Topic Editors


2. Fondazione per il futuro delle città, Firenze, Italy


Google Earth Engine Applications for Monitoring Natural Ecosystems and Land Use
Topic Information
Dear Colleagues,
Global ecosystems play a major role in mitigating global warming, but climate change is increasing the number and the magnitude of stressors, making ecosystem monitoring more important than ever. In this context, remote sensing data and the Google Earth Engine cloud computing platform represent crucial tools for comprehensively and exhaustively monitoring ecosystems globally. Google Earth Engine provides access to the vast majority of freely available, public, multi-temporal remote sensing data and offers free cloud-based computational power to apply complex algorithms over large areas.
The Topic “Google Earth Engine Applications for Monitoring Natural Ecosystems and Land Use” welcomes high-quality studies that focus on applications exploiting GEE for monitoring natural ecosystems and land use. Relevant themes include, but are not limited to: (a) ecosystem disturbance near real-time prediction and monitoring, (b) carbon storage prediction, (c) forest species classification, (d) forest harvestings, wind damages, and fires prediction, (e) climate change impact on global ecosystems, (f) drought monitoring, (g) innovative time series analysis and machine learning approaches for ecosystem monitoring, (h) development and validation of ecosystem disturbance monitoring methods, (i) forest degradation monitoring, (j) natural disaster monitoring, (k) precision and accuracy estimation and modeling of forest structure and function parameters, (l) agroforestry ecosystem visualization and management, (m) land cover and land-use change monitoring, and (n) hydrological and eco-hydrological processes monitoring.
Prof. Dr. Gherardo Chirici
Dr. Saverio Francini
Noel Gorelick
Prof. Dr. Nicholas Coops
Topic Editors
Keywords
- forests
- ecosystems
- land-cover and land-use change
- Google Earth Engine (GEE)
- remote sensing
- hydrology
- artificial intelligence
- big data
- decision making
- carbon storage estimation
- sustainability
- biodiversity
Participating Journals
Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC | |
---|---|---|---|---|---|---|
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Agriculture
|
3.408 | 3.1 | 2011 | 18.6 Days | 2000 CHF | Submit |
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Earth
|
- | - | 2020 | 16.2 Days | 1000 CHF | Submit |
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Forests
|
3.282 | 4.0 | 2010 | 18.3 Days | 2000 CHF | Submit |
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Land
|
3.905 | 3.2 | 2012 | 12.7 Days | 2200 CHF | Submit |
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Remote Sensing
|
5.349 | 7.4 | 2009 | 19.7 Days | 2500 CHF | Submit |