Zobrazeno 1 - 10
of 285
pro vyhledávání: '"C Fonte"'
Autor:
D. Duarte, C. C. Fonte
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-1-W1-2023, Pp 813-820 (2023)
Information regarding the residential status of the built-area is used within several contexts such as disaster management, urban and regional planning, among others. Currently such non-residential built-up information can be extracted for most of Eu
Externí odkaz:
https://doaj.org/article/e2ee6661a59d4db7921a89e38282e74b
Autor:
Cidália C. Fonte, Diogo Duarte, Ismael Jesus, Hugo Costa, Pedro Benevides, Francisco Moreira, Mário Caetano
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1504 (2024)
The free availability of Sentinel-1 and 2 imageries enables the production of high resolution (10 m) global Land Use Land Cover (LULC) maps by a wide range of institutions, which often make them publicly available. This raises several issues: Which m
Externí odkaz:
https://doaj.org/article/dc1066b4b1f44a3b9b5d2a4715d39cd1
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-3-2022, Pp 25-31 (2022)
Synoptic remote sensing systems have been broadly used within supervised classification methods to map land use and land cover (LULC). Such methods rely on high quality sets of training data that are able to characterize the target classes. Often, tr
Externí odkaz:
https://doaj.org/article/4833dae8efc74d2eb3ee3ecabdd147e1
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-3-2020, Pp 669-674 (2020)
Traditionally the accuracy assessment of a hard raster-based land use land cover (LULC) map uses a reference data set that contains one LULC class per pixel, which is the class that has the largest area in each pixel. However, when mixed pixels exist
Externí odkaz:
https://doaj.org/article/d4f8ad5cc4c1489ca33c4605f03b7488
Publikováno v:
Revista IBRACON de Estruturas e Materiais, Vol 13, Iss 3, Pp 628-643 (2020)
Abstract The practical evaluation of aerodynamic coefficients in unconventional concrete structures requires specific studies, which are small-scale models evaluated in wind tunnels. Sophisticated facilities and special sensors are needed, and the te
Externí odkaz:
https://doaj.org/article/e22fe0d0db124633b1565032e57baa8b
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-2-W13, Pp 1213-1220 (2019)
The aim of this paper is to perform a preliminary analysis of the compatibility and quality of the available time series of land cover data available for continental Portugal, in particular, Climate Change Initiative Land Cover maps, which are availa
Externí odkaz:
https://doaj.org/article/c49ddcb517f6449a9c6ec6a0884f4e1c
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4, Pp 217-224 (2018)
Volunteered geographical information (VGI) is an increasing source of data for many applications. In order to explore some of these sources of data, an algorithm was conceived and implemented in the ExploringVGI platform enabling the collection of ge
Externí odkaz:
https://doaj.org/article/9a4b81b88c654e72a869b0055e76a1dc
Autor:
C. C. Fonte, L. M. S. Gonçalves
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4, Pp 201-208 (2018)
The aim of this article is to assess if the data provided by soft classifiers and uncertainty measures can be used to identify regions with different levels of accuracy in a classified image. To this aim a soft Bayesian classifier was used, which ena
Externí odkaz:
https://doaj.org/article/c7bd352040a640efac514afbb4094a9f
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4, Pp 209-215 (2018)
This paper examines the feasibility of using data from OpenStreetMap (OSM), Facebook and Foursquare as a source of information on the function of buildings. Such information is rarely openly available and if available, would vary between cities by no
Externí odkaz:
https://doaj.org/article/3ea059d72f054df0872edd318ac45575
Publikováno v:
Geo-spatial Information Science, Vol 20, Iss 3, Pp 252-268 (2017)
This paper extends recent research into the usefulness of volunteered photos for land cover extraction, and investigates whether this usefulness can be automatically assessed by an easily accessible, off-the-shelf neural network pre-trained on a vari
Externí odkaz:
https://doaj.org/article/3744fc8210764fceb1a2d496c3d3bda4