Forest Biomass Change and Carbon Dynamics
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Forest Remote Sensing".
Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 2420
Special Issue Editors
Interests: optical and microwave remote sensing; biomass; forest ecology; spatial & temporal analisys; forest monitoring; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; biogeography; ecology; land cover dynamics; forests and coastal ecosystems (including mangroves)
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; global above-ground forest biomass; ecology; forest ecosystems
Interests: landscape and climate research; land surface modelling; terrestrial remote sensing; synthetic aperture radar (SAR); light detection and ranging (LIDAR); forest monitoring, carbon cycle and climate change
Special Issues, Collections and Topics in MDPI journals
Interests: tropical ecosystems; terrestrial remote sensing; canopy roughness; forest structure; light detection and ranging (LIDAR); forest dynamics and climate extremes
Interests: climate change; terrestrial remote sensing; forest monitoring; REDD+; aboveground forest biomass; permafrost; landscape restoration
Interests: terrestrial remote sensing; synthetic aperture radar (SAR) and interferometry applications; light detection and ranging (LIDAR, TLS); forest and agricultural monitoring; boreal and savanna ecosystems
Special Issue Information
Dear Colleagues,
Forests play a fundamental role in the global carbon cycle. Ensuring robust quantification of forest biomass change is essential, as there are substantive requirements for consistent and dependable information to support climate and carbon science and modelling, obligations under national and international agreements, and future planning (e.g., for the adaption to and mitigation of climate change). Over recent years, considerable effort has been placed into estimating forest carbon stocks by generating regional to global maps of aboveground biomass from Earth observation data. These efforts often consisted of a single snapshot of the carbon stock at a given time. However, processes leading to changes in stocks, such as deforestation, degradation, afforestation, and regeneration, are constantly occurring, and attention is therefore increasingly shifting towards quantifying forest biomass at finer spatial resolutions and shorter temporal frequencies. This presents a particular challenge because of the wide range and sensitivities of sensors used for biomass retrieval, the differences in algorithms employed, the different observation modes and characteristics of observing sensors, and, critically, the statistical aspects of measuring change.
This Special Issue seeks to improve our understanding of current methods and datasets to characterise forest carbon dynamics and biomass change worldwide, focusing on the principles that underlie changes in forest biomass associated with changes in extent, structure, function, and floristic composition. Therefore, submissions covering one or several of the following (non-exhaustive) activities in the scope of forest carbon dynamics and biomass change are very welcome:
The nature of change
- Drivers of biomass change.
- Spatial and temporal descriptors of change and links with forest structural attributes (e.g., biomass/carbon density, height and cover).
- Detected and omitted changes in forest biomass.
Quantifying change at or near the ground
- Use of ground (e.g., terrestrial laser scanners) or near-ground sensors (drones).
- Role of VHR sensors on aircraft or satellites.
- Recent or forthcoming methodologies for quantifying biomass change.
- Application and development of allometric models.
Quantification of uncertainty
- Adaptation of remote sensing to the production of biomass estimates.
- Establishment of confidence in estimates.
- Provision of metadata to users.
Space and time considerations
- Data combinations for assessing carbon dynamics.
- Role of different sensors.
- Data fusion.
Change algorithms and methods
- New and upcoming approaches.
- The role of time-series datasets (optical and/or radar).
- Integration of model-based approaches to change detection and quantification.
- Combining land cover information and biomass products.
Validation of biomass change products from Earth observations
- Methods, standards and best practices.
- Approaches to validation (e.g., long‐term field plots, terrestrial laser scanner data and/or higher resolution time-series imagery data).
User requirements
- Contributions to national and international initiatives and obligations (e.g. REDD+, UNFCCC).
Dr. Pedro Rodríguez-Veiga
Prof. Dr. Richard Lucas
Ms. Heather Kay
Prof. Dr. Heiko Balzter
Dr. Yhasmin Mendes de Moura
Mr. Frank Martin Seifert
Prof. Dr. Christiane Schmullius
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Biomass
- Carbon dynamics
- Time series analysis
- Change detection
- Forests
- Uncertainty
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