Year: 2021
Type: article
Abstract: 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.
Source: Remote Sensing
DOI: 10.3390/rs13183618
Authors: Stefan Dech, Stefanie Holzwarth, Sarah Asam, Thorsten Andresen, Martin Bachmann, Martin Boettcher, Andreas Dietz, Christina Eisfelder, Corinne Frey, Gerhard Gesell, Ursula Gessner, Andreas Hirner, Matthias Hofmann, Grit Kirches, Doris Klein, Igor Klein, Tanja Kraus, Detmar Krause, Simon Plank, Thomas Popp, Sophie Reinermann, Philipp Reiners, Sebastian Roessler, Thomas Ruppert, Alexander Scherbachenko, Ranjitha Vignesh, Meinhard Wolfmueller, Hendrik Zwenzner, Claudia Kuenzer
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,983
OpenAlex ID: W3201215366