期刊
REMOTE SENSING
卷 13, 期 18, 页码 -出版社
MDPI
DOI: 10.3390/rs13183618
关键词
AVHRR; Earth Observation; harmonization; time series analysis; climate related trends; automatic processing; Europe; TIMELINE
类别
资金
- German Aerospace Center (DLR)
- TIMELINE project
Earth Observation satellite data allows for monitoring large areas of the planet at predefined intervals, but long-term impacts of climate change require data spanning several decades. The AVHRR sensor family provides a 40-year daily observation time span, essential for studying climate change effects. Generating long-term time series requires meticulous preprocessing and harmonization to ensure data accuracy and reliability.
Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.
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