Use Case: Nepal Forest Research Training Centre (FRTC)

A view of the forests in Nepal with Mt. Kanchenjunga in the background. Photo credit: Jitendra Raj Bajracharya/ICIMOD

User: Forest Research Training Centre (FRTC), Ministry of Forests and Environment, Government of Nepal

SERVIR Hub: SERVIR-Hindu Kush Himalaya (SERVIR-HKH)

Geographic Location: Nepal

User Background: The FRTC, which is under the jurisdiction of Nepal’s Ministry of Forests and Environment, is the government-sanctioned organization that is responsible for forestry research and survey activities at the national level. The two primary directives of the FRTC are to update:
(1) the National Forest Inventory (NFI) and (2) the national forest cover map.


Service Summary: The RLCMS will create an operational system for annual land cover mapping and change analysis. The system will generate annual land cover data based on Landsat satellite data for Afghanistan, Bangladesh, Nepal, and Myanmar at the national level, and also at the Hindu Kush Himalayan (HKH) regional level. Land cover assessment and its dynamics are essential for the sustainable management of natural resources, environmental protection, and food security. Socioeconomic drivers can induce changes in land cover that may disrupt socio-cultural practices and the institutions associated with managing natural resources, which in turn increases the vulnerability of communities to the effects of climate change. The operationalization and generation of annual land cover maps will enable national agencies to effectively manage and enforce land cover and land use policies.

Regional Land Cover Monitoring System (RLCMS)


Situation: In 1963, the first institutional-level national land cover assessment was conducted as part of a forest resources survey using aerial photography. In 1986, another national land cover assessment was conducted for a land resources mapping project using satellite data, after which subsequent assessments focused only on national forest cover mapping. Between 2010 and 2014, the Forest Resource Assessment Nepal project conducted another significant land cover assessment of Nepal, which focused on forests and classified land cover into only three distinct classes: (1) forests, (2) other wooded land, and (3) other land.

Within Nepal, the collection of data for forest and land cover mapping has not been consistent. This data has been gathered by a variety of different agencies using varying methodologies across disparate periods of time. For example, Nepal’s National Forest Inventory is currently conducted only every five years using the permanent sample plot re-measurement program. Moreover, Nepal’s national forest cover data was last updated in 2015, as reported in the State of Nepal’s Forests report. As a result, significant gaps of data remain.

Given these data fluctuations, the existing national forest and land cover datasets are not fully reliable in helping analysts study changes over time – especially datasets that involve harmonized classification systems, resolution, and temporal frequencies.

In order for Nepal to develop more precise analysis of forest and land cover, as well as the study of their change, the country must adopt a more frequent data collection process. 


User Need: Given the infrequent data collection for the National Forest Inventory, the National Forest Reference Level (NFRL), and forest and land cover mapping, FRTC partnered with SERVIR-HKH to co-develop a Regional Land Cover Monitoring System (RLCMS) that focuses on the Hindu Kush Himalaya as an entire region, as well as a National Land Cover Monitoring System (NLCMS) that focuses on Nepal.

Using Landsat satellite data, the primary objective of the NLCMS system was to generate annual land cover data that would help Nepal’s national agencies to effectively manage and enforce land cover and land use policies, including the sustainable management of natural resources, environmental protection, and food security.

In addition to the need of more current data for domestic use and reporting, the FRTC also requires up-to-date input data for its ongoing reporting obligations from the international community. More specifically, the Government of Nepal, by way of FRTC, must communicate NFI and NFRL data to the United Nations Framework Convention on Climate Change (UNFCCC) and the Food and Agriculture Organization (FAO). Data must also be incorporated into FRTC’s national reports that detail greenhouse gas inventories as well as the nexus between economic-related activities and the environment.

User Quote: 

"This National Land Cover Monitoring System provide us with consistent land cover data from the historic to present date using the same methodology, data, and classification algorithm. This will be our milestone in reporting forest activity data for national and international reporting. The main benefit of the system is that we can use this system in future independently to derive the national land cover data ourselves."

– Raja Ram Aryal, Assistant Remote Sensing Officer, FRTC


Example of Use: In April 2018, SERVIR-HKH held the inaugural regional RLCMS workshop in Bangkok, Thailand. Collaborating with senior government officials from Afghanistan, Bangladesh, Myanmar, and Nepal, as well as representatives from FAO and SilvaCarbon, the workshop helped to build consensus on the RLCMS system architecture, which would then be customized to meet specific needs of respective participating countries.

For Nepal, follow-up national stakeholder consultation workshops, along with trainings for FRTC staff, contributed to national consensus of needs for the development of the NLCMS.

In December 2018, SERVIR-HKH signed a formal Letter of Intent with the FRTC.  As part of the collaboration, in order to build up primitives, the FRTC provided 36,000 land cover samples to HKH to be recorded into its machine-learning platform. These samples helped train the machine-learning algorithm that was being used to identify different land cover primitives.

Following a successful pre-launch of the NLCMS in 2019, the FRTC made the first version of land cover results publicly available and open for peer validation.

As a result of the positive collaboration with SERVIR-HKH, the FRTC is now pooling its own resources in order to budget for the validation of generated datasets. Once validated, the FRTC plans to fully operationalize the NLCMS across the country.


Outcome of Use: The NLCMS will be used to collect, analyze, and disseminate forest cover information at the national level. FRTC will then be able to annually report on changes in forest cover in order to sustainably manage forest resources. Doing so will aid in the reduction of forest degradation, biodiversity loss and forest encroachment. Other government agencies and development partners can also use the datasets to infer the extent of urbanization, while also using it for planning sectoral activities, including the construction of roads, installation of transmission lines, and management of the agricultural sector, among others.


Future Collaborations: National land cover workshops are being led by the FRTC, with SERVIR-HKH providing technical assistance.

The NLCMS will release land cover data in the form of 11 specific land cover classifications. These classifications can then be customized to provide outputs that are in compliance with FAO and IPCC requirements.

A mobile field data collection tool, which validates land cover data that is generated by the system, will also be incorporated.

The FRTC has allocated a total of NPR 4 million (~USD 35,118) for field work and validation of the NLCMS results.


Additional Documents: FRTC staff presented results from the collaboration at the American Geophysical Union meeting in December 2019.  https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/541301