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

机译:将国家森林类型图与年度全球树木覆盖图相结合,以更好地了解随时间推移的森林变化:泰国的案例研究

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摘要

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 foreston-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. (C) 2015 Elsevier Ltd. All rights reserved.
机译:国家和全球土地利用/土地覆盖率(LULC)/ LULC变更(LULCC)数据集通常具有不同的优势和劣势来监测随时间变化的森林变化。例如,一张国家级地图可能会在与森林相关的LULC类别的数量和类型方面非常详细,但是与具有较少LULC类别的全球地图相比却很少更新(例如,树木覆盖率地图或森林/非森林地图)。因此,通过整合国家和全球LULC数据集可能会获得更多有用的信息。作为演示,在此研究中,将2000年以来的泰国国家森林类型图与2000-2012年间的年度全球树木覆盖图相结合,以获得有关泰国森林变化的多时相信息,并为到2020年森林变化(即没有新的政策干预措施)。结果表明,从2000年到2012年,所有森林类型的面积均下降,其中混合落叶林的面积损失最大(-137,765公顷),沼泽林的百分比损失最大(-5.8%)。总体而言,从2000年到2012年,每年的森林损失以近乎线性的速度增长,预计将从2012年的39,290公顷/年增加到2015年底的51,775公顷/年(增长31.8%)和66,945根据历史趋势的线性推算,到2020年,公顷/年(增长70.4%)。相比之下,全球森林净损失目前约为每年521.1万公顷,在南亚和东南亚区域每年约为677,000公顷(联合国粮食及农业组织,2010b)。此处介绍的方法提供了一种计算简单的方法,可以使用免费的全球树木覆盖数据每年更新现有的森林地图并估算未来的森林变化。 (C)2015 Elsevier Ltd.保留所有权利。

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