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首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >COMPARISON OF PIXEL AND REGION-BASED APPROACHES FOR TREE SPECIES MAPPING IN ATLANTIC FOREST USING HYPERSPECTRAL IMAGES ACQUIRED BY UAV
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COMPARISON OF PIXEL AND REGION-BASED APPROACHES FOR TREE SPECIES MAPPING IN ATLANTIC FOREST USING HYPERSPECTRAL IMAGES ACQUIRED BY UAV

机译：基于像素和区域的无人机获取超光谱图像映射大西洋森林中树种方法的比较

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The objective of this work was the comparison of two different classification approaches to detect four different tree species of a highly diverse tropical Atlantic Forest area. In order to achieve the objective, images were acquired with the Rikola hyperspectral camera onboard the UX4 UAV. The study area is in the Western part of S?o Paulo State, a tropical Atlantic Forest area protected by governmental laws, which contains areas already deforested in the past and which are currently in regeneration. The tested approaches were one based only in the pixel values and other one based in regions. After the image acquisition, the images were radiometrically and geometrically processed. In addition, an airborne laser scanning point cloud was used to calculate the canopy height model of the area, which was used to detect the individual tree crowns with the superpixels method. Those superpixels were used to the region-based classification and to feature extraction. A total of 28 features were extracted where 25 correspond to the spectral bands acquired with the Rikola camera and three correspond to the three first principal components of the images. The features were extracted from the 91 samples recognized during a field work. From the total of samples, 19 were separated to validate the classification results. The chosen classifier was the Random Forests and the results presented a kappa coefficient of 18.20% and 36.57% for the pixel-based and region-based classifications showing that the second one had a better performance.
机译：这项工作的目的是比较两种不同的分类方法，以检测高度多样化的热带大西洋森林地区的四种不同树种。为了实现这一目标，使用UX4无人机上的Rikola高光谱摄像机获取了图像。研究区域位于圣保罗州西部，这是一个受政府法律保护的热带大西洋森林地区，其中包含过去已砍伐森林的地区，目前正在再生中。测试的方法是一种仅基于像素值的方法，另一种基于区域的方法。图像采集后，对图像进行辐射和几何处理。另外，使用机载激光扫描点云来计算该区域的冠层高度模型，该模型用于通过超像素方法检测单个树冠。这些超像素用于基于区域的分类和特征提取。总共提取了28个特征，其中25个对应于Rikola相机获取的光谱带，三个对应于图像的三个第一主成分。这些特征是从在野外工作中识别出的91个样本中提取的。从样本总数中分离出19个以验证分类结果。选择的分类器是随机森林，对于基于像素和基于区域的分类，结果的kappa系数分别为18.20％和36.57％，表明第二种分类器具有更好的性能。

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