Search Results - "Pirotti F"

Analysis of full-waveform LiDAR data for forestry applications: a review of investigations and methods by Pirotti, F

“…The goal of this review is to present leading examples of current methodologies for extracting forest characteristics from full-waveform LiDAR data. Four key…”
Get full text

SENTINEL-5P NO2 DATA: CROSS-VALIDATION AND COMPARISON WITH GROUND MEASUREMENTS by Tonion, F., Pirotti, F.

“…Sentinel-5P (S5P) data provide information on atmospheric pollutants daily, and, for higher latitudes, consequent orbits partially overlap the same day…”
Get full text

SEAWEED PRESENCE DETECTION USING MACHINE LEARNING AND REMOTE SENSING by Tonion, F., Pirotti, F.

“…The human pressure over coastal areas is becoming increasingly relevant, due to the combinations of resource depletion, climate change effects and ocean…”
Get full text

A COMPARATIVE ASSESSMENT OF LAND USE-LAND COVER DYNAMICS BETWEEN BANGLADESH AND INDIAN SUNDARBANS FROM 1975–2020: A GEOSPATIAL AND STATISTICAL-BASED APPROACH by Kanan, A. H., Pirotti, F.

“…The study aims to compare land use land cover (LULC) change between Bangladesh and Indian Sundarbans from 1975 to 2020 using Landsat Satellite images. We…”
Get full text

ASSESSMENT OF CANOPY AND GROUND HEIGHT ACCURACY FROM GEDI LIDAR OVER STEEP MOUNTAIN AREAS by Kutchartt, E., Pedron, M., Pirotti, F.

“…Active remote sensing systems orbiting the Earth are only a small portion of the current constellation of satellites and will increase in number and advance in…”
Get full text

UPDATING ABOVEGROUND BIOMASS AT A PAN-EUROPEAN SCALE THROUGH SATELLITE DATA AND ARTIFICIAL INTELLIGENCE by Pirotti, F., González-Olabarria, J. R., Kutchartt, E.

“…In this work, an ensemble of machine learning algorithms was trained using stratified sampling from an existing European-scale biomass map from 2018 to predict…”
Get full text

INFORSAT: AN ONLINE SENTINEL-2 MULTI-TEMPORAL ANALYSIS TOOL SET USING R CRAN by Pirotti, F., Kutchartt, E., Piragnolo, M.

“…Remote sensing via orbiting satellite sensors is today a common tool to monitor numerous aspects related to the Earth surface and the atmosphere. The amount of…”
Get full text

CLASSIFICATION OF AERIAL LASER SCANNING POINT CLOUDS USING MACHINE LEARNING: A COMPARISON BETWEEN RANDOM FOREST AND TENSORFLOW by Pirotti, F., Tonion, F.

“…In this investigation a comparison between two machine learning (ML) models for semantic classification of an aerial laser scanner point cloud is presented…”
Get full text

DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS by Fissore, E., Pirotti, F.

“…Using multiple sources of 3D information over buildings to go from building footprints (LOD0) to higher LODs in CityGML models is a widely investigated topic…”
Get full text

COMPARING ACCURACY OF ULTRA-DENSE LASER SCANNER AND PHOTOGRAMMETRY POINT CLOUDS by Pirotti, F., Piragnolo, M., Vettore, A., Guarnieri, A.

“…Massive point clouds have now become a common product from surveys using passive (photogrammetry) or active (laser scanning) technologies. A common question is…”
Get full text

Assessing land surface phenology in Araucaria-Nothofagus forests in Chile with Landsat 8/Sentinel-2 time series by Kosczor, E., Forkel, M., Hernández, J., Kinalczyk, D., Pirotti, F., Kutchartt, E.

“…•First analysis of landscape-scale phenology of Araucaria-Nothofagus forests.•Time series analysis of EVI from Landsat 8 & Sentinel-2 satellite imagery…”
Get full text

ASSESSMENT OF VOLUME AND ABOVE-GROUND BIOMASS IN ARAUCARIA FOREST THROUGH SATELLITE IMAGES, COMPARING DIFFERENT METHODS IN THE SOUTH OF CHILE by Pirotti, F., Kutchartt, E., Csaplovics, E.

“…Initial results of biomass estimation in the La Fusta area from existing equations found in literature are presented. As expected, accuracy of general…”
Get full text

APPLICATION OF TREE DETECTION METHODS OVER LIDAR DATA FOR FOREST VOLUME ESTIMATION by Pirotti, F., Paterno, C., Pividori, M.

“…Lidar (light detection and ranging) data are becoming more and more important in the analysis of the most relevant forest parameters. This study aims to…”
Get full text

MIGRATION OF DIGITAL CARTOGRAPHY TO CITYGML; A WEB-BASED TOOL FOR SUPPORTING SIMPLE ETL PROCEDURES by Fissore, F., Pirotti, F.

“…Digital cartography is notably produced in all countries, in different scales and formats. Latest cartographic production aims at creating 3D objects with…”
Get full text

DETECTION OF BUILDING ROOFS AND FACADES FROM AERIAL LASER SCANNING DATA USING DEEP LEARNING by Pirotti, F., Zanchetta, C., Previtali, M., Della Torre, S.

“…In this work we test the power of prediction of deep learning for detection of buildings from aerial laser scanner point cloud information. Automatic…”
Get full text

AUTOMATIC COARSE CO-REGISTRATION OF POINT CLOUDS FROM DIVERSE SCAN GEOMETRIES: A TEST OF DETECTORS AND DESCRIPTORS by Pirotti, F., Guarnieri, A., Chiodini, S., Bettanini, C.

“…Point clouds are collected nowadays from a plethora of sensors, some having higher accuracies and higher costs, some having lower accuracies but also lower…”
Get full text

DETECTING AND EVALUATING DISTURBANCE IN TEMPERATE RAINFOREST WITH SENTINEL-2, MACHINE LEARNING AND FOREST PARAMETERS by Kutchartt, E., Hernández, J., Corvalán, P., Promis, Á., Pirotti, F.

“…Earth observation via remote sensing imagery provides a fast way to define alteration levels. In this work 12 stands of Araucaria-Nothofagus forests were…”
Get full text

A COMPARISON OF TREE SEGMENTATION METHODS USING VERY HIGH DENSITY AIRBORNE LASER SCANNER DATA by Pirotti, F., Kobal, M., Roussel, J. R.

“…Developments of LiDAR technology are decreasing the unit cost per single point (e.g. single-photo counting). This brings to the possibility of future LiDAR…”
Get full text

EXTRACTION AND VISUALIZATION OF 3D BUILDING MODELS IN URBAN AREAS FOR FLOOD SIMULATION by Kilsedar, C. E., Fissore, F., Pirotti, F., Brovelli, M. A.

“…Floods pose a risk that is likely to worsen in the future due to climate change. Therefore, it is essential that decision makers and domain experts have the…”
Get full text

Preface: Workshop “Smart Forests – Forest ecosystem assessment and monitoring using Remote Sensing, Artificial Intelligence, and Robotics” by Liang, X., Wang, Y., Pirotti, F., White, J. C., Faßnacht, F., Melis, M. T., Gong, W., Yamashita, M., Hernandez, J., Mokroš, M., Campos, M., Pierdicca, R.

Get full text