3D Point Clouds in Urban Planning: Developing and Releasing High-end Methodologies based on LiDAR and UAV Data for the Extraction of Building Parameters

Os dados geográficos têm um papel determinante na formalização do plano urbano, enquanto instrumento de planeamento e documento normativo que define juridicamente as obrigações públicas e vincula os particulares, num determinado período temporal, no que respeita a disciplina urbanística de uma cidade ou de um aglomerado urbano, estabelecendo regras de uso e de ocupação do solo. O plano está associado a um processo, designado processo de planeamento; processo esse que e constituído por um conjunto de fases, dinâmicas e adaptativas, que se iniciam na sua elaboração e terminam na avaliação dos desvios entre o determinado no documento inicial e as metas e objectivos efectivamente atingidos. O plano, o processo e a praxis do planeamento exigem dados geográficos actualizados a cada instante, quer para as acções de monitorização quer para os momentos de avaliação. Um dos aspectos cruciais do plano e a quantificação da volumetria do espaço edificado existente. Outro aspecto, também fundamental, é o da gestão dessa volumetria; quer da volumetria existente quer da volumetria adicional. O tema da volumetria dos espaços edificados tem constituído, aliás, um dos temas mais sensíveis quando se trata da densificação do espaço urbano existente ou do desenho de novos espaços urbanos de expansão. Considerando o quadro teórico apresentado, o tema central da tese trata da modelação de nuvens de pontos 3D obtidas por tecnologia LiDAR e por UAV, para as aplicações na elaboração do plano e no processo de planeamento urbano, designadamente quantificação dos parâmetros urbanísticos altura da fachada e volume dos edifícios.A exploração do tema central da tese suporta-se em dois níveis: o nível da operacionalização e o nível da usabilidade. O nível da operacionalizão concretiza dois objectivos: i) demonstração da relevância e da pertinência da extracção, medição e geovisualização 3D dos parâmetros urbanísticos baseadas na experimentação e implementação de técnicas de geoprocessamento; ii) demonstração da pertinência dos parâmetros urbanísticos extraídos considerando distintas morfologias urbanas. Para o nível da usabilidade de nem-se igualmente dois objectivos: i) demonstração da usabilidade dos parâmetros urbanísticos extraídos avaliando o erro associado a extracção; ii) demonstração da usabilidade dos parâmetros urbanísticos extraídos para planeamento, em particular para o mapeamento dasimétrico de alta precisão. Da investigação decorre uma solução metodol ogica. A solução metodológica nomeada 3D Extraction Building Parameters (3DEBP) destina-se a extracção da área, da altura da fachada e do volume dos edifícios a partir de nuvens de pontos 3D. Esta solução foi criada tendo por base um conjunto de ferramentas FOSS: PostgreSQL/PostGIS, QGIS, GRASS e R-stats. Foram realizados testes em duas áreas urbanas com morfologias distintas: Praia de Faro (morfologia irregular) e Amadora (morfologia regular). O teste sobre a área urbana da Praia de Faro utilizou uma nuvem de pontos LiDAR e uma outra extra da de levantamento realizado por UAV. O teste sobre um quarteirão urbano de Amadora foi realizado apenas sobre nuvem de pontos UAV. Os testes revelaram que a qualidade da informação extra da e dependente da morfologia urbana. Nas conclusões discute-se a medição 3D com base em dados obtidos por tecnologia LiDAR e UAV, questiona-se a implementação de soluções FOSS para diferentes fases do processo de planeamento e defende-se a introdução intensiva da modelação 3D no plano urbano do futuro.Geographical data plays a major role in urban plan development, both as a planning instrument and as a normative document that legally de nes public obligations and binds individuals, in a given period of time, regarding the urban aspect of a city or an urban conglomerate, and establishes standards for land use and land cover. The plan is associated with a process, called the planning process, which consists in a set of dynamic and adaptive phases that begin with its development and end with the evaluation of any discrepancies between the provisions of the original document and the accomplished goals and objectives. The plan, the process, and the planning praxis require up-to-date geographical data at all times, both for monitoring actions and for the evaluation phases. One of the crucial aspects of the plan is the quanti cation of the existing building volume. Another fundamental aspect is managing that volume: both regarding the existing volume and any additional volumes. Actually, the building volume in built areas has been one of the most sensitive topics on the densi cation of existing urban spaces or the design of new growing urban areas. Considering the existing theoretical framework, the central topic of this thesis focuses on 3D point cloud modelling obtained from LiDAR and UAV technologies, employed in the development of a plan and in the urban planning process, namely regarding two speci c building parameters { building height and volume. The explanation of the central topic of this thesis is twofold: implementation and usability. The implementation level has two goals: i) demonstrating the relevance and pertinence of the extraction, measurement, and 3D geovisualization of building parameters based on the experimentation and implementation of geoprocessing techniques; ii) demonstrating the pertinence of the extracted building parameters considering di erent urban morphologies. At the usability level, we de ned two goals: i) demonstrating the usability of the extracted building parameters, evaluating the error associated with the extraction; ii) demonstrating the usability of these parameters for planning, particularly for high precision dasymetric mapping. Based on our research, we propose a methodological solution termed. 3D Extraction Building Parameters (3DEBP) and aimed at extracting areas, fa cade height, and building volumes from 3D point clouds. This solution was created with the following set of FOSS tools: PostgreSQL/PostGIS, GRASS, QGIS, and R-stats. We performed several tests in two urban areas with di erent morphologies: Praia de Faro (irregular morphology) and Amadora (regular morphology). The former (Praia de Faro) used a LiDAR point cloud and another one extracted from a UAV survey, while the latter (urban neighbourhood of Amadora) only used a UAV point cloud. Both experiments reveal that the quality of the information extracted depends on urban morphology. Finally, we discuss 3D measurement based on data obtained from LiDAR and UAV technology, raising questions on the implementation of FOSS solutions for di erent phases of the planning process, and arguing for the intensive introduction of 3D modelling for the future of urban planning

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications