全球冬小麦病虫害遥感监测产品

基于不同卫星传感器尤其是新发射卫星传感器高时间/空间/光谱分辨率的优势性能融合与互补，以及病虫害发生发展各个阶段的不同监测特点，在病虫害发生早期将遥感数据结合气象数据进行热点监测，在病虫害发生进展期监测，主要通过时间序列影像中的时相、光谱信息对病虫害的实时状态及发展动态进行跟踪，在病虫害发生中晚期监测及损失评估方法研究。结合星地协同观测实验，对病虫害各个过程监测中的不确定性来源进行分析。通过结合病虫害光谱特征与时相特征和景观特征，降低监测不确定性，提高监测方法鲁棒性。

This dataset is developed based on the performance fusion and complementarity of diverse satellite sensors, especially newly launched ones with superior temporal, spatial and spectral resolution, alongside the distinct monitoring characteristics across all stages of pest and disease occurrence and progression. For the early outbreak phase of pests and diseases, it enables hotspot monitoring by integrating remote sensing data with meteorological data. During the progressive outbreak stage, it tracks the real-time status and dynamic development of pests and diseases primarily via temporal and spectral information contained in time-series remote sensing images. It also covers research on monitoring and loss assessment methods for the middle and late outbreak stages. Combined with satellite-ground collaborative observation experiments, this dataset supports the analysis of uncertainty sources during the monitoring of each phase of pest and disease occurrences. By integrating the spectral, temporal and landscape characteristics of pests and diseases, it reduces monitoring uncertainty and enhances the robustness of the monitoring methods.

搜集汇总

背景与挑战

背景概述

该数据集是基于多源卫星遥感与气象数据的全球冬小麦病虫害监测产品，采用栅格格式(GeoTiff)，提供年时间分辨率的全球覆盖数据，用于病虫害全周期监测与评估。