for Ecological Risk Assessment.Washington,DC:Risk Assessment Forum,1992:1- 2.
[3] 付在毅,许学工.区域生态风险评价.地球科学进展,2001,16(2):267- 271.
[4] 邬建国.景观生态学:格局、过程、尺度与等级(第二版).北京:高等教育出版社,2007:19- 19,126- 136.
[5] 付在毅,许学工,林辉平,王宪礼.辽河三角洲湿地区域生态风险评价.生态学报,2001,21(3):365- 373.
[6] 许学工,林辉平,付在毅,布仁仓.黄河三角洲湿地区域生态风险评价.北京大学学报:自然科学版,2001,37(1):111- 120.
[7] 王春梅,王金达,刘景双,张学林,严登华.东北地区森林资源生态风险评价研究.应用生态学报,2003,14(6):863- 866.
[8] 程建龙,陆兆华,范英宏.露天煤矿区生态风险评价方法.生态学报,2004,24(12):2945- 2950.
[9] 陈辉,李双成,郑度.基于人工神经网络的青藏公路铁路沿线生态系统风险研究.北京大学学报:自然科学版,2005,41(4):586- 593.
[10] Breyta R,Black R,Kaufman J,Kurath G.Spatial and temporal heterogeneity of infectious hematopoietic necrosis virus in Pacific Northwest salmonids.Infection,Genetics and Evolution,2016,45:347- 358.
[11] 李谢辉,王磊,李景宜.基于GIS的渭河下游河流沿线区域生态风险评价.生态学报,2009,29(10):5523- 5534.
[12] 常青,邱瑶,谢苗苗,彭建.基于土地破坏的矿区生态风险评价:理论与方法.生态学报,2012,32(16):5164- 5174.
[13] 许妍,高俊峰,郭建科.太湖流域生态风险评价.生态学报,2013,33(9):2896- 2906.
[14] 张雅洲,谢小平.基于RS和GIS的南四湖生态风险评价.生态学报,2015,35(5):1371- 1377.
[15] 肖武,李素萃,王铮,杨耀淇,王涛.高潜水位煤矿区生态风险识别与评价.生态学报,2016,36(17):5611- 5619.
[16] 巫丽芸,何东进,游巍斌,邓西鹏,谭勇,纪志荣.福建东山岛灾害生态风险的时空演化.生态学报,2016,36(16):5027- 5037.
[17] 吴健生,乔娜,彭建,黄秀兰,刘建政,潘雅婧.露天矿区景观生态风险空间分异.生态学报,2013,33(12):3816- 3824.
[18] 李保杰.矿区土地景观格局演变及其生态效应研究——以徐州市贾汪矿区为例[D].徐州:中国矿业大学,2014.
[19] 胡金龙,周志翔,滕明君,罗楠.基于土地利用变化的典型喀斯特流域生态风险评估——以漓江流域为例.应用生态学报,2017,28(6):2003- 2012.
[20] 孙洪波,杨桂山,苏伟忠,朱天明,万荣荣.沿江地区土地利用生态风险评价——以长江三角洲南京地区为例.生态学报,2010,30(20):5616- 5625.
[21] 王国杰,廖善刚.土地利用强度变化的空间异质性研究.应用生态学报,2006,17(4):611- 614.
[22] 曾勇.区域生态风险评价——以呼和浩特市区为例.生态学报,2010,30(3):668- 673.
[23] 谢花林.基于景观结构和空间统计学的区域生态风险分析.生态学报,2008,28(10):5020- 5026.
[24] 谢花林.基于景观结构的土地利用生态风险空间特征分析——以江西兴国县为例.中国环境科学,2011,31(4):688- 695.
[25] 肖琳,田光进.天津市土地利用生态风险评价.生态学杂志,2014,33(2):469- 476.
[26] 赵丽红.南昌市景观格局时空变化及其驱动力研究[D].南昌:江西农业大学,2016.
[27] 于化龙,陈青锋,田超,张杰,陈亚恒.基于景观结构的土地利用生态空间特征及风险评估——以怀来县为例.水土保持研究,2016,23(3):155- 163.
[28] 卿凤婷,彭羽.基于景观结构的北京市顺义区生态风险时空特征.应用生态学报,2016,27(5):1585- 1593.
[29] 王鹏,王亚娟,刘小鹏,陈晓,孔福星.基于景观结构的生态移民安置区生态风险评价——以宁夏红寺堡区为例.生态学报,2018,38(8):2672- 2682.
[30] 胡明星,李建.空间信息技术在城镇体系规划中的应用研究.南京:东南大学出版社,2009:80- 80,82- 94.
[31] 冯益明.空间统计学理论及其在林业中的应用.北京:中国林业出版社,2008:1- 4.
[32] 闫庆武.空间数据分析方法在人口数据空间化中的应用.南京:东南大学出版社,2011:68- 74,97- 114.
[33] 刘湘南,黄方,王平.GIS空间分析原理与方法(第二版).北京:科学出版社,2008:189- 206.
[34] 吴剑,陈鹏,文超祥,傅世锋,陈庆辉.基于探索性空间数据分析的海坛岛土地利用生态风险评价.应用生态学报,2014,25(7):2056- 2062.
[35] 徐建华.计量地理学(第二版).北京:高等教育出版社,2014:158- 181.
[36] 李哈滨,王政权,王庆成.空间异质性定量研究理论与方法.应用生态学报,1998,9(6):651- 657.
[37] 邓敏,樊子德,刘启亮.空间分析实验教程.北京:测绘出版社,2015:66- 70.
[38] 岳文泽,徐建华,徐丽华,谈文琦,梅安新.不同尺度下城市景观综合指数的空间变异特征研究.应用生态学报,2005,16(11):2053- 2059.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |