Chesapeake Land Cover dataset - Learning on the prior extension

This dataset extends the "Chesapeake Land Cover" dataset at https://lila.science/datasets/chesapeakelandcover with an additional <em>layer </em>of data containing a prior of observing a 1m Chesapeake Conservancy land cover class label given an NLCD label. Specifically, for each <em>tile </em>in the original "Chesapeake Land Cover" dataset, this dataset contains another tile (named with a "_prior_from_cooccurrences_101_31_no_osm_no_buildings.tif" suffix) containing the prior probabilities of observing a four class version of the land cover classes at a 1m resolution. The prior probability is given by the normalized co-occurrence matrix between NLCD classes and the Chesapeake 1m land cover labels in each state with additional spatial smoothing (using a gaussian filter with a standard deviation of 31 pixels and a cutoff of 101 pixels) to reduce the block artifacts caused by the relatively low-resolution of the NLCD labels (30m) compared to the LC labels (1m). <strong>Note:</strong> the prior is a 4-class mapping of the 6-class labels. In the 4-class version of the dataset the "barren land", "impervious (other)", and "impervious (road)" classes are combined. This dataset also includes the per-state co-occurrence matrices. Each of these is a matrix, \(C\), with size 7 x 17, where an entry \(C_{ij}\) gives the normalized count of land cover class \(i\) for given NLCD label \(j\). The class indices \(i\) and \(j\) correspond to the indices used in the Chesapeake Conservancy land cover label and NLCD layers. The dataset is packaged in a way such that it can simply be unzipped over an existing copy of the "Chesapeake Land Cover" (i.e. follows the same directory structure). E.g., given a directory that contains the original dataset "cvpr_chesapeake_landcover/", and the file "cvpr_chesapeake_landcover_prior_extension.zip", run `unzip cvpr_chesapeake_landcover_prior_extension.zip` to create the merged dataset.本数据集基于公开地址https://lila.science/datasets/chesapeakelandcover 处的**切萨皮克土地覆盖（Chesapeake Land Cover）**数据集进行扩展，新增了一层数据，用于存储给定NLCD标签时，观测到1米分辨率切萨皮克保护局土地覆盖类别标签的先验概率。 具体而言，对于原始“切萨皮克土地覆盖”数据集中的每一张瓦片（tile），本数据集均附带一张后缀为`_prior_from_cooccurrences_101_31_no_osm_no_buildings.tif`的额外瓦片，该瓦片以1米分辨率存储了四类土地覆盖类别的先验概率。 该先验概率由各州辖区内NLCD类别与切萨皮克1米土地覆盖标签间的归一化共现矩阵（co-occurrence matrix）得到，并经过额外空间平滑处理——使用标准差为31像素、截断半径为101像素的高斯滤波器（gaussian filter），以抵消因NLCD标签分辨率（30米）远高于土地覆盖标签（1米）而产生的块状伪影。 **注意：** 该先验为6类标签到4类标签的映射。在本数据集的4类别版本中，“贫瘠土地”“其他不透水面”与“道路不透水面”三类将被合并。 本数据集还包含各州辖区的共现矩阵。每个共现矩阵(C)均为7×17大小的矩阵，其中条目(C_{ij})代表给定NLCD标签(j)时，对应切萨皮克保护局土地覆盖类别(i)的归一化计数。类别索引(i)与(j)分别对应切萨皮克保护局土地覆盖图层与NLCD图层中使用的索引。 本数据集采用适配已有数据集的打包方式，可直接解压至已存在的“切萨皮克土地覆盖”数据集目录中（即遵循完全一致的目录结构）。例如，若现有目录包含原始数据集`cvpr_chesapeake_landcover/`与扩展包文件`cvpr_chesapeake_landcover_prior_extension.zip`，只需执行`unzip cvpr_chesapeake_landcover_prior_extension.zip`即可完成数据集合并。