@article{BellKleinRieseretal.2023,
  author    = {Bell, Alexandra and Klein, Doris and Rieser, Jakob and Kraus, Tanja and Thiel, Michael and Dech, Stefan},
  title     = {Scientific evidence from space — a review of spaceborne remote sensing applications at the science-policy interface},
  series = {Remote Sensing},
  volume    = {15},
  journal   = {Remote Sensing},
  number    = {4},
  issn      = {2072-4292},
  doi       = {10.3390/rs15040940},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-303925},
  year      = {2023},
  abstract  = {On a daily basis, political decisions are made, often with their full extent of impact being unclear. Not seldom, the decisions and policy measures implemented result in direct or indirect unintended negative impacts, such as on the natural environment, which can vary in time, space, nature, and severity. To achieve a more sustainable world with equitable societies requires fundamental rethinking of our policymaking. It calls for informed decision making and a monitoring of political impact for which evidence-based knowledge is necessary. The most powerful tool to derive objective and systematic spatial information and, thus, add to transparent decisions is remote sensing (RS). This review analyses how spaceborne RS is used by the scientific community to provide evidence for the policymaking process. We reviewed 194 scientific publications from 2015 to 2020 and analysed them based on general insights (e.g., study area) and RS application-related information (e.g., RS data and products). Further, we classified the studies according to their degree of science-policy integration by determining their engagement with the political field and their potential contribution towards four stages of the policy cycle: problem identification/knowledge building, policy formulation, policy implementation, and policy monitoring and evaluation. Except for four studies, we found that studies had not directly involved or informed the policy field or policymaking process. Most studies contributed to the stage problem identification/knowledge building, followed by ex post policy impact assessment. To strengthen the use of RS for policy-relevant studies, the concept of the policy cycle is used to showcase opportunities of RS application for the policymaking process. Topics gaining importance and future requirements of RS at the science-policy interface are identified. If tackled, RS can be a powerful complement to provide policy-relevant evidence to shed light on the impact of political decisions and thus help promote sustainable development from the core.},
  language  = {en}
}
@article{DechHolzwarthAsametal.2021,
  author    = {Dech, Stefan and Holzwarth, Stefanie and Asam, Sarah and Andresen, Thorsten and Bachmann, Martin and Boettcher, Martin and Dietz, Andreas and Eisfelder, Christina and Frey, Corinne and Gesell, Gerhard and Gessner, Ursula and Hirner, Andreas and Hofmann, Matthias and Kirches, Grit and Klein, Doris and Klein, Igor and Kraus, Tanja and Krause, Detmar and Plank, Simon and Popp, Thomas and Reinermann, Sophie and Reiners, Philipp and Roessler, Sebastian and Ruppert, Thomas and Scherbachenko, Alexander and Vignesh, Ranjitha and Wolfmueller, Meinhard and Zwenzner, Hendrik and Kuenzer, Claudia},
  title     = {Potential and challenges of harmonizing 40 years of AVHRR data: the TIMELINE experience},
  series = {Remote Sensing},
  volume    = {13},
  journal   = {Remote Sensing},
  number    = {18},
  issn      = {2072-4292},
  doi       = {10.3390/rs13183618},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-246134},
  year      = {2021},
  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.},
  language  = {en}
}