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- Evaluation of machine learning algorithms in the classification of multispectral images from the Sentinel-2A/2B Orbital Sensor for mapping the environmental dynamics of Ria Formosa (Algarve, Portugal)Publication . Souza, Flavo Elano Soares de; Rodrigues, José InácioWith the growing availability of remote sensing orbital spatial data, the applications of machine learning (ML) algorithms have been leveraging the field of process automation in image classification. The present work aimed to evaluate the precision and accuracy of ML algorithms in the classification of Sentinel 2A/2B images from an area of high environmental dynamics, such as Ria Formosa (Algarve, Portugal). The images were submitted to classification by groups of ML algorithms such as the Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), and Decision Tree (DT). The Orfeo Toolbox (OTB) open-source programming package made the algorithms available. Ten samples were collected for each of the 14 land use and cover classes in the Ria Formosa area, totaling 140 samples. Of these, 70% were for training and 30% for validating the classification. The evaluation metrics used were the class discrimination measures: Recall (R), the Global Kappa Index (k), and the General Accuracy Index (OA). The results showed that the KNN and DT algorithms demonstrated a greater discrimination capacity for most classes. SVM and RF significantly improved class discrimination when using larger samples for training. Merging the classified images significantly improved the classification accuracy, ranging from 71% to 81%. This evaluation made it possible to define sets of ML algorithms sensitive to change detection for mapping and monitoring dynamic environments.
- Improving access to greenspaces in the Mediterranean city of FaroPublication . Duarte Pinto, Vanessa; Martins, Catarina; Rodrigues, José Inácio; Pires Rosa, ManuelaGreen infrastructure has received increasing attention in urban strategies in a sustainable and resilience context, since greenspaces provide diverse ecosystem services. Green roofs can be a form of compensating the loss of ecosystem services and biodiversity in urban areas, contribute to safe access to greenspaces, which is important in times of social isolation, due to viral pandemics, and can guarantee self-reliance food. Thus, this urban measure should be integrated in urban planning and management, by using urban indicators associated with citizens access to greenspaces. Hence, we study pedestrian accessibility to green areas and propose an urban solution to improve access to greenspaces. The assessment is developed using indicators related to the citizens living in the surroundings of green areas and the residential buildings that exist in these areas; the residents living in potential green buildings or blocks with private green roofs and the potential green buildings with private green roofs. The ideal standard distances were considered to analyze the proximity of green areas to the dwellings of residents. We used GIS for the assessment of distances over the pedestrian network. The results indicate the necessity of building green roofs through the private sector. The developed indicators provide an important contribution to the municipal management in the definition of criteria for the urban location of green roofs to promote better access to ecosystem services.
- 3D Modeling of the Milreu Roman Heritage with UAVsPublication . Rodrigues, José Inácio; Figueiredo, Mauro; Bernardes, João Pedro; Gonçalves, CésarIn this paper we present a methodology to build a 3D model of a roman heritage site in the South of Portugal, known as Milreu, covering a region of about one hectare. Today's Milreu ruins, a national heritage site, were once part of a 4rd century, luxurious villa-style manor house, which was subsequently converted into a thriving farm. Due to its relevance, it is important to make the 3D model of the Milreu ruins, to be available for the exploration in the Web and for virtual and augmented reality applications for mobile devices. This paper demonstrates the use of UAVs for the reconstruction of the 3D models of the ruins from vertical and oblique aerial photographs. To enhance the model quality and precision, terrestrial photographs were also incorporated in the workflow. This model is georeferenced, which give us the possibility to automatically determine accurate measurements of the Roman structures.