基于地形校正后Landsat 8的土壤重金属反演研究
|
摘要
为快速地了解玛纳斯流域土壤中重金属的污染状况和潜在生态风险,在Landsat 8 OLI的基础上引入DEM数据进行地形校正,同时对地形校正后的反射率进行倒数、导数和对数等数学变换,从每种变换中筛选出与土壤各重金属相关性最高的波段构建土壤各重金属PLSR预测模型,并对研究区土壤重金属分布情况进行探索,并利用生态风险评价方法对研究区进行预警。结果表明:在Landsat 8的基础上,引入DEM数据对反射率进行地形校正,以B1波段反射率和重金属Cu为例,经过地形校正后的反射率值与实测土壤表层Cu含量的R2从0.46提高至0.52,表明地形校正后的表观反射率能够更好地反映土壤重金属状况;利用土壤各重金属的最佳预测模型分别反演相应的土壤重金属含量,并引入土壤重金属生态风险指数用于评价研究区的土壤重金属生态风险,研究表明土壤重金属风险等级总体上呈现从西南方向至东北方向逐渐减弱的趋势,其生态风险排序为恢复区(C区)>退化区(B区)>湖泊入湖口(A区);为了验证基于遥感的土壤重金属生态风险预警的预测精度,将研究区土壤重金属含量实测数据也通过重金属生态风险指数进行计算,两者结果较为一致,表明可以用遥感的手段来反演该研究区的重金属分布情况,同时研究区土壤重金属污染总体上处于轻警以上级别,生态服务功能已开始退化,应该加强对该地区的重金属污染进行治理。
In order to quickly understand the pollution status and potential ecological risk of heavy metals in the Manas watershed,DEM data was introduced into Landsat 8 OLI for terrain correction,and mathematical transformations such as reciprocal,derivative,and logarithm were carried out. The PLSR prediction model of soil heavy metals was established by selecting the highest correlation between band reflectivity and concentration of heavy metals from each transformation. Additionally,the distribution of heavy metals in the study area was analyzed and using the ecological risk assessment method provided early warning for the study area. The results showed that: based on Landsat 8 OLI,the DEM data was introduced to correct the reflectivity. Taking the B1 band reflectivity and heavy metal Cu as an example,the coefficient of determination,R2,between the topographically corrected reflectance values and the measured soil Cu content increased from 0.46 to 0.52,which indicated that the apparent reflectance after topographic correction reflected the soil heavy metal condition better. The best prediction model for soil heavy metals was used to invert the corresponding soil heavy metal content,and the soil heavy metal ecological risk index was introduced to evaluate the soil heavy metal ecological risk in the study area. The risk level of heavy metals in soils generally showed a tendency to weaken gradually from southwestern region to northeastern area. The ecological risk of the order: recovery area( C area) > degraded area( B area) > lake into the lake( A area). In order to verify the prediction accuracy of soil heavy metal ecological risk warning based on remote sensing,the measured data of soil heavy metal content in the study area was also calculated by the heavy metal ecological risk index that showed consistent results. As a result,the distribution of heavy metals in the study area could be estimated by means of remote sensing. The results also indicated that the heavy metal pollution in the study area was above the alarm level,the ecological function had begun to degrade and the treatment of heavy metal pollution in the area should be strengthened.
In order to quickly understand the pollution status and potential ecological risk of heavy metals in the Manas watershed,DEM data was introduced into Landsat 8 OLI for terrain correction,and mathematical transformations such as reciprocal,derivative,and logarithm were carried out. The PLSR prediction model of soil heavy metals was established by selecting the highest correlation between band reflectivity and concentration of heavy metals from each transformation. Additionally,the distribution of heavy metals in the study area was analyzed and using the ecological risk assessment method provided early warning for the study area. The results showed that: based on Landsat 8 OLI,the DEM data was introduced to correct the reflectivity. Taking the B1 band reflectivity and heavy metal Cu as an example,the coefficient of determination,R2,between the topographically corrected reflectance values and the measured soil Cu content increased from 0.46 to 0.52,which indicated that the apparent reflectance after topographic correction reflected the soil heavy metal condition better. The best prediction model for soil heavy metals was used to invert the corresponding soil heavy metal content,and the soil heavy metal ecological risk index was introduced to evaluate the soil heavy metal ecological risk in the study area. The risk level of heavy metals in soils generally showed a tendency to weaken gradually from southwestern region to northeastern area. The ecological risk of the order: recovery area( C area) > degraded area( B area) > lake into the lake( A area). In order to verify the prediction accuracy of soil heavy metal ecological risk warning based on remote sensing,the measured data of soil heavy metal content in the study area was also calculated by the heavy metal ecological risk index that showed consistent results. As a result,the distribution of heavy metals in the study area could be estimated by means of remote sensing. The results also indicated that the heavy metal pollution in the study area was above the alarm level,the ecological function had begun to degrade and the treatment of heavy metal pollution in the area should be strengthened.
引文
[1] Liu M,Yang Y,Yun X,et al. Concentrations,distribution,sources,and ecological risk assessment of heavy metals in agricultural topsoil ofthe Three Gorges Dam region,China[J].Environ Monit Assess,2015,187(3):43-60.
[2] Shirkhanloo H,Mirzahosseini S A H,Shirkhanloo N,et al. The evalu-ation and determination of heavy metals pollution in edible vegetables,water and soil in the south of Tehran province by GIS[J].Archives ofEnvironmental Protection,2015,41(2):64-74.
[3]李长春,张光胜,姚峰.新疆准东煤田五彩湾露天矿区土壤重金属污染评估与分析[J].环境工程,2014,32(7):142-146.
[4]陈洪,特拉津·那斯尔,杨剑虹.伊犁河流域土壤重金属含量空间分布及其环境现状研究[J].水土保持学报,2013,27(3):100-105.
[5]吴二威,赵甲亭,乔秀文,等.滹沱河水系沉积物重金属污染特征及其污染评价[J].石河子大学学报(自然科学版),2014,32(5):621-626.
[6]江萍,刘勇,李国雷.基于BP神经网络的油松林小气候的模型研究[J].石河子大学学报(自然科学版),2013,31(2):148-153.
[7] Malley D F,Williams P C. Use of Near-Infrared Reflectance Spectros-copy in Prediction of Heavy Metals in Freshwater Sediment by TheirAssociation with Organic Matter[J]. Environmental Science&Tech-nology,1997,31(12):3461-3467.
[8] Ren H Y,Zhuang D F,Singh A N,et al. Estimation of As and Cucontamination in agricultural soils around a mining area by reflectancespectroscopy:a case study[J]. Pedosphere,2009,19(06):719-726.
[9]吴均昭.南京城郊农业土壤重金属污染的遥感地球化学基础研究[D].南京:南京大学,2006.
[10]李巨宝,田庆久,吴均昭.滏阳河两岸农田土壤Fe、Zn、Se元素光谱响应研究[J].遥感信息,2005,(03):10-13.
[11]刘三超,张万昌,蒋建军,等.用TM影像和DEM获取黑河流域地表反射率和反照率[J].地理科学,2003,23(05):585-591.
[12]段四波,阎广建,穆西晗,等.基于DEM的山区遥感图像地形校正方法[J].地理与地理信息科学,2007,23(06):18-22.
[13]宋巍巍,管东生,王刚.地形对植被生物量遥感反演的影响-以广州市为例[J].生态学报,2012,32(23):7440-7451.
[14]郭云开,安冠星,谢琼,等.针对SAIL冠层模型的土壤背景反射率修正[J].测绘工程,2017,26(8):1-4.
[15]穆悦,安裕伦,王喆,等.不同地形校正模型计算地形复杂山区地表反射率的对比[J].山地学报,2015,32(04):257-266.
[16]于雷,朱亚星,洪永胜,等.高光谱技术结合CARS算法预测土壤水分含量[J].农业工程学报,2016,32(22):138-145.
[17]于雷,洪永胜,耿雷,等.基于偏最小二乘回归的土壤有机质含量高光谱估算[J].农业工程学报,2015,31(14):103-109.
[18]薛利红,周鼎浩,李颖,等.不同利用方式下土壤有机质和全磷的可见近红外高光谱反演[J].土壤学报,2014,51(5):993-1002.
[19]赵雪雁.西北干旱区城市化进程中的生态预警初探[J].干旱区资源与环境,2004,18(6):1-5.
[20]何焰,由文辉.水环境生态安全预警评价与分析-以上海市为例[J].安全与环境工程,2004,11(4):1-4.
[21] Rapant S,Kordik J. An environmental risk assessment map of theSlovak republic:application of data from geochemical atlases[J]. En-vironmental Geology,2003,44(4):400-407.
[22]中国环境监测总站.中国土壤元素背景值[M].北京:中国环境科学出版社,1990:330-381.
[23]许学宏,纪从亮.江苏蔬菜产地土壤重金属污染现状调查与评价[J].农村生态环境,2005,21(1):35-37.
[24]左伟,王桥,王文杰,等.区域生态安全评价指标与标准研究[J].地理学与国土研究,2002,18(1):67-71.
[25]王登启.设施菜地土壤重金属的分布特征与生态风险评价研究[D].济南:山东农业大学,2008.
[26]郭云开,曹小燕,谢琼,等.模拟多光谱的土壤重金属含量反演研究初探[J].测绘工程,2015,(12):7-11.
[27]栾福明,张小雷,熊黑钢,等.基于TM影像的荒漠-绿洲交错带土壤有机质含量反演模型[J].中国沙漠,2014,34(4):1080-1086.
[28]马驰.基于HJ-1A高光谱影像的土壤盐碱化遥感研究[J].干旱区资源与环境,2014,28(2):180-185.
[29]刘娜,曾静,李旭,等.东洞庭湖湿地土壤重金属污染特征及潜在生态风险评价[J].农业现代化研究,2015,36(5):903-904.
[30]辉英,杨晓东,龚雪伟,等.乌鲁木齐市水磨河沿岸土壤重金属污染现状及评价[J].水土保持学报,2016.30(6):303-307.
[2] Shirkhanloo H,Mirzahosseini S A H,Shirkhanloo N,et al. The evalu-ation and determination of heavy metals pollution in edible vegetables,water and soil in the south of Tehran province by GIS[J].Archives ofEnvironmental Protection,2015,41(2):64-74.
[3]李长春,张光胜,姚峰.新疆准东煤田五彩湾露天矿区土壤重金属污染评估与分析[J].环境工程,2014,32(7):142-146.
[4]陈洪,特拉津·那斯尔,杨剑虹.伊犁河流域土壤重金属含量空间分布及其环境现状研究[J].水土保持学报,2013,27(3):100-105.
[5]吴二威,赵甲亭,乔秀文,等.滹沱河水系沉积物重金属污染特征及其污染评价[J].石河子大学学报(自然科学版),2014,32(5):621-626.
[6]江萍,刘勇,李国雷.基于BP神经网络的油松林小气候的模型研究[J].石河子大学学报(自然科学版),2013,31(2):148-153.
[7] Malley D F,Williams P C. Use of Near-Infrared Reflectance Spectros-copy in Prediction of Heavy Metals in Freshwater Sediment by TheirAssociation with Organic Matter[J]. Environmental Science&Tech-nology,1997,31(12):3461-3467.
[8] Ren H Y,Zhuang D F,Singh A N,et al. Estimation of As and Cucontamination in agricultural soils around a mining area by reflectancespectroscopy:a case study[J]. Pedosphere,2009,19(06):719-726.
[9]吴均昭.南京城郊农业土壤重金属污染的遥感地球化学基础研究[D].南京:南京大学,2006.
[10]李巨宝,田庆久,吴均昭.滏阳河两岸农田土壤Fe、Zn、Se元素光谱响应研究[J].遥感信息,2005,(03):10-13.
[11]刘三超,张万昌,蒋建军,等.用TM影像和DEM获取黑河流域地表反射率和反照率[J].地理科学,2003,23(05):585-591.
[12]段四波,阎广建,穆西晗,等.基于DEM的山区遥感图像地形校正方法[J].地理与地理信息科学,2007,23(06):18-22.
[13]宋巍巍,管东生,王刚.地形对植被生物量遥感反演的影响-以广州市为例[J].生态学报,2012,32(23):7440-7451.
[14]郭云开,安冠星,谢琼,等.针对SAIL冠层模型的土壤背景反射率修正[J].测绘工程,2017,26(8):1-4.
[15]穆悦,安裕伦,王喆,等.不同地形校正模型计算地形复杂山区地表反射率的对比[J].山地学报,2015,32(04):257-266.
[16]于雷,朱亚星,洪永胜,等.高光谱技术结合CARS算法预测土壤水分含量[J].农业工程学报,2016,32(22):138-145.
[17]于雷,洪永胜,耿雷,等.基于偏最小二乘回归的土壤有机质含量高光谱估算[J].农业工程学报,2015,31(14):103-109.
[18]薛利红,周鼎浩,李颖,等.不同利用方式下土壤有机质和全磷的可见近红外高光谱反演[J].土壤学报,2014,51(5):993-1002.
[19]赵雪雁.西北干旱区城市化进程中的生态预警初探[J].干旱区资源与环境,2004,18(6):1-5.
[20]何焰,由文辉.水环境生态安全预警评价与分析-以上海市为例[J].安全与环境工程,2004,11(4):1-4.
[21] Rapant S,Kordik J. An environmental risk assessment map of theSlovak republic:application of data from geochemical atlases[J]. En-vironmental Geology,2003,44(4):400-407.
[22]中国环境监测总站.中国土壤元素背景值[M].北京:中国环境科学出版社,1990:330-381.
[23]许学宏,纪从亮.江苏蔬菜产地土壤重金属污染现状调查与评价[J].农村生态环境,2005,21(1):35-37.
[24]左伟,王桥,王文杰,等.区域生态安全评价指标与标准研究[J].地理学与国土研究,2002,18(1):67-71.
[25]王登启.设施菜地土壤重金属的分布特征与生态风险评价研究[D].济南:山东农业大学,2008.
[26]郭云开,曹小燕,谢琼,等.模拟多光谱的土壤重金属含量反演研究初探[J].测绘工程,2015,(12):7-11.
[27]栾福明,张小雷,熊黑钢,等.基于TM影像的荒漠-绿洲交错带土壤有机质含量反演模型[J].中国沙漠,2014,34(4):1080-1086.
[28]马驰.基于HJ-1A高光谱影像的土壤盐碱化遥感研究[J].干旱区资源与环境,2014,28(2):180-185.
[29]刘娜,曾静,李旭,等.东洞庭湖湿地土壤重金属污染特征及潜在生态风险评价[J].农业现代化研究,2015,36(5):903-904.
[30]辉英,杨晓东,龚雪伟,等.乌鲁木齐市水磨河沿岸土壤重金属污染现状及评价[J].水土保持学报,2016.30(6):303-307.
© 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 |