[1]马仁锋,侯 勃,窦思敏,等.森林资源资产地域审计重点筛选模型构建及应用[J].南京林业大学学报(自然科学版),2018,42(04):046-52.[doi:10.3969/j.issn.1000-2006.201711009]
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森林资源资产地域审计重点筛选模型构建及应用
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《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

卷:
42
期数:
2018年04期
页码:
046-52
栏目:
研究论文
出版日期:
2018-07-12

文章信息/Info

Title:
Model construction and application of forest resource assets key auditcity
文章编号:
1000-2006(2018)04-0046-07
作者:
马仁锋侯 勃窦思敏王腾飞
宁波大学地理与空间信息技术系,浙江 宁波 315211
Author(s):
MA Renfeng HOU Bo DOU Simin WANG Tengfei
Department of Geography & Spatial Information Techniques,Ningbo University, Ningbo 315211, China
关键词:
林地 破碎度 森林资源 资产审计 国土审计 浙江省
Keywords:
Keywords:forest land fragmentation forest resource assets audit territorial audit Zhejiang Province
分类号:
S758; F326
DOI:
10.3969/j.issn.1000-2006.201711009
文献标志码:
A
摘要:
【目的】筛选区域森林资源资产审计重点地块,既可以提高中国森林资源资产审计效率,又可以完善国土审计的地理信息应用技术。【方法】基于林地景观格局视域,运用ENVI和ArcGIS将浙江省各市域2000、2005、2010、2015年4期遥感影像数据转换为网格分辨率为30 m ArcGrid数据格式,并运用Fragstats 3.3进行林地破碎度指标计算,构建基于林地破碎度综合指数和集中度指数的森林资源资产地域审计重点筛选模型,用此模型筛选浙江省森林资源资产重点审计城市。【结果】所构建的模型有望提高政府国土自然资源资产审计重点甄别效率; 利用所构建的模型对浙江省11个地级市森林资源资产进行评估,筛选出舟山、金华、湖州、嘉兴和绍兴5个重点审计城市为全省森林资源资产地域审计的重点区域,佐证了模型科学性; 模型在浙江省的案例应用表明,在森林资源资产审计中将森林资源清查和现代地理信息技术有机结合,可提升国土审计的地域主体识别效率与审计结果的可视化解读。【结论】基于林地景观格局的视角构建森林资源资产审计重点区域识别模型,可将提高审计效率的基点落在林地景观变动幅度较大行政区层面。
Abstract:
Abstract: 【Objective】Screening key areas of forest resources assets can not only improve the territorial audit efficiency of forest resources in China, but also improve the application of geo-information technology in land audit.【Method】Based on the forest landscape pattern and the statistics of land use in Zhejiang Province(Zhejiang Statistical Yearbook, 2014), ENVI and ArcGIS were used to convert the remote sensing image data of Zhejiang Province in 2000, 2005, 2010 and 2015 into ArcGrid data format. A lattice resolution of 30 m and Fragstats 3.3 was used to calculate the forest fragmentation index as a basis for screening key forest resource assets cities in Zhejiang Province. 【Result】In this paper, the key screening model of forest resource assets based on forest fragmentation index and concentration index is effective. It is expected to improve the efficiency of auditing of natural resources assets. Using the constructed model to evaluate the forest resource assets of 11 cities in Zhejiang Province. Five key auditing cities of Zhoushan, Jinhua, Huzhou, Jiaxing and Shaoxing were selected with the scientific nature of the model being supported. Zhejiang empirical evidence from the forest resource asset audit focuses on the forest resource inventory and modern geographic information technology combined. This enhances the territorial audit of the regional main body by recognizing the efficiency and audit results through visual interpretation.【Conclusion】The paper discusses the key area identification model of forest resources assets audit based on forest landscape pattern and how it will improve the efficiency of the audit in larger landscape with changes in the administrative area of woodland.

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备注/Memo

备注/Memo:
基金项目:浙江省社科规划重大招标项目(16YSXK04ZD-1YB) 第一作者:马仁锋(marfxf@126.com),副教授,博士。
更新日期/Last Update: 2018-07-27