Amazon and Atlantic Forest image datasets for semantic segmentation

This database contains images from Amazon and Atlantic Forest brazilian biomes used for training a fully convolutional neural network for the semantic segmentation of forested areas in images from the Sentinel-2 Level 2A Satellite. The images refer to the composition of bands 4, 3, 2 and 8. Each band was converted to a byte type (0-255). The images are still divided into three main sets: training, validation and testing: Training dataset: it contains 499 and 485 GeoTIFF images (Amazon and Atlantic Forest, respectively) with 512x512 pixels and associated PNG masks (forest indicated in white and background in black color). Validation dataset: it contains 100 GeoTIFF images for each biome with 512x512 pixels and associated PNG masks used for validation step. Test dataset: it contains 20 GeoTIFF images for each biome with 512x512 pixels for testing.本数据库收录源自巴西亚马逊森林与大西洋森林生物群落的影像，用于训练全卷积神经网络（fully convolutional neural network），以实现Sentinel-2 Level 2A卫星影像中林区的语义分割。 该系列影像由4、3、2及8波段合成，所有波段均已转换为取值范围0至255的字节类型。 所有影像被划分为训练集、验证集与测试集三大核心子集： 训练集：分别包含499张与485张512×512像素的GeoTIFF影像，对应亚马逊森林与大西洋森林生物群落，且配有对应的PNG掩码，其中森林区域以白色标注，背景为黑色。 验证集：每个生物群落各包含100张512×512像素的GeoTIFF影像及配套PNG掩码，用于模型验证阶段。 测试集：每个生物群落各包含20张512×512像素的GeoTIFF影像，用于模型测试。

搜集汇总

背景与挑战

背景概述

该数据集包含亚马逊和大西洋森林的卫星图像，用于语义分割任务，特别适用于训练全卷积神经网络。数据集分为训练、验证和测试三个子集，包含不同分辨率的GeoTIFF图像和对应的PNG掩码，总大小为2.3 GB。