面向水土保持监管的黄土高原区生产建设项目地块快速提取

doi:10.16843/j.sswc.2017.03.011

Abstract
Figure/Table
References
Related Citation (1)

Download: PDF (6126 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract [Background] The productive and constructive project (PCP) is one of the main sources of man-made soil and water loss in the Loess Plateau. Acquiring the location and attributes of PCP land parcels is critical to soil and water conservation supervision, management, and protection. Traditional ways of mapping PCP land parcels mainly rely on manual interpretation of remote sensing images, which is time-consuming, subjective and expensive. [Methods] Based on GF-1 images, this paper presents a rapid object-oriented method to extract PCP land parcels in the Loess Plateau. Firstly, we analyzed the separability of 29 typical PCP land parcel components in the study area. Six kinds of components were selected as extraction markers. Then, on this basis, an object-oriented multi-level extraction model, which united the multi-resolution segmentation algorithm and the fuzzy classification algorithm, was developed to extract these six kinds of components mentioned above. Final extraction results were achieved after automatic extraction and post-processing procedures. [Results] Results showed that six kinds of marked objects, which were buildings and structures, hardened grounds, bare lands, waste slags, coal covered areas and water areas, were reliable to sign PCP land parcels in the Loess Plateau. With the object-oriented multi-level extraction model, the extraction results were considered sustainable and efficient. The quantitative and area accuracy of extracting block-type PCP land parcels was 95.03% and 85.19% respectively, while the length accuracy of extracting line-type PCP land parcels was 86.34%. Besides, with the same hardware and software configuration, the overall time was 80% less than the traditional method. The results validated that the multi-resolution segmentation algorithm portrayed the edges of different objects correctly in several scales, and that the fuzzy classification algorithm described the features of the objects in a more plentiful and accurate way. It was proved that the object-oriented extraction method was suitable for extracting PCP land parcels based on GF-1 imagery. A few of block-type PCP land parcels were failed to be extracted for the broken composition and inadequate extracting area. The interferences of surroundings decreased the extraction accuracy of line-type PCP land parcels. [Conclusions] Compared to manual interpretation, this proposed method shows a solid advantage on extraction efficiency with a high accuracy, which can be applied for rapid extraction of PCP land parcels in a large region in the Loess Plateau. This method provides a better technical support for efficient and accurate implementation of soil and water conservation supervision and management.

Key words： the Loess Plateau productive and constructive project (PCP) land parcel soil and water conservation supervision and management GF-1 rapid extraction

Received: 09 January 2017

PACS:	S157
	TP751

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	GAO Zhiqiang
	SHI Mingchang
	YANG Wentao
	SUN Na
	WANG Xiaojing

Cite this article:

GAO Zhiqiang,SHI Mingchang,YANG Wentao, et al. Rapid extraction of land parcels from soil and water conservation supervision-oriented productive and constructive projects in the Loess Plateau[J]. SSWC, 2017, 15(3): 81-89.

URL:

http://journal12.magtechjournal.com/Jweb_stbc/EN/10.16843/j.sswc.2017.03.011 OR http://journal12.magtechjournal.com/Jweb_stbc/EN/Y2017/V15/I3/81

[1]	朱首军,黄炎和.开发建设项目水土保持[M].北京:科学出版社,2013:1. ZHU Shoujun, HUANG Yanhe. Soil and water conservation of development and construction projects[M].Beijing:Science Press, 2013:1.
[2]	徐林.晋陕蒙接壤地区水土保持监督执法存在问题与对策[J].中国水土保持,2014,(8):58. XU Lin. Problems and countermeasures on supervision and law enforcement of soil and water conservation in Shanxi-Shaanxi-Inner Mongolia contiguous areas[J]. Soil and Water Conservation in China, 2014, (8):58.
[3]	晋陕蒙接壤地区水土保持监督局. 2015年度晋陕蒙接壤地区水土保持监督管理公报[EB/OL]. (2016-02-22)[2017-01-05]. http://www.hwjsm.org/index.php?m=Index&a=shows&catid=7&id=439. Soil and Water Conservation Supervisory Bureau of Shanxi-Shaanxi-Inner Mongolia Contiguous areas, YRCC. Soil and water conservation supervision and management communique of Shanxi-Shaanxi-Inner Mongolia contiguous areas 2015[EB/OL]. (2016-02-22)[2017-01-05]. http://www.hwjsm.org/index.php?m=Index&a=shows&catid=7&id=439.
[4]	李智广,王敬贵.生产建设项目"天地一体化"监管示范总体实施方案[J].中国水土保持,2016,(2):15. LI Zhiguang, WANG Jinggui. Overall implementation plan of the demonstration of the Space-Earth Integration supervision and management of production and construction projects[J]. Soil and Water Conservation in China, 2016,(2):15.
[5]	戴舒,付迎春,赵耀龙.基于Cubist模型树的城市不透水面百分比遥感估算模型[J].地球信息科学学报,2016,18(10):1399. DAI Shu, FU Yingchun, ZHAO Yaolong.The remote sensing model for estimating urban impervious surface percentage based on the Cubist model tree[J]. Journal of Geo-information Science, 18(10):1399.
[6]	徐涵秋,王美雅.地表不透水面信息遥感的主要方法分析[J].遥感学报,2016,20(5):1270. XU Hanqiu, WANG Meiya.Remote sensing-based retrieval of ground impervious surfaces[J]. Journal of Remote Sensing, 2016, 20(5):1270.
[7]	樊舒迪,胡月明,刘振华.一种新的面向对象城市建筑物信息提取方法研究[J].华南师范大学学报(自然科学版),2015,47(6):91. FAN Shudi, HU Yueming, LIU Zhenhua. Research of information extraction of city building based on a new object-oriented method[J].Journal of South China Normal University (Natural Science Edition), 2015,47(6):91.
[8]	Esch T, Himmler V, Schorcht G, et al. Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data.[J]. Remote Sensing of Environment, 2009, 113(8):1678.
[9]	Jr ARNOLD C L, GIBBONS C J. Impervious surface coverage:the emergence of a key environmental indicator[J]. Journal of the American Planning Association, 1996, 62(2):243.
[10]	李德仁,罗晖,邵振峰.遥感技术在不透水层提取中的应用与展望[J]. 武汉大学学报(信息科学版),2016,41(5):573. LI Deren, LUO Hui, SHAO Zhenfeng. Review of impervious surface mapping using remote sensing technology and its application[J]. Geomatics and Information Science of Wuhan University, 2016,41(5):573.
[11]	马浩然,赵天忠,曾怡.面向对象的最优分割尺度下多层次森林植被分类[J].东北林业大学学报,2014,42(9):53. MA Haoran, ZHAO Tianzhong, ZENG Yi.Object-based multi-level classification of forest vegetation on optimal segmentation scale[J]. Journal of Northeast Forestry University, 2014,42(9):53.
[12]	王利民,刘佳,杨福刚,等.基于GF-1卫星遥感的冬小麦面积早期识别[J].农业工程学报,2015,31(11):197. WANG Limin, LIU Jia, YANG Fugang, et al.Early recognition of winter wheat area based on GF-1 satellite[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(11):197.
[13]	俞春娜,俞伟斌,谭永忠. 基于色彩和纹理特征的建设用地遥感专题信息自动提取方法[J]. 西南大学学报(自然科学版), 2012, 34(1):107. YU Chunna, YU Weibin, TAN Yongzhong. Approach of extracting RS thematic information of construction land based on the features of color and texture[J]. Journal of Southwest University(Natural Science Edition), 2012, 34(1):107.
[14]	姜德文,郭索彦,赵永军,等.生产建设项目水土保持准入条件通用条款[J].中国水土保持科学,2010,8(3):44. JIANG Dewen, GUO Suoyan, ZHAO Yongjun, et al. General terms of soil and water conservation access conditions of production and construction projects[J]. Soil and Water Conservation in China, 2010,8(3):44.
[15]	朱俊杰,范湘涛,杜小平.面向对象的高分辨率遥感图像分析[M].北京:科学出版社, 2014:9. ZHU Junjie, FAN Xiangtao, DU Xiaoping. Object-oriented high resolution remote sensing image analysis[M]. Beijing:Science Press, 2014:9.
[16]	BAATZ M, SCHÄPE A. Multiresolution segmentation:an optimization approach for high quality multi-scale image segmentation[C/OL].[2017-01-05]. http://www.ecognition.com/sites/default/files/405_baatz_fp_12.pdf?.
[17]	杨亦宁. 基于优度准则的遥感影像最优分割参数组合选择研究[D].兰州:兰州大学,2013:55 YANG Yining.Goodness criterion for selecting optimal combination of parameter values in remote sensing image segmentation[D]. Lanzhou:Lanzhou University, 2013:55.
[18]	NUSSBAUM S, NIEMEYER I, CANTY M J. SEaTH-a new tool for automated feature extraction in the context of object-based image analysis[C/OL].[2017-01-05]. http://www.isprs.org/proceedings/XXXVI/4-C42/Papers/12_Object-based%20approach%20generic%20issues%20-%20IC%20I/OBIA2006_Nussbaum_Niemeyer_Canty.pdf.
[19]	佟国峰,李勇,丁伟利,等.遥感影像变化检测算法综述[J].中国图象图形学报,2015,20(12):1567. TONG Guofeng, LI Yong, DING Weili, et al. Review of remote sensing image change detection[J]. Journal of Image and Graphics, 2015, 20(12):1567.
[20]	吴宏安,蒋建军,张海龙,等. 比值居民地指数在城镇信息提取中的应用[J]. 南京师大学报(自然科学版),2006,29(3):119. WU Hongan, JIANG Jianjun, ZHANG Hailong, et al. Application of ratio resident area index to retrieve urban residential areas based on Landsat TM data[J]. Journal of Nanjing Normal University (Natural Science), 2006,29(3):119.
[21]	XU H. Rule-based impervious surface mapping using high spatial resolution imagery[J]. Transactions of the Chinese Society of Agricultural Engineering:Transactions of the CSAE, 2013, 34(1):32.
[22]	URSULA C B, PETER H, GREGOR W, et al. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2004, 58(3/4):251.
[23]	余洁,余峰,张晶,等. 结合区域生长与道路基元的高分辨率遥感影像道路提取[J]. 武汉大学学报(信息科学版),2013,38(7):761. YU Jie, YU Feng, ZHANG Jing, et al. High resolution remote sensing image road extraction combining region growing and road-unit[J].Geomatics and Information Science of Wuhan University, 2013,38(7):761.