National-scale mapping of building height using Sentinel-1 and Sentinel-2 time series
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Patrick Hostert | Akpona Okujeni | Sebastian van der Linden | Wolfgang Wagner | Claudio Navacchi | Franz Schug | David Frantz | W. Wagner | P. Hostert | A. Okujeni | Sebastian van der Linden | D. Frantz | F. Schug | C. Navacchi
[1] Joachim Hill,et al. Improving the Spatial Resolution of Land Surface Phenology by Fusing Medium- and Coarse-Resolution Inputs , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[2] Hankui K. Zhang,et al. A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance , 2016 .
[3] George Vosselman,et al. Accuracy of 3D city models: EuroSDR comparison , 2005 .
[4] Patrick Hostert,et al. Mapping urban-rural gradients of settlements and vegetation at national scale using Sentinel-2 spectral-temporal metrics and regression-based unmixing with synthetic training data , 2020, Remote sensing of environment.
[5] Jon Atli Benediktsson,et al. Morphological Attribute Profiles for the Analysis of Very High Resolution Images , 2010, IEEE Transactions on Geoscience and Remote Sensing.
[6] Zhiqiang Xiao,et al. Estimation of Forest Canopy Height and Aboveground Biomass from Spaceborne LiDAR and Landsat Imageries in Maryland , 2018, Remote. Sens..
[7] Martino Pesaresi,et al. Update and improvement of the European Settlement map , 2019, 2019 Joint Urban Remote Sensing Event (JURSE).
[8] Adam Lewis,et al. Rapid, high-resolution detection of environmental change over continental scales from satellite data – the Earth Observation Data Cube , 2016, Int. J. Digit. Earth.
[9] Stefan Adriaensen,et al. Atmospheric Correction Inter-comparison eXercise , 2018, Remote. Sens..
[10] John Rust. Using Randomization to Break the Curse of Dimensionality , 1997 .
[11] Uwe Soergel,et al. Potential and limits of InSAR data for building reconstruction in built-up areas , 2003 .
[12] T. Tadono,et al. VALIDATION OF "AW3D" GLOBAL DSM GENERATED FROM ALOS PRISM , 2016 .
[13] C. Tucker. Red and photographic infrared linear combinations for monitoring vegetation , 1979 .
[14] A. S. Belward,et al. Who launched what, when and why; trends in global land-cover observation capacity from civilian earth observation satellites , 2015 .
[15] Karen C. Seto,et al. Developing a method to estimate building height from Sentinel-1 data , 2020 .
[16] Rainald Borck,et al. Will skyscrapers save the planet? Building height limits and urban greenhouse gas emissions* , 2016 .
[17] Matthias Drusch,et al. Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services , 2012 .
[18] Robert Hecht,et al. Measuring Completeness of Building Footprints in OpenStreetMap over Space and Time , 2013, ISPRS Int. J. Geo Inf..
[19] David Frantz,et al. FORCE - Landsat + Sentinel-2 Analysis Ready Data and Beyond , 2019, Remote. Sens..
[20] Josef Aschbacher,et al. The European Earth monitoring (GMES) programme: Status and perspectives , 2012 .
[21] Thomas Esch,et al. Towards a Large-Scale 3D Modeling of the Built Environment - Joint Analysis of TanDEM-X, Sentinel-2 and Open Street Map Data , 2020, Remote. Sens..
[22] Xiaoqin Wang,et al. Building heights estimation using ZY3 data — A case study of Shanghai, China , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.
[23] Katia Perini,et al. Effects of vegetation, urban density, building height, and atmospheric conditions on local temperatures and thermal comfort , 2014 .
[24] Y. Kaufman,et al. Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery , 1988 .
[25] T. Fishman,et al. The Weight of Society Over Time and Space: A Comprehensive Account of the Construction Material Stock of Japan, 1945–2010 , 2015 .
[26] R. Goossens,et al. Airborne photogrammetry and lidar for DSM extraction and 3D change detection over an urban area – a comparative study , 2013 .
[27] C. Woodcock,et al. Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images , 2015 .
[28] Pascal Neis,et al. Comparison of Volunteered Geographic Information Data Contributions and Community Development for Selected World Regions , 2013, Future Internet.
[29] P. Daszak,et al. Economic growth, urbanization, globalization, and the risks of emerging infectious diseases in China: A review , 2016, Ambio.
[30] Alain Royer,et al. Interannual landsat-MSS reflectance variation in an urbanized temperate zone , 1988 .
[31] Thomas Jagdhuber,et al. Sensitivity of Sentinel-1 backscatter to characteristics of buildings , 2017 .
[32] Chengquan Huang,et al. Modeling the height of young forests regenerating from recent disturbances in Mississippi using Landsat and ICESat data , 2011 .
[33] Wolfgang Wagner,et al. Optimisation of global grids for high-resolution remote sensing data , 2014, Comput. Geosci..
[34] Filip Biljecki,et al. Generating 3D city models without elevation data , 2017, Comput. Environ. Urban Syst..
[35] C. Ticehurst,et al. Radar backscatter analysis for urban environments , 1997 .
[36] K. Aringer,et al. Bavarian 3D Building Model and Update Concept Based on LiDAR, Image Matching and Cadastre Information , 2014 .
[37] Hannes Taubenböck,et al. Six fundamental aspects for conceptualizing multidimensional urban form: A spatial mapping perspective , 2018, Landscape and Urban Planning.
[38] Jardar Lohne,et al. Impact of Urban Density and Building Height on Energy Use in Cities , 2016 .
[39] Joachim Hill,et al. An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[40] E. Crist. A TM Tasseled Cap equivalent transformation for reflectance factor data , 1985 .
[41] Peter M. Atkinson,et al. Estimating the spatial distribution of the population of Riyadh, Saudi Arabia using remotely sensed built land cover and height data , 2013, Comput. Environ. Urban Syst..
[42] David A. Seal,et al. The Shuttle Radar Topography Mission , 2007 .
[43] Zhe Zhu,et al. Object-based cloud and cloud shadow detection in Landsat imagery , 2012 .
[44] Maria A. Brovelli,et al. A New Method for the Assessment of Spatial Accuracy and Completeness of OpenStreetMap Building Footprints , 2018, ISPRS Int. J. Geo Inf..
[45] Qingquan Li,et al. The Impacts of Building Orientation on Polarimetric Orientation Angle Estimation and Model-Based Decomposition for Multilook Polarimetric SAR Data in Urban Areas , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[46] Hannes Taubenböck,et al. Performance Evaluation for 3-D City Model Generation of Six Different DSMs From Air- and Spaceborne Sensors , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[47] Jay Gao,et al. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery , 2003 .
[48] Zhe Zhu,et al. Understanding an urbanizing planet: Strategic directions for remote sensing , 2019, Remote Sensing of Environment.
[49] Malcolm Davidson,et al. GMES Sentinel-1 mission , 2012 .
[50] Patrick Hostert,et al. Mapping Cropping Practices on a National Scale Using Intra-Annual Landsat Time Series Binning , 2019, Remote. Sens..
[51] Nicolas Baghdadi,et al. Rapid Urban Mapping Using SAR/Optical Imagery Synergy , 2008, Sensors.
[52] Stefan Dech,et al. A semi-automated approach for the generation of a new land use and land cover product for Germany based on Landsat time-series and Lucas in-situ data , 2017 .
[53] Stephen V. Stehman,et al. Gross forest cover loss in temperate forests: biome-wide monitoring results using MODIS and Landsat data , 2009 .
[54] T. Brandeis,et al. Mapping tropical dry forest height, foliage height profiles and disturbance type and age with a time series of cloud-cleared Landsat and ALI image mosaics to characterize avian habitat , 2010 .
[55] Michael Schmidt,et al. Enhancing the Detectability of Clouds and Their Shadows in Multitemporal Dryland Landsat Imagery: Extending Fmask , 2015, IEEE Geoscience and Remote Sensing Letters.
[56] M. Janssen,et al. A comparison of national open data policies: lessons learned , 2015 .
[57] I. Hajnsek,et al. Polarization orientation effects in urban areas on SAR data , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..
[58] P. Hostert,et al. Mining dense Landsat time series for separating cropland and pasture in a heterogeneous Brazilian savanna landscape , 2015 .
[59] Xiao Xiang Zhu,et al. Large-Area Characterization of Urban Morphology—Mapping of Built-Up Height and Density Using TanDEM-X and Sentinel-2 Data , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[60] Wolfgang Wagner,et al. Methods to Remove the Border Noise From Sentinel-1 Synthetic Aperture Radar Data: Implications and Importance For Time-Series Analysis , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[61] Hannes Taubenböck,et al. Continental-scale mapping and analysis of 3D building structure , 2020 .
[62] Christian Heipke,et al. UAV-based photogrammetry: monitoring of a building zone , 2014 .
[63] Emmanuel P. Baltsavias,et al. A comparison between photogrammetry and laser scanning , 1999 .
[64] B. Tan,et al. Land-cover change in the Caucasus Mountains since 1987 based on the topographic correction of multi-temporal Landsat composites , 2020 .
[65] P. Deschamps,et al. Atmospheric modeling for space measurements of ground reflectances, including bidirectional properties. , 1979, Applied optics.
[66] Andreas Uhl,et al. Improvement of the Fmask algorithm for Sentinel-2 images: Separating clouds from bright surfaces based on parallax effects , 2018, Remote Sensing of Environment.
[67] Hanqiu Xu. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .