中国河南省2016-2021年尾矿库目标检测数据集

A dataset of object detection of tailings ponds in Henan Province,China,2016-2021

尾矿库是矿山开采所必需的基础设施,同时也是具有高势能的人造泥石流风险源。遥感图像的尾矿库目标检测是对其在图像上进行识别和定位,相对于传统方法,采用深度学习对遥感图像中的尾矿库进行目标检测在精度、稳定性和效率上都有明显改善,但是需要高质量的训练数据集。本研究基于多年的国产高分卫星遥感图像,经过数据处理、人工解译标注、图像切片等步骤,构建了中国河南省区域的尾矿库目标检测数据集,并开放共享。本数据集有以下几个特点:(1)国产高分辨率光学遥感卫星图像尾矿库目标检测数据集,包含1183个切片,1728个目标实例;(2)多时相数据集,提供2016年、2018年、2020年和2021年总共4个不同年度的样本数据;(3)目标标注采用倾斜框,图像背景干扰少。利用本数据集可以进行深度学习尾矿库目标检测模型开发的技术研究和进行尾矿库的自动化、智能化检测,对于推动尾矿库自动提取技术的发展和尾矿库的安全监管具有重要意义。

Tailings ponds are essential infrastructures in mining operations,but they also pose a significant risk source as potential sources of manmade debris flow with high potential energy.The object detection of tailings pond in remote sensing imagery is to accurately recognize and pinpoint the locations of them on the images.Compared with traditional methods,tailings pond detection in remote sensing imagery with the aid of deep learning has seen substantial improvements in accuracy,stability,and efficiency especially when trained on high quality training dataset.Based on years of China high-resolution satellite remote sensing images,through data processing,manual interpretation and annotation,image slicing and other steps,we have constructed a dataset of object detection of tailings ponds in Henan Province,China,available for public access.This dataset has the following characteristics:(1)the domestic high-resolution dataset comprising 1,183 slices and 1,728 object instances;(2)multi temporal dataset containing a total of four different years of sample data in 2016,2018,2020 and 2021;(3)objects labeled with oriented bounding box,with less image background interference.The dataset can be used for the technical research on the development of tailings pond detection models with deep learning,as well as for the automatic and intelligent detection of tailings pond,It is of great significance for promoting the development of automatic extraction technology and safety supervision of tailings ponds.