安徽省土地利用十年动态变化遥感监测

吴见,侯功兰,刘民士,李伟涛

南京林业大学学报(自然科学版) ›› 2014, Vol. 38 ›› Issue (02) : 147-150.

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南京林业大学学报(自然科学版) ›› 2014, Vol. 38 ›› Issue (02) : 147-150. DOI: 10.3969/j.issn.1000-2006.2014.02.028
研究论文

安徽省土地利用十年动态变化遥感监测

  • 吴 见,侯功兰, 刘民士,李伟涛
作者信息 +

Land use dynamic monitoring for ten years by remote sensing of Anhui province

  • WU Jian, HOU Gonglan,LIU Minshi, LI Weitao
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文章历史 +

摘要

基于地物光谱特征,采用光谱角分类技术将主要地物覆被类型进行了分离,并依据经验知识构建了各用地类型的专题信息模型,提取了安徽省土地利用信息,通过分析2000、2005和2010年3期遥感调查结果,得到了安徽省土地利用动态变化及不同土地利用类型之间的转换情况。结果表明:安徽省的土地利用面积以耕地和林地为主,近10年来林地面积持续增加,而建设用地扩建现象严重,导致耕地被大量占用。

Abstract

The spectral features of each land use type was analyzed, and the spectral angle mapper was used to separate the main cover types, and the thematic information models of each land use type were constructed based on experience and knowledge. Remote sensing information extraction technology based on the knowledge wasused on the land use information extraction in Anhui province. Land use information of Anhui province was extracted automatically using a computer. By analyzing the three remote sensing survey results of the year of 2000, 2005 and 2010, the information of the land use dynamic changes and conversions between different land use types was obtained. The results showed that the farmland and forest land were the main land use types in Anhui province, and the forest area continued to increase, but the farmland area decreased because of the construction land expansion.

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吴见,侯功兰,刘民士,李伟涛. 安徽省土地利用十年动态变化遥感监测[J]. 南京林业大学学报(自然科学版). 2014, 38(02): 147-150 https://doi.org/10.3969/j.issn.1000-2006.2014.02.028
WU Jian, HOU Gonglan,LIU Minshi, LI Weitao. Land use dynamic monitoring for ten years by remote sensing of Anhui province[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2014, 38(02): 147-150 https://doi.org/10.3969/j.issn.1000-2006.2014.02.028
中图分类号: P237   

参考文献

[1] 渠爱雪,卞正富,朱传耿,等. 徐州土地利用变化过程与格局[J]. 地理研究, 2009, 28(1):97-108. Qu A X, Bian Z F, Zhu C G, et al. Study on the process and pattern of land use change in Xuzhou urban area[J]. Geographical Research, 2009, 28(1):97-108.
[2] Ren Q L, Ming D, Jian Y C, et al. Quantification of the impact of land-use changes on ecosystem ervices: A case study in Pingbian county, China[J]. Environmental Monitoring and Assessment, 2007, 128: 503-510.
[3] 杨静,庄家尧,张金池. 基于RS 和GIS 的徐州市20年间土地利用变化研究[J]. 南京林业大学学报:自然科学版,2013, 37(2):58-91. Yang J, Zhuang J Y, Zhang J C. Study on the change of land use in the Xuzhou city based on RS and GIS[J]. Journal of Nanjing Forestry University:Natural Sciences Edition, 2013, 37(2):58-91.
[4] 罗慧芬,苗放,杨文晖. 光谱角法在ASTER 影像土地利用分类中的应用[J]. 测绘科学,2012, 37(6):43-45. Luo H F, Miao F, Yang W H. Study of land use classification using SAM from ASTER data[J]. Science of Surveying and Mapping, 2012, 37(6):43-45.
[5] Mas J F. Mappping land use/cover in a tropical coastal area using satellite sensor data, GIS and artificial neural networks, Estuarine[J]. Coast Shelf Sci, 2004, 59: 219-230.
[6] 李秀梅. TM影像目视解译显示尺度的选择及尺度效应分析——以内陆河流域绿洲-荒漠过渡带为例[J]. 地理与地理信息科学,2012, 28(4):33-37. Li X M. Choice and effect analysis of displaying scale of the visual interpretation of TM image: A case study on the ecotones between the oases and deserts in the inland river basin[J]. Geography and Geo-Information Science, 2012, 28(4):33-37.
[7] Joshi P K, Rawat G S, Padily A H, et al. Biodiversity characterization in Nubra Valley, Ladakh with special reference to plant resource conservation and bioprospecting[J]. Biodiversity Conserv, 2006, 15(13):4253-4270.
[8] Jiang H, Strittholt J R, Frost P A, et al. The classification of late seral forests in the Pacific Northwest, USA using Landsat ETM+imagery[J]. Remote Sens Environ, 2004(91):320-331.
[9] Cohen Y, Shoshany M. Analysis of convergent evidence in an evidential reasoning knowledge-based classification[J]. Remote Sens Environ, 2005, 96: 518-528.
[10] 梁继, 王建, 王建华. 基于光谱角分类器遥感影像的自动分类和精度分析研究[J]. 遥感技术与应用, 2002, 17(6):299-303. Liang J, Wang J, Wang J H. Study on automatic classification and accuracy analysis of remote sensing image based on SAM[J]. Remote Sensing Technology and Application, 2002, 17(6):299-303.
[11] 刘汉丽,裴韬,周成虎,等. 结合MNF 变换与灰值形态学的三江平原多光谱、多时相MODIS 遥感影像分类[J]. 武汉大学学报:信息科学版, 2011, 36(2):153-156. Liu H L, Pei T, Zhou C H, et al. Multi-spectral and Multitemporal MODIS remote sensing imagery classification based on MNF Transform and grayscale morphological filter in Sanjiang Plain[J]. Geomatics and Information Science of Wuhan University, 2011, 36(2):153-156.
[12] 纪娜,李锐,李静. MNF 和SVM在遥感影像计算机分类中的应用[J]. 水土保持通报, 2009, 29(6):153-158. Ji N, Li R, Li J. Application of MNF and SVM in classification of remote sensed image[J]. Bulletin of Soil and Water Conservation, 2009, 29(6):153-158.
[13] Dabov K, Foi A, Katkovnik V, et al. Image denoising by sparse 3D transform-domain collaborative filtering[J]. IEEE Trans Image Process, 2007, 16(8):2080-2095.
[14] Katkovnik V, Foi A, Egiazarian K, et al. From local kernel to nonlocal multiple-model image denoising[J]. Int J Comput Vis, 2010, 86(1):1-32.
[15] Coup P, Yger P, Barillot C. Fast nonlocal means denoising for 3D MR images[J]. Lecture Notes Comput Sci, 2006, 4194: 33-40.

基金

收稿日期:2013-01-02 修回日期:2013-04-21
基金项目:安徽省自然科学基金项目(1208085QD73); 安徽省高校省级自然科学研究项目(KJ2013B189, KJ2012B125); 滁州学院校级科研启动基金项目(2012qd18)
第一作者:吴见,讲师,博士。E-mail: xiangfeidewujian@126.com。
引文格式:吴见,侯功兰, 刘民士,等. 安徽省土地利用十年动态变化遥感监测[J]. 南京林业大学学报:自然科学版,2014,

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