浙江钱塘江流域土地利用/覆盖自动分类研究及时空变化分析
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摘要
浙江钱塘江流域地处长江三角洲经济发达地区。近十几年来,人口、经济快速增长,土地利用显著变化,国民生产总值逐年递增,成为我国经济发展最快的地区之一。但由于在经济发展过程中对土水资源的合理开发利用和生态环境的保护重视不够,造成了土地利用方式的不合理以及土水资源的大规模无序开发,从而加剧了钱塘江流域水质下降和环境恶化。研究表明,流域内各种土地利用/覆盖类型比例的变化是造成土水质量下降和生态环境恶化的重要原因。伴随着钱塘江流域经济的飞速发展,科学大范围地进行土地资源科学有效管理迫在眉捷。因此,利用遥感技术进行土地利用/覆盖自动分类方法研究及遥感监测时空变化分析,正确认识浙江钱塘江流域土地利用/覆盖变化情况及时空演变趋势,对优化土地利用结构,实现土地资源的优化配置和集约利用将提供新的方法途径,对钱塘江流域乃至整个浙江省的可持续发展具有极其重要的意义。
     本文将光谱角制图(SAM)方法与多源信息相结合,探索了适应于地形地貌复杂、土地利用细碎地区,简便、高效的能够满足应用需求的高精度土地利用/覆盖计算机自动分类的新方法。并运用此方法,对浙江钱塘江流域1991年、1997年和2004年三年跨度近15年土地利用/覆盖进行自动分类,实现动态监测。随后,对1991年、1997年和2004年三期的土地利用/履盖变化进行时空特性分析,揭示了浙江钱塘江流域土地利用/覆盖变化的规律,寻找出该流域土地利用/覆盖变化的热点地类及热点区域,以及探明了各地类重心转移的程度和方向。为优化浙江钱塘江流域土地利用结构,实现土地资源的优化配置和科学管理,提供强有力的信息支持和研究分析的新路径方法。
     本研究的主要结果如下:
     1.基于SAM和多源信息的土地利用覆盖自动分类方法研究
     土地利用/履盖变化是全球环境变化的重要组成部分和主要原因之一。如何在地形地貌复杂、土地利用细碎地区,获得能够满足应用需求的高精度土地利用/覆盖自动分类专题图是遥感工作者所面临的挑战。为此,本研究将多源信息与光谱角制图(SAM)自动分类相结合,探求多源信息在TM图像自动分类中的作用。对引入的七个信息:海拔高程、坡度、坡向、归一化植被指数(NDVI)、归一化水体指数(NDWI)、归一化建筑指数(NDBD和归一化裸土指数(NDBaI)的作用,进行了分析。以具有代表性的浙江富阳市和义乌市为研究区,进行试验验证。结果表明,坡度信息的辅助作用最为突出。复合坡度信息后的TM图像SAM分类比单独TM图像SAM分类总精度提高10%左右。以坡度作为辅助信息与TM图像进行融合,再利用SAM方法进行分类,简便高效,对研究地区的土地利用解译工作具有实际的应用价值。
     2.浙江钱塘江流域1991年、1997年、2004年土地利用/覆盖动态监测
     结合分层分区分景的方法,根据研究区的地物特征和地形地貌,将研究区划为3层16区87个地貌分景区,运用SAM自动分类方法对浙江钱塘江流域1991年、1997年、2004年三期共87个地貌分景区进行土地利用/覆盖的自动分类,并对分类结果进行了随机点精度评价和实测点精度评价。两次评价结果,三期影像的分类总精度均在80%左右,总Kappa系数均在0.70以上,分类质量较好。浙江钱塘江流域1991年、1997年、2004年土地利用/覆盖动态监测结果:林地基本保持不变;水田呈逐年下降趋势;建筑用地呈逐年上升趋势;旱园地在1991年和1997年面积保持不变,在2004年有明显下降;水域在1991年和1997年面积变化不大,在2004年明显上升。
     3.浙江钱塘江流域1991年到2004年土地利用/覆盖时空变化分析
     浙江钱塘江流域1991年到2004年间,建筑用地变化速度最快,是浙江钱塘江流域土地利用/覆盖变化的“热点”地类;早园地和水田变化频繁,是浙江钱塘江流域土地利用/覆盖变化的“敏感”地类。1991年到2004年年间土地利用/覆盖程度不断加深,其中,1991到1997年间是浙江钱塘江流域快速发展的时期。1991年到2004年间浙江钱塘江流域土地利用/覆盖结构均衡度在不断增加,优势度在不断下降,目前流域土地利用/覆盖结构正向着逐步均衡的方向发展。
     浙江钱塘江流域1991年到2004年间诸暨市、义乌市是土地利用/覆盖变化的热点地区。其中,1991年到1997年间诸暨市、遂昌市、萧山区、富阳市、桐庐县、义乌市为土地利用/覆盖变化的热点地区,1997年到2004年间萧山区、金东区、婺城区为土地利用/覆盖变化的热点地区。
     浙江钱塘江流域1991年至2004年期间,水域和建筑用地的重心漂移量较大。建筑用地的重心漂移量最大,漂移方向为东北方。其次是水域,漂移方向为东南方;水田、旱园地、林地的重心漂移量均较小,漂移方向分别水田向北方,旱园向西北方,林地向西南方。
Qiantang River Watershed(QRW)is situated at the Yangtze River Delta where is one of the economically most developed areas.For the past decades,the economics and population of QRW have a swift growth,the land use/cover changes remarkably and the Gross National Product(GNP)increases substantially year by year.The area has becomes one of economic development fastest areas in China.However,soil and water resources have not been used and conserved properly in the course of economic development,which leads to the water quality declination and the environment quality deterioration.Previous research indicated that the proportion and changes of land use/cover in the drainage basin was the primary reason why the quality of water and soil declined and the ecological environment deteriorated.Along with the swift development of economy in QRW,there is an urgent need for us to utilize and manage the land resource scientifically and effectively.Therefore,using the remote sensing technique to classify land use/cover,to monitor land use/cover changes over space and time domains will have extremely vital significance to the sustainable development of QRW and even the entire Zhejiang Province.
     The paper found that the SAM method by integrating TM imagery and slope data was simple,efficient,and straightforward,and it had greatpotentials to be applied in the area with complex physiography and diversed land uses.Then using this method,the thesis studied the dynamics of land use/cover of QRW and performed spatio-temporal analysis for the land use/cover of the area in 1991,1997 and 2004,Which could convey substantial information for supporting the land use structure optimization and provide deep insight for the management of land resources in a scientific manner.
     The major results from this thesis were as follows:
     1.Land use/cover classification using multi-source data with SAM
     Land use/cover change is one of main causes and components of global change.It has been a great challenge for imagery interpreter that how to classify remote sensing imagery with high accuracy and apply in the area with complex physiography and diversed land uses.By using multi-source data with spectral angle mapper(SAM) algorithm,this study tested the effectiveness of these data.Fuyang City,Zhejiang Province was selected as the study site,while Yiwu City of the Province was as a verification site.Results showed that slope information provided the best assistance in land use/cover classification,comparing with other source data such as Elevation, Aspect,normalized difference vegetation index(NDVI),normalized difference water index(NDWI),normalized difference build-up index(NDBI)and normalized difference bareness index(NDBaI).In comparison with the result from TM data only,the classification accuracy with the slope information added increased by about 10%. The SAM method by integrating TM imagery and slope data is simple,efficient,and straightforward,and it has great potentials to be applied in other study areas.
     2.Land use/cover dynamic monitoring of Qiantang River Watershed in 1991,1997 and 2004
     With the classification scheme of by layers,regions and sub-region,the study areas were divided into 3 layers,16 regions and 87 sub-regions according to the local characters of geomorphology and landform.Land use/cover in 87 sub-regions of QRW in 1991,1997 and 2004 were classified with SAM from TM images and slope data.The classification results were assessed by the method of examining the random points and by the method of contrasting field-measured points.Both results of accuracy assessment showed that the classification accuracy of all three years were about 80%,with Kappa coefficients above 0.70.The main findings of land use/cover dynamic Of QRW in 1991,1997 and 2004 were:forest relatively invariant;paddy field decreasing, built-up increasing yearly;dry land/garden stable from 1991 to1997,while decreased significantly in 2004;and there was little change of water area in 1991 and 1997,whereas it increased in 2004.
     3 Spatio-temporal analysis of land use/cover dynamics of Qiantang River Watershed from 1991 to 2004
     Between 1991 and 2004,built-up was the hotspot type since its changing ratio was the largest;dry land/garden and water were the sensitive types of land since they changed frequently.The diversity of land use/cover kept increasing between 1991 and 2004,with the highest change from 1991 to 1997 in QRW.Land use/cover equilibrium kept increasing,while it was diminishing for some dominant types in QRW from 1991 to 2004.Nowadays,land use/cover of QRW has been gradually approaching the balancing point.
     Zhuji City and Yiwu City were the hotspot of land use/cover change from 1991 to 2004 in QRW.Zhuji City, Suichang County,Xiaoshan District,Fuyang City,Tonglu County and Yiwu City were the hotspots of land use/cover change from 1991 to 1997,while Xiaoshan District,Jindong District and Wucheng District were the hotspots of land use/cover change from 1997 to 2004.
     The gravity center of water and built-up shift dramatically.The gravity center of built-up drifted most towards northeast,while water towards southeast;The gravity center of paddy field,dry land/garden,forestland drifted slightly,and their directions were north,northwest,and southwest in sequence.
引文
[1] Bakkera M M, Goversb G, KosmascC, et al. Soil erosion as a driver of land-use change[J]. Agriculture Ecosystems and Environment, 2005, 105: 467-481.
    
    [2] Campbell J B. Introduction to remote sensing[M]. The Guilford Press, New York. 1987.
    [3] Chen L D, Wang J, Fu B J, et al. Land use change in a small catchment of northern Loess Plateau, China.Agriculture Ecosystem and Environment, 2001, 86(2): 163-172.
    
    [4] Fischer G, G K Heilig. Population momentum and demand on land and water resources[M]. WP-96-149. International Institute for Applied Systems Analysis: Laxenburg, Austria. 1996.
    
    [5] Gao Bo-cai. NDWI-A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space[J].Remote Sensing of Environment, 1996, 58(3): 257-266.
    
    [6] Green G M, Suasman R W. Deforestation history of the eastern rain forests of Madagascar from satellite images[J].Science, 1990, 248: 212-215.
    
    [7] Hinton J C. GIS and remote sensing integration for environmental applications[J]. International Journal of Geographical Information Science, 1996, 10: 877-890.
    [8] Imbemon J. Patterm and development of changes in the Kenyan highlands since the 1950s[J].Agriculture Ecosystems and Environment, 1999, 76: 67-73.
    
    [9] Jensen J R. Urban change detection mapping using Landsat digital data[J] .American Cartographer, 1981, 8(2): 127-147.
    
    [10] Keyzer M A , Y Ermoliev. Modelling producer decision land use in a spatial continuum[M].IR-98-026.International Institute for Applied Systems Analysis: Laxenburg, Austria. 1998.
    
    [11] Kruse F A, Lefkoff A B, Boardman J W, et al. The Spectral Image Processing System (SIPS)-Interactive Visualization and Analysis of Imaging Spectrometer Data[J] .Remote Sensing of Environment, 1993, 44: 145-163.
    
    [12] Lambin E F, Geist H J. Global land-use and land-cover change: what have we learned so far?[R].IGBPNems Letter, 2001: 27-30.
    
    [13] Lambin E F, M D A Rounsevell, H J Geist. Are agricultural land-use models able to predict chances in land-use intensity?[J].Agriculture Ecosystems and Environment, 2002, 82: 321-331.
    
    [14] Lee W T. The face of the earth as seen from the air: A study in the application of airplane photography to geography[C].New York: American Geographical Society, Special Publication 4, 1922.
    
    [15] McFeeters S K. The Use of Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features [J].International Journal of Remote Sensing, 1996, 17(7): 1425-1432.
    [16] Merchant J M , Ripple W J. Special issue: geographic information systems[J]. Photogrammetric Engineering and Remote Sensing, 1996, 62: 1243-1244.
    [17] Nangendo G, A K Skidmore, H van Osten. Mapping East African Tropical Forests and Woodlands-A Comparison of Classifiers[J].Photogrammertry & Remote Sensing, 2007, 61: 393-404.
    [18] Ojima D S, Kittrl T G T, Rosawsll T, et al. Critical issues for understanding global change effects on terrestrial ecosystems[J].EcoI Appl, 1991, 1: 316-325.
    [19]Pan Y,Li X,Gong P,et al.An integrative classification of vegetation in China based on NOAA/VAVHRR and vegetation-climate indices of the Holdridge life zone.International Journal of Remote Sensing,2003,24(5):1009-1027.
    [20]Riebsame W E,Parton W J.Integrated modeling of land use and cover change[J].Bioscieuce,1994,44(5):350-356.
    [21]Skole D,Tucker C.Tropical deforestation and habitat fragmentation in the Amazon:satellite data from1978-1988[J].Science,1993,260:1905-1910.
    [22]Skukla J,Nobre C,Sellers P.Amazon deforestation and climate change[J].Science,1990,247:1322-1325.
    [23]Green G M,Suasman R W.Deforestation history of the eastern rain forests of Madagascar from satellite images[J].Science,1990,248:212-215.
    [24]Taylor J C,Brewer T R,Bird A C.Monitoring landscape change in the national parks of England and Wales using aerial photo interpretation and GIS[J].Int.J.Remote Sensing,2000,21(13):2737-2752.
    [25]Thomson C N,Hardin P.Remote sensing/GIS integration to identify potential low-income housing sites[J].Cities,2000,17(2):97-109.
    [26]Townshend J R G,Justice C O,Kalb V T.Characterization and classification of South America land cover types using satellite data[J].International Journal of Remote Sensing,1987,8:1189-207.
    [27]Townshend J G R.Glob data sets for land application from Advanced Very High Resolution Radiometer:an introduction[J].International Journal of Remote Sensing,1994,15:3319-3332.
    [28]Tucker C J,Townshend J R G,Goff T E.Africa land cover classification using satellite data[J].Science,1985,227:369-375.
    [29]Turner Ⅱ B L,Rose R H,Skole D.Relating land use and global land cover change[R].IGBP reportNo.24,HDP report No.5,1993,65.
    [30]Turner B.L.Ⅱ等,陈百明译,全球土地利用与土地覆被变化:进行综合研究.AMBIO-人类环境杂志,1994,23(1):91-95.
    [31]Vitousek P M,Mooney H A,Lubchenco J,et al.Human domination of earth ecosystems[J].Seienee,1997,277:494-499.
    [32]William E R,William B M,Turner Ⅱ B L.Modeling land use and land cover as part of global environmental change[J].Climatic Change,1994,28:45-64.
    [33]Wu J,Ransom M D,Kluitenberg G J,et al.Land-use management using a soil survey geographic database for Finney County,Kansas[J].Soil Science Society of America Journal,2001,65(1):169-177.
    [34]Zhao H M,Chen X L.Use of Normalized Difference Bareness Index in Quickly Mapping Bare Areas from TM/ETM+[J].Geoseienee and Remote Sensing Symposium,2005,3(25-29),1666-1668.
    [1]摆万奇.深圳市土地利用动态趋势分析[J].自然资源学报,2000,15(2):112-116.
    [2]曹慧,杨浩,孙波等.太湖流域丘陵地壤养分的空间变异[J].土壤,2002,34(4):201-205.
    [3]陈百明.基于区域制定土地可持续利用指标体系的分区方案[J].地理科学进展,2001,20(3):247-253.
    [4]陈怀亮.土地利用与土地覆盖变化的遥感监测及环境影响研究综述[J].气象科技,2005,33(4):289-294.
    [5]陈彦光,刘明华.城市土地利用的熵值定律[J].人文地理,2001,16(4):20-24.
    [6]陈佑启,Peter H Verburg,徐斌.中国土地利用变化及其影响的空间建模分析[J].地理科学进展,2000,19(2):116-127.
    [7]查勇,倪绍祥,杨山.一种利用TM图像自动提取城镇用地信息的有效方法[J].遥感学报,2003,7(1):37-40.
    [8]程潞.我国的国土规划问题[J].地理学报,1983,38(3):292-297.
    [9]丁建丽,塔西甫拉堤.塔里木盆地南绿洲荒漠化遥感研究[J].遥感学报,2002,6(1):71-73.
    [10]冯永玖,刘妙龙.基于遥感的上海市土地利用时空结构演变研究[J].水土保持研究,2007,14(4):233-235.
    [11]胡焕庸.中国之农业区划[J].地理学报,1936,3(1):1-17.
    [12]顾朝林.北京土地利用/覆盖变化机制研究[J].自然资源学报,1991,14(4):309-312.
    [13]梁继,王建,王建华.基于光谱角分类器遥感影像的自动分类和精度分析研究[J].遥感技术与应用,2002,17(6):299-303.
    [14]李爱农,江小波,马泽忠等.遥感自动分类在西南地区土地利用调查中的应用研究[J].遥感技术与应用,2003,18(5):282-285.
    [15]李昌峰,高俊峰,曹慧.土地利用变化对水资源影究的现状和趋势.土壤,2002,34(4):191-197.
    [16]李存军,刘良云,王纪华等.基于Landsat影像自身特征的薄云自动探测与去除[J].浙江大学学报(工学版),2006,40(1):10-13、37.
    [17]李克让,陈育峰,黄玫等.气候变化对土地覆被变化的影响及其反馈模型[J].地理学报,2000,55(增刊):57-63.
    [18]李天宏,韩鹏.厦门市土地利用/覆盖动态变化的遥感监测与分析[J].地理科学,2001(12):537-543.
    [19]李晓兵,陈云浩,喻锋.基于遥感数据的全球及区域土地覆盖制图-现状、战略和趋势[J].地球科学进展,2004,19(1):71-80.
    [20]李晓琴,张振德,张佩民.格尔木土地荒漠化遥感动态监测研究[J].国土资源遥感,2006c2(68):61-63、78.
    [24]冷疏影,李秀彬.土地质量指标体系国际研究新进展[J].地理学报,1999,54(2):177-185.
    [22]刘纪远.国家资源环境遥感宏观调查与动态监测研究[J].遥感学报,1997,1(3):225-230.
    [23]刘纪远,布和敖斯尔.中国土地利用变化现代过程时空特征的研究:基于卫星遥感数据[J].第四纪研究,2000,20(3):229-239.
    [24]刘纪远,刘明亮,庄大方等.中国近期土地利用变化的空间格局分析[J].中国科学(D辑),2002,32(12):1031-1040.
    [25]刘彦随.区域土地利用优化配置[M].北京:学苑出版社,1999.
    [26]刘彦随.山地土地利用类型的结构分析与优化利用-以陕西秦岭山地为例[J].地理学报,2001,56(4):426-436.
    [27]毛发新.钱塘江水资源及其综合开发[J].杭州大学学报,1991,18(2):219-226.
    [28]聂娟.大尺度中国土地覆盖综合分类比较研究[硕士论文].北京:北京师范大学,2003.
    [29]倪绍祥.土地利用类型与土地评价概论[M].北京:高等教育出版社,1999.
    [30]牛文先.生态环境脆弱带Ecotone的基本判定[J].生态学报,1989,9(2):97-105.
    [31]丘君,陈利顶,傅伯杰.土地覆被变其环境效应[M].北京:星球地图出版社,2002.
    [32]彭望碌.遥感与图像解译[M].北京:电子工业出版社,2003.
    [33]潘耀忠,李晓兵,何春阳.中国土地覆盖综合分类研究-基于NOAA/VAVHRR和Holdridge PE.第四纪研究,2000,20(3):270-281.
    [34]任美锷.四川省农作物生产力的地理分布[J].地理学报,1950,16(1):21-22.
    [35]任美锷.我对于“四川省农作物生产力的地理分布”一文的检讨[J].地理学报,1952,18(3-4):120-122.
    [36]任志远,李晶.城郊土地利用变化与区域生态安全动态[M].科学出版社,2006,12-15.
    [37]史培军,陈晋,潘耀忠.深圳市土地利用变化机制分析[J].地理学报,2000,55(2):151-160.
    [38]史培军,宫鹏,李晓兵等著.土地利用/覆盖变化研究的方法与实践[M].2000.
    [39]史培军,宋长青,景贵飞.加强我国LUCC及其对生态环境安全影响的研究一从荷兰“全球变化开放科学会议”看人地系统动力学研究的发展趋势[J].地球科学进展,2002,17(2):161-168.
    [40]唐华俊等.中国土地利用/覆盖变化研究[M].中国农业科技出版社,北京,2004.
    [41]田振清,周越.信息熵基本性质的研究[J].内蒙古师范大学学报自然科学(汉文)版,2002,31(4):347-350.
    [42]吴传钧.1:100万中国土地利用图[M].北京:科学出版社,1990.
    [43]吴传钧,郭焕成.中国土地利用[M].北京:科学出版社,1994.
    [44]王建国,杨林章,马毅杰.经济发达地区低山丘陵土地持续利用和优化利用研究一以苏州市旺山村为例[J].土壤,2002,34(4):179-184.
    [45]王思远,刘纪远,张增祥.中国土地利用时空特征分析[J].地理学报.2001,56(6):631-639.
    [46]王思远,刘纪远,张增祥等.近10年来中国土地利用格局及其演变[J].地理学报,2002(9):522-530.
    [47]王晓栋,崔伟宏.县级土地利用动态监测技术系统研究[J].自然资源学报,1999,14(3):265-270.
    [48]王秀兰,包玉海.土地利用动态变化研究方法探讨[J].地理科学进展,1999,18(3):81-87.
    [49]叶笃正,符淙斌,董文杰等.全球变化科学领域的若干研究进展[J].大气科学,2003,27(4):435-450.
    [50]杨山.发达地区城乡聚落形态的信息提取与分形研究-以无锡市为例[J].地理学报,2000,55(6):671-678.
    [51]杨树珍.国土整治与经济规划[J].地理学报,1983,38(2):105-112.
    [52]延吴.中国土地覆盖变化与环境影响遥感研究[博士论文].北京:中国科学院遥感应用研究所,2002.
    [53]姚伟.基于遥感的水体悬浮物含量变化研究-以钱塘江流域浙江段为例[硕士论文].杭州:浙江大学,2006.
    [54]周立三,余之祥.中国农业地理和土地利用的近期研究[J].地理学报,1990,45(2):146-153.
    [55]张登荣,蔡志刚,俞乐.基于匹配的遥感影像自动纠正方法研究[J].浙江大学学报(工学版),2007,41(3):402-406.
    [56]张丽苏.浙江钱塘江流域土地资源利用特性分析[硕士论文].杭州:浙江大学,2007.6: 26-30.
    [57]张建明.石羊河流域土地利用/土地覆被变化及其环境效应[博士论文].兰州:兰州大学,2007.6:26-30.
    [58]张继贤,杨贵军.单一时相遥感数据土地利用与覆盖变化自动检测方法[J].遥感学报,2005,9(3):294-299.
    [59]张同铸,宋家泰,苏永煊等.农村人民公社经济规划的初步经验[J].地理学报,1959,25(2):107-119.
    [60]张新时,杨奠安.中国全球变化样带的设置与研究[J].第四纪研究,1995,15(1):43-52.
    [61]张显峰,崔伟宏.运用RS、GPS和GIS技术进行大比例尺土地利用动态监测的实验研究[J].地理科学进展,1999,18(2):137-145.
    [62]赵晶,徐剑华,梅安新.城市土地利用结构与形态的分形研究-以上海市中心城区为例[J].华东师范大学学报(自然科学版),2005,(1):78-84.
    [63]朱剑英.智能系统-非经典数学方法[M].武汉:华中科技大学出版社,2001.

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