Data on environmental and social trends and outcomes in the forest sector can be difficult to collect and access at national and local scales. This is especially true with regards to data on biodiversity, ecosystem services, and local management and use of forests, including by women and other stakeholder groups. This table has been developed by the SFT-LMR Project to improve access to shared information on a selection of  global and regional publicly available platforms, datasets and tools related to information on forests, environmental conditions, and socio-economic trends. This is not an exhaustive list, but rather a selection based on their relevance to the Lower Mekong Region, ease of access, and other factors.

Depending on the objectives, resolution, coverage and licenses of these datasets and tools, they can be used for a wide range of purposes, for example, users can use the data to visualise trends, carry out analyses and develop monitoring approaches for better understanding and tracking environmental and social trends and outcomes in the forest sector.

This table contains introductory information on more than 50 publicly available platforms, data and tools relevant for understanding and tracking environmental and social trends in the forest sector, including global and regional (Asia-Pacific / Mekong region) resources.

There are several ways to search for data and tools:

• Use the filter button to add a term or key word to select relevant data and tools. For example, adding the condition that the ‘’primary focus’’ contains ‘’biodiversity’’ will select only those data and tools focused on biodiversity.
• Use the sort button to order the data and tools by certain categories, e.g. according to the primary focus (i.e. main topic covered), scope (i.e. global, regional), or type of resource (i.e. dataset, platform, etc).
• Use the search function to search throughout the table by keyword.

To learn more about a particular platform, dataset or tool, click on each row/card to expand the full entry on that resource. Links to the resource itself are also provided wherever possible.

Contact: For more information about this resource, please contact the Nature-Based Solutions Team at UNEP-WCMC via the following email address: NBS@unep-wcmc.org

There are several important considerations when using these global and regional datasets and tools. These should be factored into how the platforms and datasets are used, particularly if used to substitute for or complement national data. For example, it is recommended that users:

• Choose the most appropriate data for the objective and the context (e.g. at the appropriate scale, resolution, time period, etc) and understand whether/how the data can complement available national level data. For example, some global or regional data may not be considered ‘official’, politically acceptable or credible by some stakeholders.
• Recognise the implications of coarser resolution of global and regional datasets for national or subnational purposes and identify ways to make them more useful. For example, IUCN species ranges may be too coarse for subnational planning purposes, but species ranges can also be refined by area of habitat using national scale data.
• Consider how to use or combine data from different timeframes, e.g. when combining datasets in a time series analysis or generating a dataset to represent a particular year. Data from different time periods may also use different definitions and methodologies.
• Clarify the methodologies that were used to create and/or process the dataset. For example, Key Biodiversity Areas (KBAs) are usually defined through an expert review process.
• Recognise the implications of the definitions that underly certain datasets. For example, different forest cover datasets may apply different definitions of forest, which could lead to different estimates of forest extent within the country/area.
• Ensure that there is capacity to process, analyse and interpret the data; this includes sufficient human resources and training, but also potentially, need for certain hardware and software in some cases.
• Consider the way that the data is visualised; the style or approaches used to present and visualise data (such as colour themes, types of comparisons, etc) can communicate different messages about the findings or trends being shown.
• Ensure the accessibility of the data for future users, making sure that citations are provided, and that data can be accessed again for future revisions and updates.
• Tailor the analysis to local/national needs, for example by consulting with local experts, partners and stakeholders when prioritising topics for analysis, selecting parameters, conducting the analysis, and validating the results.