2020
Authors
Fernandes, H; Costa, P; Filipe, V; Paredes, H; Barroso, J;
Publication
UNIVERSAL ACCESS IN THE INFORMATION SOCIETY
Abstract
The fourth author name was missed in the original publication. The correct list of authors should read as "Hugo Fernandes, Paulo Costa, Vitor Filipe, Hugo Paredes, Joao Barroso". It has been corrected in this erratum. The original article has been updated.
2020
Authors
Narciso, D; Melo, M; Rodrigues, S; Cunha, JPS; Bessa, M;
Publication
2020 IEEE 20TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE 2020)
Abstract
Training firefighters using Virtual Reality (VR) technology brings several benefits over traditional training methods including the reduction of costs and risks. The ability of causing the same level of stress as a real situation so that firefighters can learn how to deal with stress was investigated. An experiment aiming to study the influence that additional stimuli (heat, weight, smell and using personal protective equipment-PPE) have on user's stress level while performing a Virtual Environment (VE) designed to train firefighters was developed. Participants' stress and Heart Rate Variability (HRV) were obtained from electrocardiograms recorded during the experiment. The results suggest that wearing the PPE has the largest impact on user's stress level. The results also showed that HRV was able to evidence differences between two phases of the experiment, which suggests that it can be used to monitor users' quantified reaction to VEs.
2020
Authors
Adao, T; Soares, A; Padua, L; Guimaraes, N; Pinho, T; Sousa, JJ; Morais, R; Peres, E;
Publication
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
Abstract
Developed focusing agriculture sustainability, mySense is a comprehensive close-range sensor-based data management environment to improve precision farming practices. It integrates discussion platforms for quick problem solving through experts support and a computational intelligence layer for multipurpose application (e.g. vine variety discrimination, plant disease detection and identification). Attending the need for keeping track of agricultural crops not only based on close-range sensing but also at a macro perspective, mySense was complemented with proper functionalities to unlock macro-monitoring features, through the implementation of a Web-based Geographical Information System (WebGIS) planned as a sidekick application that provides agriculture professionals with visual decision support tools over remote sensed data. This paper presents and discusses its specification and implementation.
2020
Authors
Padua, L; Marques, P; Martins, L; Sousa, A; Peres, E; Sousa, JJ;
Publication
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
Abstract
Individual tree segmentation is a challenging task due to the labour-intensive and time-consuming work required. Remote sensing data acquired from sensors coupled in unmanned aerial vehicles (UAV) constitutes a viable alternative to provide a quicker data acquisition, covering broader areas in a shorter period of time. This study aims to use UAV-based multispectral imagery to automatically identify individual trees in a chestnut stand. Tree parameters were estimated allowing its characterization. The leaf area index (LAI) was measured and was correlated with the estimated parameters. A good correlation was found for NDVI (R-2 = 0.76), while this relationship was less evident in the tree crown area and tree height. This way, our results indicate that the use of UAV-based multispectral imagery is a quick and reliable way to determine canopy structural parameters and LAI of chestnut trees.
2020
Authors
Kazwiny, Y; Pedroso, JM; Zhang, Z; Boesmans, W; D'hooge, J; Vanden Berghe, P;
Publication
Abstract
2020
Authors
Hruska, J; Padua, L; Adao, T; Peres, E; Martinho, J; Sousa, JJ;
Publication
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
Abstract
Unmanned aerial vehicles (UAVs) are used nowadays as a standard tool to derive very high-resolution geospatial data. However, UAV payload limitation imposes the use of not such reliable hardware affecting the georeferencing precision. In the literature it is possible to find numerous studies investigating the parameters influencing UAV-based products quality. Even if new photogrammetry methods could, in theory, avoid the use of ground control points (GCPs), they still play a key role to assure quality products. Nevertheless, usually only the number and distribution of GCPs are taking into account, since both change the geometric accuracy of the final products. In order to improve the understanding of the actual influence of GCPs, in this study we evaluate how can different physical characteristics affect GCPs identification in aerial images. The results demonstrate that GCPs' color, material, size and shape, among others, may influence a precise identification in aerial imagery.
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