空间尺度上推转换对影像信息的影响分析
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摘要
针对尺度上推转换在不同空间分辨率遥感影像的应用结果中所产生的光谱扭曲和失真现象未受到普遍重视这一现象。以福建省河田盆地马尾松林样区为研究对象,采用同时相的1～16m卫星多尺度观测影像,基于最邻近法、双线性内插法、三次卷积内插法以及像元聚合法4种方法,将原始影像转换生成一系列低分辨率影像,并分别与同尺度真实卫星影像的光谱反射率、植被指数、光谱空间结构和影像产品数值进行对比分析,以定量评估升尺度转换对影像光谱信息的影响。结果表明:伴随升尺度倍数的增加,升尺度转换影像的光谱均值、NDVI以及变化趋势与真实观测尺度影像相比呈显著差异;经不同倍数尺度上推后的影像空间信息量和清晰度逐渐下降,其幅度明显低于真实影像的变化结果。建议通过构建经验统计方程对不同传感器数据进行光谱转换,以充分利用多尺度遥感观测优势并保证结果的准确性。
According to the fact that the spectral distortion and information failure due to scale conversion by up-scaling algorithms from different spatial resolutions are widely ignored in most multi-scale remote sensing application results,therefore its influence has not been addressed clearly so far.To clarify this situation,this paper selected the Pinus massoniana forest-covered areas in Hetian basin in Fujian province,southeast China,using the time quasi-synchronous multi-scale remotely sensed data with a resolution of 1 mto 16 m,to examine the image results of four commonly used up-scaling algorithms:Nearest Neighbor(NN),Bilinear(BI),Cubic Convolution(CC)and Pixel Aggregate(PA).This paper used above up-scaling algorithms to magnify 1 m resolution image to multiple low-resolution images,to compared the spatial scale variations of image including multiband spectral reflectance,vegetation index(NDVI),spatial structure features,as well as image product values with the real satellite images,and the effects of scaling conversion on image spectral information were quantitatively assessed.The results showed that along with the increases of spatial resolution,the mean spectral reflectance and almost all NDVI of the images changed a little after up-scaling transformation based on different algorithms,which had significant differences compared with the multi-resolution observed images at each resolution level(P<0.05).In addition,the spatial information and sharpness of all up-scaled images decreased gradually,which were significantly slower compared with the observed images.The results suggested that the real multiscale satellite images should be used whenever possible in quantitative remote sensing research by constructing the empirical statistical equation to transform the spectrum of various remote sensor data,to take full advantage of multi-scale remote sensing and ensure the accuracy of related study results.
According to the fact that the spectral distortion and information failure due to scale conversion by up-scaling algorithms from different spatial resolutions are widely ignored in most multi-scale remote sensing application results,therefore its influence has not been addressed clearly so far.To clarify this situation,this paper selected the Pinus massoniana forest-covered areas in Hetian basin in Fujian province,southeast China,using the time quasi-synchronous multi-scale remotely sensed data with a resolution of 1 mto 16 m,to examine the image results of four commonly used up-scaling algorithms:Nearest Neighbor(NN),Bilinear(BI),Cubic Convolution(CC)and Pixel Aggregate(PA).This paper used above up-scaling algorithms to magnify 1 m resolution image to multiple low-resolution images,to compared the spatial scale variations of image including multiband spectral reflectance,vegetation index(NDVI),spatial structure features,as well as image product values with the real satellite images,and the effects of scaling conversion on image spectral information were quantitatively assessed.The results showed that along with the increases of spatial resolution,the mean spectral reflectance and almost all NDVI of the images changed a little after up-scaling transformation based on different algorithms,which had significant differences compared with the multi-resolution observed images at each resolution level(P<0.05).In addition,the spatial information and sharpness of all up-scaled images decreased gradually,which were significantly slower compared with the observed images.The results suggested that the real multiscale satellite images should be used whenever possible in quantitative remote sensing research by constructing the empirical statistical equation to transform the spectrum of various remote sensor data,to take full advantage of multi-scale remote sensing and ensure the accuracy of related study results.
引文
[1]SEXTON J O,URBAN D L,DONOHUE M J,et al.Long-term land cover dynamics by multi-temporal classification across the Landsat-5record[J].Remote Sensing of Environment,2013,128:246-258.
[2]吴田军,骆剑承,沈占锋,等.高分辨率遥感土地覆盖分类技术的应用研究:以重庆市黔江贫困区为例[J].地球信息科学学报,2016,18(3):353-361.(WU Tianjun,LUO Jiancheng,SHEN Zhanfeng,et al.Application of land cover classification techniques in poverty-stricken areas using high resolution remote sensing:a case study of Qianjiang district of Chongqing city[J].Journal of Geo-Information Science,2016,18(3):353-361.)
[3]ROTH K L,ROBERTS D A,DENNISON P E,et al.The impact of spatial resolution on the classification of plant species and functional types within imaging spectrometer data[J].Remote Sensing of Environment,2015,171:45-57.
[4]LYU Z Y,HE H Q,BENEDIKTSSON J A,et al.A generalized image scene decomposition based system for supervised classification of very high resolution remote sensing imagery[J].Remote Sensing,2016,8(10):814-831.
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[6]刘良云.叶面积指数遥感尺度效应与尺度纠正[J].遥感学报,2014,18(6):1158-1168.(LIU Liangyun.Simulation and correction of spatial scaling effects for leaf area index[J].Journal of Remote Sensing,2014,18(6):1158-1168.)
[7]GARRIGUES S,ALLARD D,BARET F,et al.Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data[J].Remote Sensing of Environment,2006,105(4):286-298.
[8]李小文,王祎婷.定量遥感尺度效应刍议[J].地理学报,2013,68(9):1163-1169.(LI Xiaowen,WANG Yiting.Prospects on future developments of quantitative remote sensing[J].Acta Geographica Sinica,2013,68(9):1163-1169.)
[9]LI X,CHENG G D,LIU S M,et al.Heihe watershed allied telemetry experimental research(HiWATER):Scientific objectives and experimental design[J].Bulletin of the American Meteorological Society,2013,94(8):1145-1160.
[10]MING D P,YANG J Y,LI L,et al.Modified ALV for selecting the optimal spatial resolution and its scale effect on image classification accuracy[J].Mathematical and Computer Modeling,2011,54(3):1061-1069.
[11]杨闫君,田庆久,占玉林,等.空间分辨率与纹理特征对多光谱遥感分类的影响[J].地球信息科学学报,2018,20(1):99-107.(YANG Yanjun,TIAN Qingjiu,ZHAN Yulin,et al.Effects of spatial resolution and texture features on Multi-spectral remote sensing classification[J].Journal of Geo-information Science,2018,20(1):99-107.)
[12]LING Y,EHLERS M,USERY E L,et al.Effects of spatial resolution ratio in image fusion[J].International Journal of Remote Sensing,2008,29(7):2157-2167.
[13]韩鹏,龚健雅,李志林,等.遥感影像分类中的空间尺度选择方法研究[J].遥感学报,2010,14(3):507-518.(HAN Peng,GONG Jianya,LI Zhilin,et al.Selection of optimal scale in remotely sensed image classification[J].Journal of Remote Sensing,2010,14(3):507-518.)
[14]NAGLER P L,BROWN T,HULTINE K R,et al.Regional scale impacts of Tamarix leaf beetles(Diorhabda carinulata)on the water availability of western U.S.rivers as determined by multi-scale remote sensing methods[J].Remote Sensing of Environment,2012,118:227-240.
[15]晋锐,李新,马明国,等.陆地定量遥感产品的真实性检验关键技术与试验验证[J].地球科学进展,2017,32(6):630-642.(JIN Rui,LI Xin,MA Mingguo,et al.Key methods and experiment verification for the validation of quantitative remote sensing products[J].Advances in Earth Science,2017,32(6):630-642.)
[16]孙晨曦,刘良云,关琳琳,等.锡林浩特草原区域MODIS LAI产品真实性检验与误差分析[J].遥感学报,2014,18(3):518-536.(SUN Chenxi,LIU Liangyun,GUAN Linlin,et al.Validation and error analysis of the MODIS LAI product in Xilinhot grassland[J].Journal of Remote Sensing,2014,18(3):518-536.)
[17]ZHANG R H,TIAN J,LI Z L,et al.Principles and methods for the validation of quantitative remote sensing products[J].Science China Earth Sciences,2010,53(5):741-751.
[18]栾海军,田庆久,余涛,等.定量遥感升尺度转换研究综述[J].地球科学进展,2013,28(6):657-664.(LUAN Haijun,TIAN Qingjiu,YU Tao,et al.Review of upscaling of quantitative remote sensing[J].Advances in Earth Science,2013,28(6):657-664.)
[19]韩鹏,龚健雅,李志林,等.遥感影像空间尺度上推方法的评价[J].遥感学报,2008,12(6):964-971.(HAN Peng,GONG Jianya,LI Zhilin,et al.Comparing the effect of aggregation methods for remote sensing image[J].Journal of Remote Sensing,2008,12(6):964-971.)
[20]VIVONE G,ALPARONE L,CHANUSSOT J,et al.A critical comparison among pan sharpening algorithms[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(5):2565-2586.
[21]徐涵秋.福建省长汀县河田盆地区近35年来地表裸土变化的遥感时空分析[J].生态学报,2013,33(10):2946-2953.(XU Hanqiu.Spatiotemporal dynamics of the bare soil cover in the Hetian basinal area of County Changting,China,during the past 35years[J].Acta Ecologica Sinica,2013,33(10):2946-2953.)
[22]徐凯健,曾宏达,朱小波,等.基于五种大气校正的多时相森林碳储量遥感反演研究[J].光谱学与光谱分析,2017,37(11):3493-3498.(XU Kaijian,ZENG Hongda,ZHU Xiaobo,et al.Evaluation of five commonly used atmospheric correction algorithms for multi-temporal aboveground forest carbon storage estimation[J].Spectroscopy and Spectral Analysis,2017,37(11):3493-3498.)
[23]黄绍霖,徐涵秋,曾宏达,等.福建长汀河田盆地的马尾松林碳储量时空动态变化[J].地球科学,2013,38(5):1081-1090.(HUANG Shaolin,XU Hanqiu,ZENG Hongda,et al.Analysis of spatial and temporal dynamics of carbon storage of pinus massoniana forest in the hetian basin in county changting of Fujian province,China[J].Earth Science,2013,38(5):1081-1090.)
[24]SPRINTSIN M,KARNIELI A,BERLINER P,et al.The effect of spatial resolution on the accuracy of leaf area index estimation for a forest planted in the desert transition zone[J].Remote Sensing of Environment,2007,109(4):416-428.
[25]GARCIA-LLAMAS P,CALVO L,ALVAREZ-MARTINEZ J M,et al.Using remote sensing products to classify landscape,a multi-spatial resolution approach[J].International Journal of Applied Earth Observation and Geoinformation,2016,50:95-105.
[26]吴小丹,肖青,闻建光,等.遥感数据产品真实性检验不确定性分析研究进展[J].遥感学报,2014,18(5):1011-1023.(WU Xiaodan,XIAO Qing,WEN Jianguang,et al.Advances in uncertainty analysis for the validation of remote sensing products[J].Journal of Remote Sensing,2014,18(5):1011-1023.)
[27]栾海军,田庆久,余涛,等.基于分形理论的NDVI连续空间尺度转换模型研究[J].光谱学与光谱分析,2013,33(7):1857-1862.(LUAN Haijun,TIAN Qingjiu,YU Tao,et al.Modeling continuous scaling of NDVI based on fractal theory[J].Spectroscopy &Spectral Analysis,2013,33(7):1857-1862.)
[28]TIAN Y H,WANG Y J,ZHANG Y,et al.Radiative transfer based scaling of LAI retrievals from reflectance data of different resolutions[J].Remote Sensing of Environment,2002,84(1):143-159.
[29]CHEN D,STOW D A,GONG P.Examining the effect of spatial resolution and texture window size on classification accuracy:an urban environment case[J].International Journal of Remote Sensing,2004,25(11):2177-2192.
[30]WU H,TANG B H,LI Z L.Impact of nonlinearity and discontinuity on the spatial scaling effects of the leaf area index retrieved from remotely sensed data[J].International Journal of Remote Sensing,2013,34(9/10):3503-3519.
[31]CHANDER G,COAN M J,SCARAMUZZA P L.Evaluation and comparison of the IRS-P6 and the Landsat sensors[J].IEEE Transactions on Geoscience and Remote Sensing,2008,46(1):209-221.
[32]THENKABAIL P S.Inter-sensor relationships between IKONOS and Landsat-7ETM+NDVI data in three ecoregions of Africa[J].International Journal of Remote Sensing,2004,25(2):389-408.
[33]LU D S,BATISTELLA M,MORAN E,et al.Fractional forest cover mapping in the Brazilian Amazon with a combination of MODIS and TM images[J].International Journal of Remote Sensing,2011,32(22):7131-7149.
[34]SHI Y C,WANG J D,QIN J,et al.An upscaling algorithm to obtain the representative ground truth of LAI time series in heterogeneous land surface[J].Remote Sensing,2015,7(10):12887-12908.
[35]ZHANG X,YAN G,LI Q,et al.Evaluating the fraction of vegetation cover based on NDVI spatial scale correction model[J].International Journal of Remote Sensing,2006,27(24):5359-5372.
[2]吴田军,骆剑承,沈占锋,等.高分辨率遥感土地覆盖分类技术的应用研究:以重庆市黔江贫困区为例[J].地球信息科学学报,2016,18(3):353-361.(WU Tianjun,LUO Jiancheng,SHEN Zhanfeng,et al.Application of land cover classification techniques in poverty-stricken areas using high resolution remote sensing:a case study of Qianjiang district of Chongqing city[J].Journal of Geo-Information Science,2016,18(3):353-361.)
[3]ROTH K L,ROBERTS D A,DENNISON P E,et al.The impact of spatial resolution on the classification of plant species and functional types within imaging spectrometer data[J].Remote Sensing of Environment,2015,171:45-57.
[4]LYU Z Y,HE H Q,BENEDIKTSSON J A,et al.A generalized image scene decomposition based system for supervised classification of very high resolution remote sensing imagery[J].Remote Sensing,2016,8(10):814-831.
[5]MEDDENS A J H,HICKE J A,VIERLING L A.Evaluating the potential of multispectral imagery to map multiple stages of tree mortality[J].Remote Sensing of Environment,2011,115:1632-1642.
[6]刘良云.叶面积指数遥感尺度效应与尺度纠正[J].遥感学报,2014,18(6):1158-1168.(LIU Liangyun.Simulation and correction of spatial scaling effects for leaf area index[J].Journal of Remote Sensing,2014,18(6):1158-1168.)
[7]GARRIGUES S,ALLARD D,BARET F,et al.Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data[J].Remote Sensing of Environment,2006,105(4):286-298.
[8]李小文,王祎婷.定量遥感尺度效应刍议[J].地理学报,2013,68(9):1163-1169.(LI Xiaowen,WANG Yiting.Prospects on future developments of quantitative remote sensing[J].Acta Geographica Sinica,2013,68(9):1163-1169.)
[9]LI X,CHENG G D,LIU S M,et al.Heihe watershed allied telemetry experimental research(HiWATER):Scientific objectives and experimental design[J].Bulletin of the American Meteorological Society,2013,94(8):1145-1160.
[10]MING D P,YANG J Y,LI L,et al.Modified ALV for selecting the optimal spatial resolution and its scale effect on image classification accuracy[J].Mathematical and Computer Modeling,2011,54(3):1061-1069.
[11]杨闫君,田庆久,占玉林,等.空间分辨率与纹理特征对多光谱遥感分类的影响[J].地球信息科学学报,2018,20(1):99-107.(YANG Yanjun,TIAN Qingjiu,ZHAN Yulin,et al.Effects of spatial resolution and texture features on Multi-spectral remote sensing classification[J].Journal of Geo-information Science,2018,20(1):99-107.)
[12]LING Y,EHLERS M,USERY E L,et al.Effects of spatial resolution ratio in image fusion[J].International Journal of Remote Sensing,2008,29(7):2157-2167.
[13]韩鹏,龚健雅,李志林,等.遥感影像分类中的空间尺度选择方法研究[J].遥感学报,2010,14(3):507-518.(HAN Peng,GONG Jianya,LI Zhilin,et al.Selection of optimal scale in remotely sensed image classification[J].Journal of Remote Sensing,2010,14(3):507-518.)
[14]NAGLER P L,BROWN T,HULTINE K R,et al.Regional scale impacts of Tamarix leaf beetles(Diorhabda carinulata)on the water availability of western U.S.rivers as determined by multi-scale remote sensing methods[J].Remote Sensing of Environment,2012,118:227-240.
[15]晋锐,李新,马明国,等.陆地定量遥感产品的真实性检验关键技术与试验验证[J].地球科学进展,2017,32(6):630-642.(JIN Rui,LI Xin,MA Mingguo,et al.Key methods and experiment verification for the validation of quantitative remote sensing products[J].Advances in Earth Science,2017,32(6):630-642.)
[16]孙晨曦,刘良云,关琳琳,等.锡林浩特草原区域MODIS LAI产品真实性检验与误差分析[J].遥感学报,2014,18(3):518-536.(SUN Chenxi,LIU Liangyun,GUAN Linlin,et al.Validation and error analysis of the MODIS LAI product in Xilinhot grassland[J].Journal of Remote Sensing,2014,18(3):518-536.)
[17]ZHANG R H,TIAN J,LI Z L,et al.Principles and methods for the validation of quantitative remote sensing products[J].Science China Earth Sciences,2010,53(5):741-751.
[18]栾海军,田庆久,余涛,等.定量遥感升尺度转换研究综述[J].地球科学进展,2013,28(6):657-664.(LUAN Haijun,TIAN Qingjiu,YU Tao,et al.Review of upscaling of quantitative remote sensing[J].Advances in Earth Science,2013,28(6):657-664.)
[19]韩鹏,龚健雅,李志林,等.遥感影像空间尺度上推方法的评价[J].遥感学报,2008,12(6):964-971.(HAN Peng,GONG Jianya,LI Zhilin,et al.Comparing the effect of aggregation methods for remote sensing image[J].Journal of Remote Sensing,2008,12(6):964-971.)
[20]VIVONE G,ALPARONE L,CHANUSSOT J,et al.A critical comparison among pan sharpening algorithms[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(5):2565-2586.
[21]徐涵秋.福建省长汀县河田盆地区近35年来地表裸土变化的遥感时空分析[J].生态学报,2013,33(10):2946-2953.(XU Hanqiu.Spatiotemporal dynamics of the bare soil cover in the Hetian basinal area of County Changting,China,during the past 35years[J].Acta Ecologica Sinica,2013,33(10):2946-2953.)
[22]徐凯健,曾宏达,朱小波,等.基于五种大气校正的多时相森林碳储量遥感反演研究[J].光谱学与光谱分析,2017,37(11):3493-3498.(XU Kaijian,ZENG Hongda,ZHU Xiaobo,et al.Evaluation of five commonly used atmospheric correction algorithms for multi-temporal aboveground forest carbon storage estimation[J].Spectroscopy and Spectral Analysis,2017,37(11):3493-3498.)
[23]黄绍霖,徐涵秋,曾宏达,等.福建长汀河田盆地的马尾松林碳储量时空动态变化[J].地球科学,2013,38(5):1081-1090.(HUANG Shaolin,XU Hanqiu,ZENG Hongda,et al.Analysis of spatial and temporal dynamics of carbon storage of pinus massoniana forest in the hetian basin in county changting of Fujian province,China[J].Earth Science,2013,38(5):1081-1090.)
[24]SPRINTSIN M,KARNIELI A,BERLINER P,et al.The effect of spatial resolution on the accuracy of leaf area index estimation for a forest planted in the desert transition zone[J].Remote Sensing of Environment,2007,109(4):416-428.
[25]GARCIA-LLAMAS P,CALVO L,ALVAREZ-MARTINEZ J M,et al.Using remote sensing products to classify landscape,a multi-spatial resolution approach[J].International Journal of Applied Earth Observation and Geoinformation,2016,50:95-105.
[26]吴小丹,肖青,闻建光,等.遥感数据产品真实性检验不确定性分析研究进展[J].遥感学报,2014,18(5):1011-1023.(WU Xiaodan,XIAO Qing,WEN Jianguang,et al.Advances in uncertainty analysis for the validation of remote sensing products[J].Journal of Remote Sensing,2014,18(5):1011-1023.)
[27]栾海军,田庆久,余涛,等.基于分形理论的NDVI连续空间尺度转换模型研究[J].光谱学与光谱分析,2013,33(7):1857-1862.(LUAN Haijun,TIAN Qingjiu,YU Tao,et al.Modeling continuous scaling of NDVI based on fractal theory[J].Spectroscopy &Spectral Analysis,2013,33(7):1857-1862.)
[28]TIAN Y H,WANG Y J,ZHANG Y,et al.Radiative transfer based scaling of LAI retrievals from reflectance data of different resolutions[J].Remote Sensing of Environment,2002,84(1):143-159.
[29]CHEN D,STOW D A,GONG P.Examining the effect of spatial resolution and texture window size on classification accuracy:an urban environment case[J].International Journal of Remote Sensing,2004,25(11):2177-2192.
[30]WU H,TANG B H,LI Z L.Impact of nonlinearity and discontinuity on the spatial scaling effects of the leaf area index retrieved from remotely sensed data[J].International Journal of Remote Sensing,2013,34(9/10):3503-3519.
[31]CHANDER G,COAN M J,SCARAMUZZA P L.Evaluation and comparison of the IRS-P6 and the Landsat sensors[J].IEEE Transactions on Geoscience and Remote Sensing,2008,46(1):209-221.
[32]THENKABAIL P S.Inter-sensor relationships between IKONOS and Landsat-7ETM+NDVI data in three ecoregions of Africa[J].International Journal of Remote Sensing,2004,25(2):389-408.
[33]LU D S,BATISTELLA M,MORAN E,et al.Fractional forest cover mapping in the Brazilian Amazon with a combination of MODIS and TM images[J].International Journal of Remote Sensing,2011,32(22):7131-7149.
[34]SHI Y C,WANG J D,QIN J,et al.An upscaling algorithm to obtain the representative ground truth of LAI time series in heterogeneous land surface[J].Remote Sensing,2015,7(10):12887-12908.
[35]ZHANG X,YAN G,LI Q,et al.Evaluating the fraction of vegetation cover based on NDVI spatial scale correction model[J].International Journal of Remote Sensing,2006,27(24):5359-5372.