基于线性光谱混合模型(LSMM)的民勤绿洲荒漠化治理效果评价
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摘要
民勤绿洲是干旱荒漠化的典型区域,生态系统脆弱,对该区域的荒漠化治理效果进行评价可以为其生态修复政策的制定和管理提供参考。采用线性光谱混合模型(LSMM),将Landsat影像中的土地覆盖信息进行有效分解,通过分解后光谱在直方图上的特征值,确定合适的阈值,对荒漠化土地进行分类,分析荒漠化土地类型的时空变化特征,对民勤绿洲1992—2017年荒漠化治理效果进行评价。结果表明:(1)1992—2005年民勤绿洲荒漠化加剧面积大于改善面积,两者相差175.47 km~2,荒漠化加剧,治理效果不明显。(2)2005—2017年荒漠化改善面积大于加剧面积,两者相差174.18 km~2,荒漠化改善,治理效果显著。(3)1992—2017年民勤绿洲荒漠化总体趋于改善,局部地区加剧。其中,坝区和泉山区的荒漠化改善面积大于加剧面积,两者分别相差47.63 km~2和52.79 km~2,荒漠化改善,治理效果显著;而湖区荒漠化加剧面积大于改善面积,两者相差36.83 km~2,荒漠化加剧,治理效果不明显。
Minqin Oasis is a typical area of arid desertification with fragile ecosystem. The evaluation of desertification control effect in this area can provide reference for the formulation and management of ecological restoration policies. In this paper, the linear spectral mixture model(LSMM) was used to effectively decompose the land cover information in the Landsat image. The appropriate thresholds were determined by the eigenvalues of the decomposed spectra on the histogram, then the desertification land was classified and the temporal and spatial variation characteristics were analyzed. Finally, the desertification control effect in Minqin Oasis during 1992-2017 was evaluated. The results show that:(1) From 1992 to 2005, the worsening desertification area in the Minqin Oasis was greater than the improved area by 175.47 km~2. The desertification was aggravated and the governance effect was not obvious.(2) From 2005 to 2017, the improved area of desertification was greater than the worsening area by 174.18 km~2. Desertification was improved and the governance effect was remarkable.(3) From 1992 to 2017, desertification in the Minqin Oasis tended to be improved, and local areas intensified. Among them, the improved area of desertification in dam region and Quanshan region was greater than the worsening area, and the difference between the two areas was 47.63 km~2 and 52.79 km~2, respectively, which shows the improvement of desertification has achieved significant effect in dam region and Quanshan region. The worsening area in the lake region is greater than the improved area by 36.83 km~2. Desertification is aggravating and the governance effect is not obvious in the lake region.
Minqin Oasis is a typical area of arid desertification with fragile ecosystem. The evaluation of desertification control effect in this area can provide reference for the formulation and management of ecological restoration policies. In this paper, the linear spectral mixture model(LSMM) was used to effectively decompose the land cover information in the Landsat image. The appropriate thresholds were determined by the eigenvalues of the decomposed spectra on the histogram, then the desertification land was classified and the temporal and spatial variation characteristics were analyzed. Finally, the desertification control effect in Minqin Oasis during 1992-2017 was evaluated. The results show that:(1) From 1992 to 2005, the worsening desertification area in the Minqin Oasis was greater than the improved area by 175.47 km~2. The desertification was aggravated and the governance effect was not obvious.(2) From 2005 to 2017, the improved area of desertification was greater than the worsening area by 174.18 km~2. Desertification was improved and the governance effect was remarkable.(3) From 1992 to 2017, desertification in the Minqin Oasis tended to be improved, and local areas intensified. Among them, the improved area of desertification in dam region and Quanshan region was greater than the worsening area, and the difference between the two areas was 47.63 km~2 and 52.79 km~2, respectively, which shows the improvement of desertification has achieved significant effect in dam region and Quanshan region. The worsening area in the lake region is greater than the improved area by 36.83 km~2. Desertification is aggravating and the governance effect is not obvious in the lake region.
引文
[1] 慈龙骏.对“荒漠化”一词的认识和体会[J].中国科技术语,2000,2(4):11-13.
[2] 殷贺,李正国,王仰麟,等.荒漠化评价研究进展[J].植物生态学报,2011,35(3):345-352.
[3] 朱震达.中国荒漠化问题研究的现状与展望[J].地理学报,1994(增刊1):650-659.
[4] 王涛,宋翔,颜长珍,等.近35 a来中国北方土地沙漠化趋势的遥感分析[J].中国沙漠,2011,31(6):1351-1356.
[5] 殷贺,李正国,王仰麟,等.基于时间序列植被特征的内蒙古荒漠化评价[J].地理学报,2011,66(5):653-661.
[6] 李奇虎,陈亚宁.1981-2005年西北干旱区NDVI时空分布变化对水热条件的响应[J].冰川冻土,2014,36(2):327-334.
[7] Prince S D,Beckerreshef I,Rishmawi K.Detection and mapping of long-term land degradation using local net production scaling:application to Zimbabwe[J].Remote Sensing of Environment,2009,113(5):1046-1057.
[8] Wessels K J,Prince S D,Zambatis N,et al.Relationship between herbaceous biomass and 1-km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park,South Africa[J].International Journal of Remote Sensing,2005,27(5):951-973.
[9] 杨晓晖,慈龙骏.基于遥感技术的荒漠化评价研究进展[J].世界林业研究,2005,19(6):11-13.
[10] Asner G P,Lobell D B.A Biogeophysical approach for automated SWIR unmixing of soils and vegetation[J].Remote Sensing of Environment,2000,74(1):99-112.
[11] Okin G S,Gu J.The impact of atmospheric conditions and instrument noise on atmospheric correction and spectral mixture analysis of multispectral imagery[J].Remote Sensing of Environment,2015,164:130-141.
[12] Smith M O,Ustin S L,Adams J B,et al.Vegetation in deserts:I.a regional measure of abundance from multispectral images[J].Remote Sensing of Environment,1990,31(1):1-26.
[13] Gross H N,Schott J R.Application of spectral mixture analysis and image fusion techniques for image sharpening[J].Remote Sensing of Environment,1998,63(2):85-94.
[14] Robinson G D,Gross H N,Schott J R.Evaluation of two applications of spectral mixing models to image fusion[J].Remote Sensing of Environment,2000,71(3):272-281.
[15] 徐娜,丁建丽,刘海霞.基于NDVI和LSMM的干旱区植被信息提取研究——以新疆吐鲁番市为例[J].测绘与空间地理信息,2012,35(7):54-55.
[16] 张熙川,赵英时.应用线性光谱混合模型快速评价土地退化的方法研究[J].中国科学院大学学报,1999(2):169-176.
[17] 王继和.中国西北荒漠区持续农业与沙漠综合治理国际学术交流会论文集[M].兰州:兰州大学出版社,1998.
[18] 司建华,龚家栋,张勃.干旱地区生态需水量的初步估算——以张掖地区为例[J].干旱区资源与环境,2004,18(1):49-53.
[19] 徐先英,丁国栋,高志海,等.近50年民勤绿洲生态环境演变及综合治理对策[J].中国水土保持科学,2006,4(1):40-48.
[20] 张华,张改改,吴瑞.基于GF-1卫星数据的面向对象的民勤绿洲植被分类研究[J].干旱区地理,2017,40(4):832-833.
[21] 司建华,冯起,席海洋,等.黑河下游额济纳绿洲生态需水关键期及需水量[J].中国沙漠,2013,33(2):560-567.
[22] 鲁晖,颉耀文,张文培,等.1986—2015年民勤县绿洲时空变化分析[J].干旱区研究,2017,34(6):1410-1417.
[23] 樊风雷.基于线性光谱混合模型(LSMM)的两种不同端元值选取方法应用与评价——以广州市为例[J].遥感技术与应用,2008,23(3):273-275.
[24] 姜宛贝,孙丹峰,孙强强.基于光谱混合分解的民勤生态治理效果评价[J].中国沙漠,2018,38(1):210-218.
[25] Wu C,Murray A T.Estimating impervious surface distribution by spectral mixture analysis[J].Remote Sensing of Environment,2003,84(4):493-505.
[26] 高尚武,王葆芳,朱灵益,等.中国沙质荒漠化土地监测评价指标体系[J].林业科学,1998,34(2):8-9.
[27] 杨永春,李吉均,陈发虎,等.石羊河下游民勤绿洲变化的人文机制研究[J].地理研究,2002,21(4):449-458.
[28] 石敏俊,陶卫春,赵学涛.民勤绿洲生态重建目标下土地利用和农业结构调整的政策选择[J].干旱区地理,2009,32(2):274-280.
[29] 杨怀德,冯起,黄珊,等.民勤绿洲水资源调度的生态环境效应[J].干旱区资源与环境,2017,31(7):68-73.
[30] 郭瑞,冯起,翟禄新,等.改进型BP神经网络对民勤绿洲地下水位的模拟预测[J].中国沙漠,2010,30(3):737-741.
[31] 栾维功.以水为基,统筹兼顾,重点治理——《石羊河流域重点治理规划》特点分析[J].中国水利,2013(5):29-32.
[32] 段志明,邸士智,等.石羊河志:备考·民勤卷[M].2014.
[33] 陈丽娟,冯起,成爱芳.民勤绿洲土壤水盐空间分布特征及盐渍化成因分析[J].干旱区资源与环境,2013,27(11):99-105.
[2] 殷贺,李正国,王仰麟,等.荒漠化评价研究进展[J].植物生态学报,2011,35(3):345-352.
[3] 朱震达.中国荒漠化问题研究的现状与展望[J].地理学报,1994(增刊1):650-659.
[4] 王涛,宋翔,颜长珍,等.近35 a来中国北方土地沙漠化趋势的遥感分析[J].中国沙漠,2011,31(6):1351-1356.
[5] 殷贺,李正国,王仰麟,等.基于时间序列植被特征的内蒙古荒漠化评价[J].地理学报,2011,66(5):653-661.
[6] 李奇虎,陈亚宁.1981-2005年西北干旱区NDVI时空分布变化对水热条件的响应[J].冰川冻土,2014,36(2):327-334.
[7] Prince S D,Beckerreshef I,Rishmawi K.Detection and mapping of long-term land degradation using local net production scaling:application to Zimbabwe[J].Remote Sensing of Environment,2009,113(5):1046-1057.
[8] Wessels K J,Prince S D,Zambatis N,et al.Relationship between herbaceous biomass and 1-km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park,South Africa[J].International Journal of Remote Sensing,2005,27(5):951-973.
[9] 杨晓晖,慈龙骏.基于遥感技术的荒漠化评价研究进展[J].世界林业研究,2005,19(6):11-13.
[10] Asner G P,Lobell D B.A Biogeophysical approach for automated SWIR unmixing of soils and vegetation[J].Remote Sensing of Environment,2000,74(1):99-112.
[11] Okin G S,Gu J.The impact of atmospheric conditions and instrument noise on atmospheric correction and spectral mixture analysis of multispectral imagery[J].Remote Sensing of Environment,2015,164:130-141.
[12] Smith M O,Ustin S L,Adams J B,et al.Vegetation in deserts:I.a regional measure of abundance from multispectral images[J].Remote Sensing of Environment,1990,31(1):1-26.
[13] Gross H N,Schott J R.Application of spectral mixture analysis and image fusion techniques for image sharpening[J].Remote Sensing of Environment,1998,63(2):85-94.
[14] Robinson G D,Gross H N,Schott J R.Evaluation of two applications of spectral mixing models to image fusion[J].Remote Sensing of Environment,2000,71(3):272-281.
[15] 徐娜,丁建丽,刘海霞.基于NDVI和LSMM的干旱区植被信息提取研究——以新疆吐鲁番市为例[J].测绘与空间地理信息,2012,35(7):54-55.
[16] 张熙川,赵英时.应用线性光谱混合模型快速评价土地退化的方法研究[J].中国科学院大学学报,1999(2):169-176.
[17] 王继和.中国西北荒漠区持续农业与沙漠综合治理国际学术交流会论文集[M].兰州:兰州大学出版社,1998.
[18] 司建华,龚家栋,张勃.干旱地区生态需水量的初步估算——以张掖地区为例[J].干旱区资源与环境,2004,18(1):49-53.
[19] 徐先英,丁国栋,高志海,等.近50年民勤绿洲生态环境演变及综合治理对策[J].中国水土保持科学,2006,4(1):40-48.
[20] 张华,张改改,吴瑞.基于GF-1卫星数据的面向对象的民勤绿洲植被分类研究[J].干旱区地理,2017,40(4):832-833.
[21] 司建华,冯起,席海洋,等.黑河下游额济纳绿洲生态需水关键期及需水量[J].中国沙漠,2013,33(2):560-567.
[22] 鲁晖,颉耀文,张文培,等.1986—2015年民勤县绿洲时空变化分析[J].干旱区研究,2017,34(6):1410-1417.
[23] 樊风雷.基于线性光谱混合模型(LSMM)的两种不同端元值选取方法应用与评价——以广州市为例[J].遥感技术与应用,2008,23(3):273-275.
[24] 姜宛贝,孙丹峰,孙强强.基于光谱混合分解的民勤生态治理效果评价[J].中国沙漠,2018,38(1):210-218.
[25] Wu C,Murray A T.Estimating impervious surface distribution by spectral mixture analysis[J].Remote Sensing of Environment,2003,84(4):493-505.
[26] 高尚武,王葆芳,朱灵益,等.中国沙质荒漠化土地监测评价指标体系[J].林业科学,1998,34(2):8-9.
[27] 杨永春,李吉均,陈发虎,等.石羊河下游民勤绿洲变化的人文机制研究[J].地理研究,2002,21(4):449-458.
[28] 石敏俊,陶卫春,赵学涛.民勤绿洲生态重建目标下土地利用和农业结构调整的政策选择[J].干旱区地理,2009,32(2):274-280.
[29] 杨怀德,冯起,黄珊,等.民勤绿洲水资源调度的生态环境效应[J].干旱区资源与环境,2017,31(7):68-73.
[30] 郭瑞,冯起,翟禄新,等.改进型BP神经网络对民勤绿洲地下水位的模拟预测[J].中国沙漠,2010,30(3):737-741.
[31] 栾维功.以水为基,统筹兼顾,重点治理——《石羊河流域重点治理规划》特点分析[J].中国水利,2013(5):29-32.
[32] 段志明,邸士智,等.石羊河志:备考·民勤卷[M].2014.
[33] 陈丽娟,冯起,成爱芳.民勤绿洲土壤水盐空间分布特征及盐渍化成因分析[J].干旱区资源与环境,2013,27(11):99-105.