Astrape: A System for Mapping Severe Abiotic Forest Disturbances Using High Spatial Resolution Satellite Imagery and Unsupervised Classification

编号 030028801

推送时间 20210426

研究领域 森林经理 

年份 2021 

类型 期刊 

语种 英语

标题 Astrape: A System for Mapping Severe Abiotic Forest Disturbances Using High Spatial Resolution Satellite Imagery and Unsupervised Classification

来源期刊 REMOTE SENSING

期 第288期

发表时间 20210422

关键词 astrapeforest disturbanceSentinel-2planetdoveimage segmentationRSGISLibjenksXGBoost; 

摘要 Severe forest disturbance events are becoming more common due to climate change and many forest managers rely heavily upon airborne surveys to map damage. However, when the damage is extensive, airborne assets are in high demand and it can take managers several weeks to account for the damage, delaying important management actions. While some satellite-based systems exist to help with this process, their spatial resolution or latency can be too large for the needs of managers, as evidenced by the continued use of airborne imaging. Here, we present a new, operational-focused system capable of leveraging high spatial and temporal resolution Sentinel-2 and Planet Dove imagery to support the mapping process. This system, which we have named Astrape (“ah-STRAH-pee”), uses recently developed techniques in image segmentation and machine learning to produce maps of damage in different forest types and regions without requiring ground data, greatly reducing the need for potentially dangerous airborne surveys and ground sampling needed to accurately quantify severe damage. Although some limited field work is required to verify results, similar to current operational systems, Astrape-produced maps achieved 78–86% accuracy with respect to damage severity when evaluated against reference data. We present the Astrape framework and demonstrate its flexibility and potential with four case studies depicting four different disturbance types—fire, hurricane, derecho and tornado—in three disparate regions of the United States. Astrape is capable of leveraging various sources of satellite imagery and offers an efficient, flexible and economical option for mapping severe damage in forests.

服务人员 付贺龙

服务院士 唐守正

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