学术
摘 要:
以紫金山国家级森林公园为研究对象,以遥感图像处理与地理信息系统软件ERDAS 8.7、ArcGis 9.0为空间分析平台,分别选取研究地区2000年（IKNOS）、2002年（SPOT5）、2004（QuickBird）3种不同时期的遥感数据,在监督分类的基础上进行邻域分析,构建风景林未来10年发展的情境。从景观空间格局和景观资源保护目标两个方面对多情境规划方案进行评价,并制定了风景林的优化情境规划。研究表明：与研究地区2002年的景观结构相比,优化情境规划方案中农地完全消失,阔叶林、企业机关用地、旅游服务设施用地所占比重分别下降了18.48%、2.30%、2.85%,而针叶林、园林绿地、混交林的比例分别上升了13.26%、14.81%、4.47%,从而提高了森林公园风景林四季的美景度,满足了风景旅游、森林培育、市民休闲、生物多样性保护的多种需求。[著者文摘]
文章出处:
《南京林业大学学报：自然科学版》-2007年31卷5期 -29-33页
栏目信息:
分 类 号:
文献标识码:
A
文章编号:
1000-2006（2007）05-0029-05
A Study on Scenario Planning of Scenic Forest in Zijinshan Mountain of Nanjing
LI Ming-yang, SHEN Shi-guang, WU Yi, XI Qing （College of Forest Resources and Environment Nanjing Forestry University, Nanjing 210037, China）
Abstract:
Zijinshan Mountain national forest park is selected as a case study area. Remote sensing and GIS software Erdas 8.7, ArcGis 9.0 are employed as the spatial platforms of doing scenario planning. Three difterent periods remote sensing data in the years of 2000 （IKNOS） ,2002 （SPOTS） and 2004 （Quickgird） are used to do the supervised classification and neighborhood analysis to build three scenarios of scenic forest in ten years. After comparisons of the three scenarios from two aspects of landscape spatial pattern and protection goals, an optimized planning plan is made. Results show that, compared with the landscape pattern of 2002, farm land disappears completely in optimized planning plan. The proportion of broadleaved forest, industry and management land, land for touring service facility decreases by 18.48%, 2.30%, 2.85% respectively. The conifers, gardens, mixed forest increase by 13.26%, 14.81%, 4.47% respectively. The scenic beauty grade of scenic forest inwinter is improved, the multiple goals of landscape tourism, forest cultivation,supplying en tertainment places for local residents, biodiversity conservation can be met at the same time Thus the theoretical basis for sustainable management plan of scenic forest is put forward.[著者文摘]
Key words:
Scenic forest ; Geomatics ; Scenario planning; Zijinshan Mountain
基金资助:
国家自然科学基金资助项目（30571490）
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