应用遥感技术模拟净初级生产力的尺度效应研究进展

doi:10.11820/dlkxjz.2010.04.012

摘要/Abstract

摘要：

采用遥感技术估算地表植被净初级生产力(NPP),已经成为模拟NPP的主要发展方向.遥感技术以及数据处理能力的迅速发展和基于遥感观测生理生态理论研究的进展使大尺度生态系统格局和过程的定量、动态观测成为可能.多种卫星传感器提供了丰富的多尺度对地观测数据,从而形成了不同空间分辨率的影像数据层次体系,使得从定量遥感出发的NPP估算必然存在多尺度的问题.NPP遥感估算模型以不同分辨率的遥感数据(代表不同的研究尺度)作为输入参数时,得到的NPP模拟值差异明显.为了提高NPP的估算精度,需要充分认识不同分辨率的遥感数据对NPP估算结果的影响差异,即NPP的尺度效应问题.本文介绍了遥感尺度效应研究进展,多分辨率遥感数据监测NPP变化的多尺度研究进展,以及NPP估算尺度效应问题的研究进展.并分析了应用遥感技术研究NPP尺度效应的发展趋势.

关键词: 尺度效应, 净初级生产力, 遥感

Abstract:

Remote sensing is often used to simulate net primary productivity (NPP) of vegetation on the surface land. It has become an important direction of simulating NPP. With the rapid development of data process capability of remote sensing technology and physiology-ecology research based on remote sensing observations , dynamic quantitative observations of large scale ecosystem pattern and process have become possible. Multi-source satellite sensors have sent abundant multi-scale earth observing data, and images level system with various resolutions has been made. Therefore, simulating NPP derived from quantitative remote sensing has multi-scale problems. When remote sensing data of various resolutions are input in the NPP model as parameters, the simulated NPP values as outputs of the NPP model will be obviously different. In order to improve the precision of simulating NPP, the effect of simulated NPP results from remote sensing data derived at different resolutions should be fully studied, and that is the scale effects of the NPP model. In the paper, study examples of scale effect of remote sensing are discussed. Research cases of monitoring NPP distribution variation using multi-resolution remote sensing data and recent research progresses of scale effect of simulating NPP are also presented. In addition, future trend of researching scale effect of NPP by remote sensing is also discussed in detail.

Key words: net primary productivity, remote sensing, scale effect

卫亚星,王莉雯. 应用遥感技术模拟净初级生产力的尺度效应研究进展[J]. 地理科学进展, 2010, 29(4): 471-477.

WEI Yaxing,WANG Liwen. A Review on Researching Scale Effect of Net Primary Productivity Based on Remote Sensing[J]. PROGRESS IN GEOGRAPHY, 2010, 29(4): 471-477.

参考文献

[1] Tucker C J, Townshend J R G, Goff T E. African land-cover classification using satellite data, Science, 1985, 227: 369-375.

[2] 李小文, 赵红蕊, 张颢,等. 全球变化与地表参数的定量遥感. 地学前缘, 2002, 9(2): 365-370.

[3] 柏延臣, 王劲峰. 遥感信息的不确定性研究:分类与尺度效应模型. 北京: 地质出版社, 2003: 18-28.

[4] Woodcock Cutis E, Alan H S. The factor of scale in remote sensing. Remote Sensing of Environment, 1987, 21: 311-332.

[5] Raffy M. Heterogeneity and change of scale in models of remote sensing, Spatialization of multi-spectral models. Int. J. Remote Sensing, 1994, 15(2): 2359-2380.

[6] Friedl M A, Davis F W, Michaelsen J, et al. Scaling and uncertainty in the relationship between the NDVI and land surface biophysical variables: an analysis using a scene simulation model and data from FIFE. Remote Sensing of Environment, 1995, 54: 223-246.

[7] Arbia G, Benedeiti R, Espa G. Effect of the MAUP on Image Classification. Geographical System, 1996: 123-141.

[8] Hay G J, Niemann K O, Good D J. Spatial thresholds, image-objects and upscaling: A multi-scale evaluation. Remote Sensing of Environment, 1997, 62: 1-19.

[9] McNulty S G, Vose J W, Swank W J. Scaling predicted pine forest hydrology and productivity across the southern United States//Quattrochi D A, Goodchild M F. Scale in Remote Sensing and GIS. Boca Raton: CRC Lewis Publishers, 1997: 197-209.

[10] Milne B T, Cohent W B. Multiscale assessment of binary and continuous land cover variables for MODIS validation, mapping, and modeling applications. Remote Sensing of Environment, 1999, 70(1): 82-98.

[11] Hsieh P F, Lee L C, Chen N Y. Effect of spatial resolution on classification errors of pure and mixed pixels in remote sensing. IEEE Transactions on Geo science and Remote Sensing, 2001, 39(12): 2657-2663.

[12] Silvestri S, Marania M, Settleb J, et a1. Salt marsh vegetation radiometry data analysis and scaling. Remote Sensing of Environment, 2002, 80(3): 473-482.

[13] Tian Y H, Woodcock C E, Wang Y J, et al. Multiscale analysis and validation of the MODIS LAI product I: Uncertainty assessment. Remote Sensing of Environment, 2002, 83(3): 414-430.

[14] Wang Y J, Woodcock C E, Buermanna W, et al. Evaluation of the MODIS algorithm at a coniferous forest site in Finland. Remote Sensing of Environment, 2004, 91(1): 114-127.

[15] 张仁华, 孙晓敏, 苏红波,等. 遥感及其地球表面时空多变要素的区域尺度转换. 国土资源遥感, 1999, 41(3): 51-59.

[16] 苏理宏, 李小文, 王锦地. 三维结构非同温像元热辐射的尺度效应. 自然科学进展, 2002, 12(1): 51-55.

[17] 黄慧萍, 吴炳方. 地物提取的多尺度特征遥感应用分析. 遥感技术与应用, 2003, 18(5): 276-281.

[18] 李晓兵, 陈云浩, 李霞. 基于多尺度遥感测量的区域土地覆盖格局研究. 植物生态学报, 2003, 27(5): 577-586.

[19] 王红, 赵红蕊, 高劲松. 遥感图像成图尺度问题初探. 地矿测绘, 2004, 20(3): 8-10.

[20] 陈健, 倪绍祥, 李静静,等. 植被叶面积指数遥感反演的尺度效应及空间变异性. 生态学报, 2006, 26(5): 1502-1508.

[21] Xia Zongguo, Clarke K C. Approaches to scaling of geo-spatial data//Quattrochi D A, Goodchild M F. Scales in Remote Sensing and GIS. Boca Raton, FL: CRC/Lewis Publisher, 1997: 309-360.

[22] 张颢, 焦子锑, 杨华,等. 直方图尺度效应研究. 中国科学: D辑, 2002, 32(2): 307-316.

[23] 布和敖斯尔, 马建文, 王勤学,等. 多传感器不同分辨率遥感数字图像的尺度转换. 地理学报, 2004, 59(1): 101-110.

[24] 张永生, 戴晨光, 张云彬, 等. 天基多源遥感信息融合: 理论、算法与应用系统. 北京: 科学出版社, 2005: 33-43.

[25] 毕巍强. 全球变化研究中的数据融合. 地学前缘, 2002, 9(2): 387-391.

[26] 吴凡. 基于小波分析的线状特征数据无级表达. 武汉大学学报: 信息科学版, 2004, 29(6): 488-491.

[27] 赵西安, 李德仁. 小波多尺度影像边缘聚焦算法. 遥感学报, 2003, 7(4): 299-303.

[28] 曹明奎, 于贵瑞, 刘纪远, 等. 陆地生态系统碳循环的多尺度试验观测和跨尺度机理模拟. 中国科学: D辑, 2004, 34(增刊II): 1-14.

[29] 肖乾广, 陈维英, 盛永伟, 等. 用NOAA气象卫星的AVHRR遥感资料估算中国的净第一性生产力. 植物学报, 1996, 38(1): 35-39.

[30] 朴世龙, 方精云. 1982-1999年青藏高原植被净第一性生产力及其时空变化, 自然资源学报, 2002, 17(3): 373-380.

[31] 陈利军, 刘高焕, 励惠国. 中国植被净第一性生产力遥感动态监测. 遥感学报, 2002, 6(2): 129-135.

[32] 张杰, 张强, 郭铌, 等. 荒漠草原牧草净生产力的遥感估算及其可行性研究. 西北植物学报, 2006, 26(11): 2324-2330.

[33] 姜群鸥, 邓祥征, 战金艳, 等. 黄淮海平原耕地转移对植被碳储量的影响. 地理研究, 2008, 27(4): 839-846.

[34] 王军邦. 中国陆地净生态系统生产力和蒸散遥感研究. 浙江大学博士学位论文, 2004: 56-66.

[35] 周才平, 欧阳华, 王勤学,等. 青藏高原主要生态系统净初级生产力的估算. 地理学报, 2004, 59(1): 74-79.

[36] 朱文泉, 陈去浩, 徐丹, 等. 陆地植被净初级生产力计算模型研究进展. 生态学杂志, 2005, 24(3): 296-300.

[37] 姜立鹏, 覃志豪, 谢雯, 等. 基于MODIS数据的草地净初级生产力模型探讨. 中国草地学报, 2006, 28(6): 72-82.

[38] 刘岩, 赵英时, 冯晓明, 等. 半干旱草地净第一性生产力遥感模型研究. 中国科学院研究生院学报, 2006, 23(5): 620-627.

[39] 国志兴, 王宗明, 张柏, 等. 2000年—2006年东北地区植被NPP的时空特征及影响因素分析. 资源科学, 2008, 30(8): 1226-1235.

[40] 陈世荣, 王世新, 周艺. 基于遥感的中国草地生产力初步计算. 农业工程学报, 2008, 24(1): 208-212.

[41] 张娜, 于贵瑞, 于振良, 等. 基于3S的自然植被光能利用率的时空分布特征的模拟. 植物生态学报, 2003, 27(3): 325-336.

[42] 于德永, 潘耀忠, 刘鑫, 等. 湖州市生态资产遥感测量及其在社会经济中的应用. 植物生态学报, 2006, 30(3): 404-413.

[43] 刘阳, 吴钢, 高正文. 基于土地覆盖/利用模式的云南省抚仙湖流域生态资产评估. 生态学报, 2007, 27(12): 5282-5290.

[44] 岑奕, 张良培, 李平湘, 等. 植被净初级生产力的遥感模型在武汉地区的应用. 遥感技术与应用, 2008, 23(1): 12-16.

[45] 王臣立. 雷达与光学遥感结合在森林净初级生产力研究中应用. 中国科学院遥感应用研究所, 2006: 48-58.

[46] 卢玲, 李新, Frank Veroustraete. 中国西部地区植被净初级生产力的时空格局. 生态学报, 2005, 25(5): 1026-1032.

[47] Pierce L L, Running S W. The effects of aggregating sub-grid land surface variation on large-scale estimates of net primary production. Landscape Ecology,1995, 10(4): 239-253.

[48] Turner D P, Dodson R D, Marks D. Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain. Ecological Modeling, 1996, 90(1): 53-67.

[49] Chen J M. Spatial scaling of a remotely sensed surface parameter by contexture. Remote Sens. Environ., 1999, 69(1): 30-42.

[50] Reich P B, Turner D P, Bolstad P. An approach to spatially distributed modeling of net primary production (NPP) at the landscape scale and its application in validation of EOS NPP products. Remote Sensing of Environment, 1999, 70: 69-81.

[51] Nungesser M K, Joyce L A, McGuire A D. Effects of spatial aggregation on predictions of forest climate change response. Climate Research, 1999, 11: 109-124.

[52] Turner D P, Cohen W B, Kennedy R E. Alternative spatial resolutions and estimation of carbon flux over a managed forest landscape in Western Oregon. Landscape Ecology, 2000, 15(5): 441-452.

[53] Anita Z, Chen J M, Liu J, et al. Algorithms for spatial scaling of net primary productivity using subpixel information. 2002 IEEE International Geoscience and Remote Sensing Symposium and the 24th Canadian Symposium on Remote Sensing Proceeding. Toronto, Canada, 2002.

[54] Turner D P, Gower S T, Cohen W B, et al. Effects of spatial variability in light use efficiency on satellite-based NPP monitoring. Remote Sensing of Environment, 2002, 80(3): 397-405.

[55] Anita Z, Jing M Chen, Jane Liu, et al. Spatial scaling of net primary productivity using subpixel information. Remote Sensing of Environment, 2004, 93(1-2): 246-258.

[56] 冯险峰, 刘高焕, 陈述彭, 等. 陆地生态系统净第一性生产力过程模型研究综述. 自然资源学报, 2004, 19(3): 369-378.

[57] Zhang Y Q, Liu C M, Yu Q, et al. Energy fluxes and the Priestley-Taylor parameter over winter wheat and maize in the North China Plain. Hydrol. Process, 2004, 18: 2235-2246.

[58] Douglas E Ahl, Stith T, Gower D, et al. The effects of aggregated land cover data on estimating NPP in northern Wisconsin. Remote Sensing of Environment,2005, 97: 1-14.

[59] Sasai T, Okamoto K, Hiyama T, et al. Comparing terrestrial carbon fluxes from the scale of a flux tower to the global scale. Ecological Modelling, 2007, 208(2-4): 135-144.

[60] 王莉雯, 牛铮, 卫亚星. 应用遥感技术探测土壤侵蚀的研究进展. 地理科学进展, 2007, 26(2): 59-66.