Forest management requires reliable information on forest status and its evolution. The main intention of forest inventories is to define the extent, assess the composition and condition of forest resources to ensure sustainable forest management, which calls for an up to date forest inventory.
Great attention has been paid to biomass estimation in recent years because biomass can simply be converted to carbon storage which is very important to understand the carbon cycle in the environment. Biomass is typically defined as the oven-dry mass of the above ground portion of a group of trees in forestry. Conventionally, it is estimated using measurements which are recorded on the ground. On the other hand, LIDAR (Light Detection and Ranging) data is also very useful in estimating forest biomass. Hence time-consuming field works can be avoided, and data from inaccessible areas can be acquired using a relatively low cost and automated LIDAR system. Tactical decisions on natural resource management require accurate and up to date spatial information for sustainable forest management. Remote sensing devices using multi-spectral data obtained from satellites or airborne sensors, allow substantial data acquisition that reduces the cost of data collection and satisfies demands for continuous precise data.
RCMRD/SERVIR E&SA has been involved in capacity building of several stakeholders involved in the forest resources assessment and management. RCMRD collaborated with the Kenya Forest Service (KFS) to collect field data which will assist in training and validation of LIDAR measurements. RCMRD has over time received requests from member States to offer capacity building on specific applications of LIDAR data for tree height mapping and canopy density measurements.
Due to the inadequate technical skills in LIDAR data processing for forest biomass estimation within the region, RCMRD/SERVIR E&SA is collaborating with NASA Science Coordination Office to bridge this gap. RCMRD and NASA, with support from USAID will engage an expert in LIDAR data processing to provide training on this subject. A training workshop is scheduled that will take place at RCMRD from March 11 to 14, 2019. The lead trainer Dr. John David Armston has a wide experience in application of LIDAR data in an array of fields, which regional institutions would immensely benefit from.
For the training to be effective, a baseline forest data on tree metrics (tree heights, diameter, and the crown cover) are required in the validation of LIDAR point clouds, and hence the need to collect field plot data based on the approved KFS data collection protocol. It was for this reason that KFS/RCMRD undertook a collaborative data collection exercise in the Central highland forests in Kenya between February 3 and 8, 2019. The plots have been mapped and demarcated on the ground as per the ICFRA biophysical assessment technical manual. These were sampled with the help of highly experienced foresters from the forest department.