林地变化智能识别算法

运用AI深度学习框架和卷积神经网络对林地资源特征提取训练样本进行算法训练和资源特征匹配，通过对至少两个不同时期的影像资源数据进行AI自动识别和分析，实现高精度提取和自动绘制疑似变化区域图斑及空间位置分布图，为林草资源管理部门快速、准确、及时掌握林地资源变化信息和资源监管情况。Using AI deep learning frameworks and convolutional neural networks (CNNs), algorithm training and resource feature matching are performed on training samples for woodland resource feature extraction. Through AI-enabled automatic recognition and analysis of image data from at least two different periods, high-precision extraction and automatic mapping of suspected change area patches and their spatial distribution maps are accomplished, so as to help forest and grassland resource management departments quickly, accurately and in a timely manner grasp woodland resource change information and carry out resource supervision.

搜集汇总

背景与挑战

背景概述

该数据集是一个基于AI深度学习框架和卷积神经网络的林地变化智能识别算法，通过分析至少两个不同时期的影像资源数据，实现高精度提取和自动绘制疑似变化区域图斑及空间位置分布图，旨在帮助林草资源管理部门快速、准确地掌握林地资源变化信息。算法由湖南林科达信息科技有限公司提供，适用于工业制造场景，属于云基础服务类别，价格为¥300,000，规格为400天。