Remote mapping and characterization of riparian forests and fish habitat potential using advanced remote sensing approaches

使用先进的遥感方法对河岸森林和鱼类栖息地潜力进行遥测和表征

• 批准号: 517589-2018
• 负责人: Coops, Nicholas
• 金额: $ 11.95万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=697843
• 关键词: Remote; mapping; characterization; riparian; forests

Riparian forests, and the stream habitats within them, are critical important for the sustainable management of Canada's forested ecosystems. Fisheries sensitive watersheds are those designated to be highly important ecologically and once designated, require special forest management activities to ensure that practices undertaken maintain the natural watershed processes and conserve the ecological attributes necessary to protect and sustain fish and their habitat. With advances in remote sensing technology, the potential to derive a suite of stream and riparian zones forest attributes is now possible. Airborne laser scanning (ALS) has been shown to be highly effective for defining accurate and detailed stream networks, as well as for characterizing stream width and gradients, the potential of vegetation to shade and regulate stream temperature and estimate the likelihood of fish habitat. Our long-term research objective is to collaborate with Provincial and Federal forest agencies, as well as forest companies, to promote new tools to map, classify, and analyze streams and associated riparian areas in forested ecosystems. Our ultimate goal is to demonstrate that ALS data can provide accurate characterizations of stream networks and associated riparian vegetation, at markedly greater spatial detail than is possible with current data sources, and that these improved information sources can greatly enhance natural resource management and planning for these stream-riparian systems.

河岸森林和其中的溪流栖息地对加拿大森林生态系统的可持续管理至关重要。渔业敏感流域是指那些被指定为生态上非常重要的流域，一旦被指定，就需要特别的森林管理活动，以确保所采取的做法维持自然的流域过程，并保存保护和维持鱼类及其生境所必需的生态特性。随着遥感技术的进步，现在有可能获得一套河流和河岸带森林属性。机载激光扫描（ALS）已被证明是非常有效的定义准确和详细的河流网络，以及表征河流宽度和梯度，植被遮荫和调节河流温度的潜力，以及估计鱼类栖息地的可能性。我们的长期研究目标是与省级和联邦森林机构以及森林公司合作，推广新的工具来绘制、分类和分析森林生态系统中的溪流和相关的河岸区域。我们的最终目标是证明ALS数据可以提供河流网络和相关河岸植被的准确特征，其空间细节明显高于现有数据源，并且这些改进的信息源可以极大地增强这些河流-河岸系统的自然资源管理和规划。