陈云, 戴锦芳, 李俊杰. 2008. 基于影像多特征的CART 决策树分类方法及其应用. 地理与地理信息科学, 24(2): 33-36. [Chen Y, Dai J F, Li J J. 2008. CART-based decisiontree classifier using multi-feature of image and its application.Geography and Geo-Information Science, 24(2): 33-36.]
[2]
金卫斌, 熊勤学, 薛莲. 2011. 基于MODIS-EVI时序数据的江汉平原四湖地区土地覆被动态分析. 湖北农业科学, 50(11): 2220-2224. [Jin W B, Xiong Q X, Xue L. 2011. Dynamicanalysis of the land cover in Four-Lake area in JianghanPlain based on MODIS-EVI time-series data. HubeiAgricultural Sciences, 50(11): 2220-2224.]
[3]
孔凡明, 蒋卫国, 李京, 等. 2013. 基于MODIS的2011 年泰国洪涝受灾信息提取与分析. 灾害学, 28(2): 95-99. [KongF M, Jiang W G, Li J, et al. 2013. Extraction and analysisof Thailand flood affected region in 2011 based on MODISdata. Journal of Catastrophology, 28(2): 95-99.]
[4]
李红军, 郑力, 雷玉平. 2007. 基于EOS/MODIS数据的NDVI与EVI 比较研究. 地理科学进展, 26(1): 26-32. [Li H J,Zheng L, Lei Y P. 2007. Comparison of NDVI and EVIbased on EOS/MODIS data. Progress Progress in Geography,26(1): 26-32.]
[5]
李淼. 2007. 基于支持向量机的MODIS 数据土地覆被分类研究[D]. 阜新: 辽宁工程大学. [Li M. 2007. Land coverclassification with SVM applied to MODIS imagery[D].Fuxin, China: Liaoning Technical University.]
[6]
李文梅, 覃志豪, 杨强. 2010. MODIS NDVI 与MODIS EVI的比较分析. 遥感信息, (6): 73-78. [Li W M, Tan Z H,Yang Q. 2010. Comparison and analysis of MODIS NDVIand MODIS EVI. Remote Sensing Information, (6):73-78.]
[7]
刘爱霞, 王静, 吕春艳. 2006. 基于MODIS 数据的北京西北部地区土地覆被分类研究. 地理科学进展, 25(2): 96-102. [Liu A X, Wang J, Lv C Y. 2006. Land cover classificationbased on MODIS data in area to the north-west ofBeijing. Progress in Geography, 25(2): 96-102.]
[8]
刘建光, 李红, 孙丹峰, 等. 2010. MODIS土地利用/土地覆被多时相多光谱决策树分类. 农业工程学报, 26(10): 312-318. [Liu J G, Li H, Sun D F, et al. 2010. Land use/coverdecision tree classification fusing multi- temporal andmulti- spectral of MODIS. Transactions of the CSAE, 26(10): 312-318.]
刘勇洪, 牛铮. 2004. 基于MODIS遥感数据的宏观土地覆被特征分类方法与精度分析研究. 遥感技术与应用, 19(4): 217-224. [Liu Y H, Niu Z. 2004. Regional land coverimage classification and accuracy evaluation using MODISdata. Remote Sensing Technology and Application,19(4): 217-224.]
[11]
刘勇洪, 牛铮, 徐永明, 等. 2006. 基于MODIS数据设计的中国土地覆被分类系统与应用研究. 农业工程学报, 22(5): 99-105. [Liu Y H, Niu Z, Xu Y M, et al. 2006. Designof land cover classification system for China and itsapplication research based on MODIS data. Transactionsof the CSAE, 22(5): 99-105.]
[12]
马娜, 胡云峰, 庄大方, 等. 2010. 基于最佳波段指数和JM距离可分性的高光谱数据最佳波段组合选取研究. 遥感技术与应用, 25(3): 358-365. [Ma N, Hu Y F, Zhuang DF, et al. 2010. Determination on the optimum band combinationof HJ-1A hyperspectral data in the case region ofDongguan based on optimum index factor and J-M distance.Remote Sensing Technology and Application, 25(3): 358-365.]
[13]
马少平, 朱小燕. 2004. 人工智能. 北京: 清华大学出版社.[Ma S P, Zhu X Y. 2004. Rengong zhineng. Beijing, China:Tsinghua University Press.]
[14]
那晓东, 张树清, 李晓峰, 等. 2007. MODIS NDVI 时间序列在三江平原湿地植被信息提取中的应用. 湿地科学, 5(3): 227-236. [Na X D, Zhang S Q, Li X F, et al. 2007.Application of MODS NDVI time series to extractingwetland vegetation information in the Sanjiang Plain.Wetland Science, 5(3): 227-236.]
[15]
申文明, 王文杰, 罗江海, 等. 2007. 基于决策树分类技术的遥感影像分类方法研究. 遥感技术与应用, 22(3): 333-338. [Shen W M, Wang W J, Luo J H, et al. 2007. Classificationmethods of remote sensing image based on decisiontree technologies. Remote Sensing Technology andApplication, 22(3): 333-338.]
[16]
王大鹏, 王周龙, 李德一, 等. 2007. 综合非光谱信息的荒漠化土地CART 分类. 遥感学报, 11(4): 487-492. [Wang DP,Wang Z L, Li D Y, et al. 2007. The extraction of desertificationinformation using CART under knowledge guide.Journal of Remote Sensing, 11(4): 487-492.]
[17]
魏强. 2009. 基于MODIS和TM数据的京津冀地区土地覆被分类方法研究[D]. 石家庄: 河北师范大学[Wei Q. 2009.Research on land cover classification method of Beijing-Tianjin-Heibei region using MODIS and TM data[D]. Shijiazhuang,China: Hebei Normal University.]
[18]
徐涵秋. 2005. 利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究. 遥感学报, 9(5): 589-595. [Xu H Q.2005. A study on information extraction of water bodywith the modified normalized difference water index(MNDWI). Journal of Remote Sensing, 9(5): 589-595.]
[19]
延昊. 2002. 中国土地覆被变化与环境影响遥感研究[D]. 北京: 中国科学院遥感应用研究所. [Yan H. 2002. Remotesensing study of land cover change and its environmentalin China[D]. Beijing, China: Institute of Remote SensingApplications, CAS.]
[20]
岳瑞红. 2010. 基于MODIS 数据的蒙古高原土地覆被分类研究[D]. 呼和浩特: 内蒙古师范大学. [Yue R H. 2010.Research on land cover classification in Mongolian Plateaubased on MODIS data[D]. Hohhot, China: InnerMongolia Normal University.]
[21]
张会, 闫金凤. 2013. 基于MODIS 影像多特征的CART 决策树分类. 地理空间信息, 11(2): 111-113. [Zhang H, Yan JF. 2013. CART decision tree classifier based on multi-featureof MODIS data. Geospatial Information, 11(2): 111-113.]
[22]
张楠楠, 王文, 王胤. 2012. 鄱阳湖面积的卫星遥感估计及其与水位关系分析. 遥感技术与应用, 27(6): 947- 953.[Zhang N N, Wang W, Wang Y. 2012. Estimate the areaof the Poyang Lake using statellite remote sensing dataand analyze its relationship with water level. RemoteSensing Technology and Application, 27(6): 947-953.]
[23]
赵萍, 傅云飞, 郑刘根, 等. 2005. 基于分类回归树分析的遥感影像土地利用/覆被分类研究. 遥感学报, 9(6): 708-716. [Zhao P, Fu Y F, Zheng L G, et al. 2005. Cart-basedland use/cover classification of remote sensing images.Journal of Remote Sensing, 9(6): 708-716.]
[24]
赵英时. 2001. 美国中西部沙山地区环境变化的遥感研究.地理研究, 20(2): 213-219. [Zhao Y S. 2001. A study onenvironmental change analysis in Sand Hill of Nebraskausing remote sensing. Geographical Research, 20(2): 213-219.]
[25]
赵英时. 2003. 遥感应用分析原理与方法. 北京: 科学出版社. [Zhao Y S. 2003. Yaogan yingyong fenxi yuanli yufangfa. Beijing, China: Science Press.]
[26]
Chen Y, Huang C, Ticehurst C, et al. 2013. An evaluation of MODIs daily and 8- day composite products for floodplain and wetland inundation mapping. Wetlands, 33(5): 823-835.
[27]
DeFries R S, Hansen M, Towsend J G R, et al. 1998. Global land coverclassification at 8 km spatial resolution: the use of training data from landsat imagery in decision tree classifies. International Journal of Remote Sensing, 19(6): 3141-3168.
[28]
Friedl MA, McIver D K, Hodges J C F. 2002. Global land cover mapping from MODIS: algorithms and early results. Remote Sensing of Environment, 83: 287-302.
[29]
Gopal S, Woodcock C E, Strahler A H. 1999. Fuzzy neural network classification of global land cover from a 1° AVHRR data set. Remote Sensing of Environment, 67(2): 230-243.
[30]
Julien Y, Sobrino J A, Verhoef W. 2006. Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999. Remote Sensing of Environment, 103(1): 43-55.
[31]
Mackin K J, Nunohiro E, Ohshiro M, et al. 2006. Land cover classification from MODIS satellite data using probabilisti- cally optimal ensemble of artificial neural networks. Lecture Notes in Computer Science, 4253: 820-826.
[32]
Muchoney D, Borak J. 2000. Application of the MODIS global supervised classification refel to vegetation and land cover mapping of central America. International Journal of Remote Sensing, 21: 1115-1138.
[33]
Price J C. 2003. Compare MODIS and ETM+ data for regional and global land classification. Remote Sensing of Environment, 86(4): 491-499.
[34]
Roerink G J, Menen M, Verhoef W. 2000. Reconstructing cloudfree NDVI composites using Fourier analysis of time series. International Journal of Remote Sensing, 21 (9): 1911-1917.
[35]
Vogelmann J E, Sohl T L, Campbell P V. 1998. Regional characterization of land cover using multiple sources of data. Photogrammetric Engineering and Remote Sensing, 64 (1): 45-57.