Forest ecosystems play important roles in human living environments, climatic change, and carbon cycling. Mapping, modeling, and estimating forest volume/biomass/carbon has gained great attention in the past three decades, and considerable research has been conducted using remotely sensed data at different scales. Data from different sensors with different resolutions including ground/mobile/UAV/airborne/spaceborne Lidar, radar, and optical are available and provide new opportunities to develop novel methods for accurate estimation of forest attributes. The special issue solicitates new advances on forest volume/biomass/carbon estimation using multi-source data, advanced statistical modeling and estimation algorithms, and uncertainty analysis. The special issue will focus on the following topics:
- Advanced methods for forest volume/biomass/carbon modelling, mapping, and estimation
- Advanced methods to employ multi-source data for forest volume/biomass/carbon estimation
- Advanced methods to integrate multi-scale remotely sensed data for modeling forest volume/biomass/carbon
- Approaches using time series of remotely sensed data to model forest volume/biomass/carbon dynamics
- Impacts of forest disturbance on forest volume/biomass/carbon change
- Uncertainty analysis for forest volume/biomass/carbon estimation
- Comprehensive literature review on forest volume/biomass/carbon modeling
