This Special Issue Remote Sensing for Biodiversity Mapping and Monitoring aims to publish original research that specifically addresses various aspects of biodiversity mapping and monitoring over space and time using remote sensing from local to global scales. We invite a wide range of contributions from methodological to applied and multidisciplinary research about the following (non-exclusive) topics:
- Taxonomic, structural, and functional diversity mapping from RS data;
- Species distribution modeling based on RS data;
- Retrieving biophysical and biochemical variables from RS data and radiative transfer models;
- Assessing and predicting ecosystem services from RS data;
- Ecosystems health monitoring from RS data;
- Reconstructing ecosystem trajectories over time from RS data;
- Advanced machine learning techniques (deep learning, transfer learning, active learning) for biodiversity mapping based on RS data;
- Fusion of multimodal images (optical/thermal/radar/lidar) to improve biodiversity mapping and monitoring.
Reviews covering one or more topics are welcome. We encourage the authors to make their sample data and computational tools publicly available through online resources to ensure the reproducibility and transparency of all the experiments.
Deadline for manuscript submissions: 30 November 2020
Dr. David Sheeren Dr. Jean-Baptiste Féret Dr. Laurence Hubert-Moy Dr. Sophie Fabre (Guest Editors)
More details on MDPI Remote Sensing Journal website.