格网化资源环境综合科学调查的若干问题思考
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摘要
资源环境综合科学调查,是获取反映区域自然基础和社会发展情况的科学数据和资料的重要手段。中国幅员辽阔、地理国情复杂且数据资料积累薄弱,因此,我国重视并长期发展资源环境综合科学调查。然而,由于不同时期、不同区域开展的综合科学调查,在时空尺度、调查内容、技术规范等方面存在很大差异,尽管资料获取越来越多,但仍难以集成利用,缺少对我国总体资源环境的认识。能否以格网化的思路来获取和管理考察资料,能否有适宜于资源环境调查的标准规范,来集成历史资料并指导未来的动态监测,能否建成一个中观尺度的长期资源环境调查系统?针对这些问题,结合当前正在实施的格网化资源环境综合科学调查规范项目的实践,提出以下一些思考,包括:资源环境调查格网体系、格网的剖分与编码、资源环境调查标准规范、资源环境调查适宜尺度、属性数据格网化、格网化数据获取与管理、资源环境数据共享与应用。
Comprehensive scientific expedition is one of the important approaches to acquire regional resources and environment background data. China is a vast country with complex geographical conditions. However, the incompatibly weak capacity in data collection has raised great attention to Chinese government for the long-term development of integrated environmental and scientific investigation. Nonetheless, many setbacks exist in the integrated applications of acquired data due to the differences in spatio- temporal scales, survey contents and technical standards of historical scientific investigations. Thus, although we have acquired more and more data during long term investigations, it is still quite difficult to use these data correlatively, which also leads to the lack of understanding about the country's natural resources and surrounding environment. Thereby, some questions arise, such as is it possible to get and further manage the investigated data by the methods of gridding;are there any existing norm standards, which are suitable for the investigation of natural resources and environment, to help aggregate the long-term accumulated data and guide the dynamic monitoring process in the near future; and is it truly feasible to build a long term medium scale system for natural resources and environment survey? Based on an ongoing integrated investigation on natural and environmental resources, this paper, brings up with some in-depth thoughts, such as the grid system for resources and environment surveys, the standards and subdivision of geographical grids, the norm standards of resources and environment investigation,the appropriate scale for resources and environment survey, the gridding process of attribute data, the acquisition and management of grid-based data, and the sharing and application of resources and environmental data.
Comprehensive scientific expedition is one of the important approaches to acquire regional resources and environment background data. China is a vast country with complex geographical conditions. However, the incompatibly weak capacity in data collection has raised great attention to Chinese government for the long-term development of integrated environmental and scientific investigation. Nonetheless, many setbacks exist in the integrated applications of acquired data due to the differences in spatio- temporal scales, survey contents and technical standards of historical scientific investigations. Thus, although we have acquired more and more data during long term investigations, it is still quite difficult to use these data correlatively, which also leads to the lack of understanding about the country's natural resources and surrounding environment. Thereby, some questions arise, such as is it possible to get and further manage the investigated data by the methods of gridding;are there any existing norm standards, which are suitable for the investigation of natural resources and environment, to help aggregate the long-term accumulated data and guide the dynamic monitoring process in the near future; and is it truly feasible to build a long term medium scale system for natural resources and environment survey? Based on an ongoing integrated investigation on natural and environmental resources, this paper, brings up with some in-depth thoughts, such as the grid system for resources and environment surveys, the standards and subdivision of geographical grids, the norm standards of resources and environment investigation,the appropriate scale for resources and environment survey, the gridding process of attribute data, the acquisition and management of grid-based data, and the sharing and application of resources and environmental data.
引文
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[42]Maryland.Recreation Atlas[EB/OL].http://geodata.md.gov/recreationatlas/.
[43]曾梦岐,谭平嶂,陈剑锋.美军GIG3.0进展研究[J].信息安全与通信保密,2011(12):50-53.
[2]于德福.中国地质工作新的里程碑——国土资源大调查巡礼[J].国土资源遥感,2010(9):4-15.
[3]吴晓青.环保部:将适时公布全国土壤环境质量状况调查结果[Z].2012.
[4]王卷乐,朱立君,孙崇亮.资源环境综合科学考察中的多维数据集成管理模式研究与实践——以中国北方及其毗邻地区综合科学考察为例[J].自然资源学报,2011,26(7):1129-1138.
[5]陈述彭,陈秋晓,周成虎.网格地图与网格计算[J].测绘科学,2002(4):1-6.
[6]周成虎,欧阳,杨辽,等.矢量多边形栅格化的保积优化模型[J].中国科学D辑:地球科学,2006(S2):157-163.
[7]李德仁,邵振峰.空间信息多级网格及其功能[J].地理空间信息,2005(4):1-3.
[8]陈述彭.人口统计的时空分析[J].中国人口、资源与环境,2002(4):5-9.
[9]武继磊.Lattice数据分析方法、模型及其应用[D].北京:中国科学院研究生院,2005.
[10]杨皓月.地理国情监测地理格网划分及统计[D].阜新:辽宁工程技术大学,2012
[11]张永生,贲进,童晓冲,等.基于球面六边形网格系统的空间信息处理方法[J].测绘科学技术学报,2006(2):110-114.
[12]程承旗,任伏虎,濮国梁,等.空间信息剖分组织导论[M].北京:科学出版社,2012.
[13]Goodchild M F,Yang S.A hierarchical data structure for global geographic information systems[J].GVGIP:Graphical Models and Image Processing,1992,54(1):31-44.
[14]Sahr K,White D,Kimerling A J.Geodesic discrete global grid systems.cartography and geographic information science[J].Cartography and Geographic Information Science,2003,30(2):121-134.
[15]李秦,高锡章,张涛,等.最优分割尺度下的多层次遥感地物分类实验分析[J].地球信息科学学报,2011,13(3):409-417.
[16]Dutton G.Universal geospatial data exchange via global hierarchical coordinates[C].International Conference on Discrete Global Grids,California,Santa Barbara,2000.
[17]赵学胜,陈军,王金庄.基于O-QTM的球面VORONOI图的生成算法[J].测绘学报,2002,31(2):157-163.
[18]李德仁,邵振峰,朱欣焰.论空间信息多级格网及其典型应用[J].武汉大学学报(信息科学版),2004,29(11):945-950.
[19]周成虎,欧阳,杨辽,等.矢量多边形栅格化的保积优化模型[J].中国科学D辑:地球科学,2006(S2):157-163.
[20]The Federal Geographic Data Committee.The US National Grid(USNG):A Simple and Powerful Geospatial Tool[EB/OL].http://www.fgdc.gov/usng,2001.
[21]Survey Ordnance.Using the National Grid[EB/OL].http://www.ordnancesurvey.co.uk,2006.
[22]GB/T 12409-2009.Geographic grid[S].2009.
[23]姜超,徐青,孙庆辉,等.基于OGCWPS的GIS空间分析方法[J].测绘科学,2011,36(6):198-200.
[24]ISO 19101.地理信息标准参考模型简介[S].2002.
[25]标准体系表编制原则和要求[S]GB/T 13016-2009.2009.
[26]樊杰,王亚飞,汤青,等.全国资源环境承载能力监测预警(2014版)学术思路与总体技术流程[J].地理科学,2015(1):1-10.
[27]史文中,秦昆,陈江平,等.可靠性地理国情动态监测的理论与关键技术探讨[J].科学通报,2012(24):2239-2248.
[28]国务院第一次全国地理国情普查领导小组办公室.GDPJ 01—2013[S].2013.
[29]Treitz P.Variogram analysis of high spatial resolution remote sensing data:An examination of boreal forest ecosystems[J].International Journal of Remote Sensing,2001,22(18):3895-3900.
[30]刘玉锋,陈冬花,郑朝贵.高分辨率遥感数据云杉林林分冠幅估计[J].新疆农业大学学报,2013(2):153-157.
[31]柏中强,王卷乐,杨飞.人口数据空间化研究综述[J].地理科学进展,2013,32(11):1692-1702.
[32]Liao Y,Wang J,Meng B,et al.Integration of GP and GA for mapping population distribution[J].International Journal of Geographical Information Science,2008,24(1):47-67.
[33]Liu X H,Kyriakidis P C,Goodchild M F.Population-density estimation using regression and area-to-point residual kriging[J].International Journal of Geographical Information Science,2008,22(4):431-447.
[34]Azar D,Engstrom R,Graesser J,et al.Generation of finescale population layers using multi-resolution satellite imagery and geospatial data[J].Remote Sensing of Environment,2013,130:219-232.
[35]冯甜甜.基于高分辨率遥感数据的城市精细尺度人口估算研究[D].武汉:武汉大学,2010.
[36]Stevens F R,Gaughan A E,Linard C,et al.Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data[J].PLo S ONE,2015,10(2):e107042.
[37]http://na.unep.net/siouxfalls/datasets/datalist.php[EB/OL].
[38]Balk D L,Deichmann U,Yetman G,et al.Determining global population distribution:methods,applications and data[J].Advances in Parasitology,2006,62:119-156.
[39]Dobson J E,Bright E A,Coleman P R,et al.Land Scan:A global population database for estimating populations at risk[J].Photogrammetric engineering and remote sensing,2000,66(7):849-857.
[40]World Pop.The World Pop project[EB/OL].http://www.worldpop.org.uk/.
[41]江东,杨小唤,王乃斌,等.基于RS、GIS的人口空间分布研究[J].地球科学进展,2002,17(5):734-738.
[42]Maryland.Recreation Atlas[EB/OL].http://geodata.md.gov/recreationatlas/.
[43]曾梦岐,谭平嶂,陈剑锋.美军GIG3.0进展研究[J].信息安全与通信保密,2011(12):50-53.