Combining national forest type maps with annual global tree cover maps to better understand forest change over time: Case study for Thailand

National and global land use/land cover (LULC)/LULC change (LULCC) data sets often have different strengths and weaknesses for monitoring forest change over time. For example, a national-level map may be very detailed in terms of number and type of forest-related LULC classes, but infrequently updated compared to a global map with fewer LULC classes (e.g. percent tree cover maps or forest/non-forest maps). So, additional useful information might be gained by integrating national and global LULC data sets. As a demonstration, in this study a national forest type map of Thailand from the year 2000 was combined with annual global tree cover maps for the years 2000-2012 to obtain multi-temporal information on forest change in Thailand and to create a baseline estimate of forest change to 2020 (i.e. with no new policy interventions). Results showed that all forest types experienced declines in area from 2000 to 2012, with the greatest area losses for Mixed Deciduous Forests (−137,765 ha) and the greatest percentage losses for Swamp Forests (−5.8%). Annual forest losses, in general, increased at a near-linear rate from 2000 to 2012, and are projected to increase from 39,290 ha/year in 2012 to 51,775 ha/year by the end of 2015 (an increase of 31.8%) and 66,945 ha/year by 2020 (an increase of 70.4%) based on linear extrapolation of the historical trend. For comparison, net forest loss is currently around 5,211,000 ha/year at the global level and 677,000 ha/year at the South and Southeast Asia regional level (Food and Agriculture Organization of the United Nations, 2010b). The methods presented here provide a computationally-simple approach to annually update existing forest maps and estimate future forest change using free global tree cover data.