ForestSemantics:A Dataset for Forest Semantic Learning of Forest from Close-Range Sensing

<h1>ForestSemantic:A Dataset for Forest Semantic Learning of Forest from Close-Range Sensing</h1> <p><strong>ForestSemantic</strong> is a new open point cloud dataset ForestSemantic for forest semantic studies at both individual tree- and plot-levels. The dataset supports both instance and semantic segmentation, such as tree detection and segmentation and classification between ground, trunk, branches, and foliage components at both tree- and plot- levels. Also, the instance of each first-order branch is provided,</p> <p>For each plot, three files are provided, i.e., "Plotx.las", "plotx_Tree_Reference.xlsx" and "plotx_Branch_Reference.txt", where x means the x-th plot.<br>1) &nbsp; &nbsp;"Plotx.las" is the data file, which records the position, tree-ID, classification and First-order branch ID and other attributes of each point. The tree-ID is stored in the field of "Point Source ID", classification is stored in the field of "Classification" and First-order branch ID is stored in the field of "GPS Time".<br>2) &nbsp; &nbsp;"plotx_Tree_Reference.xlsx" provides the reference structure traits of each tree in the plot. The reference of each tree takes up one row, and each column in turn is tree-ID, position_x, position_y, tree height (m), DBH (m), First-order branch (m), Crown Projection area (m2), Crown Surface area (m2), Crown Volume (m3).<br>3) &nbsp; &nbsp;"plotx_Branch_Reference.txt" provides the reference length of each First-order branch in the plot. Each individual First-order branch takes up one row, and each column in turn is tree-ID, First-order Branch ID, Start_x, Start_y, Start_z, End_x, End_y, End_z, Length.</p> <p><strong>More details please refer to "Read me.pdf".</strong></p>