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Case Studies

The wide range of global and regional platforms, data and tools, and their multiple users, including governments, researchers, and civil society, means that there is a wide range of possible uses of these resources. This section gives a set of  examples of how countries and other actors have used some of the platforms, data and tools profiled in this webpage to support analysis, policy development and monitoring in the forest sector. While these case studies differ in terms of data inputs, methods and tools, geographic scale, and purposes of planning and monitoring, they provide some examples of how these resources can be used, including in combination with national data and approaches.


Mapping Essential Life Support Areas


In recognition of the importance of spatial data for identifying and monitoring nature-based solutions for biodiversity, climate change and sustainable development, Cambodia is mapping its Essential Life Support Areas (ELSAs). 

ELSAs are areas that maintain critical biodiversity and provide essential ecosystem services for humans, such as food, fresh water, water filtration, carbon storage, and disaster risk reduction. This work has been carried out under the project “Mapping Nature for People and Planet”, led by the Ministry of Environment (MoE) and partners, promoting spatial data as a tool to identify nature-based solutions that meet multiple national priorities.

After identifying ten priority commitments from national policy and plans, the MoE has engaged more than 45 Cambodian policymakers and practitioners in capacity building and mapping activities, surveying existing national and global data on agriculture, carbon stocks, protected areas, forests, degradation, and urban greening to determine which would be most appropriate to include in the final ELSA map. This resulted in a list of priority data to support the mapping exercise.

The ELSA mapping process shows how global data sources can complement national data to derive spatial information that can be used to guide progress on national and global commitments. Key global datasets and sources that helped to shape the ELSA map are: Key Biodiversity Areas; Global Mangrove Watch; global biomass carbon datasets including ‘’at risk carbon’’; and forecast changes in agriculture suitability, among others. The figure below shows an example of some constituent layers and potential policy uses for an ELSA map.



Image: Example of layers to inform Cambodia’s ELSA map (MoE et al, 2021). The figure depicts key global datasets and sources that helped to shape the ELSA map which include, Key Biodiversity Areas; Global Mangrove Watch; global biomass carbon datasets including ‘’at risk carbon’’; and forecast changes in agriculture suitability, among others

The ELSA map is expected to provide information to decision-makers to support conservation, restoration, and sustainable development, and is considered an important input to the development of the Cambodia Environment Management Information System (CEMIS), a central spatial data platform for managing and distributing environmental information.

Source: Ministry of Environment, UNDP, Impact Observatory (IO) and University of Northern British Columbia (UNBC) and the Sustainable Market Foundation (SMF) (2021) Mapping Nature for People and Planet in Cambodia: Report from the First Stakeholder Consultation.

Disclaimer: The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations.


Using global biodiversity data to inform REDD+ planning


Nigeria’s forest cover is about 10% of the country’s total land cover, with more than 50% of its remaining ‘tropical high forest’ found in the Cross-River State. The use of global spatial biodiversity data together with national data has been instrumental in exploring the multiple benefits from REDD+ actions in the State.

In 2017 as part of the country’s National UN-REDD Programme, Nigeria conducted a comprehensive study on potential multiple benefits from forests in Cross River State, drawing from local, national, and international datasets, platforms and tools. The study aimed to support the planning and development of REDD+ actions.

The use of spatial analysis was especially important for the study, highlighting the distribution of forest values across landscapes in an accessible format. Using global data sources such as IUCN species richness data and biomass carbon data, as well as national land use and other data, the researchers produced maps indicating areas where the potential for promoting multiple benefits from selected REDD+ actions may be higher. For example, global data was used to complement national data to develop a species distribution map that also showed the location of priority areas for biodiversity conservation (e.g. Key Biodiversity Areas and gorilla sites). The researchers identified that in Cross River State there is a clear concentration of threatened species in the forested areas of the national park, and in the mangroves and delta area in the South-East of the State.


Map: Threatened species richness, key biodiversity areas and gorilla sites in Cross River State (Adapted from Maukonen et al (2017)

The spatial analysis also used national data to show areas where forests had been affected by deforestation and degradation, helping to consider where forest values may be under threat in the future.


Map: Forest cover change in Cross River State between 2000-2014 (Adapted from Maukonen et al (2017)

Information on species richness, priority species for conservation and potential threats to habitats, among other data and informed by stakeholder consultation, provided an initial basis for identifying areas for REDD+ actions to benefit biodiversity and indicated areas of priority for conservation and restoration investments.


Maukonen et al (2017). Using Spatial Analysis to Explore Multiple Benefits from REDD+ Actions in Cross River State, Nigeria,

Disclaimer: The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations.


Monitoring forest degradation


In 2021, the Lao People’s Democratic Republic (Lao PDR) signed an Emissions Reduction Payment Agreement with the Forest Carbon Partnership Facility of the World Bank. As part of the implementation of the Agreement, the country must reduce the uncertainty of emissions estimates emanating from shifting cultivation and selective logging.

The use of the Collect Earth Online (CEO) platform and its Geo-Dash Degradation Tool has been crucial for the Lao PDR team in achieving this goal.

The tool enables the monitoring of forest degradation – a major source of carbon emissions – via access to an inexpensive methodology to collect a sample inventory, estimate the area of degradation, and assess uncertainty. It helps users confirm and verify cases of forest degradation, or temporary change in tree canopy cover, by combining the Normalized Difference Fraction Index (NDFI) with a time series of Landsat and Sentinel imagery. The Degradation Tool leverages Google Earth Engine to make this information available to users.



Image: Example of forest degradation due to shifting cultivation detected by the CEO Degradation Tool. The degradation event occurred in early 2018, as indicated by a sharp decrease in Normalized Difference Fraction Index (NDFI), after which NDFI rose to previous levels. (Source: Collect Earth Online, 2021)

Use of the Geo-Dash Degradation tool has helped the Lao PDR team to identify when and where key degradation activities, such as logging, are occurring. Thanks to the multiple types of satellite imagery available on the tool, such as Planetscope, Sentinel-1, and Sentinel-2, the team is also able to understand historical land cover change accurately.


Photo: Hin Nam No, Lao PDR (Charlotte Hicks)


Source: Collect Earth Online. 7 June 2021. Detecting Forest Degradation with CEO’s Geo-Dash.


Improving forest inventory


In 2007, Bangladesh conducted its first national forest and tree cover assessment. This provided the country with national estimates of forest resources, but it was inadequate in monitoring tree and forest cover, due to:

  • Lack of awareness of the data generated
  • Limited access to the data
  • Insufficient information on key forest types and coastal forests
  • Challenges in relocation of the field inventory plots 
  • Limited documentation of previous data collection

To overcome these limitations, the Forest Department designed the new, more comprehensive, accurate and reliable Bangladesh Forest Inventory (BFI), which would also inform the government’s actions towards sustainable forest management. 

To develop the BFI, the Forest Department conducted a biophysical inventory, a socio-economic survey, and remote sensing-based land cover mapping. Improved data and tools for the collection and analysis of forest data played a critical role in the design of the new inventory. For example, the Open Foris Collect Mobile application was used to collect field data from 1,144 locations across Bangladesh. Using innovative technological methods as well as global data allowed for the development of 7 criteria and 47 indicators for monitoring progress towards sustainable forest management goals in Bangladesh. For example, the IUCN Red List of trees was used to establish which threatened species are present in the country. By combining the global IUCN list with results from local research, the Forest Department was able to identify four species of trees which are considered threatened at both the global and national level.


Photo: Kaptai, Chittagong, Bangladesh - by Tareq on Adobe Stock


Using remote sensing for agricultural and forest information


Thailand’s Geo-Informatics and Space Technology Development Agency (GISTDA) is a public organisation which maintains a Geo-Informatics Applications and Services Office (GIAS). This office provides data drawn from remote sensing and a series of applications allowing users to explore information about land, forests, water resources, marine and coastal resources, agricultural crops, social security, and natural disasters.

For example, the Eco Plant platform monitors parameters related to the cultivation of economic crops in Thailand (including rice, maize, cassava and sugarcane), providing important information for a country where a large proportion of the population is employed in agriculture. Agricultural monitoring requires cooperation across several government departments, such as the Rice Department, Royal Irrigation Department, Department of Agricultural Extension and the Office of Agricultural Economics, and brings together systems for:

  • Identifying and mapping crop types

  • Assessing conditions for different crops

  • Monitoring crop area, growth and yields

  • Assessing damages from natural disasters

Eco Plant uses and interprets data from several satellites, including Landsat, Sentinel, Theos and Radarsat to estimate crop area and yields; the platform is developing approaches based on remote sensing to measure evapotranspiration and crop water stress.


Image: Screenshot of the Eco Plant online platform Source:

Another example is Thailand’s Pitak Prai application. This operating system for near-real time monitoring of forest was developed in collaboration with the Royal Forest Department and Ministry of Natural Resources and Environment to monitor and analyze forest encroachment, illegal logging, and forest fire through mobile and web-based applications. The public can provide online notifications with precise coordinates utilizing data from the Sentinel-2AB and Landsat-8 satellites, which record every 5 days at 16 meter resolution. A hotspot or heat map also helps to estimate the density of encroachment in targeted areas before notifying the local authorities and forest rangers for further investigation.



Disclaimer: The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations.