Forests’ critical role in mitigating climate change has increased the demand for information on forest and tree resources. To manage and develop forests in a sustainable way, a reliable forest monitoring system is required. In recent years, the Natural Resources Institute Finland has supported several developing countries in designing National Forest Inventory and building capacity in forest monitoring, most recently Kenya.

Piloting, training, and software development – strengthening Kenya’s capacity in forest inventory

The main objective of the Improving Capacity in Forest Resources Assessment in Kenya (IC-FRA) project (2013 – 2016), was to increase capacity of the Kenyan partner agencies in forest inventory by strengthening human and technological capabilities to collect, manage and disseminate forest information. The IC-FRA project had two primary goals: to plan a National Forest Resources Assessment (NFRA) based on statistical sampling and enabling estimation of forest carbon stock, and to promote utilization of Remote Sensing (RS) material in forest inventory and change detection.

The project involved preparation activities required before implementing an actual NFRA, such as sampling design, preparing instructions for field measurements and implementation of data processing and analyses tools. A pilot inventory on five test areas was carried out to collect prior information on forest variation in different vegetation types for designing a nation-wide sampling, and to test and gain experience in sample plot measurements in Kenyan conditions. Soil sampling and analyses of soil organic carbon were included in the pilot inventory. In addition, a socioeconomic survey to collect data on community interaction with forests was conducted on the same test areas afterwards.

Foto: Pekka Hyvönen, Luke.
In order to calculate inventory results from field measurements, tree-level models to predict tree volume and biomass are required. Currently, there is lack of species-specific equations, and one of the objectives of the IC-FRA project was to build prediction models for five indigenous tree species. The project collected and analysed tree data for selected tree species, and completed tree-level biomass and volume models for Crevillea robusta. Foto: Pekka Hyvönen, Luke.

In the RS section, Landsat satellite imagery was utilized in estimation of forest biomass and detecting changes in land use over large areas. The project also tested Airborne Laser Scanning (ALS), also known as LiDAR (Light Detection and Ranging), in collecting forest data for management planning at the local level. The ALS and acquisition of aerial photographs, as well as ground truthing were conducted in two test sites comprising natural forests and plantations.

The project succeeded in improving the Kenyan partner agencies’ capacity in forest inventory and monitoring through several training courses and providing opportunities for on-the-job learning. Staff members achieved capacity to record field data digitally and calculate inventory results by means of Open Foris tools, which are freely available software tools developed by FAO for forest data collection, analysis and reporting. The same data collection and calculation methods have already been used in other local inventory projects.

The Kenyan project team also went on an excursion to Tanzania to learn about the National Forestry Resources Monitoring and Assessment (NAFORMA) carried out there from 2010 to 2013. In addition, the project introduced and tested new technology, such as a hypsometer based on ultrasound or laser, a bluetooth GPS device, a high-precision GNSS (Global Navigation Satellite System) device and rugged field tablets in the field work.

(The Natural Resources Institute Finland’s partners in Kenya were Kenya Forest Service (KFS), The Kenyan Forestry Research Institute (KEFRI), the University of Eldoret (UoE), and the Department of Resource Surveys and Remote Sensing (DRSRS).)

Picture on top of the page: Pekka Hyvönen, Luke.

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