About the training
Our SERVIR-HKH Initiative and SilvaCarbon are organising a training workshop on improving forest carbon estimation and degradation monitoring in Nepal. The training will cover three components that support forest carbon emission monitoring efforts: terrestrial laser scanning (TLS), the Global Ecosystem Dynamics Investigation (GEDI), and continuous degradation detection (CODED) algorithm.
Participants will learn necessary skills and knowledge to collect high-quality TLS data for biomass estimation at the individual tree scale, which will help improve the capacity to scale biomass estimations from the plot to the regional level. Participants will also become familiar with Online Biomass Inference using Waveforms And iNventory (OBIWAN), GEDI-incorporated model-based aboveground biomass estimation, and tools to understand timeseries wall-to-wall biomass estimation. They will be introduced to CODED algorithms for tracing forest degradation.
We developed this training content and delivery in collaboration with SilvaCarbon’s TLS team, SilvaCarbon, NASA SERVIR Applied Sciences Team (AST), and the Government of Nepal’s Forest Research and Training Centre (FRTC).
Objectives
- Familiarise participants with biomass estimation tools and techniques including TLS and GEDI.
- Share background and updates on the CODED algorithm, used by FRTC for forest degradation monitoring, and discuss further improvements for the application of CODED. Share the planned activities and methodology for the development of forest emission reduction through both statistical estimation and improved resource mapping. This innovative approach aims to provide reliable spatially consistent carbon predictions on an annual basis.
- Seek feedback from participants regarding the performance of TLS- and GEDI-based models and gather suggestions for possible upgrades. This feedback will help refine the methods and models to meet the specific needs of stakeholders.
- Bring together relevant stakeholders who are actively involved in forest carbon-related works and management. The training workshop will provide a platform for them to share their experiences, challenges, and emerging forest monitoring requirements.
Expected outcomes
Upon completion of the training workshop, the participants will have a better understanding of the applications of TLS, GEDI, and CODED in monitoring forest condition and carbon stocks, enabling them to apply this knowledge in their working areas. At the end of the training workshop, participants will outline practical application and integration of GEDI, TLS, and field-level data.
Expected participants
We will organise the training in-person for 24 participants from national agencies in Nepal, including FRTC, Ministry of Forest and Environment (MoFE), REDD Implementation Centre, Department of Forest and Soil Conservation (DoFSC), and ICIMOD.
Resource persons/facilitators
Amul Kumar Acharya, Assistant Research Officer, FRTC
Eric Bullock, Research Geographer, U.S. Department of Agriculture (USDA) Forest Service
Tim Devereux, Research Associate, Earth Observation Ecology
Sean Healey, Lead – NASA SERVIR Applied Science Team, and Research Ecologist, USDA Forest Service
Ashraful Islam, Research Assistant, USDA Forest Service
Prakash Lamichhane, Assistant Research Officer, FRTC
Shaun Levick, Principle Research Scientist, Earth Observation Ecology
Atticus Stoval, Assistant Research Professor, University of Maryland/NASA
Rajesh Bahadur Thapa, Lead Science and Data, SERVIR-HKH, ICIMOD
Background
This training workshop incorporates three components that support forest carbon emission monitoring efforts.
The first component, TLS, is a powerful tool for biomass estimation, offering valuable insights into forest ecosystems while supporting conservation, carbon accounting, and resource management efforts. TLS has several advantages for biomass estimation, including its ability to capture detailed 3D information, non-intrusive nature, and high accuracy. It provides comprehensive data on forest structure, enabling more precise biomass estimation compared to traditional methods. However, it is important to note that TLS also has limitations. Effective operation and data processing require considerable expertise and resources. Moreover, occlusions caused by dense vegetation or steep terrain can impact the accuracy of biomass estimation in certain cases.
Secondly, GEDI is a spaceborne LiDAR sampling instrument, collecting waveform return data for 25-m footprints spaced at 60-m intervals along parallel ground tracks that are approximately 600 m apart. Transparent methods have been developed to use GEDI to infer mean biomass with clear estimates of uncertainty. These methods have been built into OBIWAN, an interactive public tool developed to address carbon estimation in individual jurisdictions.
Lastly, the CODED algorithm relies upon time series analysis of the forest component of a spectral unmixing process applied to all available Landsat imagery. It is a leading algorithm for mapping forest degradation, which is canopy disturbance that does not result in deforestation. The amount of area affected by degradation, and its carbon consequences, are often greater than those of forest conversion. The algorithm has been applied to map degradation across the Amazon and has been tested in Nepal.
