沿海防护林建设防护效益的遥感监测研究
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摘要
沿海防护林工程建设防护效益的监测与评价是进行沿海防护林森林资源经营改造的重要基础,本文以福建省漳浦县的沿海防护林建设防护效益的监测与评价为研究对象,研究主体以1988年和2003年的遥感影像数据,结合辅助数据,通过实地调查、指标选取、数据分析、模型构建、方法验证的技术环节,从沿海防护林工程建设的水土保持、防风固沙首要功能入手,从不同功能角度,分析沿海防护林工程建设前后区域水土保持、防风固沙的效益变化,在此基础上,构建沿海防护林综合防护模型,体现沿海防护林工程建设的综合防护效益；并基于遥感影像构建人为干扰指数模型,体现基于工程造林的人为干扰影响分析；从综合防护效益和人为干扰影响两个角度,共同分析、验证了沿海防护林工程建设的良好防护效益,实现了沿海防护林防护效益的空间化、具体化和定量化的综合体现,为合理的沿海防护林经营、改造、规划提供重要决策依据和技术支持。主要研究结果如下：
(1)研究参考国土资源部的一级土地利用分类系统,结合区域具体情况,确定漳浦县的土地利用分类系统：一级为耕地、水域、居民地、林地、沙地和未利用地,林地进一步划分为木麻黄、湿地松、相思树、经济林以及其他类型林地。
(2)采用OIF指数法、相关系数法和标准差等分析方法选取最佳波段,结合野外测定光谱的基础数据,对反射光谱差异较大的土地利用类型,选取适宜的光谱阈值,采用分层分类方法实现土地利用类型专题信息提取；而对于不易区分的地物类型采用监督分类方法、局部区域使用人机交互进行目视解译,实现专题信息的提取。分类结果是1988年的土地利用分类精度为91.08%,2003年的土地利用分类精度为90.63%,1988年的森林类型分类精度为85.49%,2003年的森林类型分类精度为87.94%。2008年的土地利用和森林类型利用野外实地验证,其总体分类精度为89.41%。
(3)利用相关地面辅助数据,根据中式USLE土壤侵蚀模型实现了1988、2003和2008年的漳浦县土壤侵蚀的动态监测,体现沿海防护林水土保持防护效益分析。结果表明,1988年的发生土壤侵蚀的面积最大达21.86 hm2·a,侵蚀强度最大仅为中度侵蚀并且发生面积仅为总面积的0.03%；从1988～2008年,土壤侵蚀强度和土壤侵蚀面积均在显下降趋势,在一定程度上表明,防护林建设起到积极的防护作用,促进了区域植被的恢复。
(4)通过土地利用变化、景观格局变化和植被覆盖变化综合实现区域防风固沙效益的区域定性分析。结果表明沿海防护林工程建设,较好地发挥了防风固沙的作用,区域的沙化面积不断减少,总体向耕地和林地转化,植被覆盖呈增加趋势。
(5)首次构建了基于遥感技术的沿海防护林防风固沙效益监测模型,模型回归相关系数为0.909,总体精度达77.82%。通过1988年、2003年漳浦县临海7个乡镇沙化面积的动态监测分析表明,非沙化面积从1988年43.51%提高到80.30%,而轻度、中度以上沙化面积分别由41.71%、14.78%降为18.44%、1.27%。
(6)研究利用1988和2003年的影像数据,构建了体现工程造林的人为干扰影响分析的干扰指数模型,制作干扰指数图,并以乡镇为单元,分析沿海防护林人为干扰影响的正效益与土壤侵蚀、植被盖度和防风固沙效益间的相关性,结果表明,构建的人为干扰指数值的大小与土壤侵蚀、植被盖度和防风固沙效益的正效益发展有着良好相关性,较好地体现了防护林工程建设人为干扰影响的正效益,从基于人为干扰的正效应角度进一步体现沿海防护林工程建设的良好效益。
(7)选定土壤侵蚀模数、植被盖度、裸沙占地面积比、森林生产力、国内生产总值(GDP)作为沿海防护林防护综合效益的评价因子,采用综合指数法,结果表明：在1988年,漳浦县防护效益等级在较好以上的比例为50.48%,而2003年达到了72.59%。
(8)通过干扰指数值和综合效益指数值各自与土壤侵蚀间的二项式方程分析、结合这两个指标以乡镇为单元的均值和标准差,综合确定漳浦县干扰指数体现沿海防护林防护正效应的阈值为1.5812,综合效益指数比值体现沿海防护林防护正效应的阈值为0.89575。并依据确定的二者阈值,提取漳浦县各指数图体现沿海防护林防护正效应的专题信息,叠加分析表明,漳浦县二者体现正效应的重叠面积为149327 hm2,达到79.1436%,具有较高的一致性。从而从综合防护效益和人为干扰影响两个角度,共同分析、验证了沿海防护林工程建设的良好防护效益。
The monitoring and evaluation of coastal shelterbelt protection effective is an important foundation for coastal shelterbelt forest resource management and reform. In this paper, the research object is the monitoring and evaluation of effectiveness of coastal protection forest construction. The paper use1988 and 2003 remote sensing data, combined with ancillary data, through field surveys, index selection, data analysis, modeling, and method validation to analyze the effectiveness channge of the regional water and soil conservation before and after the coastal shelterbelt construction from different functions. And on this basis, the coastal protection forest protection model was constructed to reflect the comprehensive benefit of coastal forest protected construction. Building model of human interference through the remote sensing index to reflect the impact of human afforestation. From two aspects of comprehensive protection and impact of human disturbance to analyze and verify the good benefit of the coastal shelterbelt protected construction and achieve the space-based, specific and quantitative of protected effectiveness of coastal protection forest. It provide an important basis and technical support for reasonable coastal shelter forest management, transformation and planning. The main conclusions are as follows:
(1) Referenced to land use classification system of ministry of land resources and combined with the regional situation, the land use classification systems of Zhuangpu county was determined:class one was divided into the land, water, residential areas, woodland, sand and unused land, forest land was further divided into casuarina, slash pine, acacia economic forest and other types of woodland.
(2) Based on the analysis approach such as OIF index, correlation coefficient and standard deviation, selected the best band and combined with the basis for field determination of spectral data, using hierarchical classification to extract land use thematic information by the appropriate threshold spectrum to those reflectance difference for the larger land-use type, while using supervised classification to those dfficult to distinguish and human-computer interaction for visual interpretation in local area. Classification result was the 1988 land use classification accuracy of 91.08% in 2003, the land use classification accuracy of 90.63%, in1988, the forest type classification accuracy of 85.49% in 2003, the forest type classification accuracy of 87.94%. using field validation to verify 2008 land use and forest types, the overall classification accuracy of 89.41%.
(3) Using the data related to ground support and according to Chinese USLE soil erosion model, it implemented the dynamic monitoring of soil erosion of Zhangpu in 1988,2003 and 2008 and reflected the analysis of soil and water conservation the protection benefit of coastal protection forest. The results showed that in 1988 the incidence of soil erosion in the area of up to 21.86 hm2·a, the maximum intensity was only moderate erosion erosion and the area was only 0.03% of total area.
(4) Through the land use change, landscape pattern channges and channges in vegetation cover, comprehensive qualitative analysis of regional protection fixing benefits was achieved. The results showed that the coastal shelterbelt played the role of sand-fixing better, desertified area of the region continueis decreasing, the overall conversion to farmland and forest land and vegetation cover was increased.
(5) It was the first time to build the model of monitoring the benefits of coastal protection forest based on emote sensing technology, the regression correlation coefficient was 0.909 and the overall accuracy was 77.82%.Dynamic monitoring of desertification of the 7 seaside villages and towns in Zhangpu county showed that non-desertified area increased from 43.51% in 1988 to 80.30%, while mild, moderate or sandy area were reduced from 41.71% and 14.78% to 18.44% and 1.27% respectively.
(6) The paper used 1988 and 2003 image data to build the interference index model based on afforestation of the impact of human disturbance and made interference index map. By used the township as a unit to analysze the correlation of positive effective of impact of human disturbance of coastal protection forest and soil erosion, vegetation cover and sand-fixing effectiveness. The results showed that it had a good correlation of the overall value of the index of human disturbance and soil erosion, vegetation cover and sand-fixing positive efficiency.
(7) The paper selected soil erosion modulus, vegetation cover, bare sand area ratio, forest productivity, gross domestic product (GDP) as the assessment factors of comprehensive protection benefits of coastal protection forest and used the integrated index, the results show that:the protective effect of Zhangpu county level and above in a better ratio of 50.48% in 1988 and then reached 72.59% in 2003.
(8) Through the binomial equations of interference index value and the overall efficiency index value own and soil erosion and combined with mean and standard deviation of this two indicators, integrated to determine the threshold value of interference index which reflected the positive effects of coastal protection forest protection in Zhangpu county was 1.5812 and the overall efficiency index ratio was 0.89575.And then according to the threshold set the two index, the project information of Zhangpu county index map which reflected the positive effect of the coastal protection forest protection was extracted. The results showed that overlapping area between them was 149327 hm2, accounting for 79.1436%, with high consistency. Finally the paper analysis and verify the good benefit of the construction of coastal shelterbelt protection from two aspects of comprehensive protection and Impact of human disturbance.
(1)研究参考国土资源部的一级土地利用分类系统,结合区域具体情况,确定漳浦县的土地利用分类系统：一级为耕地、水域、居民地、林地、沙地和未利用地,林地进一步划分为木麻黄、湿地松、相思树、经济林以及其他类型林地。
(2)采用OIF指数法、相关系数法和标准差等分析方法选取最佳波段,结合野外测定光谱的基础数据,对反射光谱差异较大的土地利用类型,选取适宜的光谱阈值,采用分层分类方法实现土地利用类型专题信息提取；而对于不易区分的地物类型采用监督分类方法、局部区域使用人机交互进行目视解译,实现专题信息的提取。分类结果是1988年的土地利用分类精度为91.08%,2003年的土地利用分类精度为90.63%,1988年的森林类型分类精度为85.49%,2003年的森林类型分类精度为87.94%。2008年的土地利用和森林类型利用野外实地验证,其总体分类精度为89.41%。
(3)利用相关地面辅助数据,根据中式USLE土壤侵蚀模型实现了1988、2003和2008年的漳浦县土壤侵蚀的动态监测,体现沿海防护林水土保持防护效益分析。结果表明,1988年的发生土壤侵蚀的面积最大达21.86 hm2·a,侵蚀强度最大仅为中度侵蚀并且发生面积仅为总面积的0.03%；从1988～2008年,土壤侵蚀强度和土壤侵蚀面积均在显下降趋势,在一定程度上表明,防护林建设起到积极的防护作用,促进了区域植被的恢复。
(4)通过土地利用变化、景观格局变化和植被覆盖变化综合实现区域防风固沙效益的区域定性分析。结果表明沿海防护林工程建设,较好地发挥了防风固沙的作用,区域的沙化面积不断减少,总体向耕地和林地转化,植被覆盖呈增加趋势。
(5)首次构建了基于遥感技术的沿海防护林防风固沙效益监测模型,模型回归相关系数为0.909,总体精度达77.82%。通过1988年、2003年漳浦县临海7个乡镇沙化面积的动态监测分析表明,非沙化面积从1988年43.51%提高到80.30%,而轻度、中度以上沙化面积分别由41.71%、14.78%降为18.44%、1.27%。
(6)研究利用1988和2003年的影像数据,构建了体现工程造林的人为干扰影响分析的干扰指数模型,制作干扰指数图,并以乡镇为单元,分析沿海防护林人为干扰影响的正效益与土壤侵蚀、植被盖度和防风固沙效益间的相关性,结果表明,构建的人为干扰指数值的大小与土壤侵蚀、植被盖度和防风固沙效益的正效益发展有着良好相关性,较好地体现了防护林工程建设人为干扰影响的正效益,从基于人为干扰的正效应角度进一步体现沿海防护林工程建设的良好效益。
(7)选定土壤侵蚀模数、植被盖度、裸沙占地面积比、森林生产力、国内生产总值(GDP)作为沿海防护林防护综合效益的评价因子,采用综合指数法,结果表明：在1988年,漳浦县防护效益等级在较好以上的比例为50.48%,而2003年达到了72.59%。
(8)通过干扰指数值和综合效益指数值各自与土壤侵蚀间的二项式方程分析、结合这两个指标以乡镇为单元的均值和标准差,综合确定漳浦县干扰指数体现沿海防护林防护正效应的阈值为1.5812,综合效益指数比值体现沿海防护林防护正效应的阈值为0.89575。并依据确定的二者阈值,提取漳浦县各指数图体现沿海防护林防护正效应的专题信息,叠加分析表明,漳浦县二者体现正效应的重叠面积为149327 hm2,达到79.1436%,具有较高的一致性。从而从综合防护效益和人为干扰影响两个角度,共同分析、验证了沿海防护林工程建设的良好防护效益。
The monitoring and evaluation of coastal shelterbelt protection effective is an important foundation for coastal shelterbelt forest resource management and reform. In this paper, the research object is the monitoring and evaluation of effectiveness of coastal protection forest construction. The paper use1988 and 2003 remote sensing data, combined with ancillary data, through field surveys, index selection, data analysis, modeling, and method validation to analyze the effectiveness channge of the regional water and soil conservation before and after the coastal shelterbelt construction from different functions. And on this basis, the coastal protection forest protection model was constructed to reflect the comprehensive benefit of coastal forest protected construction. Building model of human interference through the remote sensing index to reflect the impact of human afforestation. From two aspects of comprehensive protection and impact of human disturbance to analyze and verify the good benefit of the coastal shelterbelt protected construction and achieve the space-based, specific and quantitative of protected effectiveness of coastal protection forest. It provide an important basis and technical support for reasonable coastal shelter forest management, transformation and planning. The main conclusions are as follows:
(1) Referenced to land use classification system of ministry of land resources and combined with the regional situation, the land use classification systems of Zhuangpu county was determined:class one was divided into the land, water, residential areas, woodland, sand and unused land, forest land was further divided into casuarina, slash pine, acacia economic forest and other types of woodland.
(2) Based on the analysis approach such as OIF index, correlation coefficient and standard deviation, selected the best band and combined with the basis for field determination of spectral data, using hierarchical classification to extract land use thematic information by the appropriate threshold spectrum to those reflectance difference for the larger land-use type, while using supervised classification to those dfficult to distinguish and human-computer interaction for visual interpretation in local area. Classification result was the 1988 land use classification accuracy of 91.08% in 2003, the land use classification accuracy of 90.63%, in1988, the forest type classification accuracy of 85.49% in 2003, the forest type classification accuracy of 87.94%. using field validation to verify 2008 land use and forest types, the overall classification accuracy of 89.41%.
(3) Using the data related to ground support and according to Chinese USLE soil erosion model, it implemented the dynamic monitoring of soil erosion of Zhangpu in 1988,2003 and 2008 and reflected the analysis of soil and water conservation the protection benefit of coastal protection forest. The results showed that in 1988 the incidence of soil erosion in the area of up to 21.86 hm2·a, the maximum intensity was only moderate erosion erosion and the area was only 0.03% of total area.
(4) Through the land use change, landscape pattern channges and channges in vegetation cover, comprehensive qualitative analysis of regional protection fixing benefits was achieved. The results showed that the coastal shelterbelt played the role of sand-fixing better, desertified area of the region continueis decreasing, the overall conversion to farmland and forest land and vegetation cover was increased.
(5) It was the first time to build the model of monitoring the benefits of coastal protection forest based on emote sensing technology, the regression correlation coefficient was 0.909 and the overall accuracy was 77.82%.Dynamic monitoring of desertification of the 7 seaside villages and towns in Zhangpu county showed that non-desertified area increased from 43.51% in 1988 to 80.30%, while mild, moderate or sandy area were reduced from 41.71% and 14.78% to 18.44% and 1.27% respectively.
(6) The paper used 1988 and 2003 image data to build the interference index model based on afforestation of the impact of human disturbance and made interference index map. By used the township as a unit to analysze the correlation of positive effective of impact of human disturbance of coastal protection forest and soil erosion, vegetation cover and sand-fixing effectiveness. The results showed that it had a good correlation of the overall value of the index of human disturbance and soil erosion, vegetation cover and sand-fixing positive efficiency.
(7) The paper selected soil erosion modulus, vegetation cover, bare sand area ratio, forest productivity, gross domestic product (GDP) as the assessment factors of comprehensive protection benefits of coastal protection forest and used the integrated index, the results show that:the protective effect of Zhangpu county level and above in a better ratio of 50.48% in 1988 and then reached 72.59% in 2003.
(8) Through the binomial equations of interference index value and the overall efficiency index value own and soil erosion and combined with mean and standard deviation of this two indicators, integrated to determine the threshold value of interference index which reflected the positive effects of coastal protection forest protection in Zhangpu county was 1.5812 and the overall efficiency index ratio was 0.89575.And then according to the threshold set the two index, the project information of Zhangpu county index map which reflected the positive effect of the coastal protection forest protection was extracted. The results showed that overlapping area between them was 149327 hm2, accounting for 79.1436%, with high consistency. Finally the paper analysis and verify the good benefit of the construction of coastal shelterbelt protection from two aspects of comprehensive protection and Impact of human disturbance.
引文
[1]Alferdo D. Satellite Remote Sensing Analysis to Monitor Desertification Processes in the Croprangeland Boundary ofArgentina [J].Journal of Arid Environments,2002,52:121～133.
[2]Anatoly A Gitelson, Yoram J Kaufman, Robert Stark, et al. Novel algorithms for remote estimation of vegetation fraction [J]. Remote Sensing of Environment,2002,80 (1):76～87
[3]Arturo Ruiz-Luna, Cesar A, Berlanga-Robles. Land use, land cover changes and coastal lagoon surface reduction associated with urban growth in northwest Mexico[J]. Landscape Ecology,2003,18:159～171
[4]Chepil W S, et al. Climatic factor for estimating wind erodibility fields [J]. Journal of Soil and Water Conservation,1962,17(4):162-165.
[5]De Roo P J, Offermans R J E, Cremers N H.LISEM:a Single-event physically based hydrological and soil erosion model for drainagebasins. II:sensitivity analysis, validation and application [J].Hydrological Processes,1996,10:1119-1126
[6]Eimern, J.Van etal,1964, Windbreaks and shelterbelts[M], WMO Technical note no.59, Geneva, Switzenland
[7]Erin J Nelson,Derek B Booth.Sediment sources in an urbanizing,mixed land-use watershed[J].Journal of Hydrology,2002,264(1～4):51～68
[8]Hall B, Motzkin G, David R. Three hundred years of forestand land-use change in Massachusetts, USA[J].Journal of Biogeography,2002,29:1319～1335
[9]http://tieba.baidu.com/f?kz=106363294
[10]http://www.fujian.gov.cn/bmdd/sxgk/zz/200804/t20080409_64634.htm
[11]http://www.xzqh.org/html/fj/0922.html
[12]http://zhidao.baidu.com/question/35153266.html?si=l
[13]J M Garcia-Ruiz,T Lasanta,C Gonzalez,et al.Sedimentsources during the traditional land-use system in the Spanish Pyrenees[J].Physics and Chemistry of the Earth,1997,22(3-4):351～354
[14]Jaejoon L.Consensual and hierarchical classification of remotely sensed multispectral images [J]. Transaction on Geoscience and Remote Sensing,2007,45 (9):2953～2963
[15]Jagdish Krishnaswamy,Patrick N Halpin,Daniel DRichter.Dynamics of sediment discharge in relation tolanduse and hydroclimatology in a humid tropical watershed in Costa Rica[J].Journal of Hydrology, 2001,253(1～4):91～109.
[16]Jordan G,van Rompaey A,Szilassi P,et al.Historical landuse changes and their impact on sediment fluxes in theBalaton Basin(Hungary)[J].Agriculture,Ecosystems&Environment,2005,108(2):119～133
[17]K M Turnage, et al. Comparison of soil erosion and deposit ion rates using gradiocesium, RU SL E, and buried soil indo lines in East Tennessee [J]. Environmental Geology,1997,29(7):1～10
[18]Kan fistikoglu, Nilgun B Harmancioglu.Integrate ion of GIS with USLE in An assessments of Soil Erosion [J].Water Resources Management,2002,(16):447-467
[19]Kanellopoulos I, Wilkinson G G. Strategies and best practice for neural networks image classification [J]. International Journal of Remote Sensing,1997,18(4):711～725
[20]LAI R.可蚀性和侵蚀性[M]／／水土保持学会.黄河水利委员会宣传出版中心译,土壤侵蚀研究方法.北京：科学出版社,1991：137～146
[21]Liu B Y, Nearing M A, Risse L M. Slope gradient effects on soil loss for steep slopes [J].Transactions of the ASAE,1994,37:1835～1840
[22]Lucas R, Rowlands A, Brown A, et al. Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping[J].ISPRS Journal of Photogrammetry & Remote Sensing, 2007,62(3):165～185
[23]Mccusker B. Land use and cover change as an indicator of transformation on recently redistributed farms in Limpopo Province [J], South Africa. Human Ecology,2004,32(1):49～75.
[24]Miller, D. R. ETAL. Microclimate modification with shelterbelts [J]. Soil and Water Cons.,1974, 29(1):41～44
[25]Mota G L, Feitosa R Q, Coutinho H L,et al. Multitemporal fuzzy classification model based on class transition possibilities[J] ISPRS Journal of Photogrammetry & Remote Sensing,2007,62(3):186～200
[26]Nearing M A. A single continuous function for slope steepness influence on soil loss [J]. Soil Science Society of America Journal,1997,61(3):917-919
[27]Norman, W.B. Shelterbelts and windbracks in the Great Plains [J]. J. For.,1989,87(4).32～36.
[28]Pal M, Mather P M. Support vector machines for classification in remote sensing[J].International Journal of Remote Sensing,2005,26(5):1007～1011
[29]Peterson DL, ParkerVT. Ecological Scale:Theory and Application [M]. New York:Columbia University Press,1998:429～457
[30]Renard K G, et al. RUSLE revisited status and the future [J]. Soil and Water Conservation,1994,49(3): 213-220
[31]Renard K G, Foster G R, Weesies G A, et al. Predicting soil erosion by water:A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE)[M]. Handbook Department of Agriculture. Washington D. C.1997
[32]Renard K G. RUSLE-A guide to conservation planning with the revised universal soil loss equation. USDA Agricultural Handbook No.703[M]. Washington D C:USDA,1995.
[33]Skidmore E L wind erosion climatic erosivity [J]. climate change,1986,9(12):195～208
[34]Sollberg S H A, Toxt T, Jain K A. A markov random field model for classification of multi-source satellite imagery [J].IEEE Transaction on Geoscience and Remote Sensing,1999,34(1):100～113
[35]TimoTokola, SatuLfman, and AnttiErkkil. Relative calibration of Multitemporal Landsat Data for Forest Cover Change Detection [J]. Remote Sens. Envir,1999(68):1～11.
[36]Wallin D O, Swanson F J, Mark sB. Landscape pat tern response to changes in pat tern generates ion rules21and2use legacies in forestry [J]. Ecologic Lapp licit ion,1994,(4):569～580
[37]Wilkinson G G. Results and implications of a study of fifteen years of satellite image classification experiments[J].Transaction on Geoscience and Remote Sensing,2005,43 (3):433～439
[38]Wischmeier W H,Smith D D.Rainfall energy and its relationship to soil loss[J].Transactions American Geophysical Union,1958,39:285-291
[39]Wischmeier W H. A soil erodibility monograph farmland and const ruction sites [J]. Soil and Water Conservation,1971,26:189-193
[40]Wischmele W H. A rainfall erosion Index for universal soil loss equation [J]. Soil Science Proceedings.1959,23(3):246～249.
[41]Wishchmeier W H, smith D D. Predicting rainfall erosion losses:a guide to conservation planning [M]. Washington D. C; USDA, ARS, Agricultural Handbook,1978:537
[42]Zhao G X,Lin G,Fletcher J J,et al.Cultivated landchanges and their driving forces:A satellite remote sensing analysis in the Yellow River Delta[J],China.Pedosphere,2004,14(1):93～102
[43]“湘中丘陵洞庭湖水系生态经济型防护林体系建设技术研究”专题组,湘中丘陵洞庭湖水系生态经济型防护林体系建设技术研究(专题报告)[R],1996
[44]卜兆宏,卜宇行,陈炳贵,等.用定量遥感方法监测UNDP试区小流域水土流失研究[J].水科学进展,1999,(1).31-36
[45]卜兆宏,董勤瑞,周伏建,张立文.降雨侵蚀力因子新算法的初步研究.土壤学报.1992,29(4)：408～418
[46]卜兆宏,李全英.土壤可蚀性(K)图编制方法的初步研究.遥感技术与应用.1994,9(4)：22～27
[47]卜兆宏,刘绍清.土壤流失量及其参数实测的新方法.土壤学报.1995,32(2)：10～20
[48]卜兆宏,孙金庄,董勤瑞,等.应用水土流失定量遥感方法监测山东全省山丘区的研究[J].土壤学报,1999,(1).1-7
[49]卜兆宏,孙金庄,周伏建等.水土流失定量遥感方法及其应用的研究.土壤学报.1997,34(3)：235～245
[50]卜兆宏,唐万龙,席承藩,等.水土流失定量遥感方法应用与研究的新进展[J].世界科技研究与发展,2000,(S1).64-67
[51]卜兆宏,唐万龙,杨林章,等.水土流失定量遥感方法新进展及其在太湖流域的应用[J].土壤学报,2003,(1).1-8
[52]卜兆宏,唐万龙.像元坡度新算法的初步研究.遥感技术与应用,1993,8(1)：1～6
[53]卜兆宏,赵宏夫,刘绍清等.用于土壤流失量遥感监测的植被因子算法的初步研究.遥感技术与应用.1993,8(4)：16～22
[54]曹新孙.农田防护林国外研究现状(二)[C],中国科学院林业土壤研究所集刊,第五集,1981
[55]曹新孙.农田防护林国外研究现状(一)[C],中国科学院林业土壤研究所集刊,第五集,1981
[56]陈晋,陈云浩,何春阳,等.基于土地覆盖分类的植被覆盖率估算亚像元模型与应用[J].遥感学报,2001,5(6)：416～422
[57]陈述彭,童庆禧,郭华东.遥感信息机理研究[M].北京：科学出版社,1998,：345～349
[58]陈正宜.晋陕蒙接壤地区脆弱生态系统遥感监测与管理研究[M]／北京：宇航出版社,1994：24～26
[59]成军锋,贾宝全,赵秀海,等.干旱半干旱地区植被覆盖度的动态变化分析——以毛乌素沙漠南部为例[J].干旱区资源与环境,2009,(12)：72～76
[60]程天文,农田蒸发与蒸发力的测定及其计算方法[A],地理集刊第12号[C].北京：科学出版社,1980
[61]川口武雄(方华荣译).森林的水土保持机能(Ⅰ,Ⅱ,Ⅲ)[J].水利科学,1988,185.54～72
[62]戴昌达.TM图像的光谱信息特征与最佳波段组合[J].环境遥感,1989,4(4)：282～29
[63]党安荣,王晓栋,陈晓峰等..ERDAS IMAGINE遥感图像处理方法[M],北京：清华大学出版社,2003：187
[64]丁艳梅,张继贤,王坚,等.基于TM数据的植被覆盖度反演[J].测绘科学,2006,36(1)：43～45
[65]方纲清,阮伏水,吴雄海,等.福建省主要土壤可蚀性特征初探[J].福建水土保持,1997(2)：19～23
[66]冯恩国,李淑香.居民地信息提取的最佳假彩色合成方法——以开封市区为例[J].平顶山学院学报,2006,21(2)：91～94.
[67]冯露,岳德鹏,郭祥.植被指数的应用研究综述[J].林业调查规划,2009,(2)：48～52
[68]冯石,马友鑫,刘文俊,等.城市化过程中昆明周边景观格局特征分析[J].云南大学学报(自然科学版),2009,(S1).338～343
[69]傅伯杰,陈利顶,马克明,等.景观生态学原理与应用[M].北京：科技出版社,2000
[70]高文韬,丁伟,李胜.长白山林区天然过伐林中蒙古栎适生立地研究[J].北华大学学报(自然科学版),2000,1(1)：77～81
[71]郭志民,陈永宝,陈志伟.土壤可蚀性特征及其K值图制作研究[J].山西水土保持科技,2002(1)：15-17.
[72]郭忠升.水土保持植被建设中的三个盖度：潜势盖度、临界盖度和有效盖度[J].中国水土保持,2004(4)：30-31
[73]洪伟,吴承祯.Krige方法在我国降雨侵蚀力地理分布规律研究中的应用[J].土壤侵蚀与水土保持学报,1997,3(1)：91～96
[74]胡召玲,李志江,杜培军.分层信息提取法在县域土地利用／覆被遥感中的应用[J].地理研究,2009,28(2)：409～418
[75]黄炎和,卢程隆,郑添发,等.闽东南降雨侵蚀力指标R值的研究[J].水土保持学报,1993,6(4)：1～5
[76]回良玉.在海南省沿海防护林建设调研时的批示[J].林业科学,2005,(07B)：4-9.
[77]季小妹,陈田,郑芳.半城市化地区生态环境研究进展[J].生态环境学报,2009,(4)：1579-1586
[78]江东.人文要素空间化研究进展[J].地理学报,2003,58(1)：25～33
[79]姜小三,潘剑君,杨林章,等.土壤可蚀性K值的计算和K值图的制作方法研究——以南京市方便水库小流域为例[J].土壤.2004,36(2)：177-180
[80]李栋梁.基于TM影像的水系信息提取及变化制图研究[D].南京,河海大学,2006
[81]李际平,陈端吕,袁晓红,等.人类干扰对森林景观类型相关性的影响研究[J].中南林业科技大学学报,2009,(5)：39～43
[82]李苗苗,吴炳方,颜长珍,等.密云水库上游植被覆盖度的遥感估算[J].资源科学,2004,26(4)：153～158
[83]李蓉,李俊祥,李铖,秦海,徐明策,张挺,.快速城市化阶段上海海岸带景观格局的时空动态[J].生态学杂志,2009,(11)：2353～2359
[84]李亚云,杨秀春,朱晓华,等.遥感技术在中国土地荒漠化监测中的应用进展[J].地理科学进展,2009,(1)：55～62
[85]刘宝元,谢云,张科利.土壤侵蚀预报模型[M].北京：中国科学技术出版社,2001
[86]刘纪元.中国资源环境遥感宏观调查与动态研究[M].北京：中国科学技术出版社,1996,158～188,276～281
[87]刘建波,戴昌达.TM图像在大型水库库情监测管理中的应用[J].环境遥感,1996,11(1)：53～58
[88]刘建平,赵时英.高光谱遥感数据解译的最佳波段选择方法研究[J].中国科学院研究生院学报,1999,16(2)：153～161
[89]刘健,余坤勇,亓兴兰,等.基于3S技术生态公益林空间格局优化配置技术模拟研究[J].北京林业大学学报,2009,(S2)：78-85
[90]刘健.基于3S技术闽江流域生态公益林体系高效空间配置研究[D].北京林业大学.2006.
[91]刘世荣,温远光等主编.中国森林生态系统水文生态功能规律[M],中国林业出版社,1996
[92]刘韬,彭明春,王崇云,等.基于可视域分析的景观生态恢复[J].云南大学学报(自然科学版),2009,(S 1)：344～349
[93]刘小平,黎夏,陈逸敏,等.景观扩张指数及其在城市扩展分析中的应用[J].地理学报,2009,(12).1430～1438
[94]刘燕,刘康.水土流失敏感性与土壤类型格局相关性分析——以陕北黄土高原为例[J].水土保持通报,2009,(5)：94～97,122
[95]刘志丽,陈曦.基于ERDAS IMAGING软件的TM影像几何精校正方法初探[J].干旱区地理,2001,24(4)：353～358
[96]卢敬华,陈伟.植被覆盖与土壤水分的动力学模型[J].成都气象学院学报,1998,46(3)：209～216.
[97]路京选,曲伟,付俊娥.国内外干旱遥感监测技术发展动态综述[J].中国水利水电科学研究院学报,2009,(2)：265～271
[98]罗为检,王克林,刘明.土地利用及其格局变化的环境生态效应研究进展[M].中国生态农业学报,2003,11(2)：150～152
[99]罗伟祥,白立强,宋西德,等.不同覆盖度林地和草地的径流量与冲刷量[J].水土保持学报,1990,4(1)：30-35
[100]马超飞,马建文,布和敖斯尔.USLE模型中植被覆盖因子的遥感数据定量估算[J].水土保持通报,2001,21(4)：6-9.
[101]马克明,傅伯杰.北京东灵山地区景观格局及破碎化评价[J].植物生态学报,2000,24(3)：320～326
[102]慕长龙.长江中上游防护林体系综合效益的计量与评价[J],四川林业科技,2001,22(1)：15～23
[103]年波,杨士剑,王金亮.植被遥感信息提取的最佳波段选择——以云岭中部山区为例[J].云南地理环境研究,2004,16(2)：18～21
[104]欧立业,何忠焕,马海州,等.基于知识的分层综合分类法在土地利用／土地覆盖遥感信息提取中的应用[J].测绘科学,2008,(1)：173～175
[105]欧维新,杨桂山,李恒鹏等.苏北盐城海岸带景观格局时空变化及驱动力分析.地理科学,2004,24(5)：610～615
[106]漆良华,张旭东,周金星,等.湘西北侵蚀小流域生态恢复适宜度与景观格局特征[J].山地学报,2009,(5)：524～530
[107]秦伟,朱清科,张学霞,等.植被覆盖度及其测算方法研究进展[J].西北农林科技大学学报(自然科学版),2006,(9).164-170
[108]史培军,陈晋.深圳市土地利用变化机制分析[J].地理学报,2000,55(2)：151～160
[109]孙立达,朱金兆主编,水土保持林体系综合效益研究与评价[M],中国科学技术出版社,1995
[110]孙晓娟.基于“3s”技术的区域林业生态工程空间配置的研究[D].2003,东北林业大学硕士学位论文,2--6
[111]田静,阎雨,陈圣波.植被覆盖率的遥感研究进展[J].国土资源遥感,2004,(1)：1-5
[112]王爱娟,章文波.林冠截留降雨研究综述[J].水土保持研究,2009,(4)：55～59
[113]王冬,赵同林,.基于3S技术的湿地景观格局研究方法进展[J].信息系统工程,2009,(10)：72～75
[114]王繁,周斌,蒋钏.浙江沿海地区近十年土地利用／覆盖变化遥感监测研究.科技通报,2007,23(3)：332～336.
[115]王礼先,解明曙主编.山地防护林水土保持水文生态经济效益及其信息系统[M],中国林业出版社,1997
[116]王万中,焦菊英,郝小品,等.中国降雨侵蚀力R值的计算与分布(Ⅰ)[J].水土保持学报,1995,9(4)：5～18
[117]王万中,焦菊英.中国的土壤侵蚀因子定量评价研究[J].水土保持通报,1996,16(5)：1～20
[118]王万忠,焦菊英,郝小品,等.中国降雨侵蚀力R值的计算与分布(Ⅱ)[J].土壤侵蚀与水土保持学报,1996,2(1)：29～39
[119]魏伟,赵军,王旭峰,.GIS、RS支持下的石羊河流域景观利用优化研究[J].地理科学,2009,(5).750～754
[120]邬建国编著.景观生态学一格局、过程、尺度与等级[M].北京：高等教育出版社2001
[121]吴浩,孙钰蓉,崔巍,等.基于景观指数的武汉市轨道交通沿线土地利用变化研究[J].安徽农业科学,2009,(31)：15602～15604
[122]伍育鹏,谢云,章文波.国内外降雨蚀力简易计算方法的比较[J].水土保持学报,2001,15(3)：31～34
[123]武文波,陈静.基于ETM-+的遥感影像信息提取研究[J].甘肃农业大学学报,2008,(5)：142～146
[124]席武俊,王金亮,王学良,等.香格里拉县土地利用／土地覆被景观格局动态分析[J].楚雄师范学院学报,2009,(9)：79～85
[125]向天梁,汪小钦,周小成,等.基于分层分析的ASTER影像土地利用／覆盖遥感监测研究[J].遥感技术与应用,2006,21(6)：527～531
[126]谢云,章文波,刘宝云.用日雨量和日雨强计算降雨侵蚀力[J].水土保持通报,2001,21(6)：53～56
[127]徐孝庆主编.森林综合效益计量评价[M],中国林业出版社,1992
[]28]杨存建,许美.遥感信息机理的水体提取方法的探讨[J].地理研究,1998,17(SO)：86-89
[129]杨华庭.近十年来的海洋灾害与减灾[J].海洋预报,2002,19(1)：2～7
[130]杨树文,薛重生.航片二次几何校正的应用研究[J].遥感技术与应用,2002,17(3)：154～157
[131]姚坤,师庆东,逢淑女,等.遥感反演土壤湿度综述[J].楚雄师范学院学报,2008,(6)：89～92
[132]游晓斌,游先祥,相莹莹.混合像元及混合像元分析[J].北京林业大学学报.2003,12(s1)：28～32
[133]于君明,王世新,周艺,等.植被水分遥感监测研究综述[J].遥感信息,2008,(2)：97～102
[134]余坤勇,林芳,刘健,等.基于RS的闽江流域马尾松林分蓄积量估测模型研究[J].福建林业科技,2006,33(1)：16～20.
[135]袁金国.森林植被遥感分类研究[J].河北师范大学学报(自然科学版),1999,(2)：274～277
[136]岳天祥,程彤.景观动态及其驱动因素和效应分析[J].自然资源,1997,6：19-26
[137]曾祥坤,王仰麟,李贵才.城市水土流失的景观生态学研究[J].水土保持研究,2009,(5)：25～30
[138]张光灿.树冠截留降雨模型研究进展及其述评[J],南京林业大学学报,2000,24(1)64～68
[139]张光辉.土壤侵蚀模型研究现状与展望[J].水科学进展,2002,13(3)：389～396
[140]张海霞,卞正富.遥感影像植被信息提取方法研究及思考[J].地理空间信息,2007,(6)：65～67
[141]张金池,李海东,林杰,等.基于小流域尺度的土壤可蚀性K值空间变异[J].生态学报,2008,28(5)：2199～2206
[142]张娟.关于卫星影像多项式法纠正中若干问题的分析[J].成果与方法,2004,20(2)：67～69
[143]张黎明.我国南方不同类型土壤可蚀性K值及相关因子研究[D].海口：华南热带农业大学,2005
[144]张丽苏,吴嘉平.分层分区分景相结合的区域土地利用／覆盖分类方法——以浙江钱塘江流域分类为例[J].国土资源遥感,2007,(3)：74～77,81
[145]张清春,刘宝元,翟刚.植被与水土流失研究综述[J].水土保持研究,2002,(4)：96～101
[146]张志东,臧润国,.海南岛霸王岭热带天然林景观格局与动态[J].植物生态学报,2009,(6)：1034～1043
[147]赵萍,傅云飞,郑刘根.基于分类回归树分析的遥感影像土地利用／覆被分类研究[J].遥感学报,2005,9(6)：708～716
[148]郑荣宝,庄剑顺,张金前.广州市土地利用与NDVI变化的关联分析.国土资源遥感,2008,2：102～108
[149]周成虎,骆剑承等.高分辨率卫星遥感影像地学计算[M].北京：科学出版社,2009：15
[150]周伏建,陈明华,林福兴,等.福建省降雨侵蚀力指标R值[J].水土保持学报,1995,9(1)：13～18
[151]周生贤.全面加强沿海防护林体系建设加快构筑我国万里海疆的绿色屏障——在全国沿海防护林体系建设座谈会上的讲话[J].世界林业研究,2005,18(4)：1-6
[152]周为峰,吴炳方.土壤侵蚀调查中的遥感应用综述[J].遥感技术与应用,2005,(5).537～542
[153]周忠发,李波,杨晓英.贵州喀斯特高原景观遥感监测与空间格局分析——以大方县桶井示范区为例[J].安徽农业科学,2009,(31).15391～15393
[]54]朱劲伟,朱廷曜.应用数量化理论I分析林带防风作用[J].林业科学,1980(6)：110～115
[155]朱丽,李金霞,秦富仓,姚云峰,.鄂托克旗风蚀荒漠化景观格局动态变化研究[J].中国沙漠,2009,(6).1063～1068
[156]朱廷曜等,林网化地区的动量通量变化规律及区域性防风效应分析,防护林体系生态效益及近地面物理特征的观测研究,气象出版社.1992：162～168
[2]Anatoly A Gitelson, Yoram J Kaufman, Robert Stark, et al. Novel algorithms for remote estimation of vegetation fraction [J]. Remote Sensing of Environment,2002,80 (1):76～87
[3]Arturo Ruiz-Luna, Cesar A, Berlanga-Robles. Land use, land cover changes and coastal lagoon surface reduction associated with urban growth in northwest Mexico[J]. Landscape Ecology,2003,18:159～171
[4]Chepil W S, et al. Climatic factor for estimating wind erodibility fields [J]. Journal of Soil and Water Conservation,1962,17(4):162-165.
[5]De Roo P J, Offermans R J E, Cremers N H.LISEM:a Single-event physically based hydrological and soil erosion model for drainagebasins. II:sensitivity analysis, validation and application [J].Hydrological Processes,1996,10:1119-1126
[6]Eimern, J.Van etal,1964, Windbreaks and shelterbelts[M], WMO Technical note no.59, Geneva, Switzenland
[7]Erin J Nelson,Derek B Booth.Sediment sources in an urbanizing,mixed land-use watershed[J].Journal of Hydrology,2002,264(1～4):51～68
[8]Hall B, Motzkin G, David R. Three hundred years of forestand land-use change in Massachusetts, USA[J].Journal of Biogeography,2002,29:1319～1335
[9]http://tieba.baidu.com/f?kz=106363294
[10]http://www.fujian.gov.cn/bmdd/sxgk/zz/200804/t20080409_64634.htm
[11]http://www.xzqh.org/html/fj/0922.html
[12]http://zhidao.baidu.com/question/35153266.html?si=l
[13]J M Garcia-Ruiz,T Lasanta,C Gonzalez,et al.Sedimentsources during the traditional land-use system in the Spanish Pyrenees[J].Physics and Chemistry of the Earth,1997,22(3-4):351～354
[14]Jaejoon L.Consensual and hierarchical classification of remotely sensed multispectral images [J]. Transaction on Geoscience and Remote Sensing,2007,45 (9):2953～2963
[15]Jagdish Krishnaswamy,Patrick N Halpin,Daniel DRichter.Dynamics of sediment discharge in relation tolanduse and hydroclimatology in a humid tropical watershed in Costa Rica[J].Journal of Hydrology, 2001,253(1～4):91～109.
[16]Jordan G,van Rompaey A,Szilassi P,et al.Historical landuse changes and their impact on sediment fluxes in theBalaton Basin(Hungary)[J].Agriculture,Ecosystems&Environment,2005,108(2):119～133
[17]K M Turnage, et al. Comparison of soil erosion and deposit ion rates using gradiocesium, RU SL E, and buried soil indo lines in East Tennessee [J]. Environmental Geology,1997,29(7):1～10
[18]Kan fistikoglu, Nilgun B Harmancioglu.Integrate ion of GIS with USLE in An assessments of Soil Erosion [J].Water Resources Management,2002,(16):447-467
[19]Kanellopoulos I, Wilkinson G G. Strategies and best practice for neural networks image classification [J]. International Journal of Remote Sensing,1997,18(4):711～725
[20]LAI R.可蚀性和侵蚀性[M]／／水土保持学会.黄河水利委员会宣传出版中心译,土壤侵蚀研究方法.北京：科学出版社,1991：137～146
[21]Liu B Y, Nearing M A, Risse L M. Slope gradient effects on soil loss for steep slopes [J].Transactions of the ASAE,1994,37:1835～1840
[22]Lucas R, Rowlands A, Brown A, et al. Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping[J].ISPRS Journal of Photogrammetry & Remote Sensing, 2007,62(3):165～185
[23]Mccusker B. Land use and cover change as an indicator of transformation on recently redistributed farms in Limpopo Province [J], South Africa. Human Ecology,2004,32(1):49～75.
[24]Miller, D. R. ETAL. Microclimate modification with shelterbelts [J]. Soil and Water Cons.,1974, 29(1):41～44
[25]Mota G L, Feitosa R Q, Coutinho H L,et al. Multitemporal fuzzy classification model based on class transition possibilities[J] ISPRS Journal of Photogrammetry & Remote Sensing,2007,62(3):186～200
[26]Nearing M A. A single continuous function for slope steepness influence on soil loss [J]. Soil Science Society of America Journal,1997,61(3):917-919
[27]Norman, W.B. Shelterbelts and windbracks in the Great Plains [J]. J. For.,1989,87(4).32～36.
[28]Pal M, Mather P M. Support vector machines for classification in remote sensing[J].International Journal of Remote Sensing,2005,26(5):1007～1011
[29]Peterson DL, ParkerVT. Ecological Scale:Theory and Application [M]. New York:Columbia University Press,1998:429～457
[30]Renard K G, et al. RUSLE revisited status and the future [J]. Soil and Water Conservation,1994,49(3): 213-220
[31]Renard K G, Foster G R, Weesies G A, et al. Predicting soil erosion by water:A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE)[M]. Handbook Department of Agriculture. Washington D. C.1997
[32]Renard K G. RUSLE-A guide to conservation planning with the revised universal soil loss equation. USDA Agricultural Handbook No.703[M]. Washington D C:USDA,1995.
[33]Skidmore E L wind erosion climatic erosivity [J]. climate change,1986,9(12):195～208
[34]Sollberg S H A, Toxt T, Jain K A. A markov random field model for classification of multi-source satellite imagery [J].IEEE Transaction on Geoscience and Remote Sensing,1999,34(1):100～113
[35]TimoTokola, SatuLfman, and AnttiErkkil. Relative calibration of Multitemporal Landsat Data for Forest Cover Change Detection [J]. Remote Sens. Envir,1999(68):1～11.
[36]Wallin D O, Swanson F J, Mark sB. Landscape pat tern response to changes in pat tern generates ion rules21and2use legacies in forestry [J]. Ecologic Lapp licit ion,1994,(4):569～580
[37]Wilkinson G G. Results and implications of a study of fifteen years of satellite image classification experiments[J].Transaction on Geoscience and Remote Sensing,2005,43 (3):433～439
[38]Wischmeier W H,Smith D D.Rainfall energy and its relationship to soil loss[J].Transactions American Geophysical Union,1958,39:285-291
[39]Wischmeier W H. A soil erodibility monograph farmland and const ruction sites [J]. Soil and Water Conservation,1971,26:189-193
[40]Wischmele W H. A rainfall erosion Index for universal soil loss equation [J]. Soil Science Proceedings.1959,23(3):246～249.
[41]Wishchmeier W H, smith D D. Predicting rainfall erosion losses:a guide to conservation planning [M]. Washington D. C; USDA, ARS, Agricultural Handbook,1978:537
[42]Zhao G X,Lin G,Fletcher J J,et al.Cultivated landchanges and their driving forces:A satellite remote sensing analysis in the Yellow River Delta[J],China.Pedosphere,2004,14(1):93～102
[43]“湘中丘陵洞庭湖水系生态经济型防护林体系建设技术研究”专题组,湘中丘陵洞庭湖水系生态经济型防护林体系建设技术研究(专题报告)[R],1996
[44]卜兆宏,卜宇行,陈炳贵,等.用定量遥感方法监测UNDP试区小流域水土流失研究[J].水科学进展,1999,(1).31-36
[45]卜兆宏,董勤瑞,周伏建,张立文.降雨侵蚀力因子新算法的初步研究.土壤学报.1992,29(4)：408～418
[46]卜兆宏,李全英.土壤可蚀性(K)图编制方法的初步研究.遥感技术与应用.1994,9(4)：22～27
[47]卜兆宏,刘绍清.土壤流失量及其参数实测的新方法.土壤学报.1995,32(2)：10～20
[48]卜兆宏,孙金庄,董勤瑞,等.应用水土流失定量遥感方法监测山东全省山丘区的研究[J].土壤学报,1999,(1).1-7
[49]卜兆宏,孙金庄,周伏建等.水土流失定量遥感方法及其应用的研究.土壤学报.1997,34(3)：235～245
[50]卜兆宏,唐万龙,席承藩,等.水土流失定量遥感方法应用与研究的新进展[J].世界科技研究与发展,2000,(S1).64-67
[51]卜兆宏,唐万龙,杨林章,等.水土流失定量遥感方法新进展及其在太湖流域的应用[J].土壤学报,2003,(1).1-8
[52]卜兆宏,唐万龙.像元坡度新算法的初步研究.遥感技术与应用,1993,8(1)：1～6
[53]卜兆宏,赵宏夫,刘绍清等.用于土壤流失量遥感监测的植被因子算法的初步研究.遥感技术与应用.1993,8(4)：16～22
[54]曹新孙.农田防护林国外研究现状(二)[C],中国科学院林业土壤研究所集刊,第五集,1981
[55]曹新孙.农田防护林国外研究现状(一)[C],中国科学院林业土壤研究所集刊,第五集,1981
[56]陈晋,陈云浩,何春阳,等.基于土地覆盖分类的植被覆盖率估算亚像元模型与应用[J].遥感学报,2001,5(6)：416～422
[57]陈述彭,童庆禧,郭华东.遥感信息机理研究[M].北京：科学出版社,1998,：345～349
[58]陈正宜.晋陕蒙接壤地区脆弱生态系统遥感监测与管理研究[M]／北京：宇航出版社,1994：24～26
[59]成军锋,贾宝全,赵秀海,等.干旱半干旱地区植被覆盖度的动态变化分析——以毛乌素沙漠南部为例[J].干旱区资源与环境,2009,(12)：72～76
[60]程天文,农田蒸发与蒸发力的测定及其计算方法[A],地理集刊第12号[C].北京：科学出版社,1980
[61]川口武雄(方华荣译).森林的水土保持机能(Ⅰ,Ⅱ,Ⅲ)[J].水利科学,1988,185.54～72
[62]戴昌达.TM图像的光谱信息特征与最佳波段组合[J].环境遥感,1989,4(4)：282～29
[63]党安荣,王晓栋,陈晓峰等..ERDAS IMAGINE遥感图像处理方法[M],北京：清华大学出版社,2003：187
[64]丁艳梅,张继贤,王坚,等.基于TM数据的植被覆盖度反演[J].测绘科学,2006,36(1)：43～45
[65]方纲清,阮伏水,吴雄海,等.福建省主要土壤可蚀性特征初探[J].福建水土保持,1997(2)：19～23
[66]冯恩国,李淑香.居民地信息提取的最佳假彩色合成方法——以开封市区为例[J].平顶山学院学报,2006,21(2)：91～94.
[67]冯露,岳德鹏,郭祥.植被指数的应用研究综述[J].林业调查规划,2009,(2)：48～52
[68]冯石,马友鑫,刘文俊,等.城市化过程中昆明周边景观格局特征分析[J].云南大学学报(自然科学版),2009,(S1).338～343
[69]傅伯杰,陈利顶,马克明,等.景观生态学原理与应用[M].北京：科技出版社,2000
[70]高文韬,丁伟,李胜.长白山林区天然过伐林中蒙古栎适生立地研究[J].北华大学学报(自然科学版),2000,1(1)：77～81
[71]郭志民,陈永宝,陈志伟.土壤可蚀性特征及其K值图制作研究[J].山西水土保持科技,2002(1)：15-17.
[72]郭忠升.水土保持植被建设中的三个盖度：潜势盖度、临界盖度和有效盖度[J].中国水土保持,2004(4)：30-31
[73]洪伟,吴承祯.Krige方法在我国降雨侵蚀力地理分布规律研究中的应用[J].土壤侵蚀与水土保持学报,1997,3(1)：91～96
[74]胡召玲,李志江,杜培军.分层信息提取法在县域土地利用／覆被遥感中的应用[J].地理研究,2009,28(2)：409～418
[75]黄炎和,卢程隆,郑添发,等.闽东南降雨侵蚀力指标R值的研究[J].水土保持学报,1993,6(4)：1～5
[76]回良玉.在海南省沿海防护林建设调研时的批示[J].林业科学,2005,(07B)：4-9.
[77]季小妹,陈田,郑芳.半城市化地区生态环境研究进展[J].生态环境学报,2009,(4)：1579-1586
[78]江东.人文要素空间化研究进展[J].地理学报,2003,58(1)：25～33
[79]姜小三,潘剑君,杨林章,等.土壤可蚀性K值的计算和K值图的制作方法研究——以南京市方便水库小流域为例[J].土壤.2004,36(2)：177-180
[80]李栋梁.基于TM影像的水系信息提取及变化制图研究[D].南京,河海大学,2006
[81]李际平,陈端吕,袁晓红,等.人类干扰对森林景观类型相关性的影响研究[J].中南林业科技大学学报,2009,(5)：39～43
[82]李苗苗,吴炳方,颜长珍,等.密云水库上游植被覆盖度的遥感估算[J].资源科学,2004,26(4)：153～158
[83]李蓉,李俊祥,李铖,秦海,徐明策,张挺,.快速城市化阶段上海海岸带景观格局的时空动态[J].生态学杂志,2009,(11)：2353～2359
[84]李亚云,杨秀春,朱晓华,等.遥感技术在中国土地荒漠化监测中的应用进展[J].地理科学进展,2009,(1)：55～62
[85]刘宝元,谢云,张科利.土壤侵蚀预报模型[M].北京：中国科学技术出版社,2001
[86]刘纪元.中国资源环境遥感宏观调查与动态研究[M].北京：中国科学技术出版社,1996,158～188,276～281
[87]刘建波,戴昌达.TM图像在大型水库库情监测管理中的应用[J].环境遥感,1996,11(1)：53～58
[88]刘建平,赵时英.高光谱遥感数据解译的最佳波段选择方法研究[J].中国科学院研究生院学报,1999,16(2)：153～161
[89]刘健,余坤勇,亓兴兰,等.基于3S技术生态公益林空间格局优化配置技术模拟研究[J].北京林业大学学报,2009,(S2)：78-85
[90]刘健.基于3S技术闽江流域生态公益林体系高效空间配置研究[D].北京林业大学.2006.
[91]刘世荣,温远光等主编.中国森林生态系统水文生态功能规律[M],中国林业出版社,1996
[92]刘韬,彭明春,王崇云,等.基于可视域分析的景观生态恢复[J].云南大学学报(自然科学版),2009,(S 1)：344～349
[93]刘小平,黎夏,陈逸敏,等.景观扩张指数及其在城市扩展分析中的应用[J].地理学报,2009,(12).1430～1438
[94]刘燕,刘康.水土流失敏感性与土壤类型格局相关性分析——以陕北黄土高原为例[J].水土保持通报,2009,(5)：94～97,122
[95]刘志丽,陈曦.基于ERDAS IMAGING软件的TM影像几何精校正方法初探[J].干旱区地理,2001,24(4)：353～358
[96]卢敬华,陈伟.植被覆盖与土壤水分的动力学模型[J].成都气象学院学报,1998,46(3)：209～216.
[97]路京选,曲伟,付俊娥.国内外干旱遥感监测技术发展动态综述[J].中国水利水电科学研究院学报,2009,(2)：265～271
[98]罗为检,王克林,刘明.土地利用及其格局变化的环境生态效应研究进展[M].中国生态农业学报,2003,11(2)：150～152
[99]罗伟祥,白立强,宋西德,等.不同覆盖度林地和草地的径流量与冲刷量[J].水土保持学报,1990,4(1)：30-35
[100]马超飞,马建文,布和敖斯尔.USLE模型中植被覆盖因子的遥感数据定量估算[J].水土保持通报,2001,21(4)：6-9.
[101]马克明,傅伯杰.北京东灵山地区景观格局及破碎化评价[J].植物生态学报,2000,24(3)：320～326
[102]慕长龙.长江中上游防护林体系综合效益的计量与评价[J],四川林业科技,2001,22(1)：15～23
[103]年波,杨士剑,王金亮.植被遥感信息提取的最佳波段选择——以云岭中部山区为例[J].云南地理环境研究,2004,16(2)：18～21
[104]欧立业,何忠焕,马海州,等.基于知识的分层综合分类法在土地利用／土地覆盖遥感信息提取中的应用[J].测绘科学,2008,(1)：173～175
[105]欧维新,杨桂山,李恒鹏等.苏北盐城海岸带景观格局时空变化及驱动力分析.地理科学,2004,24(5)：610～615
[106]漆良华,张旭东,周金星,等.湘西北侵蚀小流域生态恢复适宜度与景观格局特征[J].山地学报,2009,(5)：524～530
[107]秦伟,朱清科,张学霞,等.植被覆盖度及其测算方法研究进展[J].西北农林科技大学学报(自然科学版),2006,(9).164-170
[108]史培军,陈晋.深圳市土地利用变化机制分析[J].地理学报,2000,55(2)：151～160
[109]孙立达,朱金兆主编,水土保持林体系综合效益研究与评价[M],中国科学技术出版社,1995
[110]孙晓娟.基于“3s”技术的区域林业生态工程空间配置的研究[D].2003,东北林业大学硕士学位论文,2--6
[111]田静,阎雨,陈圣波.植被覆盖率的遥感研究进展[J].国土资源遥感,2004,(1)：1-5
[112]王爱娟,章文波.林冠截留降雨研究综述[J].水土保持研究,2009,(4)：55～59
[113]王冬,赵同林,.基于3S技术的湿地景观格局研究方法进展[J].信息系统工程,2009,(10)：72～75
[114]王繁,周斌,蒋钏.浙江沿海地区近十年土地利用／覆盖变化遥感监测研究.科技通报,2007,23(3)：332～336.
[115]王礼先,解明曙主编.山地防护林水土保持水文生态经济效益及其信息系统[M],中国林业出版社,1997
[116]王万中,焦菊英,郝小品,等.中国降雨侵蚀力R值的计算与分布(Ⅰ)[J].水土保持学报,1995,9(4)：5～18
[117]王万中,焦菊英.中国的土壤侵蚀因子定量评价研究[J].水土保持通报,1996,16(5)：1～20
[118]王万忠,焦菊英,郝小品,等.中国降雨侵蚀力R值的计算与分布(Ⅱ)[J].土壤侵蚀与水土保持学报,1996,2(1)：29～39
[119]魏伟,赵军,王旭峰,.GIS、RS支持下的石羊河流域景观利用优化研究[J].地理科学,2009,(5).750～754
[120]邬建国编著.景观生态学一格局、过程、尺度与等级[M].北京：高等教育出版社2001
[121]吴浩,孙钰蓉,崔巍,等.基于景观指数的武汉市轨道交通沿线土地利用变化研究[J].安徽农业科学,2009,(31)：15602～15604
[122]伍育鹏,谢云,章文波.国内外降雨蚀力简易计算方法的比较[J].水土保持学报,2001,15(3)：31～34
[123]武文波,陈静.基于ETM-+的遥感影像信息提取研究[J].甘肃农业大学学报,2008,(5)：142～146
[124]席武俊,王金亮,王学良,等.香格里拉县土地利用／土地覆被景观格局动态分析[J].楚雄师范学院学报,2009,(9)：79～85
[125]向天梁,汪小钦,周小成,等.基于分层分析的ASTER影像土地利用／覆盖遥感监测研究[J].遥感技术与应用,2006,21(6)：527～531
[126]谢云,章文波,刘宝云.用日雨量和日雨强计算降雨侵蚀力[J].水土保持通报,2001,21(6)：53～56
[127]徐孝庆主编.森林综合效益计量评价[M],中国林业出版社,1992
[]28]杨存建,许美.遥感信息机理的水体提取方法的探讨[J].地理研究,1998,17(SO)：86-89
[129]杨华庭.近十年来的海洋灾害与减灾[J].海洋预报,2002,19(1)：2～7
[130]杨树文,薛重生.航片二次几何校正的应用研究[J].遥感技术与应用,2002,17(3)：154～157
[131]姚坤,师庆东,逢淑女,等.遥感反演土壤湿度综述[J].楚雄师范学院学报,2008,(6)：89～92
[132]游晓斌,游先祥,相莹莹.混合像元及混合像元分析[J].北京林业大学学报.2003,12(s1)：28～32
[133]于君明,王世新,周艺,等.植被水分遥感监测研究综述[J].遥感信息,2008,(2)：97～102
[134]余坤勇,林芳,刘健,等.基于RS的闽江流域马尾松林分蓄积量估测模型研究[J].福建林业科技,2006,33(1)：16～20.
[135]袁金国.森林植被遥感分类研究[J].河北师范大学学报(自然科学版),1999,(2)：274～277
[136]岳天祥,程彤.景观动态及其驱动因素和效应分析[J].自然资源,1997,6：19-26
[137]曾祥坤,王仰麟,李贵才.城市水土流失的景观生态学研究[J].水土保持研究,2009,(5)：25～30
[138]张光灿.树冠截留降雨模型研究进展及其述评[J],南京林业大学学报,2000,24(1)64～68
[139]张光辉.土壤侵蚀模型研究现状与展望[J].水科学进展,2002,13(3)：389～396
[140]张海霞,卞正富.遥感影像植被信息提取方法研究及思考[J].地理空间信息,2007,(6)：65～67
[141]张金池,李海东,林杰,等.基于小流域尺度的土壤可蚀性K值空间变异[J].生态学报,2008,28(5)：2199～2206
[142]张娟.关于卫星影像多项式法纠正中若干问题的分析[J].成果与方法,2004,20(2)：67～69
[143]张黎明.我国南方不同类型土壤可蚀性K值及相关因子研究[D].海口：华南热带农业大学,2005
[144]张丽苏,吴嘉平.分层分区分景相结合的区域土地利用／覆盖分类方法——以浙江钱塘江流域分类为例[J].国土资源遥感,2007,(3)：74～77,81
[145]张清春,刘宝元,翟刚.植被与水土流失研究综述[J].水土保持研究,2002,(4)：96～101
[146]张志东,臧润国,.海南岛霸王岭热带天然林景观格局与动态[J].植物生态学报,2009,(6)：1034～1043
[147]赵萍,傅云飞,郑刘根.基于分类回归树分析的遥感影像土地利用／覆被分类研究[J].遥感学报,2005,9(6)：708～716
[148]郑荣宝,庄剑顺,张金前.广州市土地利用与NDVI变化的关联分析.国土资源遥感,2008,2：102～108
[149]周成虎,骆剑承等.高分辨率卫星遥感影像地学计算[M].北京：科学出版社,2009：15
[150]周伏建,陈明华,林福兴,等.福建省降雨侵蚀力指标R值[J].水土保持学报,1995,9(1)：13～18
[151]周生贤.全面加强沿海防护林体系建设加快构筑我国万里海疆的绿色屏障——在全国沿海防护林体系建设座谈会上的讲话[J].世界林业研究,2005,18(4)：1-6
[152]周为峰,吴炳方.土壤侵蚀调查中的遥感应用综述[J].遥感技术与应用,2005,(5).537～542
[153]周忠发,李波,杨晓英.贵州喀斯特高原景观遥感监测与空间格局分析——以大方县桶井示范区为例[J].安徽农业科学,2009,(31).15391～15393
[]54]朱劲伟,朱廷曜.应用数量化理论I分析林带防风作用[J].林业科学,1980(6)：110～115
[155]朱丽,李金霞,秦富仓,姚云峰,.鄂托克旗风蚀荒漠化景观格局动态变化研究[J].中国沙漠,2009,(6).1063～1068
[156]朱廷曜等,林网化地区的动量通量变化规律及区域性防风效应分析,防护林体系生态效益及近地面物理特征的观测研究,气象出版社.1992：162～168
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