@article{DhillonDahmsKuebertFlocketal.2022,
  author    = {Dhillon, Maninder Singh and Dahms, Thorsten and K{\"u}bert-Flock, Carina and Steffan-Dewenter, Ingolf and Zhang, Jie and Ullmann, Tobias},
  title     = {Spatiotemporal Fusion Modelling Using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {3},
  issn      = {2072-4292},
  doi       = {10.3390/rs14030677},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323471},
  year      = {2022},
  abstract  = {The increasing availability and variety of global satellite products provide a new level of data with different spatial, temporal, and spectral resolutions; however, identifying the most suited resolution for a specific application consumes increasingly more time and computation effort. The region's cloud coverage additionally influences the choice of the best trade-off between spatial and temporal resolution, and different pixel sizes of remote sensing (RS) data may hinder the accurate monitoring of different land cover (LC) classes such as agriculture, forest, grassland, water, urban, and natural-seminatural. To investigate the importance of RS data for these LC classes, the present study fuses NDVIs of two high spatial resolution data (high pair) (Landsat (30 m, 16 days; L) and Sentinel-2 (10 m, 5-6 days; S), with four low spatial resolution data (low pair) (MOD13Q1 (250 m, 16 days), MCD43A4 (500 m, one day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, eight day)) using the spatial and temporal adaptive reflectance fusion model (STARFM), which fills regions' cloud or shadow gaps without losing spatial information. These eight synthetic NDVI STARFM products (2: high pair multiply 4: low pair) offer a spatial resolution of 10 or 30 m and temporal resolution of 1, 8, or 16 days for the entire state of Bavaria (Germany) in 2019. Due to their higher revisit frequency and more cloud and shadow-free scenes (S = 13, L = 9), Sentinel-2 (overall R\(^2\) = 0.71, and RMSE = 0.11) synthetic NDVI products provide more accurate results than Landsat (overall R\(^2\) = 0.61, and RMSE = 0.13). Likewise, for the agriculture class, synthetic products obtained using Sentinel-2 resulted in higher accuracy than Landsat except for L-MOD13Q1 (R\(^2\) = 0.62, RMSE = 0.11), resulting in similar accuracy preciseness as S-MOD13Q1 (R\(^2\) = 0.68, RMSE = 0.13). Similarly, comparing L-MOD13Q1 (R\(^2\) = 0.60, RMSE = 0.05) and S-MOD13Q1 (R\(^2\) = 0.52, RMSE = 0.09) for the forest class, the former resulted in higher accuracy and precision than the latter. Conclusively, both L-MOD13Q1 and S-MOD13Q1 are suitable for agricultural and forest monitoring; however, the spatial resolution of 30 m and low storage capacity makes L-MOD13Q1 more prominent and faster than that of S-MOD13Q1 with the 10-m spatial resolution.},
  language  = {en}
}
@article{MuellerDomokosAmersbachetal.2023,
  author    = {M{\"u}ller, Christina and Domokos, Bruno and Amersbach, Tanja and Hausmayer, Eva-Maria and Roßmann, Christin and Wallmann-Sperlich, Birgit and Bucksch, Jens},
  title     = {Development and reliability testing of an audit toolbox for the assessment of the physical activity friendliness of urban and rural environments in Germany},
  series = {Frontiers in Public Health},
  volume    = {11},
  journal   = {Frontiers in Public Health},
  issn      = {2296-2565},
  doi       = {10.3389/fpubh.2023.1153088},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-326116},
  year      = {2023},
  abstract  = {Background: According to socio-ecological theories, physical activity behaviors are linked to the physical and social neighborhood environment. Reliable and contextually adapted instruments are needed to assess environmental characteristics related to physical activity. This work aims to develop an audit toolbox adapted to the German context, to urban and rural settings, for different population groups, and different types of physical activity; and to evaluate its inter-rater reliability. Methods: We conducted a systematic literature search to collect existing audit tools and to identify the latest evidence of environmental factors influencing physical activity in general, as well as in German populations. The results guided the construction of a category system for the toolbox. Items were assigned to the categories based on their relevance to physical activity and to the German context as well as their comprehensibility. We piloted the toolbox in different urban and rural areas (100 street segments, 15 parks, and 21 playgrounds) and calculated inter-rater reliability by Cohen's Kappa. Results: The audit toolbox comprises a basic streetscape audit with seven categories (land use and destinations, traffic safety, pedestrian infrastructure, cycling infrastructure, attractiveness, social environment, and subjective assessment), as well as supplementary tools for children and adolescents, seniors and people with impaired mobility, parks and public open spaces, playgrounds, and rural areas. 76 \% of all included items had moderate, substantial, or almost perfect inter-rater reliability (κ > 0.4). Conclusions: The audit toolbox is an innovative and reliable instrument for the assessment of the physical activity friendliness of urban and rural environments in Germany.},
  language  = {en}
}