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基于SOFM网络的京津冀地区生态系统服务分区
引用本文:马程,李双成,刘金龙,高阳,王阳. 基于SOFM网络的京津冀地区生态系统服务分区[J]. 地理科学进展, 2013, 32(9): 1383-1393. DOI: 10.11820/dlkxjz.2013.09.008
作者姓名:马程  李双成  刘金龙  高阳  王阳
作者单位:1. 北京大学城市与环境学院地表过程分析与模拟教育部重点实验室, 北京100871;2. 北京大学深圳研究生院城市人居环境科学与技术重点实验室, 深圳518055
摘    要:生态系统服务与土地利用之间有密切关联,生态系统服务分区对区域生态系统服务的管理和土地利用政策的制定有重要意义。本文以京津冀地区为研究区,依据IGBP2001-2009年间的土地利用数据,在对谢高地等制定的中国陆地生态系统单位面积服务价值系数进行校正的基础上,核算了区域内各县(市)级行政单元单位面积生态系统服务的价值量,构建自组织特征映射网络(SOFM)对京津冀的生态系统服务进行分区,并用ArcGIS识别了不同服务类型的热点区,归纳和总结了每个分区的主导服务类型,并结合全国功能主体区划对该区域未来的发展重点和土地利用政策提出建议。依据分类结果,可将京津冀地区分为4 个区域:Ⅰ. 坝上高原和冀西北山区;Ⅱ. 燕山和太行山地;Ⅲ. 冀中南平原区;Ⅳ. 环渤海滨海区。2001-2009年间,除Ⅳ区的生态系统服务价值呈现增加趋势外,其他区域均有不同程度的减少,减少程度依次为Ⅱ>Ⅰ>Ⅲ。Ⅰ区域发展重点为防风固沙和水源涵养;Ⅱ区域为生物多样性重点保护区域;Ⅲ区域应重点调整城镇用地的比例,适当增加其他生态系统服务;Ⅳ区域应增加水源涵养价值,治理土壤盐渍化。

关 键 词:SOFM网络  分区  京津冀地区  生态系统服务  
收稿时间:2013-01-01
修稿时间:2013-07-01

Regionalization of ecosystem services of Beijing-Tianjin-Hebei Area based on SOFM neural network
MA Cheng , LI Shuangcheng , LIU Jinlong , GAO Yang , WANG Yang. Regionalization of ecosystem services of Beijing-Tianjin-Hebei Area based on SOFM neural network[J]. Progress in Geography, 2013, 32(9): 1383-1393. DOI: 10.11820/dlkxjz.2013.09.008
Authors:MA Cheng    LI Shuangcheng    LIU Jinlong    GAO Yang    WANG Yang
Affiliation:1. Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China;2. Key Laboratory for Environmental and Urban Sciences, Shenzhen Graduate School, Peking University, Shenzhen 518055, China
Abstract:Abstract:Studies showed that ecosystem services are closely related to land utilization. Human activities have been relentlessly developing and using the land, causing serious exhaustion of land resources and making ecological environment change from bad to worse, which in turn poses severe threat to the sustainable utilization of ecosystem services. For sustainable land use and human well-being promotion, it is important to integrate ecosystem service into the land use decision-making process. Creating partitions based on different ecosystem services is of great significance for land use and management of ecosystem services. Taking Beijing-Tianjin-Hebei as a case area, the study in this report assessed the ecosystem service value of each unit based on IGBP land use data from 2001 to 2009. Regionalization of ecosystem service was created by SOFM Neural Network. In order to recognize the main ecosystem services of each region, the study calculated the hot spots of ecosystem service by ArcGIS. Combined with national major function oriented zoning, the study put forward proposals for making the policies on the future land development. The results indicated that Beijing-Tianjin-Hebei Area can be divided into four regions based on ecosystem service values: Ⅰ. Bashang Plateau and northwest Hebei mountain region, Ⅱ. Yanshan and Taihang Mountains region, Ⅲ. Central and southern Hebei Plain region, and Ⅳ. Bohai Sea coastal area. The ecosystem service value of Bohai Sea coastal area continued to rise while that of the other areas decreased to different degrees: Ⅱ>Ⅰ>Ⅲ. Wind and spring floods eroded soils in region Ⅰ and the soil are quite fragile. In order to conserve water and soil, proper land-use policies should be made for region Ⅰ. The key restoration measures include improvement of rangeland management, financial incentives to elimination of overstocking, and re-vegetation with appropriate rest periods during which grazing should be banned. Most of the hot spots of biodiversity service are distributed in region Ⅱ, but the value goes down with each passing year. Therefore, policy makers should pay more attention to biodiversity conversation in this region. As part of rapid urbanization efforts, the type of ecosystem service in region Ⅲ is quite simple. Food production is the dominant service while other services are quite low especially for water conservation and soil formation. On the premise of guaranteeing food production, proper policies should be made to adjust the proportion of urban land use to increase other ecosystem service such as carbon sink and pollination services. The resources of beach soils of region Ⅳ are rich, but the utilization ratio is low because of serious soil salinization. It is urgent for decision makers to provide guidance for salinization control, such as promoting water saving agricultural techniques and reducing artificial recharge of groundwater, to limit the increase of salinity. In addition, region Ⅳ should make full use of wetland because wetland can provide many services such as water conservation. The results indicated that SOFM Neural Network has strong advantage in objectivity and clear classification and is of great importance as a supplement to ecosystem service regionalization. The dividing method of GIS and SOFM clustering can identify regional differences and similarities of ecosystem services value and works well on ecosystem services regionalization.
Keywords:ecosystem service  SOFM neural network  regionalization  Beijing-Tianjin-Hebei Area
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