定量遥感尺度转换方法研究进展
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摘要
首先对遥感科学和气象学、水文学、生态学、地理学和的尺度概念及其转换方法进行了区分。其次对遥感数据空间尺度转换方法的国内外研究进展情况进行了系统梳理,重点比对了目前空间尺度转换常用6种转换方法:统计转换法、分类转换法、数据融合转换方法、分形分析法、基于局域动态模型的转换方法和基于物理意义尺度转换方法及其各自所属方法的优点和缺点。再次以遥感时间尺度转换应用最为广泛的地表蒸散发和农业旱情监测等2个领域为例,对遥感时间尺度转换方法进行了总结。最后预测了今后定量遥感尺度转换研究可能的研究重点,以期为今后更好地开展尺度效应和尺度转换研究工作提供参考。
The advance of remote sensing technology provides an effective way for disaster prediction, environmental monitoring, resource surveys. Remote sensing technology has become a effective tools to get geo-information comprehensively, accurately, and quickly. Undoubtedly, remote sensing technology in the 21 th century has entered an era of quantitative analysis. Thus, the scale issues have always attracted increasing the attention in quantitative remote sensing owing to scale effects limite the accuracy of retrieval the development of its applications. It is a significant problem in remote sensing research, and the methods of scale transformation have been proved is useful to resolve this problem. In ordert to study the scale issues of remote sensing, the advances in methodology of scale issues in quantitative remote sensing must be discussed. Firstly, as we know, the concept of scale is now suffering from a discrepancy in different research area, such as remote sensing, meteorology, hydrology, ecology and geography. Therefore, the definition of scale and relevant methodology in above mentioned research area are introduced in the first of this paper. Secondly, in reviewing the scale issues in remote sensing, the approaches for spatial and temporal scale transformation are reviewed. We summarize the advanges and disadvantages of the mainly spatial scale transformation methods, such as statistical transformation method, classification transformation method, data fusion transformation method, fractal analysis method, local dynamic model based scaling approach and scale transformation method based on physical meaning.Thirdly, the application of measured vapotranspiration and agricultural drought are restricted by remotely sensed data owing to the direct result are instantaneous value estimated at the passing time of satellite. Consequently, different time scales values have practiacal significance. We have summarized many remote sensing data time scale extrapolation methods. The results obtained show that each method has its own advantages and disadvantages. Finally, the future research directions were equally proposed in order to provide a reference for future researchers interested in quantitative remote sensing.
The advance of remote sensing technology provides an effective way for disaster prediction, environmental monitoring, resource surveys. Remote sensing technology has become a effective tools to get geo-information comprehensively, accurately, and quickly. Undoubtedly, remote sensing technology in the 21 th century has entered an era of quantitative analysis. Thus, the scale issues have always attracted increasing the attention in quantitative remote sensing owing to scale effects limite the accuracy of retrieval the development of its applications. It is a significant problem in remote sensing research, and the methods of scale transformation have been proved is useful to resolve this problem. In ordert to study the scale issues of remote sensing, the advances in methodology of scale issues in quantitative remote sensing must be discussed. Firstly, as we know, the concept of scale is now suffering from a discrepancy in different research area, such as remote sensing, meteorology, hydrology, ecology and geography. Therefore, the definition of scale and relevant methodology in above mentioned research area are introduced in the first of this paper. Secondly, in reviewing the scale issues in remote sensing, the approaches for spatial and temporal scale transformation are reviewed. We summarize the advanges and disadvantages of the mainly spatial scale transformation methods, such as statistical transformation method, classification transformation method, data fusion transformation method, fractal analysis method, local dynamic model based scaling approach and scale transformation method based on physical meaning.Thirdly, the application of measured vapotranspiration and agricultural drought are restricted by remotely sensed data owing to the direct result are instantaneous value estimated at the passing time of satellite. Consequently, different time scales values have practiacal significance. We have summarized many remote sensing data time scale extrapolation methods. The results obtained show that each method has its own advantages and disadvantages. Finally, the future research directions were equally proposed in order to provide a reference for future researchers interested in quantitative remote sensing.
引文
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[5] Estes J E, Jensen J R, Simonett D S. Impacts of remote sensing on U.S. geography[J]. Remote Sensing of Environment, 1980,10:43-80.
[6]李小文,王祎婷.定量遥感尺度效应刍议[J].遥感学报, 2013,68(9):1163-1169.[Li Xiaowen, Wang Yiting. Prospects on future developments of quantitative remote sensing. Journal of Remote Sensing, 2013, 68(9):1163-1169.]
[7] Silvestri S, Marani M, Settle J et al. Salt marsh vegetation radiometry:Data analysis and scaling[J]. Remote Sensing of Environment, 2002, 80(3):473-482.
[8] Robinson W S. Ecological correlations and the behavior of individuals[J]. American Sociological Review, 1950, 15(3):351-357.
[9] Boville B A. Sensitivity of simulated climate to model resolution[J]. Journal of Climate, 1991, 4:469-485.
[10] Boyle J S. Sensitivity of dynamical quantities to horizontal resolution for a climate simulation using the ECMWF(Cycle33)Model[J]. Journal of Climate, 1993, 6:796-815.
[11] Kioutsioukis I, Melas D, Zanis P. Statistical downscaling of daily precipitation over Greece[J]. International Journal of Climatology, 2008, 28(5):679-691.
[12] Bl?schl G, Sivapalan M. Scale issues in hydrological modelling:a review[J]. Hydrological Processes, 1995, 9(3-4):251-290.
[13]钟晔,金昌杰,裴铁璠.水文尺度转换探讨[J].应用生态学报,2005, 16(8):1537-1540.[Zhong Ye, Jin Changjie, Pei Tiefan.Discussion on hydrological scaling. Chinese Journal of Applied Ecology, 2005, 16(8):1537-1540.]
[14] Wu J G, Jones K B, Li H et al. Scaling and uncertainty analysis in ecology[M]. Dordrecht:Springer, 2006.
[15]张娜.生态学中的尺度问题[J].生态学报, 2007, 27(10):4252-4266.[Zhang Na. Scale issues in ecology:Upscaling. Acta Ecologica Sinica, 2007, 27(10):4252-4266.]
[16] McCarthy Albert J P. The Irish national electrification scheme[J]. Geographical Review, 1957, 47(4):539-554.
[17] Openshaw S. Ecological fallacies and the analysis of the areal census data[J]. Environment and Planning A, 1984, 16(1):17-31.
[18] Cao C Y, Lam N. Understanding the scale and resolution effects in remote sensing and GIS[M]. New York:Lewis Publishers,1997.
[19] Bierkens M F P, Finke P A, De Willigen P. Upscaling and downscaling methods for environmental research[M]. Dordrecht:Kluwer Academic Publishers, 2000.
[20] Woodcock C E, Strahler A H. The factor of scale in remote sensing[J]. Remote Sensing of Environment, 1987, 21(3):311-332.
[21]彭晓鹃,邓儒儒,刘小平.遥感尺度转换研究进展[J].地理与地理信息科学, 2004, 20(5):6-14.[Peng Xiaojuan, Deng Ruru,Liu Xiaoping. A review of transformation in remote sensing.Geography and Geo-Information Science, Geography and GeoInformation Science, 2004, 20(5):6-14.
[22] Quattrochi D A, Goodchild M F. Scale in remote sensing and GIS[M]. New York:Lewis Publishers, 1997:100-118.
[23]周觅,张杰林.遥感影像尺度转换及最优尺度选择探讨[J].世界核地质科学, 2011, 28(2):94-98.[Zhou Mi, Zhang Jielin. Review on scale transformation for remote sensing image and selection of optimal spatial resolution. World Nuclear Geoscience, 2011, 28(2):94-98.]
[24]秦承志,呼雪梅.栅格数字地形分析中的尺度问题研究方法[J].地理研究, 2014, 33(2):270-283.[Qin Chengzhi, Hu Xuemei. Review on scale-related researches in grid-based digital terrain analysis. Geographical Research, 2014, 33(2):270-283.]
[25] Bian L, Butler R. Comparing effects of aggregation methods on statistical and spatial properties of simulated spatial data[J].Photogrammetric Engineering and Remote Sensing, 1999, 65(1):73-84.
[26] Liang S L. Quantitative remote sensing of land surfaces[M].Hoboken:John Wiley and Sons, 2005.
[27] Hay G J, Niernann K O, Goodenough D G. Spatial thresholds,image-objects, and upscaling:A multiscale evaluation[J]. Remote Sensing of Environment, 1997, 62(1):1-19.
[28] Jin Z, Tian Q, Chen J M et al. Spatial scaling between leaf area index maps of different resolutions[J]. Journal of Environmental Management, 2007, 85(3):628-637.
[29]梁顺林,李小文,王锦地,等.定量遥感:理念与算法[M].北京:科学出版社, 2013.[Liang Shunlin, Li Xiaowen, Wang Jindi et al. Quantitative remote sensing:Idea and algorithm. Beijing:Science Press, 2013.]
[30] Brice M, Michael A. An approach using Dempster-Shafer Theory to fuse spatial data and satellite image derived crown metrics for estimation of forest stand leading species[J]. Information Fusion, 2012, 121(4):122-134.
[31] Al-Ani A, Deriche M. A new technique for combining multiple classifiers using the Dempster-Shafer Theory of evidence[J].Journal of Artificial Intelligence Research, 2002, 17:333-361.
[32] Zhang Y, Hong G. An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural color IKONOS and QuickBird images[J]. Information Fusion, 2005, 6(3):225-234.
[33] Da Cunha A L, Zhou J, Do M N. The nonsubsampled contourlet transform:theory, design, and applications[J]. IEEE Transactions on Image Processing, 2006, 15(10):3089-3101.
[34]卢炎.多源遥感影像融合方法研究[J].吉林大学学报, 2007,37:176-179.[Lu Yan. The research on multi-source remote sensing images fusion technology. Journal of Jilin University,2007, 37:176-179.]
[35] Arivazhagan S, Ganesan L, Kumar T G S. A modified statistical approach for image fusion using wavelet transform[J]. Signal Image and Video Processing, 2009, 3(2):137-144.
[36] Amolins K, Zhang Y, Dare P. Wavelet based image fusion techniques-An introduction, review and comparison[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2007, 62(4):249-263.
[37] Pohl C, Genderen J L V. Multisensor image fusion in remote sensing:Concepts, methods and applications[J]. International Journal of Remote Sensing, 1998, 19(5):823-854.
[38]高永刚.多尺度多平台遥感影像在城市遥感中的应用研究[D].福州:福州大学, 2013.[Gao Yonggang. Study on the application of multi-source and multi-scale images in the urban remote sensing. Fuzhou:Fuzhou University, 2013.]
[39]庞振平.遥感影像融合技术理论与方法研究[D].长春:吉林大学, 2008.[Pang Zhenping. Research on the theory and method of remote sensing image fusion. Changchun:Jilin University,2008.]
[40]刘宇琼.基于像素级多源遥感影像融合技术的研究[D].西安:长安大学, 2007.[Liu Yuqiong. Study on pixel-level multi-source remote sensing data fusion technique. Xi’an:Chang’an University, 2007.]
[41] Xia Z G, Clarke K C. Approaches to scaling of geo-spatial data[M]. Boca Raton:CRC Lewis Publishers, 1997.
[42]徐希孺.遥感物理[M].北京:北京大学出版社, 2005.[Xu Xiru. Physical principles of remote sensing. Beijing:Peking University Press, 2005.]
[43]徐建华.现代地理学中的数学方法[M].北京:高等教育出版社, 2002.[Xu Jianhua. Mathematical methods in contemporary geography. Beijing:Higher Education Press, 2002.]
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