Artiklar
[1]
P. Zhang et al.,
"Assessing Sentinel-2, Sentinel-1, and ALOS-2 PALSAR-2 Data for Large-Scale Wildfire-Burned Area Mapping : Insights from the 2017–2019 Canada Wildfires,"
Remote Sensing, vol. 16, no. 3, 2024.
[2]
Y. Sun et al.,
"Cross-Modal Hashing With Feature Semi-Interaction and Semantic Ranking for Remote Sensing Ship Image Retrieval,"
IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.
[3]
Y. Zhou et al.,
"DCTN: Dual-Branch Convolutional Transformer Network With Efficient Interactive Self-Attention for Hyperspectral Image Classification,"
IEEE Transactions on Geoscience and Remote Sensing, vol. 62, s. 1-16, 2024.
[4]
R. Yadav et al.,
"Unsupervised flood detection on SAR time series using variational autoencoder,"
International Journal of Applied Earth Observation and Geoinformation, vol. 126, 2024.
[5]
I. Ioannidis et al.,
"Using remote sensing data to derive built-form indexes to analyze the geography of residential burglary and street thefts,"
Cartography and Geographic Information Science, s. 1-17, 2024.
[6]
L. Seegmiller och T. Shirabe,
"A method for finding a least-cost corridor on an ordinal-scaled raster cost surface,"
Annals of GIS, vol. 29, no. 2, s. 205-225, 2023.
[7]
R. Hosseini et al.,
"A Novel Method for Extracting and Analyzing the Geometry Properties of the Shortest Pedestrian Paths Focusing on Open Geospatial Data,"
ISPRS International Journal of Geo-Information, vol. 12, no. 7, 2023.
[8]
J. Huang och P. Zhang,
"Beyond Pixel-Wise Unmixing : Spatial-Spectral Attention Fully Convolutional Networks for Abundance Estimation,"
Remote Sensing, vol. 15, no. 24, 2023.
[9]
V. Belloni et al.,
"Crack Monitoring from Motion (CMfM) : Crack detection and measurement using cameras with non-fixed positions,"
Automation in Construction, vol. 156, 2023.
[10]
Y. Wang et al.,
"Effect of Manufacturing Conditions and Al Addition on Inclusion Characteristics in Co-Based Dual-Phase High Entropy Alloy,"
Metallurgical and Materials Transactions. A, vol. 54, no. 7, s. 2715-2729, 2023.
[11]
X. Hu et al.,
"GAN-based SAR and optical image translation for wildfire impact assessment using multi-source remote sensing data,"
Remote Sensing of Environment, vol. 289, s. 113522, 2023.
[12]
X. Hu, P. Zhang och Y. Ban,
"Large-scale burn severity mapping in multispectral imagery using deep semantic segmentation models,"
ISPRS journal of photogrammetry and remote sensing (Print), vol. 196, s. 228-240, 2023.
[13]
J. Hatzenbühler et al.,
"Modular vehicle routing for combined passenger and freight transport,"
Transportation Research Part A : Policy and Practice, vol. 173, s. 103688-103688, 2023.
[14]
S. Hafner, Y. Ban och A. Nascetti,
"Semi-Supervised Urban Change Detection Using Multi-Modal Sentinel-1 SAR and Sentinel-2 MSI Data,"
Remote Sensing, vol. 15, no. 21, 2023.
[15]
M. Nhangumbe et al.,
"Supervised and unsupervised machine learning approaches using Sentinel data for flood mapping and damage assessment in Mozambique,"
Remote Sensing Applications: Society and Environment, vol. 32, 2023.
[16]
Y. Zhao, Y. Ban och J. Sullivan,
"Tokenized Time-Series in Satellite Image Segmentation With Transformer Network for Active Fire Detection,"
IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.
[17]
P. Zhang, Y. Ban och A. Nascetti,
"Total-variation regularized U-Net for wildfire burned area mapping based on Sentinel-1 C-Band SAR backscattering data,"
ISPRS journal of photogrammetry and remote sensing (Print), vol. 203, s. 301-313, 2023.
[18]
S. Georganos et al.,
"A census from heaven : Unraveling the potential of deep learning and Earth Observation for intra-urban population mapping in data scarce environments,"
International Journal of Applied Earth Observation and Geoinformation, vol. 114, 2022.
[19]
S. Georganos och S. Kalogirou,
"A Forest of Forests : A Spatially Weighted and Computationally Efficient Formulation of Geographical Random Forests,"
ISPRS International Journal of Geo-Information, vol. 11, no. 9, s. 471, 2022.
[20]
L. Seegmiller och T. Shirabe,
"A method for finding least-cost corridors in three-dimensional raster space,"
Transactions on GIS, vol. 26, no. 2, s. 1098-1115, 2022.
[21]
R. Yadav, A. Nascetti och Y. Ban,
"Deep attentive fusion network for flood detection on uni-temporal Sentinel-1 data,"
Frontiers in Remote Sensing, vol. 3, 2022.
[22]
K. Maier et al.,
"Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation,"
ISPRS journal of photogrammetry and remote sensing (Print), vol. 186, s. 1-18, 2022.
[23]
A. Lotfata et al.,
"Ecological Associations between Obesity Prevalence and Neighborhood Determinants Using Spatial Machine Learning in Chicago, Illinois, USA,"
ISPRS International Journal of Geo-Information, vol. 11, no. 11, 2022.
[24]
X. Li et al.,
"GCDB-UNet : A novel robust cloud detection approach for remote sensing images,"
Knowledge-Based Systems, vol. 238, 2022.
[25]
Y. Zhao och Y. Ban,
"GOES-R Time Series for Early Detection of Wildfires with Deep GRU-Network,"
Remote Sensing, vol. 14, no. 17, 2022.
[26]
A. Abascal et al.,
"Identifying degrees of deprivation from space using deep learning and morphological spatial analysis of deprived urban areas,"
Computers, Environment and Urban Systems, vol. 95, 2022.
[27]
T. Mugiraneza et al.,
"Monitoring urbanization and environmental impact in Kigali, Rwanda using Sentinel-2 MSI data and ecosystem service bundles,"
International Journal of Applied Earth Observation and Geoinformation, vol. 109, 2022.
[28]
Y. Sun et al.,
"Multisource Data Reconstruction-Based Deep Unsupervised Hashing for Unisource Remote Sensing Image Retrieval,"
IEEE Transactions on Geoscience and Remote Sensing, vol. 60, s. 1-16, 2022.
[29]
J. Wang et al.,
"On the knowledge gain of urban morphology from space,"
Computers, Environment and Urban Systems, vol. 95, 2022.
[30]
S. Hafner et al.,
"Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection Using a Dual Stream U-Net,"
IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.
[31]
C. Morlighem et al.,
"The Multi-Satellite Environmental and Socioeconomic Predictors of Vector-Borne Diseases in African Cities : Malaria as an Example,"
Remote Sensing, vol. 14, no. 21, 2022.
[32]
R. Palmberg et al.,
"Towards a better understanding of the health impacts of one’s movement in space and time,"
Journal of Literature and Science, s. 1-24, 2022.
[33]
S. Hafner, Y. Ban och A. Nascetti,
"Unsupervised domain adaptation for global urban extraction using Sentinel-1 SAR and Sentinel-2 MSI data,"
Remote Sensing of Environment, vol. 280, s. 113192, 2022.
[34]
L. Seegmiller, T. Shirabe och C. D. Tomlin,
"A method for finding least-cost corridors with reduced distortion in raster space,"
International Journal of Geographical Information Science, vol. 35, no. 8, s. 1570-1591, 2021.
[35]
R. Palmberg et al.,
"Built Environment Characteristics, Daily Travel, and Biometric Readings : Creation of an Experimental Tool Based on a Smartwatch Platform,"
Sustainability, vol. 13, no. 17, 2021.
[36]
J. Chen et al.,
"Collaborative validation of GlobeLand30 : Methodology and practices,"
GEO-SPATIAL INFORMATION SCIENCE, vol. 24, no. 1, s. 134-144, 2021.
[37]
T. Campisi et al.,
"Gender Equality and E-Scooters : Mind the Gap! A Statistical Analysis of the Sicily Region, Italy,"
Social Sciences, vol. 10, no. 10, 2021.
[38]
S. Georganos et al.,
"Is It All the Same? : Mapping and Characterizing Deprived Urban Areas Using WorldView-3 Superspectral Imagery. A Case Study in Nairobi, Kenya,"
Remote Sensing, vol. 13, no. 24, 2021.
[39]
P. Zhang, Y. Ban och A. Nascetti,
"Learning U-Net without Forgetting for Near Real-Time Wildfire Monitoring by the Fusion of SAR and Optical Time Series,"
Remote Sensing of Environment, vol. 261, no. 112467, 2021.
[40]
S. Hosseini et al.,
"Mapping the intellectual structure of GIS-T field (2008–2019) : a dynamic co-word analysis,"
Scientometrics, vol. 126, no. 4, s. 2667-2688, 2021.
[41]
R. M. Murekatete och T. Shirabe,
"On the effects of spatial resolution on effective distance measurement in digital landscapes,"
ECOLOGICAL PROCESSES, vol. 10, no. 1, 2021.
[42]
X. Hu, Y. Ban och A. Nascetti,
"Sentinel-2 MSI data for active fire detection in major fire-prone biomes : A multi-criteria approach,"
International Journal of Applied Earth Observation and Geoinformation, vol. 101, 2021.
[43]
S. P. Cumbane och G. Gidofalvi,
"Spatial Distribution of Displaced Population Estimated Using Mobile Phone Data to Support Disaster Response Activities,"
ISPRS International Journal of Geo-Information, vol. 10, no. 6, s. 421, 2021.
[44]
M. Kuffer et al.,
"Spatial Information Gaps on Deprived Urban Areas (Slums) in Low-and-Middle-Income-Countries : A User-Centered Approach,"
URBAN SCIENCE, vol. 5, no. 4, s. 72, 2021.
[45]
X. Hu, Y. Ban och A. Nascetti,
"Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning,"
Remote Sensing, vol. 13, no. 8, s. 1509, 2021.
[46]
J. W. Joubert et al.,
"A matching algorithm to study the evolution of logistics facilities extracted from GPS traces,"
Transportation Research Procedia, vol. 46, no. 2020, s. 237-244, 2020.
[47]
R. M. Murekatete och T. Shirabe,
"An experimental analysis of least-cost path models on ordinal-scaled raster surfaces,"
International Journal of Geographical Information Science, 2020.
[48]
T. Mugiraneza, A. Nascetti och Y. Ban,
"Continuous Monitoring of Urban Land Cover Change Trajectories with Landsat Time Series and LandTrendr-Google Earth Engine Cloud Computing,"
Remote Sensing, vol. 12, no. 18, 2020.
[49]
O. Stromann et al.,
"Dimensionality Reduction and Feature Selection for Object-Based Land Cover Classification based on Sentinel-1 and Sentinel-2 Time Series Using Google Earth Engine,"
Remote Sensing, vol. 12, no. 1, 2020.
[50]
B. Mao, Y. Ban och B. Laumert,
"Dynamic Online 3D Visualization Framework for Real-Time Energy Simulation Based on 3D Tiles,"
ISPRS International Journal of Geo-Information, vol. 9, no. 3, 2020.