Global Forest Change datasets have the potential to assist countries with national forest measuring, reporting and verification (MRV) requirements. This paper assesses the accuracy of the Global Forest Change data against nationally derived forest change data by comparing the forest loss estimates from the global data with the equivalent data from Guyana for the period 2001–2017. To perform a meaningful comparison between these two datasets, the initial year 2000 forest state needs first to be matched to the definition of forest land cover appropriate to a local national setting. In Guyana, the default definition of 30% tree cover overestimates forest area is by 483,000 ha (18.15%). However, by using a tree canopy cover (i.e., density of tree canopy coverage metric) threshold of 94%, a close match between the Guyana-MRV non-forest area and the Global Forest Change dataset is achieved with a difference of only 24,210 ha (0.91%) between the two maps. A complimentary analysis using a two-stage stratified random sampling design showed the 94% tree canopy cover threshold gave a close correspondence (R² = 0.98) with the Guyana-MRV data, while the Global Forest Change default setting of 30% tree canopy cover threshold gave a poorer fit (R² = 0.91). Having aligned the definitions of forest for the Global Forest Change and the Guyana-MRV products for the year 2000, we show that over the period 2001–2017 the Global Forest Change data yielded a 99.34% overall Correspondence with the reference data and a 94.35% Producer’s Accuracy. The Guyana-MRV data yielded a 99.36% overall Correspondence with the reference data and a 95.94% Producer’s Accuracy. A year-by-year analysis of change from 2001–2017 shows that in some years, the Global Forest Change dataset underestimates change, and in other years, such as 2016 and 2017, change is detected that is not forest loss or gain, hence the apparent overestimation. The conclusion is that, when suitably calibrated for percentage tree cover, the Global Forest Change datasets give a good first approximation of forest loss (and, probably, gains). However, in countries with large areas of forest cover and low levels of deforestation, these data should not be relied upon to provide a precise annual loss/gain or rate of change estimate for audit purposes without using independent high-quality reference data.

Keywords: Deforestation, Forest Degradation, Landsat, RapidEye, MRV System, and persistent cloud Monitoring deforestation and forest degradation at national scale has been identified as a national priority under Guyana‟s REDD+ Programme. Based on Guyana‟s MRV (Monitoring Reporting and Verification) System Roadmap developed in 2009, Guyana sought to establish a comprehensive, national system to monitor, report and verify forest carbon emissions resulting from deforestation and forest degradation in Guyana. To date, four national annual assessments have been conducted: 2010, 2011, 2012 and 2013. Monitoring of forest change in 2010 was completed with medium resolution imagery, mainly Landsat 5. In 2011, assessment was conducted using a combination of Landsat (5 and 7) and for the first time, 5m high resolution imagery, with RapidEye coverage for approximately half of Guyana where majority of land use changes were taking place. Forest change in 2013 was determined using high resolution imagery for the whole of Guyana. The current method is an automated-assisted process of careful systematic manual interpretation of satellite imagery to identify deforestation based on different drivers of change. The minimum mapping unit (MMU) for deforestation is 1 ha (Guyana‟s forest definition) and a country-specific definition of 0.25 ha for degradation. The total forested area of Guyana is estimated as 18.39 million hectares (ha). In 2012 as planned, Guyana‟s forest area was reevaluated using RapidEye 5 m imagery. Deforestation in 2013 is estimated at 12 733 ha which equates to a total deforestation rate of 0.068%. Significant progress was made in 2012 and 2013, in mapping forest degradation. The area of forest degradation as measured by interpretation of 5 m RapidEye satellite imagery in 2013 was 4 352 ha. All results are subject to accuracy assessment and independent third party verification.

In 2010 Guyana started work on the development of a national Monitoring Reporting and Verification System (MRVs) to quantify and measure the changes in the country’s forest cover carbon and carbon emissions. A necessary part of this process involved the identification of reliable Earth Observation data of sufficient resolution to detect and quantify land use change in Guyana's forests. Over the past 10 years the MRVs has evaluated and integrated many data streams used to; map national-scale forest change, support the analysis, and importantly datasets suitable to determine the accuracy of the change area mapped. Guyana’s approach has evolved over time, to accommodate new technologies, but at its core the MRVs recognises the importance of local management, existing datasets and linking these elements to appropriate EO data such as Landsat, RapidEye, Sentinel, Planet Scope and very high spatial resolution aerial imagery. From the outset the MRVs development was divided into phases. This approach recognises that not all MRVs reporting functions can be satisfied immediately. For Phase 1 (Years 2010 to 2014) of the MRVS, historical change analysis was conducted using Landsat 30 m resolution imagery. Being a persistently cloudy country alternative EO data sources were included, with Landsat and DMC imagery largely superseded by 5 m resolution RapidEye imagery. After five years of monitoring the forest change baselines, methods, reporting processes and standard operating procedures had been well established and able to provide the required performance-based indicators. The focus of MRVs phase 2 (Years 2015 to 2019) was to retain the reporting standards already achieved while also streamlining processes, improving functionality and reducing operational costs (i.e. the reliance on commercial image data) post-2019. Process improvements and operational research targeted two areas; the feasibility of using freely available Landsat and 10 metre resolution Sentinel data to map countrywide deforestation, and development of a sample-based approach to estimate degradation from aerial imagery and Planet Scope (3–5 metres resolution). Guyana’s move to integrate multiple data streams has been driven by the need for higher temporal resolution, repeated monitoring, and the creation of a data agnostic system to supports multiple decision-making processes on forest management. While the originally the MRVs was intended to support REDD+ reporting, the flexibility of the system design has meant it is proving to be invaluable tool for natural resources management in Guyana.

The Guyana Forestry Commission’s (GFC) Monitoring, Reporting and Verification System (MRVS) is a combined Geographic Information System (GIS) and field-based monitoring system, which has underpinned the conducting of a historical assessment of forest cover as well as eight national assessments of forest area change to date. The System seeks to provide the basis for measuring verifiable changes in Guyana’s forest cover and resultant carbon emissions from Guyana’s forests, which will provide the basis for results-based REDD+ compensation in the long-term. With the continuous compilation, analysis and dissemination of MRVS results on a typically annual basis, the GFC envisioned a larger role for this data, in informing national processes such as natural resources policy and management. This resulted in a significant broadening of the application of the MRVS data and products for purposes that are aligned or complementary to national REDD+ objectives and forest policy and management. These broader applications have allowed for a beneficial shift towards the increased use of remote sensing data and scientific reporting to inform forest management, governance and decision making on natural resource management across forested land. This has resulted in a transformation in the nature of data available to inform decision making on forest management and governance, and overall environmental oversight, from predominantly social science data and factors to now incorporating remote sensing and scientific observations and reporting. Primary decision makers are turning to scientific based reporting to determine best approaches for developmental initiatives in Guyana. This study shows how Guyana has demonstrated significant progress in making remote sensing products accessible and useful to policy makers in Guyana.