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林业科学 ›› 2010, Vol. 46 ›› Issue (7): 155-163.doi: 10.11707/j.1001-7488.20100723

• 论文 • 上一篇    下一篇

3S技术在鸟类栖息地研究中的应用

江红星1,刘春悦2,3,侯韵秋1,钱法文1   

  1. 1.中国林业科学研究院森林生态环境与保护研究所国家林业局森林保护学重点实验室 北京 100091;2.中国科学院东北地理与农业生态研究所 长春 130012;3.中国科学院研究生院 北京 100049
  • 收稿日期:2008-12-05 修回日期:2009-04-17 出版日期:2010-07-25 发布日期:2010-07-25

Application of RS, GIS and GPS Techniques in Study of Avian Habitat

Jiang Hongxing1;Liu Chunyue2,3;Hou Yunqiu1;Qian Fawen1   

  1. 1.Key Laboratory of Forestry Protection of State Forestry AdministrationResarch Institute of Forest Ecology, Environment and Protection, CAF Beijing 100091;2.Northeast Institute of Geography and Agricultural Ecology, CAS Changchun 130012;3.Graduate University of Chinese Academy of Sciences Beijing 100049
  • Received:2008-12-05 Revised:2009-04-17 Online:2010-07-25 Published:2010-07-25

摘要:

3S技术在鸟类栖息地研究中发挥越来越重要的作用,特别是在不同尺度条件下,以及对于一些广袤且偏远的地区,能够有效地分析、评估、监测和预测鸟类与栖息地关系,推动实现物种保护管理目标。本文主要回顾遥感数据源、遥感信息提取方法以及地理信息系统技术在鸟类栖息地研究中的应用。同时,分析影像数据源和影像时相的选择,以及遥感信息提取和鸟类野外调查方法等存在的缺陷和不足,提出一些具体的改进和完善措施。

关键词: 3S技术, 鸟类栖息地, 遥感信息提取, 栖息地监测与评估, 物种分布预测

Abstract:

Remote sensing (RS), Geographic Information Systems (GIS) and Global Positioning System (GPS) technologies play increasingly important role in ornithology study, including habitat evaluation, habitat modeling and monitoring programmes and in achieving overall wildlife conservation and management objectives effectively, especially with a large range of scales and for remote regions where few habitat studies have been undertaken to date due to difficult to access but those studies are urgently needed. In this paper, satellite-based imageries, methodologies in acquisition of satellite information, and application of GIS in avian habitat study were reviewed. In order to improve the quality of inference and for comparative analyses, some improvement suggestion was proposed based on the analysis of selection of source and time of satellite imageries, and approaches of information acquisition and bird ground survey.

Key words: 3S technologies, avian habitat, remote sensing information acquisition, habitat monitoring and evaluation, prediction of species distribution