高寒草地生态系统区土地利用空间变化的分析方法研究
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摘要
目前，国内对草地生态系统区变化的监测研究多是以牧草生物量为对象进行的，而没有对各种土地利用方式综合考虑。变化研究没有对草地生态系统区各种土地利用的空间变化方式分析及驱动因素分析；没有多尺度综合研究。建立的众多草地监测模型只能在特定的区域、特定的时间段内有效，而缺乏大范围内草地生态系统区土地利用变化的监测模型。本研究以高寒草地生态系统区的土地利用变化情况为对象，借助遥感和GIS技术，探索高寒草地生态系统区土地利用空间变化的分析方法，并在选择的试验区进行了方法试验，结果如下：
(1) 在对研究区域土地利用特点分析的基础上，结合本研究的目的，对所获得的两期遥感影像数据，采用ISODATA算法进行图像分割。采用判读解译、NDVI分析和地物波谱特征分析相结合的方法对遥感影像进行解译，将区域土地利用类型划分为高盖度草地、中盖度草地、低盖度草地、农田、弃耕地或休耕地、水体和裸地。居民点、道路和河流采用已有的数字化地图。对分类后的结果进行了检验，精度达到90.91％。
(2) 根据目前土地利用变化研究中的实际需求，提出并实践一种新的土地利用变化监测模型，并以通用商业遥感软件ERDAS为支撑平台，对该模型进行了实现。应用该模型对试验区1987年～2002年的土地利用变化进行试验，验证结果表明，该模型对土地利用变化监测的精度只受土地利用分类精度的影响，模型对分类专题图的处理结果准确度可达100％。该模型的优点在于简单、易于理解和应用，适宜推广应用。
(3) 对土地利用变化研究中应用的两种重心模型进行了实例检验和对比分析，得出重心模型二优于重心模型一的结论。针对地学研究中的三维空间特点，结合高寒草地生态系统区土地利用的特征及本研究的目的，对重心模型二进行了改进，将其由2维模型扩展为3维模型。
(4) 对研究区域土地利用的变化分析得出：1987年～2002年，高盖度草地类型面积减少了90634hm~2，中盖度草地类型面积减少了124600hm~2，低盖度草地类型面积增加了157539hm~2，裸地类型面积增加了21675hm~2，现耕地类型、弃耕地或休耕地类型面积分别增加18840hm~2和18409hm~2。
(5) 应用改进的重心模型对土地利用类型的分布进行了分析，结果表明，高盖度草地类型的分布以山地区比较集中，中盖度草地类型主要分布于山区与平坦地形的交错地带，低盖度草地类型、现耕地类型、弃耕地或休耕地类型、裸地类型和水体类型主要分布在平坦地形区；对土地利用类型在空间上的变化分析结果表明，2002年与1987年相比较，低盖度草地的分布向东南移动了28732m；裸地类型的分布向东南移动15671m，其它类型的分布均发生了明显的移动；对
土地利用类型的分布高程变化研究结果表明，中盖度草地类型的分布重心海拔上
升241 .27m，高盖度草地类型的分布重心海拔上升182.48m，裸地类型的分布重
心海拔下降173.48m，低盖度草地类型的分布重心海拔下降127.74m，弃耕地或
休耕地类型的分布重心海拔上升42.78m，现耕地类型的分布重心海拔上升
36.45m。
(6)对山地区和平坦地形区1987年一2002年的土地利用类型分布及变化
的空间特征进行了较为详细的对比分析。
(7)采用选择窗口法，应用景观指数对1987年和2002年土地利用的景观
特征分别在类型水平和景观水平进行了分析。
(8)采用与地图制图比例尺相联系的景观尺度确定方法，分别在比例尺l:
5万、l:10万、l:20万、l:25万、1:50万和1:100万的尺度上，对1987
年和2002年各个选择窗口内的景观表现特征、变化进行了分析和比较。研究认
为，对高寒草地生态系统区土地利用的景观特征及变化分析，采用以1:25万比
例尺的空间数据为基础进行分析比较合理。
The resent survey research about grassland ecosystem placed more attentions on grass biomass productivity on the grassland, and take no integrative consideration about various types of land use. Studies about grassland ecosystem change, lacking of the analysis of spatial trend and drivering force,were also not be operated in a multi-scale integrative analysis. Many models that had been built for grassland survey can only work correctly in particular condtion and in limited period. There is still no survey model that can be used in large area extent to inspect land-use changes in gralssland ecosystem.
In this dissertation, the changes of land use in the Alpine Grassland Ecosystem (AGES) were analyzed by using the technologies of Remote Sensing (RS) and Geographical Information System (GIS), and a new set of methods suitting to analysis spatial change in the AGES were worked out and proved effectively in experiment area. With large quantity of analysis, the following results were mainly reached.
(1) With the analysis of land use characteristics of experiment region in Alpine grassland ecosystem, and taking consideration of the aims research, the two gainned images, Landsat TM image gainned in 1987 and Landsat ETM+ image gainned in 2002, were segmented by used the arithmetic of Iterative-Orgnizing Data Analysize Technique (ISODATA). Then these fragments were identified by using land-use indicators, which were built during the image interpreting work prcocess in field, such as, the color, texture, shape, position, etc.,and also by using the methods of NDVI and characteristic analysis of spectrum of land-use types in a man-compute interactive manner. The final land-use thematic maps were achieved in the images, and also the land-use types of the High Coverage Grassland (HCG), the Middle Coverage Grassland (MCG), the Low Coverage Grassland (LCG), Field (F), abandoned/rested Field (F1), Bareness land (B), and Water body (W) were achieved. The distribution condition of resident sites, roads and rivers we
re got from digited maps. Precision was assessed on the final land-use classified results, and a precision of 90.91% was gainned.
(2) For the purpose of meeting the need in land-use change research, a new land-use change survey model were built and carried out to use on the basis of commom business Remote Sensing software ERDAS in this study. Finally, this model was used to inspect the land use changes in the experiment area from 1987 to 2002. Outcome showed that the precision of land use change inspection was only influenced by the precision of land-use classification, and for the land-use thematic maps, the precision of land-use type change detection can reach 100%. It is simple to be
understood and easy to use, suitable to generalization and use in LUCC research field.
(3) Two types of gravity center model were detected and compared by using the land-use thematic maps of the experiment area in this study. It was concluded that model 2 is super to model 1. Considerring the 3-dimension characteristics of objects studied in geo-science field, the gravity center model 2 was advanced from 2-dimension to 3-dimension.
(4) By analyzing the area of different land-use types in the experiment region from 1987 to 2002, it was found that the area of High Coverage Grassland reduced 90634hm2, the area of Middle Coverage Grassland reduced 124600hm2, the area of Low Coverage Grassland increased 157539hm2, the area of Bareness Land increased 21675hm2, the area of Field increased 18840hm2, and the area of abandoned/rested Field increased 18409hm2.
(5) Analyzing the spatial distribution and changes of different types of land use in experiment with the advanced gravity center model, the results showed the distribution of different types of land use , that the High Coverage Grassland mainly distributed in mountainous area, the Middle Coverage Grassland mainly distributed between mountainous sub-region and flat sub-region in the experiment area, the Low Coverage Grassland, the Field, the abandoned/rested Field, the Bareness land,
(1) 在对研究区域土地利用特点分析的基础上，结合本研究的目的，对所获得的两期遥感影像数据，采用ISODATA算法进行图像分割。采用判读解译、NDVI分析和地物波谱特征分析相结合的方法对遥感影像进行解译，将区域土地利用类型划分为高盖度草地、中盖度草地、低盖度草地、农田、弃耕地或休耕地、水体和裸地。居民点、道路和河流采用已有的数字化地图。对分类后的结果进行了检验，精度达到90.91％。
(2) 根据目前土地利用变化研究中的实际需求，提出并实践一种新的土地利用变化监测模型，并以通用商业遥感软件ERDAS为支撑平台，对该模型进行了实现。应用该模型对试验区1987年～2002年的土地利用变化进行试验，验证结果表明，该模型对土地利用变化监测的精度只受土地利用分类精度的影响，模型对分类专题图的处理结果准确度可达100％。该模型的优点在于简单、易于理解和应用，适宜推广应用。
(3) 对土地利用变化研究中应用的两种重心模型进行了实例检验和对比分析，得出重心模型二优于重心模型一的结论。针对地学研究中的三维空间特点，结合高寒草地生态系统区土地利用的特征及本研究的目的，对重心模型二进行了改进，将其由2维模型扩展为3维模型。
(4) 对研究区域土地利用的变化分析得出：1987年～2002年，高盖度草地类型面积减少了90634hm~2，中盖度草地类型面积减少了124600hm~2，低盖度草地类型面积增加了157539hm~2，裸地类型面积增加了21675hm~2，现耕地类型、弃耕地或休耕地类型面积分别增加18840hm~2和18409hm~2。
(5) 应用改进的重心模型对土地利用类型的分布进行了分析，结果表明，高盖度草地类型的分布以山地区比较集中，中盖度草地类型主要分布于山区与平坦地形的交错地带，低盖度草地类型、现耕地类型、弃耕地或休耕地类型、裸地类型和水体类型主要分布在平坦地形区；对土地利用类型在空间上的变化分析结果表明，2002年与1987年相比较，低盖度草地的分布向东南移动了28732m；裸地类型的分布向东南移动15671m，其它类型的分布均发生了明显的移动；对
土地利用类型的分布高程变化研究结果表明，中盖度草地类型的分布重心海拔上
升241 .27m，高盖度草地类型的分布重心海拔上升182.48m，裸地类型的分布重
心海拔下降173.48m，低盖度草地类型的分布重心海拔下降127.74m，弃耕地或
休耕地类型的分布重心海拔上升42.78m，现耕地类型的分布重心海拔上升
36.45m。
(6)对山地区和平坦地形区1987年一2002年的土地利用类型分布及变化
的空间特征进行了较为详细的对比分析。
(7)采用选择窗口法，应用景观指数对1987年和2002年土地利用的景观
特征分别在类型水平和景观水平进行了分析。
(8)采用与地图制图比例尺相联系的景观尺度确定方法，分别在比例尺l:
5万、l:10万、l:20万、l:25万、1:50万和1:100万的尺度上，对1987
年和2002年各个选择窗口内的景观表现特征、变化进行了分析和比较。研究认
为，对高寒草地生态系统区土地利用的景观特征及变化分析，采用以1:25万比
例尺的空间数据为基础进行分析比较合理。
The resent survey research about grassland ecosystem placed more attentions on grass biomass productivity on the grassland, and take no integrative consideration about various types of land use. Studies about grassland ecosystem change, lacking of the analysis of spatial trend and drivering force,were also not be operated in a multi-scale integrative analysis. Many models that had been built for grassland survey can only work correctly in particular condtion and in limited period. There is still no survey model that can be used in large area extent to inspect land-use changes in gralssland ecosystem.
In this dissertation, the changes of land use in the Alpine Grassland Ecosystem (AGES) were analyzed by using the technologies of Remote Sensing (RS) and Geographical Information System (GIS), and a new set of methods suitting to analysis spatial change in the AGES were worked out and proved effectively in experiment area. With large quantity of analysis, the following results were mainly reached.
(1) With the analysis of land use characteristics of experiment region in Alpine grassland ecosystem, and taking consideration of the aims research, the two gainned images, Landsat TM image gainned in 1987 and Landsat ETM+ image gainned in 2002, were segmented by used the arithmetic of Iterative-Orgnizing Data Analysize Technique (ISODATA). Then these fragments were identified by using land-use indicators, which were built during the image interpreting work prcocess in field, such as, the color, texture, shape, position, etc.,and also by using the methods of NDVI and characteristic analysis of spectrum of land-use types in a man-compute interactive manner. The final land-use thematic maps were achieved in the images, and also the land-use types of the High Coverage Grassland (HCG), the Middle Coverage Grassland (MCG), the Low Coverage Grassland (LCG), Field (F), abandoned/rested Field (F1), Bareness land (B), and Water body (W) were achieved. The distribution condition of resident sites, roads and rivers we
re got from digited maps. Precision was assessed on the final land-use classified results, and a precision of 90.91% was gainned.
(2) For the purpose of meeting the need in land-use change research, a new land-use change survey model were built and carried out to use on the basis of commom business Remote Sensing software ERDAS in this study. Finally, this model was used to inspect the land use changes in the experiment area from 1987 to 2002. Outcome showed that the precision of land use change inspection was only influenced by the precision of land-use classification, and for the land-use thematic maps, the precision of land-use type change detection can reach 100%. It is simple to be
understood and easy to use, suitable to generalization and use in LUCC research field.
(3) Two types of gravity center model were detected and compared by using the land-use thematic maps of the experiment area in this study. It was concluded that model 2 is super to model 1. Considerring the 3-dimension characteristics of objects studied in geo-science field, the gravity center model 2 was advanced from 2-dimension to 3-dimension.
(4) By analyzing the area of different land-use types in the experiment region from 1987 to 2002, it was found that the area of High Coverage Grassland reduced 90634hm2, the area of Middle Coverage Grassland reduced 124600hm2, the area of Low Coverage Grassland increased 157539hm2, the area of Bareness Land increased 21675hm2, the area of Field increased 18840hm2, and the area of abandoned/rested Field increased 18409hm2.
(5) Analyzing the spatial distribution and changes of different types of land use in experiment with the advanced gravity center model, the results showed the distribution of different types of land use , that the High Coverage Grassland mainly distributed in mountainous area, the Middle Coverage Grassland mainly distributed between mountainous sub-region and flat sub-region in the experiment area, the Low Coverage Grassland, the Field, the abandoned/rested Field, the Bareness land,
引文
1. A.J. Comber, R. V. Birnie, M. Hodgson; A retrospective analysis of land cover change using a polygon shape index; Global Ecology & Biogeography, 2003, vol. 12(3): 207-215.
2. A.J.Tatem, H.G.Lewis, P.M.Atkinson, M.S.Nixon; Super-resolution land cover pattern prediction using a Hopfield neural network. Remote Sensing of Environment, 2002, Vol. 79(1): 1-14.
3. Abuelgasim, W. D. Ross, S. Gopal, and C. E. Woodcock. Change detection using adaptive fuzzy neural networks: Environmental damage assessment after the gulf war. Remote Sensing of Environment, 1999, vol. 70(2): 208-223.
4. Alcamo, J., R. Leemans and G.J.J. Kreileman, Global change scenarios of the 21st.1998
5. Alcamo, J.. Scenarios as tools for international assessments, Expert's corner report Prospects and Scenarios No. 5. European Environment Agency. Copenhagen, Denmark, 2001.
6. Arturo Ruiz-Luna and César A. Berlanga-Robles. Land use, land cover changes and coastal lagoon surface reduction associated with urban growth in northwest Mexico. Landscape Ecology, 2003, 18: 159-171.
7. Beat Peter and Robert Weibel. Integrating Vector and Raster-Based Techniques for the Generalization of Categorical Data. Proceedings of the 19th International Cartographic Conference, Ottawa, Canada, 16-20 August 1999
8. Benoit Mertens, Eric Lambin; Modelling land cover dynamics: integration of fine-scale land cover data with landscape attributes. International Journal of Applied Earth Observation and Geoinformation, 1999, Vol(1): 48-52
9. Bilsborrow, R.E. and H.W.O. Ogendo. Population-driven changes in land use in developing countries. Ambio, 1992, 21: 37-45.-
10. Bilsborrow, R.E.. Population pressure and agricultural development in developing countries: conceptual framework and recent evidence. World Development, 1987, 15: 183-203.
11. Blaikie P., H. Brookfield. Land Degradation and Society. Methuen, New York. 1987.
12. Boerner R.E. Markov models of inertia and dynamism on two contiguous Ohio landscape. Geographical Analysis, 1996, 28( 1): 55-66.
13. Brigitte Dorner, Ken Lertzrnan, Joseph Fall. Landscape pattem in topographically complex landscapes: issues and techniques for analysis. Landscape Ecology, 2002, 17: 729-743.
14. Bugmarm, H., M. Lindner, P. Lasch, M. Flechsig, B. Ebert and W. Cramer. Scaling issues in forest succession modeling. Climatic Change, 2000, 44: 265-289.
15. C. Wu, A. T. Murray. Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment, 2003, Vol. 84(4): 493-505.
16. C.C. Petit, E.F. Lambin. Impact of data integration technique on historical land-use/land-cover change: Comparing historical maps with remote sensing data in the Belgian Ardennes. Landscape Ecology, 2002, Vol.17(2): 117-132
17. Carpenter, S. Gopal, S. Macomber, S. Martens, C. E. Woodcock, J. Franklin. A neural network method for efficient vegetation mapping. Remote Sensing of Environment, 1999, vol. 70(3): 326-338.
18. Cash, D.W. and S.C. Moser. Cross-scale interactions in assessments, information systems,
and decision-making. In: Critical Evaluation of Global Environmental Assessments, Global Environmental Assessment Project, Harvard University, Cambridge, MA, 1998.
19. Costanza. R., and T. Maxwell. Resolution and Predictability: An Approach to the Scaling Problem. Landscape Ecology, 1994, 9: 47-57.
20. Darla K.Munroe, JaneSouthworth, Catherine M.Tucker. The dynamics of land-cover change in western Honduras: exploring spatial and temporal complexity. Agricultural Economics, 2002, Vol.27(3): 355-369.
21. David Miller. A method for estimating changes in the visibility of land cover. Landscape and Urban Planning, 2001, Vol. 54(1): 93-106.
22. E.Mapedza, J.Wright, R.Fawcett. An investigation of land cover change in Mafungautsi Forest, Zimbabwe, using GIS and participatory mapping. Applied Geography, 2003, vol.23(1): 1-21.
23. E.V.Milanova, E.Yu.Lioubimtseva, P.A.Tcherkashin, L.F.Yanvareva. Land use/cover change in Russia: mapping and GIS. Land Use Policy, 1999, Vol.16(3): 153-159.
24. Easterling W. E.. Spatial Scales of Climate Information for Simulating Wheat and Maize Productivity. Agricultural and Forest Meteorology, 1998, 90: 51-63.
25. Ehrlich P., J. Holdren. Impact of Population Growth. Science, 1971, 171: 1212-1217.
26. Elijah W. Ramsey Ⅲ, Sijan K. Sapkota, Frank G. Barnes, Gene A. Nelson. Monitoring the recovery of Juncus roemerianus marsh burns with the normalized difference vegetation index and Landsat Thematic Mapper data. Wetlands Ecology and Management, 2002, 10: 85-96.
27. Felix Rembold, Stefano Carnicelli, Michele Nori, Giovanni A Ferrari. Use of aerial photographs, Landsat TM imagery and multidisciplinary field survey for land-cover change analysis in the lakes region(Ethiopia). International Journal of Applied Earth Observation and Geoinformation, 2000, Vol.2, (3-4): 181-189.
28. Florian PKressler, Klaus Tsteinnocher. Detecting land cover changes from NOAA-AVHRR data by using spectral mixture analysis. International Journal of Applied Earth Observation and Geoinformation, 1999, Vol.1(1): 21-26
29. Forman R. T. T, Godron M.. Landscape Ecology. New York: John Wiley, 1986.
30. Forman, R. T.T.. The ethics of isolation, the spread of disturbance, and landscape ecology. In M. Turner(ed.), Landscape Heterogeneity and Disturbance. Springer-verlag, New York, 1987: 213～229.
31. Forman, R. T. T.. Land Mosaics: The Ecology of Landscapes and Regions. Cambridge University Press, 1995.
32. Foster B.C.. Coefficient of variation as a measure of urban spatial attributes using Spot HRV and Landsat TM. International Journal of Remote Sensing, 1993, 14: 2403-2409.
33. Fox J., J. Krummel, S. Yarnasam, M. Ekasingh, N. Podger. Land use and landscape dynamics in northern Thailand: Assessing change in three upland watersheds. Ambio, 1995, 24: 328-334.
34. Gibson C.C., E. Ostrom, T. K. Alan. The concept of scale and the human dimensions of Global Change: A survey. Ecological Economics, 2000 Vol.32(2): 217-239.
35. Giles M. Foody, Doreen S. Boyd. Fuzzy mapping of tropical land cover along an environmental gradient from remotely sensed data with an artificial neural network. Journal of Geographical Systems, 1999, Vol.(1): 23-35
36. Gong, P., P.J. Howarth. Frequency-based contextual classification and gray-level vector reduction for land use identification. Photogrammetric Engineering and Remote Sensing, 1992,
58: 423-437.
37. Harini Nagendra., Ghate Utkarsh. Landscape ecological planning through a multi-scale characterization of pattern: studies in thewestem Ghats, south india. Environmental Monitoring and Assessment, 2003, 87: 15-233.
38. Harvey L.D.D.. Upscaling in Global Change research. Climatic Change, 2000, 44, : 225-263.
39. Hasan Ozcan, Mahmut Cetin, Kenan Diker. Monitoring and assessment of land use status by GIS. Environmental Monitoring and Assessment, 2003, 87: 33-45.
40. Hidenori Morita. An application of the land-use change model for the Japan case study area. Interim Report, IR-97-065, 1997.
41. Hubert Gulinck, MartaMu "gica, Jose" Vicentede Lucio, Jose" AntonioAtauri. A framework for comparative landscape analysis and evaluation based on land cover data, with an application in the Madrid region(Spain). Landscape and Urban Planning, 2001, Vol.55(4): 257-270.
42. J.D. Miller, S. R. Yool. Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data. Remote Sensing of Environment, 2002, Vol. 82(2-3): 481-496.
43. J. Helmschrot, W.-A. Flügel. Land use characterization and change detection analysis for hydrological model parameterization of large scale afforested areas using remote sensing. Physics and Chemistry of the Earth, Parts A/B/C, 2002, Vol. 27(9-10): 711-718.
44. J. Tapiador, J. L. Casanova. Land use mapping methodology using remote sensing for the regional planning directives in Segovia, Spain. Landscape and Urban Planning, 2003, Vol. 62(2): 103-115.
45. J. Zhang, G. M. Foody. Fully-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: statistical and neural network approaches. International Journal of Remote Sensing, 2001, Vol. 22(4): 615-628.
46. Javier Eduardo Mendoza S., Andre' s Etter R.. Multitemporal analysis(1940-1996)of land cover changes in the southwestern Bogota' highplain(Colombia). Landscape and Urban Planning, 2002, Vol. 59(3): 147-158.
47. K.P.Wittich. Some simple relationships between land-surface emissivity, greenness and the plant cover fraction for use in satellite remote-sensing: International Journal of Biometeorology, 1997, Vol. 41(2): 58-64.
48. Kates R., V. Haarman. Where the poor live: are the assumptions correct?. Environment, 1992, 34: 4-11, 25-28
49. Kevin McGarigal, Joseph Berry, David Buckley.FRAGSTATS Manual, 1995.
50. Kienast F. Analysis of historic landscape patterns with a geographic information system-a methodological outlines. Landscape Ecology, 1993, 8(2): 103-118.
51. Klaus Hubacek, Laixiang Sun. A scenario analysis of-China-& apos's land use and land cover change: incorporating biophysical information into input-output modeling. Structural Change and Economic Dynamics, 2001, Vol.12(4): 367-397.
52. Lam N., D.A. Quattrochi. On the issues of scale, resolution and fractal analysis in the mapping sciences. Professional Geographer, 1992, Vol. 44(1): 88-98.
53. Lambin E. F. Modelling and monitoring land-cover change processes in tropical region. Progress in Physical Geography, 1997, Vol. 21(3): 375-393.
54. Lambin E.E, Baulies X, Bockstael N.. Land-use-and land-cover change(LUCC)
implementation strategy. IGBP Report No.48 and HDP Report No. 10 Stockholm: IGBP, 1999.
55. Lambin E.F.. Modelling and monitoring land-cover change processes in tropical regions. Progress in Physical Geography, 1997, 21(3): 375-393.
56. Louisa J. M. Jansen, Antonio D. I. Gregorio. Parametric land cover and land-use classifications as tools for environmental change detection. Agriculture, Ecosystems and Environment, 2002, Vol. 91(1-3): 89-100.
57. Loveland T. R., Reed B. C., Brown J. F. Development of a global land cover characteristics database and IGBP discover from lkm AVHRR data. International Journal of Remote Sensing(in review), 1998.
58. M.A. Fried, D. K. McIver, J. C. F. Hodges, X. Y. Zhang, D. Muchoney, A. H. Strahler, C. E. Woodcock, S. Gopal, A. Schneider, A. Cooper, A. Baccini, F. Gao, C. Schaaf. Global land cover mapping from MODIS: algorithms and early results. Remote Sensing of Environment, 2002, Vol. 83(1-2): 287-302.
59. M. A.Friedl, C. E.Brodley. Decision Tree Classification of Land Cover from Remotely Sensed Data. Remote Sensing of Environment, 1997, Vol. 61(3): 399-409.
60. M. L. Mendonc, Santos C. Claramunt. An integrated landscape and local analysis of land cover evolution in an alluvial zone. Computers, Environment and Urban Systems, 2001, Vol. 25(6): 557-577.
61. M. Pax-Lenney, C. E. Woodcock, S. A. Macomber, S. Gopal and C. Song. Forest mapping with a generalized classifier and Landsat TM data. Remote Sensing of Environment, 2001, Vol. 77(3): 241-250.
62. Martin Herold, Keith C. Clarke. Gunter Menz. A multi-scale framework for mapping and analysis of the spatial and temporal pattern of urban growth. Proceedings of 22nd EARSEL Symposium "Geoinformation for European-wide integration, Prague, June 2002.
63. MatthiasBürgi, Monica G.Turner. Factors and Processes Shaping Land Cover and Land Cover Changes Along the Wisconsin River. Ecosystems, 2002, Vol.5(2): 0184-0201.
64. Mesev V. The use of Census data in urban image classification. Photogrammetric Engine and Remote Sensing, 1998, Vol. 64(5): 431-438.
65. O'Neill R. V., Krummel J. R., Gardner R. H., Sugihara G, Jackson B.G., Zygmunt B., Christenson S. W., Dale V. H., Graham R. L. Indices of landscape pattern. Landscape ecology, 1988, Vol. 1(3): 153～162.
66. Ostrom E., T. Dietz, N. Dolsak, P. C. Stern, S. Stonich, E. U. Weber(eds). The drama of the commons. National Academy Press, Washington D.C., 2002.
67. P. Kalivas, V. J. Kollias, G. Karantounias. A GIS for the Assessment of the Spatio-Temporal Changes of the Kotychi Lagoon, Western Peloponnese, Greece. Water Resources Management, 2003, 17: 19-36.
68. Paul Aplin, Peter M. Atkinson, Paul J. Curran. Fine Spatial Resolution Simulated Satellite Sensor Imagery for Land Cover Mapping in the United Kingdom. Remote Sensing of Environment, 1999, Vol. 68(3): 206-216.
69. Penner J. E.. Atmospheric chemistry and air quality. In Changes in Land use and land cover: A global perspective.: 175-210. Edited by W. B. Meyer and B. L. Turner. Cambridge University Press, Cambridge, 1994.
70. Peterson G. Scaling ecological dynamics: self-organization, hierarchical structure, and ecological resilience. Climatic Change, 2000, 44: 291-309.
71. R.A. Schowengerdt. Remote Sensing: Models and Methods for Image Processing, 2nd ed. New York, NY: Academic Press, 1997.
72. R. K. Gupta, S. Prasad, P. V. Krishna Rao. Evaluation of spatial upscaling algorithms for different land cover types. Advances in Space Research, 1998, Vol. 22(5).
73. R. Oetter, W. B. Cohen, M. Berterretche, T. K. Maiersperger, R. E. Kennedy. Land cover mapping in an agricultural setting using multiseasonal Thematic Mapper data. Remote Sensing of Environment, 2001, Vol. 72(2): 139-155.
74. Ranchin T., Wald L., Mangolini M.. Improving spatial resolution of remotely-sensed images by means of sensor fusion: a general solution using ARSIS methods. Donnay J. P., Bamsley M. J., Longley P. A.(eds.). Remote sensing and urban analysis, Taylor and Francis, London and New York, pp. 21-37, 2001.
75. Rapport D. J., C. Gaudet and P. Calow(eds.). Evaluating and Monitoring the Health of Large-Scale Ecosystems. Springer-Verlag, Heidelberg, 1995.
76. Ricotta, P. Corona, M. Marchetti, G. Chirici, S. Innamorati. LaDy: software for assessing local landscape diversity profiles of raster land cover maps using geographic windows. Environmental Modelling and Software, 2003, Vol.18(4): 373-378.
77. Ridd M. K.. Exploring a VIS(vegetation-impervioussurface-soit)model for urban ecosystem analysis through remote sensing: comparative anatomy for cities. International Journal of Remote Sensing, 1995, Vol. 16(12): 2165-2185.
78. Robert Walker. SOUTH FLORIDA: THE REALITY OF CHANGE AND THE PROSPECTS FOR SUSTAINABILITY Urban sprawl and natural areas encroachment: linking land cover change and economic development in the Florida Everglades. Ecological Economics, 2001, Vo. 37(3): 357-369.
79. Robin S. Reid, Russell L. Kruska, Nyawira Muthui, Andualem Taye, Sara Wotton, Cathleen J. Wilson and Woudyalew Mulatu. Land-use and land-cover dynamics in response to changes in climatic, biological and socio-political forces: the case of southwestern Ethiopia. Landscape Ecology, 2000, 15: 339-355.
80. Robinson J. B.. Modelling interactions between human and natural systems. International Social Science Journal, 1991, 43: 629-648.
81. Ross S. Lunetta, Jayantha Ediriwickrema, David M. Johnson, John G. Lyon, Alexa McKerrow. Impacts of vegetation dynamics on the identification of land-cover change in a biologically complex community in North Carolina, USA. Remote Sensing of Environment, 2002, Vol. 82(2-3): 258-270.
82. S. de Bruin. Predicting the Areal Extent of Land-Cover Types Using Classified Imagery and Geostatistics. Remote Sensing of Environment, 2000, Vol. 74(3): 387-396.
83. S. E.WALSH, P. A. SORANNO, D. T. RUTLEDGE. Lakes, Wetlands, and Streams as Predictors of Land Use/Cover Distribution. Environmental Management, 2003, Vol.31(2): 0198-0214.
84. S. Takeuchi, A. Inanaga. Scaling-Up of Land Cover Information by Using Multiple Resolution Satellite Data. Advances in Space Research, 2000, Vol. 26(7).
85. Sadler, G. J., M. J. Barnsley, S. L. Barr. Information extraction from remotely sensed images for urban land analysis. Proceeding of the 2nd European Conference on Geographical Information Systems EGIS'91, Brussels, Belgium, April, EGIS Foundation, Utrecht, pp. 955-964, 1991.
86. Sam A. Cushman, David O. Wallin. Rates and patterns of landscape change in the Central
Sikhote-alin Mountains, Russian Far East. Landscape Ecology, 2000, 15: 643-659.
87. Skinner C. N. Change in spatial characteristics of forest openings in the Klamath Mountains of north California, USA. Landscape Ecology, 1995, Vol. 10(4): 219-228.
88. Stafford Smith, J. F. Reynolds(eds). Integrated Assessment and Desertification. Dahlem University Press, Berlin, 2002.
89. Stedman-Edwards P. Root Causes of Biodiversity Loss: An Analytical Approach. World Wide Fund for Nature, Washington, D.C., 1998.
90. Tanaka S., Sugimura T.. A new frontier of remote sensing from IKONOS images. International Journal of Remote Sensing, 2001, Vol. 22(1): 1-5.
91. Todd M. Scanlon, John D. Albertson, Kelly K. Caylor, Chris A.Williams. Determining land surface fractional cover from NDVI and rainfall time series for a savanna ecosystem. Remote Sensing of Environment, 2002, Vol. 82(2-3): 376-388.
92. Turner Ⅱ, B.L., Moss R.H., Skole D.L..Relating land use and global land-cover change-A proposal for an IGBP-HDP core project. IGBP Report No.24 and HDP Report No.5. Stockholm: IGBP, 1993.
93. Turner B. L. Ⅱ. Land-use and land-cover change science/research plan. IGBP Report, 35, HDP Report, 7. IGBP, Stockholm, 1995.
94. Turner B. L. Ⅱ. Two Types of Global Environmental Change: Definitional and Spatial Scale Issues in Their Human Dimensions. Global Environmental Change, 1990, 1: 14-22.
95. Tumer M. G., Gardner R. H.. Quantitative Methods in Landscape Ecology. New York: Springer-Verlag, 1991.
96. Turner M. G. Landscape ecology-living in mosaic. In: Dodson S et al eds. Ecology. Oxford University Press.77～122.
97. W.B. Clapham Jr. Continuum-based classification of remotely sensed imagery to describe urban sprawl on a watershed scale. Remote Sensing of Environment, 2003, Vol. 86(3): 322-340.
98. W.L. Stefanov, M. S. Ramsey, P. R. Christensen. Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to add urban centers. Remote Sensing of Environment, 2001, Vol. 77(2): 173-185.
99. Witbanks T. J.. Geographic Scaling Issues in Integrated Assessments of Climate Change. Rotmans, J. and M. van Asselt(eds.)Scaling Issues in Integrated Assessment. Swets and Zeitlinger, 2002.
100. William G. Kepner, Christopher J. Watts, Curtis M. Edmonds, John K. Maingi, Stuart E. Marsh and Gonzalo Luna. A landscape approach for detecting and evaluating change in a semi-arid environment. Environmental Monitoring and Assessment, 2000, 64: 179-195
101. William L. Stefanov, Michael S.Ramsey, Philip R.Christensen. Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to add urban centers. Remote Sensing of Environment, 2001, Vol. 77(2): 173-185.
102. X. Zhan, R. A. Sohlberg, J. R. G.. Townshend, C. DiMiceli, M. L. Carroll, J. C. Eastman, M. C. Hansen, R. S. DeFries. Detection of land cover changes using MODIS 250 m data. Remote Sensing of Environment, 2002, Vol. 83(1-2): 336-350
103. Yong Du, Philippe M. Teillet, Josef Cihlar. Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection. Remote Sensing of Environment, 2002, Vol. 82(1): 123-134.
104．E．B．邓肯 A．A．尤什凯维奇著；张饴慈，刘吉江译．马尔可夫过程(定理与问题)，科学
出版社，1988．
105．摆万奇，丁贤忠．内蒙古自治区奈曼旗土地利用变化预测研究．资源科学，2003，25(2)：73～76
106．摆万奇，赵士洞．土地利用和土地覆盖变化研究模型综述．自然资源学报，1997，12(2)：169～175．
107．摆万奇．深圳市土地利用动态趋势分析．自然资源学报，2000，15(2)：112～116
108．包玉海，乌兰图雅，香宝，赵晓丽．内蒙古耕地重心移动及其驱动因子分析．1998，17(4)：47-54
109．布仁仓，王宪礼，肖笃宁．黄河三角洲景观组分判定与景观破碎化分析．应用生态学报，1999，10(3)：321～324
110．曹慧，杨浩，赵其国．长江三角洲地区土壤质量退化的类型、驱动力与对策．中国人口．资源与环境，2001，11(2)：47～48
111．陈百明，刘新卫，杨红．LUCC研究的最新进展评述．地理科学进展，2003，22(1)：22～29
112．陈百明．试论中国土地利用和土地覆被变化及其人类驱动力研究．自然资源，1997，2：31～36．
113．陈利顶，傅伯杰．黄河三角洲地区人类活动对景观结构的影响分析——以山东省东营市为例．生态学报，1996，16(4)：337～344．
114．陈述彭主编．遥感信息机理研究．科学出版社，1998．
115．董玉祥．西藏沙漠化灾害现状及其驱动力研究．自然灾害学报．2001b，10(2)：96～102
116．董玉祥．我国半干旱地区现代沙漠化驱动因素的定量辩识．中国沙漠，2001，21(4)：411～416
117．樊锦沼，张传道．应用气象卫星资料估算草场产草量方法的研究．干旱区资源与环境，1990(3)：23～27
118．冯利华，骆高远．中国热带气旋的时间活动性研究．热带地理，1999，19(2)：113-116
119．傅伯杰，陈利顶，马克明，王仰麟等．景观生态学原理及应用．科学出版社，2001．
120．傅伯杰，王仰麟．国际景观生态学的发展动态与趋势．地球科学进展，1990，(3)：23～25．
121．傅伯杰．景观多样性的类型及其生态意义．地理学报，1996，51(5)：454～462
122．傅泽强，蔡运龙，杨友孝，戴尔阜．中国粮食安全与耕地资源变化的相关分析．自然资源学报，2001，16(4)：313-319．
123．甘红，刘彦随，李宪文．区域土地利用变化与水资源利用相关分析．南京师大学报(自然科学版)，2003，26(3)：82-88．
124．高清竹，何立环，江源，王家骥．农牧交错带典型区农业与牧业用地互动关系研究．地球科学进展，2002，17(2)：209～215
125．高志强，刘纪远，庄大方．我国耕地面积重心及耕地生态背景质量的动态变化．自然资源学报，1998，13(1)：92-96
126．何春阳，史培军，陈晋，周宇宇．北京地区土地利用／覆盖变化研究．地理研究，2001，20(6)：679-687
127．黄敬峰，桑长青，冯振武．天山北坡天然草地产量遥感动态监测模式．自然资源学报，1993(1)：10～17
128．黄敬峰，王秀珍，蔡承侠，胡新博．利用NOAA／AVHRR资料监测北疆天然草地生产力．草业科学，1999，16(5)：62-69
129．黄敬峰，王秀珍，胡新博．新疆北部不同类型天然草地产草量遥感监测模型．中国草地，1999，1：7～11，18
130．黄敬峰，王秀珍，王人潮，蔡承侠，胡新博．天然草地牧草产量与气象卫星植被指数的相关分析．农业现代化研究，2000，21(1)：33-36
131．贾宝全，慈龙骏，杨晓晖，杨洁泉，潘伯荣．人工绿洲潜在景观格局及其与现实格局的比较分析．应用生态学报，2000，11(6)：912～916
132．贾宝全，慈龙骏，杨晓晖，孙林，杨洁泉．石河子莫索湾垦区绿洲景观格局变化分析．生态学报，2001，21(1)：34～40
133．江洪，张艳丽，JamesRStrittholt．干扰与生态系统演替的空间分析．生态学报，2003，23(9)：1861-1876．
134．姜琦刚，高村弘毅，后藤真太郎．中国新疆且末绿洲土地利用变化及驱动力分析．吉林大学学报(地球科学版)，2003，33(1)：83～87
135．李博，任志强，史培军等．中国北方草地畜牧业动态监测研究．北京：中国农业科技出版社，1993．1～33
136．李博，史培军，林小泉．我国温带草地草畜平衡动态监测系统的研究．草地学报，1995，3(2)：95-102．
137．李博等．中国北方草地畜牧业动态监测研究(一)．中国农业科技出版社，1993．
138．李德成，徐彬彬，石晓日．利用马氏过程模拟和预测土壤侵蚀的动态演变．环境遥感，1995，10(2)：89～96．
139．李建龙，黄敬峰，维纳汗．不同类型草地监测与估产遥感指标和光学模型建立的研究．中国草地，1996，6：6～10．
140．李建龙，蒋平，梁天刚．我国草地遥感科学发展的轨迹、内涵及展望．中国草地，1998，3：53～56
141．李建龙，蒋平，徐雨清．利用遥感技术和地理信息系统动态监测天山草地与农业资源研究．兰州大学学报(自然科学版)，1998，34(3)：110～116
142．李京．应用NOAA／AVHRR遥感资料对大面积草场进行产草量估量定算的方法研究．自然资源学报，1994，4：365．
143．李平，李秀彬，刘学军．我国现阶段土地利用变化驱动力的宏观分析．地理研究，2001，20(2)：129～138
144．李秀彬．地球系统科学的核心领域——土地利用／土地覆被变化国际研究动向[J]．地理学报，1996，51(6)：553—557
145．李秀彬．全球环境变化研究的核心领域—土地利用／土地覆被变化的国际研究动向．地理学报，1996，vol．51(6)：553-558
146．李秀彬．土地利用变化的解释．地理科学进展，2002，21(3)：195～204
147．李艳霞，陈同斌，罗维，黄启飞，吴吉夫．中国城市污泥有机质及养分含量与土地利用．生态学报，2003，23(11)：2464-2474．
148．刘德钦，刘宇，薛新玉．中国人口分布及空间相关分析．遥感信息，2002，6：2-6．
149．刘先华，陈佐忠，富久尾步等．定居放牧方式下归一化植被指数(NDVI)的空间变化特征．植物生态学报，2000，24(6)：662～666
150．钱家忠，朱学愚，吴剑锋．地下水资源评价中降水量的时间序列-马尔可夫模型．地理科学，2001，21(4)：350-353．
151．青海省农牧业区划委员会办公室，海南州农牧业区划委员会办公室，共和县农牧业区划委员会办公室．青海省共和县农牧业资源调查及区划图册．1984．
152．青海省农牧业区划委员会办公室，海南州农牧业区划委员会办公室，共和县农牧业区划委员会办公室．青海省共和县综合农牧业区划报告．1988．
153．青海省统计局．青海省统计年鉴1988．中国统计出版社，1988．10．
154．青海省统计局．青海省统计年鉴2002．中国统计出版社，2002．7．
155．全志杰．泥河沟土地利用动态的遥感研究．中国农业科学，1995，28(增刊)：131～136
156．史培军．人地系统动力学研究的现状与展望．地学前缘 1997，4(1-2)：201～211．
157．王思远，张增祥，周全斌，王长有，刘纪远．近10年中国土地利用格局及其演变．地理学报，2002，57(5)：523-530．
158．王宪礼，布仁仓，胡远满，肖笃宁．辽河三角洲湿地的景观格局分析．生态学报，1997，17(3)：317-323
159．王秀兰，包玉海．土地利用动态变化研究方法探讨．地理科学进展，1999，18(1)：81-87
160．王秀兰．基于遥感的呼伦贝尔盟农牧业土地利用变化及其对地区农业持续发展影响的研究．地理科学进展，1999，18(4)：322-329．
161．王艳荣，吕玉华．内蒙古锡林郭勒盟草原植被的光谱反射特征与牧草产量相关性的分析．植物生态学与地植物学学报，1990，3：5～9
162．邬建国．景观生态学——格局、过程、尺度与等级．北京：高等教育出版社，2000
163．徐岚，赵羿．利用马尔可夫过程预测东陵区土地利用格局变化．应用生态学报，1993，4(3)：272～277．
164．徐岚，赵羿．利用马尔可夫过程预测东陵区土地利用格局的变化．应用生态学报，1993，4(3)：272-277．
165．严登华，何岩，邓伟，王春梅．东辽河流域地表水水质空间格局演化．中国环境科学 2001，21(6)：564～568．
166．杨正礼，杨改河．中国高寒草地生产潜力与载畜量研究．资源科学，2000，22(4)：72-77．
167．岳天祥，程彤，张红旗等．景观动态及其驱动因素和效应分析自然资源，1997，6：19～26．
168．曾辉，郭庆华，刘晓东．景观格局空间分辨率效应的试验研究．北京大学学报，1998，34(6)：820～826．
169．张明．区域土地利用结构及其驱动因子的统计分析．自然资源学报，1999，14(4)：381-384．
170．中国植被编辑委员会．中国植被，第1版，科学出版社，1980
171．周炳中，赵其国，杨浩．江苏省耕地变化及其驱动机制的数理探讨．土壤学报，2003，40(5)：665-671．
172．周华锋，马克明，傅伯杰．人类活动对北京东灵山地区景观格局影响分析．自然资源学报，1999，14(2)：117～122．
173．祝卓．人口地理学．中国人民大学出版社，1991．79～80．
174．庄大方，刘纪远．中国土地利用程度的区域分异模型研究．自然资源学报，1997，12(2)：105-111．
175．邹亚荣，张增祥，周全斌，赵晓丽．中国农牧交错区土地利用变化空间格局与驱动力分析．自然资源学报，2003，18(2)：222～228
2. A.J.Tatem, H.G.Lewis, P.M.Atkinson, M.S.Nixon; Super-resolution land cover pattern prediction using a Hopfield neural network. Remote Sensing of Environment, 2002, Vol. 79(1): 1-14.
3. Abuelgasim, W. D. Ross, S. Gopal, and C. E. Woodcock. Change detection using adaptive fuzzy neural networks: Environmental damage assessment after the gulf war. Remote Sensing of Environment, 1999, vol. 70(2): 208-223.
4. Alcamo, J., R. Leemans and G.J.J. Kreileman, Global change scenarios of the 21st.1998
5. Alcamo, J.. Scenarios as tools for international assessments, Expert's corner report Prospects and Scenarios No. 5. European Environment Agency. Copenhagen, Denmark, 2001.
6. Arturo Ruiz-Luna and César A. Berlanga-Robles. Land use, land cover changes and coastal lagoon surface reduction associated with urban growth in northwest Mexico. Landscape Ecology, 2003, 18: 159-171.
7. Beat Peter and Robert Weibel. Integrating Vector and Raster-Based Techniques for the Generalization of Categorical Data. Proceedings of the 19th International Cartographic Conference, Ottawa, Canada, 16-20 August 1999
8. Benoit Mertens, Eric Lambin; Modelling land cover dynamics: integration of fine-scale land cover data with landscape attributes. International Journal of Applied Earth Observation and Geoinformation, 1999, Vol(1): 48-52
9. Bilsborrow, R.E. and H.W.O. Ogendo. Population-driven changes in land use in developing countries. Ambio, 1992, 21: 37-45.-
10. Bilsborrow, R.E.. Population pressure and agricultural development in developing countries: conceptual framework and recent evidence. World Development, 1987, 15: 183-203.
11. Blaikie P., H. Brookfield. Land Degradation and Society. Methuen, New York. 1987.
12. Boerner R.E. Markov models of inertia and dynamism on two contiguous Ohio landscape. Geographical Analysis, 1996, 28( 1): 55-66.
13. Brigitte Dorner, Ken Lertzrnan, Joseph Fall. Landscape pattem in topographically complex landscapes: issues and techniques for analysis. Landscape Ecology, 2002, 17: 729-743.
14. Bugmarm, H., M. Lindner, P. Lasch, M. Flechsig, B. Ebert and W. Cramer. Scaling issues in forest succession modeling. Climatic Change, 2000, 44: 265-289.
15. C. Wu, A. T. Murray. Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment, 2003, Vol. 84(4): 493-505.
16. C.C. Petit, E.F. Lambin. Impact of data integration technique on historical land-use/land-cover change: Comparing historical maps with remote sensing data in the Belgian Ardennes. Landscape Ecology, 2002, Vol.17(2): 117-132
17. Carpenter, S. Gopal, S. Macomber, S. Martens, C. E. Woodcock, J. Franklin. A neural network method for efficient vegetation mapping. Remote Sensing of Environment, 1999, vol. 70(3): 326-338.
18. Cash, D.W. and S.C. Moser. Cross-scale interactions in assessments, information systems,
and decision-making. In: Critical Evaluation of Global Environmental Assessments, Global Environmental Assessment Project, Harvard University, Cambridge, MA, 1998.
19. Costanza. R., and T. Maxwell. Resolution and Predictability: An Approach to the Scaling Problem. Landscape Ecology, 1994, 9: 47-57.
20. Darla K.Munroe, JaneSouthworth, Catherine M.Tucker. The dynamics of land-cover change in western Honduras: exploring spatial and temporal complexity. Agricultural Economics, 2002, Vol.27(3): 355-369.
21. David Miller. A method for estimating changes in the visibility of land cover. Landscape and Urban Planning, 2001, Vol. 54(1): 93-106.
22. E.Mapedza, J.Wright, R.Fawcett. An investigation of land cover change in Mafungautsi Forest, Zimbabwe, using GIS and participatory mapping. Applied Geography, 2003, vol.23(1): 1-21.
23. E.V.Milanova, E.Yu.Lioubimtseva, P.A.Tcherkashin, L.F.Yanvareva. Land use/cover change in Russia: mapping and GIS. Land Use Policy, 1999, Vol.16(3): 153-159.
24. Easterling W. E.. Spatial Scales of Climate Information for Simulating Wheat and Maize Productivity. Agricultural and Forest Meteorology, 1998, 90: 51-63.
25. Ehrlich P., J. Holdren. Impact of Population Growth. Science, 1971, 171: 1212-1217.
26. Elijah W. Ramsey Ⅲ, Sijan K. Sapkota, Frank G. Barnes, Gene A. Nelson. Monitoring the recovery of Juncus roemerianus marsh burns with the normalized difference vegetation index and Landsat Thematic Mapper data. Wetlands Ecology and Management, 2002, 10: 85-96.
27. Felix Rembold, Stefano Carnicelli, Michele Nori, Giovanni A Ferrari. Use of aerial photographs, Landsat TM imagery and multidisciplinary field survey for land-cover change analysis in the lakes region(Ethiopia). International Journal of Applied Earth Observation and Geoinformation, 2000, Vol.2, (3-4): 181-189.
28. Florian PKressler, Klaus Tsteinnocher. Detecting land cover changes from NOAA-AVHRR data by using spectral mixture analysis. International Journal of Applied Earth Observation and Geoinformation, 1999, Vol.1(1): 21-26
29. Forman R. T. T, Godron M.. Landscape Ecology. New York: John Wiley, 1986.
30. Forman, R. T.T.. The ethics of isolation, the spread of disturbance, and landscape ecology. In M. Turner(ed.), Landscape Heterogeneity and Disturbance. Springer-verlag, New York, 1987: 213～229.
31. Forman, R. T. T.. Land Mosaics: The Ecology of Landscapes and Regions. Cambridge University Press, 1995.
32. Foster B.C.. Coefficient of variation as a measure of urban spatial attributes using Spot HRV and Landsat TM. International Journal of Remote Sensing, 1993, 14: 2403-2409.
33. Fox J., J. Krummel, S. Yarnasam, M. Ekasingh, N. Podger. Land use and landscape dynamics in northern Thailand: Assessing change in three upland watersheds. Ambio, 1995, 24: 328-334.
34. Gibson C.C., E. Ostrom, T. K. Alan. The concept of scale and the human dimensions of Global Change: A survey. Ecological Economics, 2000 Vol.32(2): 217-239.
35. Giles M. Foody, Doreen S. Boyd. Fuzzy mapping of tropical land cover along an environmental gradient from remotely sensed data with an artificial neural network. Journal of Geographical Systems, 1999, Vol.(1): 23-35
36. Gong, P., P.J. Howarth. Frequency-based contextual classification and gray-level vector reduction for land use identification. Photogrammetric Engineering and Remote Sensing, 1992,
58: 423-437.
37. Harini Nagendra., Ghate Utkarsh. Landscape ecological planning through a multi-scale characterization of pattern: studies in thewestem Ghats, south india. Environmental Monitoring and Assessment, 2003, 87: 15-233.
38. Harvey L.D.D.. Upscaling in Global Change research. Climatic Change, 2000, 44, : 225-263.
39. Hasan Ozcan, Mahmut Cetin, Kenan Diker. Monitoring and assessment of land use status by GIS. Environmental Monitoring and Assessment, 2003, 87: 33-45.
40. Hidenori Morita. An application of the land-use change model for the Japan case study area. Interim Report, IR-97-065, 1997.
41. Hubert Gulinck, MartaMu "gica, Jose" Vicentede Lucio, Jose" AntonioAtauri. A framework for comparative landscape analysis and evaluation based on land cover data, with an application in the Madrid region(Spain). Landscape and Urban Planning, 2001, Vol.55(4): 257-270.
42. J.D. Miller, S. R. Yool. Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data. Remote Sensing of Environment, 2002, Vol. 82(2-3): 481-496.
43. J. Helmschrot, W.-A. Flügel. Land use characterization and change detection analysis for hydrological model parameterization of large scale afforested areas using remote sensing. Physics and Chemistry of the Earth, Parts A/B/C, 2002, Vol. 27(9-10): 711-718.
44. J. Tapiador, J. L. Casanova. Land use mapping methodology using remote sensing for the regional planning directives in Segovia, Spain. Landscape and Urban Planning, 2003, Vol. 62(2): 103-115.
45. J. Zhang, G. M. Foody. Fully-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: statistical and neural network approaches. International Journal of Remote Sensing, 2001, Vol. 22(4): 615-628.
46. Javier Eduardo Mendoza S., Andre' s Etter R.. Multitemporal analysis(1940-1996)of land cover changes in the southwestern Bogota' highplain(Colombia). Landscape and Urban Planning, 2002, Vol. 59(3): 147-158.
47. K.P.Wittich. Some simple relationships between land-surface emissivity, greenness and the plant cover fraction for use in satellite remote-sensing: International Journal of Biometeorology, 1997, Vol. 41(2): 58-64.
48. Kates R., V. Haarman. Where the poor live: are the assumptions correct?. Environment, 1992, 34: 4-11, 25-28
49. Kevin McGarigal, Joseph Berry, David Buckley.FRAGSTATS Manual, 1995.
50. Kienast F. Analysis of historic landscape patterns with a geographic information system-a methodological outlines. Landscape Ecology, 1993, 8(2): 103-118.
51. Klaus Hubacek, Laixiang Sun. A scenario analysis of-China-& apos's land use and land cover change: incorporating biophysical information into input-output modeling. Structural Change and Economic Dynamics, 2001, Vol.12(4): 367-397.
52. Lam N., D.A. Quattrochi. On the issues of scale, resolution and fractal analysis in the mapping sciences. Professional Geographer, 1992, Vol. 44(1): 88-98.
53. Lambin E. F. Modelling and monitoring land-cover change processes in tropical region. Progress in Physical Geography, 1997, Vol. 21(3): 375-393.
54. Lambin E.E, Baulies X, Bockstael N.. Land-use-and land-cover change(LUCC)
implementation strategy. IGBP Report No.48 and HDP Report No. 10 Stockholm: IGBP, 1999.
55. Lambin E.F.. Modelling and monitoring land-cover change processes in tropical regions. Progress in Physical Geography, 1997, 21(3): 375-393.
56. Louisa J. M. Jansen, Antonio D. I. Gregorio. Parametric land cover and land-use classifications as tools for environmental change detection. Agriculture, Ecosystems and Environment, 2002, Vol. 91(1-3): 89-100.
57. Loveland T. R., Reed B. C., Brown J. F. Development of a global land cover characteristics database and IGBP discover from lkm AVHRR data. International Journal of Remote Sensing(in review), 1998.
58. M.A. Fried, D. K. McIver, J. C. F. Hodges, X. Y. Zhang, D. Muchoney, A. H. Strahler, C. E. Woodcock, S. Gopal, A. Schneider, A. Cooper, A. Baccini, F. Gao, C. Schaaf. Global land cover mapping from MODIS: algorithms and early results. Remote Sensing of Environment, 2002, Vol. 83(1-2): 287-302.
59. M. A.Friedl, C. E.Brodley. Decision Tree Classification of Land Cover from Remotely Sensed Data. Remote Sensing of Environment, 1997, Vol. 61(3): 399-409.
60. M. L. Mendonc, Santos C. Claramunt. An integrated landscape and local analysis of land cover evolution in an alluvial zone. Computers, Environment and Urban Systems, 2001, Vol. 25(6): 557-577.
61. M. Pax-Lenney, C. E. Woodcock, S. A. Macomber, S. Gopal and C. Song. Forest mapping with a generalized classifier and Landsat TM data. Remote Sensing of Environment, 2001, Vol. 77(3): 241-250.
62. Martin Herold, Keith C. Clarke. Gunter Menz. A multi-scale framework for mapping and analysis of the spatial and temporal pattern of urban growth. Proceedings of 22nd EARSEL Symposium "Geoinformation for European-wide integration, Prague, June 2002.
63. MatthiasBürgi, Monica G.Turner. Factors and Processes Shaping Land Cover and Land Cover Changes Along the Wisconsin River. Ecosystems, 2002, Vol.5(2): 0184-0201.
64. Mesev V. The use of Census data in urban image classification. Photogrammetric Engine and Remote Sensing, 1998, Vol. 64(5): 431-438.
65. O'Neill R. V., Krummel J. R., Gardner R. H., Sugihara G, Jackson B.G., Zygmunt B., Christenson S. W., Dale V. H., Graham R. L. Indices of landscape pattern. Landscape ecology, 1988, Vol. 1(3): 153～162.
66. Ostrom E., T. Dietz, N. Dolsak, P. C. Stern, S. Stonich, E. U. Weber(eds). The drama of the commons. National Academy Press, Washington D.C., 2002.
67. P. Kalivas, V. J. Kollias, G. Karantounias. A GIS for the Assessment of the Spatio-Temporal Changes of the Kotychi Lagoon, Western Peloponnese, Greece. Water Resources Management, 2003, 17: 19-36.
68. Paul Aplin, Peter M. Atkinson, Paul J. Curran. Fine Spatial Resolution Simulated Satellite Sensor Imagery for Land Cover Mapping in the United Kingdom. Remote Sensing of Environment, 1999, Vol. 68(3): 206-216.
69. Penner J. E.. Atmospheric chemistry and air quality. In Changes in Land use and land cover: A global perspective.: 175-210. Edited by W. B. Meyer and B. L. Turner. Cambridge University Press, Cambridge, 1994.
70. Peterson G. Scaling ecological dynamics: self-organization, hierarchical structure, and ecological resilience. Climatic Change, 2000, 44: 291-309.
71. R.A. Schowengerdt. Remote Sensing: Models and Methods for Image Processing, 2nd ed. New York, NY: Academic Press, 1997.
72. R. K. Gupta, S. Prasad, P. V. Krishna Rao. Evaluation of spatial upscaling algorithms for different land cover types. Advances in Space Research, 1998, Vol. 22(5).
73. R. Oetter, W. B. Cohen, M. Berterretche, T. K. Maiersperger, R. E. Kennedy. Land cover mapping in an agricultural setting using multiseasonal Thematic Mapper data. Remote Sensing of Environment, 2001, Vol. 72(2): 139-155.
74. Ranchin T., Wald L., Mangolini M.. Improving spatial resolution of remotely-sensed images by means of sensor fusion: a general solution using ARSIS methods. Donnay J. P., Bamsley M. J., Longley P. A.(eds.). Remote sensing and urban analysis, Taylor and Francis, London and New York, pp. 21-37, 2001.
75. Rapport D. J., C. Gaudet and P. Calow(eds.). Evaluating and Monitoring the Health of Large-Scale Ecosystems. Springer-Verlag, Heidelberg, 1995.
76. Ricotta, P. Corona, M. Marchetti, G. Chirici, S. Innamorati. LaDy: software for assessing local landscape diversity profiles of raster land cover maps using geographic windows. Environmental Modelling and Software, 2003, Vol.18(4): 373-378.
77. Ridd M. K.. Exploring a VIS(vegetation-impervioussurface-soit)model for urban ecosystem analysis through remote sensing: comparative anatomy for cities. International Journal of Remote Sensing, 1995, Vol. 16(12): 2165-2185.
78. Robert Walker. SOUTH FLORIDA: THE REALITY OF CHANGE AND THE PROSPECTS FOR SUSTAINABILITY Urban sprawl and natural areas encroachment: linking land cover change and economic development in the Florida Everglades. Ecological Economics, 2001, Vo. 37(3): 357-369.
79. Robin S. Reid, Russell L. Kruska, Nyawira Muthui, Andualem Taye, Sara Wotton, Cathleen J. Wilson and Woudyalew Mulatu. Land-use and land-cover dynamics in response to changes in climatic, biological and socio-political forces: the case of southwestern Ethiopia. Landscape Ecology, 2000, 15: 339-355.
80. Robinson J. B.. Modelling interactions between human and natural systems. International Social Science Journal, 1991, 43: 629-648.
81. Ross S. Lunetta, Jayantha Ediriwickrema, David M. Johnson, John G. Lyon, Alexa McKerrow. Impacts of vegetation dynamics on the identification of land-cover change in a biologically complex community in North Carolina, USA. Remote Sensing of Environment, 2002, Vol. 82(2-3): 258-270.
82. S. de Bruin. Predicting the Areal Extent of Land-Cover Types Using Classified Imagery and Geostatistics. Remote Sensing of Environment, 2000, Vol. 74(3): 387-396.
83. S. E.WALSH, P. A. SORANNO, D. T. RUTLEDGE. Lakes, Wetlands, and Streams as Predictors of Land Use/Cover Distribution. Environmental Management, 2003, Vol.31(2): 0198-0214.
84. S. Takeuchi, A. Inanaga. Scaling-Up of Land Cover Information by Using Multiple Resolution Satellite Data. Advances in Space Research, 2000, Vol. 26(7).
85. Sadler, G. J., M. J. Barnsley, S. L. Barr. Information extraction from remotely sensed images for urban land analysis. Proceeding of the 2nd European Conference on Geographical Information Systems EGIS'91, Brussels, Belgium, April, EGIS Foundation, Utrecht, pp. 955-964, 1991.
86. Sam A. Cushman, David O. Wallin. Rates and patterns of landscape change in the Central
Sikhote-alin Mountains, Russian Far East. Landscape Ecology, 2000, 15: 643-659.
87. Skinner C. N. Change in spatial characteristics of forest openings in the Klamath Mountains of north California, USA. Landscape Ecology, 1995, Vol. 10(4): 219-228.
88. Stafford Smith, J. F. Reynolds(eds). Integrated Assessment and Desertification. Dahlem University Press, Berlin, 2002.
89. Stedman-Edwards P. Root Causes of Biodiversity Loss: An Analytical Approach. World Wide Fund for Nature, Washington, D.C., 1998.
90. Tanaka S., Sugimura T.. A new frontier of remote sensing from IKONOS images. International Journal of Remote Sensing, 2001, Vol. 22(1): 1-5.
91. Todd M. Scanlon, John D. Albertson, Kelly K. Caylor, Chris A.Williams. Determining land surface fractional cover from NDVI and rainfall time series for a savanna ecosystem. Remote Sensing of Environment, 2002, Vol. 82(2-3): 376-388.
92. Turner Ⅱ, B.L., Moss R.H., Skole D.L..Relating land use and global land-cover change-A proposal for an IGBP-HDP core project. IGBP Report No.24 and HDP Report No.5. Stockholm: IGBP, 1993.
93. Turner B. L. Ⅱ. Land-use and land-cover change science/research plan. IGBP Report, 35, HDP Report, 7. IGBP, Stockholm, 1995.
94. Turner B. L. Ⅱ. Two Types of Global Environmental Change: Definitional and Spatial Scale Issues in Their Human Dimensions. Global Environmental Change, 1990, 1: 14-22.
95. Tumer M. G., Gardner R. H.. Quantitative Methods in Landscape Ecology. New York: Springer-Verlag, 1991.
96. Turner M. G. Landscape ecology-living in mosaic. In: Dodson S et al eds. Ecology. Oxford University Press.77～122.
97. W.B. Clapham Jr. Continuum-based classification of remotely sensed imagery to describe urban sprawl on a watershed scale. Remote Sensing of Environment, 2003, Vol. 86(3): 322-340.
98. W.L. Stefanov, M. S. Ramsey, P. R. Christensen. Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to add urban centers. Remote Sensing of Environment, 2001, Vol. 77(2): 173-185.
99. Witbanks T. J.. Geographic Scaling Issues in Integrated Assessments of Climate Change. Rotmans, J. and M. van Asselt(eds.)Scaling Issues in Integrated Assessment. Swets and Zeitlinger, 2002.
100. William G. Kepner, Christopher J. Watts, Curtis M. Edmonds, John K. Maingi, Stuart E. Marsh and Gonzalo Luna. A landscape approach for detecting and evaluating change in a semi-arid environment. Environmental Monitoring and Assessment, 2000, 64: 179-195
101. William L. Stefanov, Michael S.Ramsey, Philip R.Christensen. Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to add urban centers. Remote Sensing of Environment, 2001, Vol. 77(2): 173-185.
102. X. Zhan, R. A. Sohlberg, J. R. G.. Townshend, C. DiMiceli, M. L. Carroll, J. C. Eastman, M. C. Hansen, R. S. DeFries. Detection of land cover changes using MODIS 250 m data. Remote Sensing of Environment, 2002, Vol. 83(1-2): 336-350
103. Yong Du, Philippe M. Teillet, Josef Cihlar. Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection. Remote Sensing of Environment, 2002, Vol. 82(1): 123-134.
104．E．B．邓肯 A．A．尤什凯维奇著；张饴慈，刘吉江译．马尔可夫过程(定理与问题)，科学
出版社，1988．
105．摆万奇，丁贤忠．内蒙古自治区奈曼旗土地利用变化预测研究．资源科学，2003，25(2)：73～76
106．摆万奇，赵士洞．土地利用和土地覆盖变化研究模型综述．自然资源学报，1997，12(2)：169～175．
107．摆万奇．深圳市土地利用动态趋势分析．自然资源学报，2000，15(2)：112～116
108．包玉海，乌兰图雅，香宝，赵晓丽．内蒙古耕地重心移动及其驱动因子分析．1998，17(4)：47-54
109．布仁仓，王宪礼，肖笃宁．黄河三角洲景观组分判定与景观破碎化分析．应用生态学报，1999，10(3)：321～324
110．曹慧，杨浩，赵其国．长江三角洲地区土壤质量退化的类型、驱动力与对策．中国人口．资源与环境，2001，11(2)：47～48
111．陈百明，刘新卫，杨红．LUCC研究的最新进展评述．地理科学进展，2003，22(1)：22～29
112．陈百明．试论中国土地利用和土地覆被变化及其人类驱动力研究．自然资源，1997，2：31～36．
113．陈利顶，傅伯杰．黄河三角洲地区人类活动对景观结构的影响分析——以山东省东营市为例．生态学报，1996，16(4)：337～344．
114．陈述彭主编．遥感信息机理研究．科学出版社，1998．
115．董玉祥．西藏沙漠化灾害现状及其驱动力研究．自然灾害学报．2001b，10(2)：96～102
116．董玉祥．我国半干旱地区现代沙漠化驱动因素的定量辩识．中国沙漠，2001，21(4)：411～416
117．樊锦沼，张传道．应用气象卫星资料估算草场产草量方法的研究．干旱区资源与环境，1990(3)：23～27
118．冯利华，骆高远．中国热带气旋的时间活动性研究．热带地理，1999，19(2)：113-116
119．傅伯杰，陈利顶，马克明，王仰麟等．景观生态学原理及应用．科学出版社，2001．
120．傅伯杰，王仰麟．国际景观生态学的发展动态与趋势．地球科学进展，1990，(3)：23～25．
121．傅伯杰．景观多样性的类型及其生态意义．地理学报，1996，51(5)：454～462
122．傅泽强，蔡运龙，杨友孝，戴尔阜．中国粮食安全与耕地资源变化的相关分析．自然资源学报，2001，16(4)：313-319．
123．甘红，刘彦随，李宪文．区域土地利用变化与水资源利用相关分析．南京师大学报(自然科学版)，2003，26(3)：82-88．
124．高清竹，何立环，江源，王家骥．农牧交错带典型区农业与牧业用地互动关系研究．地球科学进展，2002，17(2)：209～215
125．高志强，刘纪远，庄大方．我国耕地面积重心及耕地生态背景质量的动态变化．自然资源学报，1998，13(1)：92-96
126．何春阳，史培军，陈晋，周宇宇．北京地区土地利用／覆盖变化研究．地理研究，2001，20(6)：679-687
127．黄敬峰，桑长青，冯振武．天山北坡天然草地产量遥感动态监测模式．自然资源学报，1993(1)：10～17
128．黄敬峰，王秀珍，蔡承侠，胡新博．利用NOAA／AVHRR资料监测北疆天然草地生产力．草业科学，1999，16(5)：62-69
129．黄敬峰，王秀珍，胡新博．新疆北部不同类型天然草地产草量遥感监测模型．中国草地，1999，1：7～11，18
130．黄敬峰，王秀珍，王人潮，蔡承侠，胡新博．天然草地牧草产量与气象卫星植被指数的相关分析．农业现代化研究，2000，21(1)：33-36
131．贾宝全，慈龙骏，杨晓晖，杨洁泉，潘伯荣．人工绿洲潜在景观格局及其与现实格局的比较分析．应用生态学报，2000，11(6)：912～916
132．贾宝全，慈龙骏，杨晓晖，孙林，杨洁泉．石河子莫索湾垦区绿洲景观格局变化分析．生态学报，2001，21(1)：34～40
133．江洪，张艳丽，JamesRStrittholt．干扰与生态系统演替的空间分析．生态学报，2003，23(9)：1861-1876．
134．姜琦刚，高村弘毅，后藤真太郎．中国新疆且末绿洲土地利用变化及驱动力分析．吉林大学学报(地球科学版)，2003，33(1)：83～87
135．李博，任志强，史培军等．中国北方草地畜牧业动态监测研究．北京：中国农业科技出版社，1993．1～33
136．李博，史培军，林小泉．我国温带草地草畜平衡动态监测系统的研究．草地学报，1995，3(2)：95-102．
137．李博等．中国北方草地畜牧业动态监测研究(一)．中国农业科技出版社，1993．
138．李德成，徐彬彬，石晓日．利用马氏过程模拟和预测土壤侵蚀的动态演变．环境遥感，1995，10(2)：89～96．
139．李建龙，黄敬峰，维纳汗．不同类型草地监测与估产遥感指标和光学模型建立的研究．中国草地，1996，6：6～10．
140．李建龙，蒋平，梁天刚．我国草地遥感科学发展的轨迹、内涵及展望．中国草地，1998，3：53～56
141．李建龙，蒋平，徐雨清．利用遥感技术和地理信息系统动态监测天山草地与农业资源研究．兰州大学学报(自然科学版)，1998，34(3)：110～116
142．李京．应用NOAA／AVHRR遥感资料对大面积草场进行产草量估量定算的方法研究．自然资源学报，1994，4：365．
143．李平，李秀彬，刘学军．我国现阶段土地利用变化驱动力的宏观分析．地理研究，2001，20(2)：129～138
144．李秀彬．地球系统科学的核心领域——土地利用／土地覆被变化国际研究动向[J]．地理学报，1996，51(6)：553—557
145．李秀彬．全球环境变化研究的核心领域—土地利用／土地覆被变化的国际研究动向．地理学报，1996，vol．51(6)：553-558
146．李秀彬．土地利用变化的解释．地理科学进展，2002，21(3)：195～204
147．李艳霞，陈同斌，罗维，黄启飞，吴吉夫．中国城市污泥有机质及养分含量与土地利用．生态学报，2003，23(11)：2464-2474．
148．刘德钦，刘宇，薛新玉．中国人口分布及空间相关分析．遥感信息，2002，6：2-6．
149．刘先华，陈佐忠，富久尾步等．定居放牧方式下归一化植被指数(NDVI)的空间变化特征．植物生态学报，2000，24(6)：662～666
150．钱家忠，朱学愚，吴剑锋．地下水资源评价中降水量的时间序列-马尔可夫模型．地理科学，2001，21(4)：350-353．
151．青海省农牧业区划委员会办公室，海南州农牧业区划委员会办公室，共和县农牧业区划委员会办公室．青海省共和县农牧业资源调查及区划图册．1984．
152．青海省农牧业区划委员会办公室，海南州农牧业区划委员会办公室，共和县农牧业区划委员会办公室．青海省共和县综合农牧业区划报告．1988．
153．青海省统计局．青海省统计年鉴1988．中国统计出版社，1988．10．
154．青海省统计局．青海省统计年鉴2002．中国统计出版社，2002．7．
155．全志杰．泥河沟土地利用动态的遥感研究．中国农业科学，1995，28(增刊)：131～136
156．史培军．人地系统动力学研究的现状与展望．地学前缘 1997，4(1-2)：201～211．
157．王思远，张增祥，周全斌，王长有，刘纪远．近10年中国土地利用格局及其演变．地理学报，2002，57(5)：523-530．
158．王宪礼，布仁仓，胡远满，肖笃宁．辽河三角洲湿地的景观格局分析．生态学报，1997，17(3)：317-323
159．王秀兰，包玉海．土地利用动态变化研究方法探讨．地理科学进展，1999，18(1)：81-87
160．王秀兰．基于遥感的呼伦贝尔盟农牧业土地利用变化及其对地区农业持续发展影响的研究．地理科学进展，1999，18(4)：322-329．
161．王艳荣，吕玉华．内蒙古锡林郭勒盟草原植被的光谱反射特征与牧草产量相关性的分析．植物生态学与地植物学学报，1990，3：5～9
162．邬建国．景观生态学——格局、过程、尺度与等级．北京：高等教育出版社，2000
163．徐岚，赵羿．利用马尔可夫过程预测东陵区土地利用格局变化．应用生态学报，1993，4(3)：272～277．
164．徐岚，赵羿．利用马尔可夫过程预测东陵区土地利用格局的变化．应用生态学报，1993，4(3)：272-277．
165．严登华，何岩，邓伟，王春梅．东辽河流域地表水水质空间格局演化．中国环境科学 2001，21(6)：564～568．
166．杨正礼，杨改河．中国高寒草地生产潜力与载畜量研究．资源科学，2000，22(4)：72-77．
167．岳天祥，程彤，张红旗等．景观动态及其驱动因素和效应分析自然资源，1997，6：19～26．
168．曾辉，郭庆华，刘晓东．景观格局空间分辨率效应的试验研究．北京大学学报，1998，34(6)：820～826．
169．张明．区域土地利用结构及其驱动因子的统计分析．自然资源学报，1999，14(4)：381-384．
170．中国植被编辑委员会．中国植被，第1版，科学出版社，1980
171．周炳中，赵其国，杨浩．江苏省耕地变化及其驱动机制的数理探讨．土壤学报，2003，40(5)：665-671．
172．周华锋，马克明，傅伯杰．人类活动对北京东灵山地区景观格局影响分析．自然资源学报，1999，14(2)：117～122．
173．祝卓．人口地理学．中国人民大学出版社，1991．79～80．
174．庄大方，刘纪远．中国土地利用程度的区域分异模型研究．自然资源学报，1997，12(2)：105-111．
175．邹亚荣，张增祥，周全斌，赵晓丽．中国农牧交错区土地利用变化空间格局与驱动力分析．自然资源学报，2003，18(2)：222～228