Remote Sensing to Detect Urban Ecology, to Reveal Provisions of Urban Ecosystem Services and as Basis to Develop Nature-Based Solutions at High Spatial Resolution
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".
Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 9112
Special Issue Editor
Interests: green infrastructure; urban ecology; ultra-high-resolution urban land use / land cover classification; urban streams
Special Issue Information
Dear Colleagues,
The ecology of urban areas is increasingly being investigated in the context of the benefits that ecological features deliver to society conceptualized as urban ecosystem services. Approaches such as green infrastructures or nature-based solutions are developed and their implementation is promoted to simultaneously solve ecological and societal problems. The basis for the spatial analysis of the ecological potential of existing urban green spaces and of those to be developed is often remotely sensed data. Because of the complex and usually detailed land cover structures in urban areas, a high spatial resolution of information is needed. For this Special Issue, we call for studies that present advances in remotely sensed detection of urban ecological features (e.g., small-scale structures, blue-green networks), innovative methodologies to reveal provisions of urban ecosystem services, as well as approaches to develop and assess nature-based solutions on the basis of remote sensing data at high spatial resolution. Not limited to, but of special interest are urban river corridors and densely urbanized areas with limited ecological functions where retrofitted and multi-functional nature-based solutions are developed and assessed.
Prof. Dr. Jochen Hack
Guest Editor
Manuscript Submission Information
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Keywords
- Urban ecology
- urban ecosystem services
- nature-based solutions
- urban green infrastructure
- high resolution
- multi-functionality
- retrofitting
- urban river corridors
