Deforestation and degradation assessment is an important element of carbon mitigation strategy. While satellite-based monitoring of deforestation is largely technically proven, many countries in the Hindu Kush Himalayan (HKH) region
still have a long way to go in terms of establishing and applying forest cover monitoring systems on different scales. Degradation assessment and monitoring of forest biomass is currently carried out by community and state owned monitoring systems on the ground. The consistency and efficiency of such systems depend on the spatial details of the given observations, the estimation methods and the approaches used for scaling up the system..
The scope for generating biophysical information and estimating forest biomass has widened enormously over the last few decades. This is due to the launch of very high resolution optical sensors, air borne and space borne microwave and LiDAR systems. Very high spatial resolution optical systems have the potential to provide details on canopy morphology at stand and species level, which can be related to biomass.
Remote sensing can provide precise stratification in terms of forest crown density, forest types, communities and species formations. However, forest structure (i.e. CPA, DBH, BA) and biomass often exhibit nonlinear variations and variable correlation across temporal and spatial scales. In this context remote sensing based spatial information, geo-statistical tools and non-parametric tools provide effective means to develop robust models. These approaches use spatial variability of forest spectral reflectance across each unit (pixel) of the remotely sensed image, relate with field based biomass and develop a model to associate a biomass value for each pixel.
As a result spatial explicit biomass is estimated as a function of the resolution of remotely sensed data. The model can hence be developed on a local, national, and regional scale. When methods are developed for medium and coarse spatial resolution datasets, there is a potential for forest cover mapping and above ground biomass (AGB) estimation at national and regional levels.
Remote sensing offers the advantage of repeated data collection, a synoptic view, and a digital format that allows fast processing of large quantities of data. Remote sensing based approaches can provide for low cost, quick and periodic biomass assessments, which can support perspective planning and monitoring. At the same time, community level field measurements and spatially balanced low intensity field measurements can be scaled up into sub national systems (landscapes) through remote sensing based multi scale frameworks.
The Mountain Environment Regional Information System (MENRIS)
programme of the International Centre for Integrated Mountain Development (ICIMOD) works on promoting applications of geospatial and Earth observation tools and technologies for mountain development in the HKH. To facilitate the REDD+ projects in achieving its goals, MENRIS, under the USAID/NASA-SERVIR Himalaya regional initiative, is involved in the activities related to the identification and demarcation of the REDD+ project area, the development of a GIS database and the analysis of satellite imagery for land cover analysis, and the development of models for biomass estimation. Against this background, a one-week training course has been designed with the following objectives:
The overall objective of the course is to impart advanced Remote Sensing (RS) knowledge and techniques to monitor forest cover and associated biomass. More specifically, the course aims to:
• Impart RS based knowledge and techniques for forest monitoring and deforestation at medium level spatial resolution
• Impart RS based knowledge and techniques to assess forest degradation at very high spatial resolution level
• Impart RS based knowledge and techniques to assess biomass at very high spatial resolution level
• Impart RS based knowledge and techniques to upscale biomass estimation from very high resolution to medium resolution level
The participants of the training course will be from ICIMOD regional member countries. This technical training is targeted to professionals in the field of forest carbon stock estimation. The participants should have knowledge of remote sensing and GIS as well as forestry. To assure gender equity, female participation will be highly encouraged.
The participants will learn about the concepts of remote sensing for forest monitoring and techniques for biomass estimation using different biomass estimation models. Participants can use this knowledge to develop REDD projects that rely on RS technology for MRV processes.
Venue and logistics:
The training is being organized and supported by ICIMOD. It will take place in the training room of ICIMOD from 4--8 August 2014. Participants are requested to attend the event for the entire duration. Lunch and refreshments will be provided during the training session.