Land use dynamic remote sensing monitoring region partitioning method based on the development pressure state: A case study of Jinnan district,Tianjin City

doi:10.6046/gtzyyg.2013.03.21

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Abstract

In order to conduct land use dynamic remote sensing monitoring with clearer aim, this paper proposes appropriate monitoring ideas and methods. With Jinnan district as the study area and on the basis of establishing the development pressure evaluation index system,the authors selected the appropriate quantitative indicators and used the multi-factor evaluation method to evaluate development pressure grade of each unit in the study area and zone the area. The zoning results show that the key monitoring area of land use remote sensing dynamic monitoring in Jinnan district is 11 650.5 hectares,and the general monitoring area is 9 011.7 hectares,respectively accounting for 56.4% and 43.6% of the total area of the evaluation unit. In combination with the land-use characteristics of each zone,the selection of different remote sensing monitoring ideas and methods according to the local conditions is of great significance for efficient promotion of land use dynamic monitoring by remote sensing technology.

Keywords road extraction high resolution remote sensing image watershed object-oriented method mathematical morphology

TP 79

Issue Date: 03 July 2013

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	CAI Hongyue
	YAO Guoqing

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CAI Hongyue,YAO Guoqing. Land use dynamic remote sensing monitoring region partitioning method based on the development pressure state: A case study of Jinnan district,Tianjin City[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(3): 124-129.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2013.03.21 OR https://www.gtzyyg.com/EN/Y2013/V25/I3/124

[1] 高振宇,吴学瑜,范清东,等.土地利用动态遥感监测中的问题探析[J].国土资源遥感,2011,23(3):20-24. Gao Z Y,Wu X Y,Fan Q D,et al.An analysis of the problems concerning remote sensing dynamic monitoring of land use[J].Remote Sensing for Land and Resources,2011,23(3):20-24.

[2] 赵晓丽,刘斌,易玲,等.郑州城市空间扩展特征及其驱动因素分析[J].国土资源遥感,2009,21(4):90-95. Zhao X L,Liu B,Yi L,et al.An analysis of characteristics and dring force of urban spatial expansion in Zhengzhou[J].Remote Sensing for Land and Resources,2009,21(4):90-95.

[3] 吴见,彭道黎.多伦县土地利用动态遥感监测[J].国土资源遥感,2010,22(3):86-91. Wu J,Peng D L.Land use dynamic monitoring based on remote sensing in Duolun County[J].Remote Sensing for Land and Resources,2010,22(3):86-91.

[4] 雒燕飞,徐泮林,李英成,等.3S技术在土地督察中的应用[J].国土资源遥感,2010,22(3):12-15. Luo Y F,Xu P L,Li Y C,et al.The application of 3S technology to land supervision[J].Remote Sensing for Land and Resources,2010,22(3):12-15.

[5] 高迎春,王利香,佟连军,等.石家庄城市边缘区土地利用变化分析[J].国土资源遥感,2010,22(1):107-111. Gao Y C,Wang L X,Tong L J,et al.An analysis of land use change in urban border areas of Shijiazhuang City[J].Remote Sensing for Land and Resources,2010,22(1):107-111

[6] 周亦,李琦,马熹肇,等.土地利用动态遥感监测中不同数据源正射影像制作关键技术浅析[J].矿产勘查,2011,2(6):827-833. Zhou Y,Li Q,Ma Y Z,et al.Analysis on key techniques in orthophoto production of different data sources inthe land use dynamic remote-sensing monitoring[J].Mineral Exploration,2011,2(6):827-833.

[7] 马小计,杨自安,刘邵峰,等.辽宁锦州市土地利用动态遥感监测方法应用研究[J].地质与勘探,2008,44(1):97-101. Ma X J,Yang Z A,Liu S F,et al.Remote sensing technology for dynamic monitoring of land use in Jinzhou City,Liaoning Province[J].Geology and Prospecting,2008,44(1):97-101.

[8] 柴渊,谢俊琦.全国重点城市和重点区域土地利用动态遥感监测[J].中国建设信息,2007,10:37-42. Chai Y,Xie J Q. Land use dynamic monitoring by remote sensing in China’s major cities and key areas[J].Information of China Construction,2007,10:37-42.

[9] 付海英,郝晋珉,朱德举,等.耕地适宜性评价及其在新增其他用地配置中的应用研究[J].农业工程学报,2007,23(1):60-66. Fu H Y,Hao J M,Zhu D J,et al.Cultivated land suitability evaluation and its application to other increasedland allocation[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(1):60-66.

[10] 郝晋珉,朱道林.土地利用规划[M].北京:中国农业科技出版社,1995. Hao J M,Zhu D L.Land use planning[M].Beijing:China Agricultural Science and Technology Press,1995.

[11] 张心怡,刘敏,孟飞.基于RS和GIS的上海城建用地扩展研究[J].长江流域资源与环境,2006,15(1):29-33. Zhang X Y,Liu M,Meng F.Expansion of urban construction land in Shanghai City based on RS and GIS[J].Resources and Environment in the Yangtze Basin,2006,15(1):29-33.

[12] 李宁,郑新奇.耕地资源非农转化定量预测模型——以济南市为例[J].资源科学,2005,27(6):46-52. Li N,Zheng X Q.Models for quantitative prediction of transmission of cultivated land resources:A case in Jinan City[J].Resources Science,2005,27(6):46-52.

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