基于植被信息季节变换的植被覆盖度变化——以福建省连江县为例
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摘要
基于植被覆盖度的植被信息遥感变化检测已成为研究植被及其相关生态系统变化的主要途径,但由于云覆盖等天气条件的影响,很难获得不同年份同一季节覆盖整个研究区的光学遥感影像来进行植被变化检测,而采用季节差异的影像必然会影响植被变化检测的结果.为此,本研究利用中高分辨率遥感数据的空间分辨率优势和MODIS遥感数据的时间分辨率优势,基于二者关系的拟合,提出一种植被信息季节变换的方法,将不同季节影像的植被覆盖度变换到研究所需的季节上.结果表明:将该方法应用到福建敖江流域连江片区发现,植被信息变换的效果较好,经过将覆盖研究区的2007年冬季和2013年春季的中高分辨率影像的植被信息统一变换到夏季后,2007年的植被覆盖度由66.5%上升到79.7%,2013年由58.6%上升到77.9%,有效消除了因季节差异而对植被覆盖度估算产生的误差,提高了结果的准确性.
Remote sensing change detection based on fractional vegetation cover( FVC) has become an important way in the research of vegetation and related ecosystems. It is difficult to meet the requirement for optical remote sensing in subtropical areas because of cloudy/rainy weather conditions. Using images from different seasons in the vegetation change detection will inevitably lead to errors in the change detection results due to the seasonal difference. To overcome this problem,we proposed a method for correcting vegetation seasonal variations by taking advantage of high temporal resolution advantage of MODIS remote sensing data and the high spatial resolution of remote sensing data. Based on the relationship between MODIS vegetation data in different seasons via regression analysis,we transformed the vegetation information of the high resolution images of corresponding years to the required season of the years. The method was applied in the Aojiang basin area of Lianjiang County in Fujian Province,China,with good results of vegetation information transformation.The results showed that after transforming vegetation information of the 2007 winter scene and 2013 spring scene of high resolution images to those of summer season,the FVC was enhanced from66.5% to 79.7% for 2007,and from 58.6% to 77.9% for 2013. Our method effectively removed the seasonal difference of FVC and improved the accuracy of the FVC-based change detection results.
Remote sensing change detection based on fractional vegetation cover( FVC) has become an important way in the research of vegetation and related ecosystems. It is difficult to meet the requirement for optical remote sensing in subtropical areas because of cloudy/rainy weather conditions. Using images from different seasons in the vegetation change detection will inevitably lead to errors in the change detection results due to the seasonal difference. To overcome this problem,we proposed a method for correcting vegetation seasonal variations by taking advantage of high temporal resolution advantage of MODIS remote sensing data and the high spatial resolution of remote sensing data. Based on the relationship between MODIS vegetation data in different seasons via regression analysis,we transformed the vegetation information of the high resolution images of corresponding years to the required season of the years. The method was applied in the Aojiang basin area of Lianjiang County in Fujian Province,China,with good results of vegetation information transformation.The results showed that after transforming vegetation information of the 2007 winter scene and 2013 spring scene of high resolution images to those of summer season,the FVC was enhanced from66.5% to 79.7% for 2007,and from 58.6% to 77.9% for 2013. Our method effectively removed the seasonal difference of FVC and improved the accuracy of the FVC-based change detection results.
引文
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[5]Zhang X-L(张学玲),Zhang Y(张莹),Niu D-K(牛德奎),et al.Spatial-temporal dynamics of upland meadow coverage on Wugong Mountain based on TMNDVI.Acta Ecologica Sinica(生态学报),2018,38(7):2414-2424(in Chinese)
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[8]Zhou Z-M(周在明),Yang Y-M(杨燕明),Chen B-Q(陈本清).Estimating the Spartina alterniflora fractional vegetation cover using high spatial resolution remote sensing in a coastal wetland.Acta Ecologica Sinica(生态学报),2017,37(2):505-512(in Chinese)
[9]Ma N(马娜),Hu Y-F(胡云锋),Zhuang D-F(庄大方),et al.Vegetation coverage distribution and its changes in plan blue banner based on remote sensing data and dimidiate pixel model.Scientia Geographica Sinica(地理科学),2012,32(2):251-256(in Chinese)
[10]Zhu L-F(朱林富),Xie S-Y(谢世友),Yang H(杨华),et al.Seasonal variation of vegetation coverage based on MODIS-EVI data in Chongqing during 2000-2015.Resources and Environment in the Yangtze Basin(长江流域资源与环境),2017,26(12):2146-2155(in Chinese)
[11]Coy A,Rankine D,Taylor M,et al.Increasing the accuracy and automation of fractional vegetation cover estimation from digital photographs.Remote Sensing,2016,8:doi:10.3390/rs8070474
[12]Cho J,Lee YW,Han KS.The effect of fractional vegetation cover on the relationship between EVI and soil moisture in non-forest regions.Remote Sensing Letters,2014,5:37-45
[13]Wu DH,Wu H,Zhao X,et al.Evaluation of spatiotemporal variations of global fractional vegetation cover based on GIMMS NDVI data from 1982 to 2011.Remote Sensing,2014,6:4217-4239
[14]Zhang Y-X(张云霞),Li X-B(李晓兵),Chen Y-H(陈云浩).Overview of field and multi-scale remote sensing measurement approaches to grassland vegetation coverage.Advance in Earth Sciences(地球科学进展),2003,18(1):85-93(in Chinese)
[15]Ju J,Roy DP.The availability of cloud-free Landsat ETM+data over the conterminous United States and globally.Remote Sensing of Environment,2008,112:1196-1211
[16]Roy DP,Ju J,Lewis P,et al.Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization,gap filling,and prediction of Landsat data.Remote Sensing of Environment,2008,112:3112-3130
[17]Zhang X-W(张喜旺),Wu B-F(吴炳方).A temporal transformation method of fractional vegetation cover derived from high and moderate resolution remote sensing data.Acta Ecologica Sinica(生态学报),2015,35(4):1155-1164(in Chinese)
[18]Xu H-Q(徐涵秋).Comparison of the models for the normalization of Landsat imagery.Geo-Information Science(地球信息科学),2008,10(3):294-301(in Chinese)
[19]Xu HQ.Evaluation of two absolute radiometric normalization algorithms for pre-processing of Landsat imagery.Journal of China University of Geosciences,2006,17:146-150
[20]Wang J(王静),Zhou W-Q(周伟奇),Xu K-P(许开鹏),et al.Quantitative assessment of ecological quality in Beijing-Tianjin-Hebei urban megaregion,China.Chinese Journal of Applied Ecology(应用生态学报),2017,28(8):2667-2676(in Chinese)
[21]Otto M,H9pfner C,Curio J,et al.Assessing vegetation response to precipitation in northwest Morocco during the last decade:An application of MODIS NDVI and high resolution reanalysis data.Theoretical and Applied Climatology,2016,123:23-41
[22]Gutman G,Ignatov A.The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models.International Journal of Remote Sensing,1998,19:1533-1543
[23]Carlson TN,Ripley DA.On the relation between NDVI,fractional vegetation cover,and leaf area index.Remote Sensing of Environment,1997,62:241-252
[24]Xu H-Q(徐涵秋),He H(何慧),Huang S-L(黄绍霖).Analysis of fractional vegetation cover change and its impact on thermal environment in the Hetian basinal area of County Changting,Fujian Province,China.Acta Ecologica Sinica(生态学报),2013,33(10):2954-2963(in Chinese)
[25]Rundquist BC.The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie.Remote Sensing of Environment,2002,81:129-135
[26]Gao Y-G(高永刚),Xu H-Q(徐涵秋).Estimation of multi-scale urban vegetation coverage based on multisource remote sensing images.Journal of Infrared and Millimeter Waves(红外与毫米波学报),2017,36(2):225-234(in Chinese)
[27]Xu H-Q(徐涵秋).Analysis on urban heat island effect on the dynamics of urban surface biophysical descriptors.Acta Ecologica Sinica(生态学报),2011,31(14):3890-3901(in Chinese)
[28]Shi T-T(施婷婷),Xu H-Q(徐涵秋),Tang F(唐菲).Built-up land change and its impact on ecological quality in a fast-growing economic zone:Jinjiang County,Fujian Province,China.Chinese Journal of Applied Ecology(应用生态学报),2017,28(4):1317-1325(in Chinese)
[2]Yang GJ,Pu RL,Zhang JX,et al.Remote sensing of seasonal variability of fractional vegetation cover and its object-based spatial pattern analysis over mountain areas.ISPRS Journal of Photogrammetry and Remote Sensing,2013,77:79-93
[3]Jiapaer G,Chen X,Bao AM.A comparison of methods for estimating fractional vegetation cover in arid regions.Agricultural and Forest Meteorology,2011,151:1698-1710
[4]Sun H-Y(孙红雨),Wang C-Y(王长耀),Niu Z(牛铮),et al.Analysis of the vegetation cover change and the relationship between NDVI and environmental factors by using NOAA time series data.Journal of Remote Sensing(遥感学报),1998,2(3):204-210(in Chinese)
[5]Zhang X-L(张学玲),Zhang Y(张莹),Niu D-K(牛德奎),et al.Spatial-temporal dynamics of upland meadow coverage on Wugong Mountain based on TMNDVI.Acta Ecologica Sinica(生态学报),2018,38(7):2414-2424(in Chinese)
[6]Hu Y-F(胡玉福),Jiang S-L(蒋双龙),Liu Y(刘宇),et al.Temporal and spatial variation of vegetation coverage on upper Anning River based on RS.Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2014,45(5):205-215(in Chinese)
[7]Gitelson AA,Kaufman YJ,Stark R,et al.Novel algorithms for remote estimation of vegetation fraction.Remote Sensing of Environment,2002,80:76-87
[8]Zhou Z-M(周在明),Yang Y-M(杨燕明),Chen B-Q(陈本清).Estimating the Spartina alterniflora fractional vegetation cover using high spatial resolution remote sensing in a coastal wetland.Acta Ecologica Sinica(生态学报),2017,37(2):505-512(in Chinese)
[9]Ma N(马娜),Hu Y-F(胡云锋),Zhuang D-F(庄大方),et al.Vegetation coverage distribution and its changes in plan blue banner based on remote sensing data and dimidiate pixel model.Scientia Geographica Sinica(地理科学),2012,32(2):251-256(in Chinese)
[10]Zhu L-F(朱林富),Xie S-Y(谢世友),Yang H(杨华),et al.Seasonal variation of vegetation coverage based on MODIS-EVI data in Chongqing during 2000-2015.Resources and Environment in the Yangtze Basin(长江流域资源与环境),2017,26(12):2146-2155(in Chinese)
[11]Coy A,Rankine D,Taylor M,et al.Increasing the accuracy and automation of fractional vegetation cover estimation from digital photographs.Remote Sensing,2016,8:doi:10.3390/rs8070474
[12]Cho J,Lee YW,Han KS.The effect of fractional vegetation cover on the relationship between EVI and soil moisture in non-forest regions.Remote Sensing Letters,2014,5:37-45
[13]Wu DH,Wu H,Zhao X,et al.Evaluation of spatiotemporal variations of global fractional vegetation cover based on GIMMS NDVI data from 1982 to 2011.Remote Sensing,2014,6:4217-4239
[14]Zhang Y-X(张云霞),Li X-B(李晓兵),Chen Y-H(陈云浩).Overview of field and multi-scale remote sensing measurement approaches to grassland vegetation coverage.Advance in Earth Sciences(地球科学进展),2003,18(1):85-93(in Chinese)
[15]Ju J,Roy DP.The availability of cloud-free Landsat ETM+data over the conterminous United States and globally.Remote Sensing of Environment,2008,112:1196-1211
[16]Roy DP,Ju J,Lewis P,et al.Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization,gap filling,and prediction of Landsat data.Remote Sensing of Environment,2008,112:3112-3130
[17]Zhang X-W(张喜旺),Wu B-F(吴炳方).A temporal transformation method of fractional vegetation cover derived from high and moderate resolution remote sensing data.Acta Ecologica Sinica(生态学报),2015,35(4):1155-1164(in Chinese)
[18]Xu H-Q(徐涵秋).Comparison of the models for the normalization of Landsat imagery.Geo-Information Science(地球信息科学),2008,10(3):294-301(in Chinese)
[19]Xu HQ.Evaluation of two absolute radiometric normalization algorithms for pre-processing of Landsat imagery.Journal of China University of Geosciences,2006,17:146-150
[20]Wang J(王静),Zhou W-Q(周伟奇),Xu K-P(许开鹏),et al.Quantitative assessment of ecological quality in Beijing-Tianjin-Hebei urban megaregion,China.Chinese Journal of Applied Ecology(应用生态学报),2017,28(8):2667-2676(in Chinese)
[21]Otto M,H9pfner C,Curio J,et al.Assessing vegetation response to precipitation in northwest Morocco during the last decade:An application of MODIS NDVI and high resolution reanalysis data.Theoretical and Applied Climatology,2016,123:23-41
[22]Gutman G,Ignatov A.The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models.International Journal of Remote Sensing,1998,19:1533-1543
[23]Carlson TN,Ripley DA.On the relation between NDVI,fractional vegetation cover,and leaf area index.Remote Sensing of Environment,1997,62:241-252
[24]Xu H-Q(徐涵秋),He H(何慧),Huang S-L(黄绍霖).Analysis of fractional vegetation cover change and its impact on thermal environment in the Hetian basinal area of County Changting,Fujian Province,China.Acta Ecologica Sinica(生态学报),2013,33(10):2954-2963(in Chinese)
[25]Rundquist BC.The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie.Remote Sensing of Environment,2002,81:129-135
[26]Gao Y-G(高永刚),Xu H-Q(徐涵秋).Estimation of multi-scale urban vegetation coverage based on multisource remote sensing images.Journal of Infrared and Millimeter Waves(红外与毫米波学报),2017,36(2):225-234(in Chinese)
[27]Xu H-Q(徐涵秋).Analysis on urban heat island effect on the dynamics of urban surface biophysical descriptors.Acta Ecologica Sinica(生态学报),2011,31(14):3890-3901(in Chinese)
[28]Shi T-T(施婷婷),Xu H-Q(徐涵秋),Tang F(唐菲).Built-up land change and its impact on ecological quality in a fast-growing economic zone:Jinjiang County,Fujian Province,China.Chinese Journal of Applied Ecology(应用生态学报),2017,28(4):1317-1325(in Chinese)