2020年中国幼龄林林龄数据集

研发了一套适用于大尺度林龄制图的模型，使用连续变化检测与分类（CCDC）算法，通过分析1990至2020年的Landsat数据并识别森林替代性干扰事件来确定森林年龄，成功绘制了2020年中国区域幼龄林的林龄空间分布图，经过多种数据集和实地测量验证，数据集总体精度达到90.28%。数据集空间分辨率为30米，采用TIFF格式存储，数据单位为年，有效值区间：1-32。

We developed a model tailored for large-scale forest age mapping. Leveraging the Continuous Change Detection and Classification (CCDC) algorithm, forest age was determined by analyzing Landsat data from 1990 to 2020 and identifying alternative forest disturbance events. The spatial distribution map of young forest age across China in 2020 was successfully produced. Verified by multiple datasets and field measurements, the overall accuracy of this dataset reached 90.28%. The dataset has a spatial resolution of 30 meters, is stored in TIFF format, uses year as the data unit, and the valid value range is 1–32.

搜集汇总

背景与挑战

背景概述

该数据集提供了2020年中国幼龄林的林龄空间分布图，基于连续变化检测与分类（CCDC）算法分析1990至2020年Landsat数据并识别森林干扰事件生成，总体精度为90.28%。数据集空间分辨率为30米，采用TIFF格式存储，林龄值范围为1至32年，适用于地球科学和生态学领域的相关研究。