Results 1 to 10 of about 24,595,895 (312)

S1S2-Water: A Global Dataset for Semantic Segmentation of Water Bodies From Sentinel- 1 and Sentinel-2 Satellite Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
This study introduces the S1S2-Water dataset—a global reference dataset for training, validation, and testing of convolutional neural networks (CNNs) for semantic segmentation of surface water bodies in publicly available Sentinel-1 and Sentinel-2
Marc Wieland, Florian Fichtner, Sandro Martinis, Sandro Groth, Christian Krullikowski, Simon Plank, Mahdi Motagh   +6 more
doaj   +1 more source

Systematic Evaluation of Four Satellite AOD Datasets for Estimating PM_2.5 Using a Random Forest Approach

Remote Sensing, 2023
The latest epidemiological studies have revealed that the adverse health effects of PM2.5 have impacts beyond respiratory and cardio-vascular diseases and also affect the development of the brain and metabolic diseases.
Jana Handschuh, Thilo Erbertseder, Frank Baier   +2 more
doaj   +1 more source

Spatial and semantic effects of LUCAS samples on fully automated land use/land cover classification in high-resolution Sentinel-2 data

International Journal of Applied Earth Observations and Geoinformation, 2020
In this study, we test the use of Land Use and Coverage Area frame Survey (LUCAS) in-situ reference data for classifying high-resolution Sentinel-2 imagery at a large scale.
Matthias Weigand, Jeroen Staab, Michael Wurm, Hannes Taubenböck   +3 more
doaj   +1 more source

Urbanization between compactness and dispersion: designing a spatial model for measuring 2D binary settlement landscape configurations

International Journal of Digital Earth, 2019
Measuring spatial patterns is a crucial task in spatial sciences. Multiple indicators have been developed to measure patterns in a quantitative manner.
Hannes Taubenböck, Michael Wurm, Christian Geiß, Stefan Dech, Stefan Siedentop   +4 more
doaj   +1 more source

Fusing AVHRR LST With Geostationary SEVIRI LST to Create a Long-Term Daily Maximum LST Time Series Over Europe

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Longtime series of satellite-derived land surface temperature (LST) data are an indispensable resource to study climate and global change. The advanced very high-resolution radiometer (AVHRR) provides thermal infrared measurements, which can be ...
Philipp Reiners, Stefanie Holzwarth, Andreas Dietz, Martin Bachmann, Jose Antonio Sobrino, Claudia Kuenzer   +5 more
doaj   +1 more source

USING AIRBORNE REMOTE SENSING TO INCREASE SITUATIONAL AWARENESS IN CIVIL PROTECTION AND HUMANITARIAN RELIEF – THE IMPORTANCE OF USER INVOLVEMENT [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
Enhancing situational awareness in real-time (RT) civil protection and emergency response scenarios requires the development of comprehensive monitoring concepts combining classical remote sensing disciplines with geospatial information science. In the
H. Römer, R. Kiefl, F. Henkel, C. Wenxi, R. Nippold, F. Kurz, U. Kippnich   +6 more
doaj   +1 more source

Exploiting big earth data from space – first experiences with the timescan processing chain

Big Earth Data, 2018
The European Sentinel missions and the latest generation of the United States Landsat satellites provide new opportunities for global environmental monitoring.
T. Esch, S. Üreyen, J. Zeidler, A. Metz–Marconcini, A. Hirner, H. Asamer, M. Tum, M. Böttcher, S. Kuchar, V. Svaton, M. Marconcini   +10 more
doaj   +1 more source

Automatic Flood Duration Estimation Based on Multi-Sensor Satellite Data

Remote Sensing, 2020
Flood duration is a crucial parameter for disaster impact assessment as it can directly influence the degree of economic losses and damage to structures.
Michaela Rättich, Sandro Martinis, Marc Wieland   +2 more
doaj   +1 more source

Spatiotemporal analysis of tropical vegetation ecosystems and their responses to multifaceted droughts in Mainland Southeast Asia using satellite-based time series

GIScience & Remote Sensing
Drought ranks among the costliest of all climate-related phenomena and manifests in various forms, posing significant challenges in understanding its influence on agriculture and natural ecosystems. Mainland Southeast Asia (MSEA), a significant region of
Tuyen V. Ha, Soner Uereyen, Claudia Kuenzer   +2 more
doaj   +1 more source

A Deep Learning Approach for Burned Area Segmentation with Sentinel-2 Data

Remote Sensing, 2020
Wildfires have major ecological, social and economic consequences. Information about the extent of burned areas is essential to assess these consequences and can be derived from remote sensing data.
Lisa Knopp, Marc Wieland, Michaela Rättich, Sandro Martinis   +3 more
doaj   +1 more source