2000-2019中亚五国500m土地退化指数OLDI

筛选出植被、土壤和气候的关键土地退化监测指标，构建评估指标体系（NDVI、albedo、LST和TVDI）。以NPP数据产品为标准，结合约束最优权重算法通过迭代计算得到最优权重分配体系，基于评估指标体系建立优化的土地退化指数OLDI（Optimal land degradation index）。数据时间为2000-2019年，空间分辨率为500米，时间分辨率为逐年。注：NPP、NDVI、albedo和LST分别来自MOD17A3HGF、MOD13A1、MCD43A3和MOD11A2数据集。TVDI数据集由中国科学院的地球大数据科学工程（CASEarth）专项提供。

Key land degradation monitoring indicators related to vegetation, soil and climate were screened, and an evaluation index system was established, consisting of NDVI, albedo, LST and TVDI. Taking the NPP data product as the reference standard, the optimal weight allocation system was derived via iterative computation combined with the constrained optimal weight algorithm. Subsequently, an optimized land degradation index (OLDI, Optimal Land Degradation Index) was constructed based on the established evaluation index system. The dataset spans the years 2000 to 2019, with a spatial resolution of 500 meters and an annual temporal resolution. Note: The NPP, NDVI, albedo and LST datasets are sourced from MOD17A3HGF, MOD13A1, MCD43A3 and MOD11A2 respectively. The TVDI dataset was provided by the Earth Big Data Science Engineering Project (CASEarth) of the Chinese Academy of Sciences.

搜集汇总

背景与挑战

背景概述

该数据集提供了2000年至2019年中亚五国的土地退化指数OLDI，空间分辨率为500米，时间分辨率为逐年。它通过整合植被、土壤和气候指标（如NDVI、albedo和LST），并基于NPP数据采用约束最优权重算法构建，旨在评估土地退化状况，数据来源包括MODIS等遥感产品。