BENCHMARK OF MACHINE LEARNING METHODS FOR CLASSIFICATION OF A SENTINEL-2 IMAGE

Pirotti, F.; Sunar, F.; Piragnolo, M.

doi:https://doi.org/10.5194/isprs-archives-XLI-B7-335-2016

COMPARING ACCURACY OF ULTRA-DENSE LASER SCANNER AND PHOTOGRAMMETRY POINT CLOUDS

F. Pirotti, M. Piragnolo, A. Vettore, and A. Guarnieri

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 353–359, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-353-2022,https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-353-2022, 2022

HOW EFFICIENT CAN SENTINEL-2 DATA HELP SPATIAL MAPPING OF MUCILAGE EVENT IN THE MARMARA SEA?

F. Sunar, A. Dervisoglu, N. Yagmur, E. Colak, E. Kuzyaka, and S. Mutlu

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 181–186, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-181-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-181-2022, 2022

A COMPARISON BETWEEN UWB AND LASER-BASED PEDESTRIAN TRACKING

A. Masiero, P. Dabove, V. Di Pietra, M. Piragnolo, A. Vettore, A. Guarnieri, C. Toth, V. Gikas, H. Perakis, K.-W. Chiang, L. M. Ruotsalainen, S. Goel, and J. Gabela

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 839–844, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-839-2022,https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-839-2022, 2022

A COMPARISON BETWEEN CYCLE-GAN BASED FEATURE TRANSLATION AND OPTICAL-SAR VEGETATION INDICES

E. Çolak and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 583–588, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-583-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-583-2022, 2022

A COMPARATIVE ASSESSMENT OF LAND USE-LAND COVER DYNAMICS BETWEEN BANGLADESH AND INDIAN SUNDARBANS FROM 1975–2020: A GEOSPATIAL AND STATISTICAL-BASED APPROACH

A. H. Kanan and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 625–632, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-625-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-625-2022, 2022

SENTINEL-5P NO2 DATA: CROSS-VALIDATION AND COMPARISON WITH GROUND MEASUREMENTS

F. Tonion and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 749–756, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-749-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-749-2022, 2022

DETECTING AND EVALUATING DISTURBANCE IN TEMPERATE RAINFOREST WITH SENTINEL-2, MACHINE LEARNING AND FOREST PARAMETERS

E. Kutchartt, J. Hernández, P. Corvalán, Á. Promis, and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 913–920, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-913-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-913-2022, 2022

SEAWEED PRESENCE DETECTION USING MACHINE LEARNING AND REMOTE SENSING

F. Tonion and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1011–1017, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1011-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1011-2022, 2022

ASSESSMENT OF CANOPY AND GROUND HEIGHT ACCURACY FROM GEDI LIDAR OVER STEEP MOUNTAIN AREAS

E. Kutchartt, M. Pedron, and F. Pirotti

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 431–438, https://doi.org/10.5194/isprs-annals-V-3-2022-431-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-431-2022, 2022

THE USE OF SENTINEL 1/2 VEGETATION INDEXES WITH GEE TIME SERIES DATA IN DETECTING LAND COVER CHANGES IN THE SINOP NUCLEAR POWER PLANT CONSTRUCTION SITE

E. Çolak, M. Chandra, and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 701–706, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-701-2021,https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-701-2021, 2021

SPATIOTEMPORAL CHANGE ANALYSIS OF THE PROTECTED AREAS: A CASE STUDY – İĞNEADA FLOODPLAIN FORESTS

M. Toker, E. Çolak, and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 735–740, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-735-2021,https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-735-2021, 2021

A CASE STUDY OF PEDESTRIAN POSITIONING WITH UWB AND UAV CAMERAS

A. Masiero, P. Dabove, V. Di Pietra, M. Piragnolo, A. Vettore, S. Cucchiaro, A. Guarnieri, P. Tarolli, C. Toth, V. Gikas, H. Perakis, K.-W. Chiang, L. M. Ruotsalainen, S. Goel, and J. Gabela

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2021, 111–116, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-111-2021,https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-111-2021, 2021

THE USE OF SPECTRAL AND TEXTURAL FEATURES IN CROP TYPE MAPPING USING SENTINEL-2A IMAGES: A CASE STUDY, ÇUKUROVA REGION, TURKEY

A. Tuzcu Kokal, A. F. Sunar, A. Dervisoglu, and S. Berberoglu

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 117–122, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-117-2021,https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-117-2021, 2021

ASSESSMENT OF VOLUME AND ABOVE-GROUND BIOMASS IN ARAUCARIA FOREST THROUGH SATELLITE IMAGES, COMPARING DIFFERENT METHODS IN THE SOUTH OF CHILE

F. Pirotti, E. Kutchartt, and E. Csaplovics

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 331–336, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-331-2020,https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-331-2020, 2020

TRAINING IN INNOVATIVE TECHNOLOGIES FOR CLOSE-RANGE SENSING IN ALPINE TERRAIN – 3RD EDITION

M. Rutzinger, K. Anders, M. Bremer, B. Höfle, R. Lindenbergh, S. Oude Elberink, F. Pirotti, M. Scaioni, and T. Zieher

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 243–250, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-243-2020,https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-243-2020, 2020

APPLICATION OF TREE DETECTION METHODS OVER LIDAR DATA FOR FOREST VOLUME ESTIMATION

F. Pirotti, C. Paterno, and M. Pividori

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1055–1060, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1055-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1055-2020, 2020

MACHINE LEARNING FOR CLASSIFICATION OF AN ERODING SCARP SURFACE USING TERRESTRIAL PHOTOGRAMMETRY WITH NIR AND RGB IMAGERY

H. Bernsteiner, N. Brožová, I. Eischeid, A. Hamer, S. Haselberger, M. Huber, A. Kollert, T. M. Vandyk, and F. Pirotti

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 431–437, https://doi.org/10.5194/isprs-annals-V-3-2020-431-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-431-2020, 2020

A MACHINE LEARNING APPROACH TO MULTISPECTRAL SATELLITE DERIVED BATHYMETRY

F. Tonion, F. Pirotti, G. Faina, and D. Paltrinieri

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 565–570, https://doi.org/10.5194/isprs-annals-V-3-2020-565-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-565-2020, 2020

A spatially explicit database of wind disturbances in European forests over the period 2000–2018

Giovanni Forzieri, Matteo Pecchi, Marco Girardello, Achille Mauri, Marcus Klaus, Christo Nikolov, Marius Rüetschi, Barry Gardiner, Julián Tomaštík, David Small, Constantin Nistor, Donatas Jonikavicius, Jonathan Spinoni, Luc Feyen, Francesca Giannetti, Rinaldo Comino, Alessandro Wolynski, Francesco Pirotti, Fabio Maistrelli, Ionut Savulescu, Stéphanie Wurpillot-Lucas, Stefan Karlsson, Karolina Zieba-Kulawik, Paulina Strejczek-Jazwinska, Martin Mokroš, Stefan Franz, Lukas Krejci, Ionel Haidu, Mats Nilsson, Piotr Wezyk, Filippo Catani, Yi-Ying Chen, Sebastiaan Luyssaert, Gherardo Chirici, Alessandro Cescatti, and Pieter S. A. Beck

Earth Syst. Sci. Data, 12, 257–276, https://doi.org/10.5194/essd-12-257-2020,https://doi.org/10.5194/essd-12-257-2020, 2020

Short summary

URBAN GEO BIG DATA

M. A. Brovelli, P. Boccardo, G. Bordogna, A. Pepe, M. Crespi, M. Munafò, and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W14, 23–30, https://doi.org/10.5194/isprs-archives-XLII-4-W14-23-2019,https://doi.org/10.5194/isprs-archives-XLII-4-W14-23-2019, 2019

THE USE OF MULTI-TEMPORAL SENTINEL SATELLITES IN THE ANALYSIS OF LAND COVER/LAND USE CHANGES CAUSED BY THE NUCLEAR POWER PLANT CONSTRUCTION

E. Çolak, M. Chandra, and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W8, 491–495, https://doi.org/10.5194/isprs-archives-XLII-3-W8-491-2019,https://doi.org/10.5194/isprs-archives-XLII-3-W8-491-2019, 2019

FLOOD ANALYSIS WITH REMOTE SENSING DATA – A CASE STUDY: MARITSA RIVER, EDIRNE

A. F. Sunar, N. Yagmur, and A. Dervisoglu

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W8, 497–502, https://doi.org/10.5194/isprs-archives-XLII-3-W8-497-2019,https://doi.org/10.5194/isprs-archives-XLII-3-W8-497-2019, 2019

CLASSIFICATION OF AERIAL LASER SCANNING POINT CLOUDS USING MACHINE LEARNING: A COMPARISON BETWEEN RANDOM FOREST AND TENSORFLOW

F. Pirotti and F. Tonion

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1105–1111, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1105-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-1105-2019, 2019

DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS

E. Fissore and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1539–1544, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1539-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-1539-2019, 2019

DETECTION OF BUILDING ROOFS AND FACADES FROM AERIAL LASER SCANNING DATA USING DEEP LEARNING

F. Pirotti, C. Zanchetta, M. Previtali, and S. Della Torre

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 975–980, https://doi.org/10.5194/isprs-archives-XLII-2-W11-975-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W11-975-2019, 2019

EXTRACTION AND VISUALIZATION OF 3D BUILDING MODELS IN URBAN AREAS FOR FLOOD SIMULATION

C. E. Kilsedar, F. Fissore, F. Pirotti, and M. A. Brovelli

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 669–673, https://doi.org/10.5194/isprs-archives-XLII-2-W11-669-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W11-669-2019, 2019

PLANNING HARVESTING OPERATIONS IN FOREST ENVIRONMENT: REMOTE SENSING FOR DECISION SUPPORT

M. Piragnolo, S. Grigolato, and F. Pirotti

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3-W1, 33–40, https://doi.org/10.5194/isprs-annals-IV-3-W1-33-2019,https://doi.org/10.5194/isprs-annals-IV-3-W1-33-2019, 2019

INITIAL EVALUATION OF 3D RECONSTRUCTION OF CLOSE OBJECTS WITH SMARTPHONE STEREO VISION

A. Masiero, F. Fissore, M. Piragnolo, A. Guarnieri, F. Pirotti, and A. Vettore

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 289–293, https://doi.org/10.5194/isprs-archives-XLII-1-289-2018,https://doi.org/10.5194/isprs-archives-XLII-1-289-2018, 2018

MIGRATION OF DIGITAL CARTOGRAPHY TO CITYGML; A WEB-BASED TOOL FOR SUPPORTING SIMPLE ETL PROCEDURES

F. Fissore and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 193–200, https://doi.org/10.5194/isprs-archives-XLII-4-193-2018,https://doi.org/10.5194/isprs-archives-XLII-4-193-2018, 2018

COMPARISON OF VEGETATION INDICES FROM RPAS AND SENTINEL-2 IMAGERY FOR DETECTING PERMANENT PASTURES

M. Piragnolo, G. Lusiani, and F. Pirotti

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1381–1387, https://doi.org/10.5194/isprs-archives-XLII-3-1381-2018,https://doi.org/10.5194/isprs-archives-XLII-3-1381-2018, 2018

PREFACE

T. Tanzi, M. Chandra, O. Altan, and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 1–2, https://doi.org/10.5194/isprs-archives-XLII-3-W4-1-2018,https://doi.org/10.5194/isprs-archives-XLII-3-W4-1-2018, 2018

LAND USE/LAND COVER CHANGE DETECTION USING MULTI–TEMPORAL SATELLITE DATASET: A CASE STUDY IN ISTANBUL NEW AIRPORT

D. Akyürek, Ö. Koç, E. M. Akbaba, and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 17–22, https://doi.org/10.5194/isprs-archives-XLII-3-W4-17-2018,https://doi.org/10.5194/isprs-archives-XLII-3-W4-17-2018, 2018

REMOTE SENSING & GIS INTEGRATION FOR MONITORING THE AREAS AFFECTED BY FOREST FIRES: A CASE STUDY IN IZMIR, TURKEY

E. Çolak and A. F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 165–170, https://doi.org/10.5194/isprs-archives-XLII-3-W4-165-2018,https://doi.org/10.5194/isprs-archives-XLII-3-W4-165-2018, 2018

OPEN SOURCE WEB TOOL FOR TRACKING IN A LOWCOST MOBILE MAPPING SYSTEM

F. Fissore, F. Pirotti, and A. Vettore

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W8, 99–104, https://doi.org/10.5194/isprs-archives-XLII-2-W8-99-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W8-99-2017, 2017

COMPARISON OF LOW COST PHOTOGRAMMETRIC SURVEY WITH TLS AND LEICA PEGASUS BACKPACK 3D MODELSS

A. Masiero, F. Fissore, A. Guarnieri, M. Piragnolo, and A. Vettore

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W8, 147–153, https://doi.org/10.5194/isprs-archives-XLII-2-W8-147-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W8-147-2017, 2017

A COMPARISON OF TREE SEGMENTATION METHODS USING VERY HIGH DENSITY AIRBORNE LASER SCANNER DATA

F. Pirotti, M. Kobal, and J. R. Roussel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 285–290, https://doi.org/10.5194/isprs-archives-XLII-2-W7-285-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W7-285-2017, 2017

PRELIMINARY RESULTS OF EARTHQUAKE-INDUCED BUILDING DAMAGE DETECTION WITH OBJECT-BASED IMAGE CLASSIFICATION

A. Sabuncu, Z. D. Uca Avci, and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 347–350, https://doi.org/10.5194/isprs-archives-XLI-B7-347-2016,https://doi.org/10.5194/isprs-archives-XLI-B7-347-2016, 2016

SOIL SALINITY MAPPING USING MULTITEMPORAL LANDSAT DATA

A. Azabdaftari and F. Sunar

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 3–9, https://doi.org/10.5194/isprs-archives-XLI-B7-3-2016,https://doi.org/10.5194/isprs-archives-XLI-B7-3-2016, 2016

KERNEL FEATURE CROSS-CORRELATION FOR UNSUPERVISED QUANTIFICATION OF DAMAGE FROM WINDTHROW IN FORESTS

F. Pirotti, D. Travaglini, F. Giannetti, E. Kutchartt, F. Bottalico, and G. Chirici

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 17–22, https://doi.org/10.5194/isprs-archives-XLI-B7-17-2016,https://doi.org/10.5194/isprs-archives-XLI-B7-17-2016, 2016

BENCHMARK OF MACHINE LEARNING METHODS FOR CLASSIFICATION OF A SENTINEL-2 IMAGE

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