Assessing Forest Landscape-Level Responses to Climate Change by Remote Sensing Analysis and Ecological Modelling
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Forest Remote Sensing".
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 11977
Special Issue Editor
Interests: disturbance ecology; forest ecology; ecosystem ecology; environmental science
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Exploration of the ecological effects of climate change is among the most urgent challenges in global change ecology. Ecosystems are interconnected in multiple ways at the landscape level such that a landscape-level approach is necessary to assess the ecological responses to climate change. Due to the broad spatial coverage, frequent lack of replicates, and uncertainties and complexity of climate effects, remote sensing analysis and ecological modeling are of increasing importance in the assessment of landscape-level responses to climate change.
This Special Issue welcome research using broadly defined remote sensing techniques and/or the application of ecological modeling to assess and/or predict climate effects on structure and function of all types of landscapes. We welcome a wide range of submissions including but not limited to the application of rapidly evolving remotely sensed data and diverse ecological modeling (e.g., niche modeling, modeling involving graph theory, Bayesian belief networks, Markov chain, etc.) to assess broad-scale responses to climate change. Submissions focusing on methodological development in remote sensing techniques and/or ecological modeling approaches for assessing landscape–climate interactions are also encouraged. In addition, we welcome both original studies and reviews and syntheses so long as they fit the main theme of this Special Issue.
Prof. Dr. Teng-Chiu Lin
Guest Editor
Manuscript Submission Information
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Keywords
- climate change
- ecological modeling
- landscape
- resilience
- Markov chain
- graph theory
- Bayesian belief network
- niche modeling
- vegetation index