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Attributing changes in land cover using independent disturbance datasets: a case study of the Yucatan Peninsula, Mexico

机译：利用独立的干扰数据集来描述土地覆盖的变化：以墨西哥尤卡坦半岛为例

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Detailed observations of natural and anthropogenic disturbance events that impact forest structure and the distribution of carbon are essential to estimate changes in terrestrial carbon pools and the associated emissions and removals of greenhouse gasses. Recent advances in remote sensing approaches have resulted in annual and decadal estimates of land-cover change derived from observations using broad-scale moderate resolution imaging spectroradiometer (MODIS) 250 m-1 km imagery. These land-use change estimates, however, are often not attributed directly to a cause or activity and are not well validated, especially in tropical areas. Knowledge of the type of disturbance that caused the observed land-cover changes is important, however, for the quantification of the associated impacts on ecosystem carbon stocks and fluxes. In this paper, we provide estimates of the amount of forest land-cover change in a Mexican forested region and propose an approach for attributing the cause of the observed changes to the underlying disturbance driver. To do so, we collate geospatial and remote sensing data from a variety of sources to summarize statistics about the major disturbances within the Yucatan Peninsula, an "early action" region for the reduction of emissions from deforestation and degradation, from 2005 to 2010. We combine the datasets to develop rules to estimate the likely disturbances that caused the observed land-cover changes based on their spatially explicit location. Finally, we compare our observed disturbance rates to those detected using classified land-cover data derived from MODIS.
机译：对影响森林结构和碳分布的自然和人为干扰事件的详细观察对于估算陆地碳库的变化以及相关的温室气体排放和清除至关重要。遥感方法的最新进展已导致对土地覆盖变化的年度和十年估算，这些估算是通过使用250 m-1 km的大规模中分辨率成像光谱仪（MODIS）进行观测得出的。但是，这些土地利用变化的估计值通常不能直接归因于某个原因或活动，并且没有得到很好的验证，尤其是在热带地区。然而，了解引起观测到的土地覆盖变化的干扰类型对于量化对生态系统碳库和通量的相关影响很重要。在本文中，我们提供了墨西哥林区森林土地覆被变化量的估算值，并提出了一种将观测到的变化原因归因于潜在干扰驱动因素的方法。为此，我们整理了来自各种来源的地理空间和遥感数据，以总结有关尤卡坦半岛内部主要动乱的统计数据，尤卡坦半岛是2005年至2010年间减少砍伐和退化所致排放量的“早期行动”地区。结合数据集以制定规则，以根据其空间明确的位置来估计可能引起的扰动，这些扰动会导致观测到的土地覆被变化。最后，我们将观测到的干扰率与使用来自MODIS的分类土地覆盖数据检测到的干扰率进行比较。

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