Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
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DOI：
10.1016/j.rse.2018.06.044
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发表时间：
2018-10-01
影响因子：
13.5
通讯作者：
Kuemmerle, Tobias
中科院分区：
文献类型：
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作者：
Baumann, Matthias;Levers, Christian;Kuemmerle, Tobias
热带干燥森林和热带稀树草原提供了重要的生态系统服务，拥有高度的生物多样性，但在全球范围内受到土地利用变化的压力。因此，绘制干燥森林和稀树草原状况变化的地图是至关重要的。这可能是具有挑战性的，因为这些生态系统的特点是乔木和灌木覆盖的连续梯度，导致相当大的结构复杂性。我们开发了一种新的方法，充分利用Landsat-8光学和Sentinel-1合成孔径雷达(SAR)图像档案，分别绘制南美洲大查科地区(1,100,000公里(2))连续的乔木覆盖和灌木覆盖区域的地图。我们收集了一个从非常高分辨率的图像数字化的大型训练数据集，并使用梯度增强框架来模拟30米分辨率的树木覆盖和灌木覆盖的连续场。我们的回归模型具有高到中等的预测能力(乔木盖度为85.5%，灌木盖度为68.5%)，并得到了可靠的乔木和灌木盖度图(乔木和灌木盖度的均方误差分别为4.4%和6.4%)。联合使用光学和合成孔径雷达图像的模型比使用单一传感器图像的模型表现要好得多，模型预报器在一些地区差异很大，特别是在植被覆盖密集的地区。分别绘制乔木和灌木覆盖图可以识别不同的植被结构，灌木为主的系统主要位于非常干燥的查科，大树的林地主要位于干燥的查科，乔木占主导地位的稀树草原主要位于潮湿的查科。我们的乔木和灌木覆盖层在远离农田(边缘效应延伸约2公里)、小农牧场(约1.2公里)以及公路和铁路(分别约1.4公里和0.9公里)方面也显示出相当大的边缘效应。我们的分析既突出了土地利用对查科剩余自然植被的巨大影响，也强调了多感官方法监测森林退化的潜力。更广泛地说，我们的方法表明，绘制干燥森林和稀树草原的树冠结构和不同的木质植被层是可能的，并突出了不断增长的陆地卫星和哨兵档案对此的价值。
Tropical dry forests and savannas provide important ecosystem services and harbor high biodiversity, yet are globally under pressure from land-use change. Mapping changes in the condition of dry forests and savannas is therefore critical. This can be challenging given that these ecosystems are characterized by continuous gradients of tree and shrub cover, resulting in considerable structural complexity. We developed a novel approach to map, separately, continuous fields of tree cover and shrub cover across the South American Gran Chaco (1,100,000 km(2)), making full use of the Landsat-8 optical and Sentinel-1 synthetic aperture radar (SAR) image archives. We gathered a large training dataset digitized from very-high resolution imagery and used a gradient-boosting framework to model continuous fields of tree cover and shrub cover at 30-m resolution. Our regression models had high to moderate predictive power (85.5% for tree cover, and 68.5% for shrub cover) and resulted in reliable tree and shrub cover maps (mean squared error of 4.4% and 6.4% for tree- and shrub cover respectively). Models jointly using optical and SAR imagery performed substantially better than models using single-sensor imagery, and model predictors differed strongly in some regions, especially in areas of dense vegetation cover. Mapping tree and shrub cover separately allowed identifying distinct vegetation formations, with shrub-dominated systems mainly in the very dry Chaco, woodlands with large trees mainly in the dry Chaco, and tree-dominated savannas in the wet Chaco. Our tree and shrub cover layers also revealed considerable edge effects in terms of woody cover away from agricultural fields (edge effects extending about 2 km), smallholder ranches (about 1.2 km), and roads and railways (about 1.4 and 0.9 km, respectively). Our analyses highlight both the substantial footprint of land-use on remaining natural vegetation in the Chaco, and the potential of multi-sensoral approaches to monitor forest degradation. More broadly, our approach shows that mapping canopy structure and distinct layers of woody vegetation in dry forest and savannas is possible across large areas, and highlights the value of the growing Landsat and Sentinel archives for doing so.