Vigiando o ambiente terrestre açoriano desde o espaço

A secção UAciência é coordenada pelo Professor Universitário Armindo Rodrigues.[…]. Nos últimos anos tem crescido de modo assinalável o leque de satélites disponíveis para Detecao Remota (DR) cujo único objetivo e obter imagens que permitam identificar e cartografar desde o espaço diferentes áreas (exemplos: urbanas, florestais, naturais, planos de agua, rochosas) ou fenómenos (exemplos: stress hídrico em plantações, erosão hídrica superficial em solos, derrocadas em vertentes, ilhas de calor em cidades) em toda a superfície terrestre num determinado período de tempo. A crescente utilização combinada e integrada dos distintos sensores de observação terrestre disponíveis tem vindo a originar uma enorme quantidade de informação, assim como uma nova forma de estudar a superfície terrestre. […].info:eu-repo/semantics/publishedVersio

Cartografia de vegetação invasora nos Açores : imagens de satélite como solução barata e eficiente

A secção UAciência é coordenada pelo Professor Universitário Armindo Rodrigues.[…]. Pelas suas características geográficas, ambientais e socioeconómicas, o uso de DR por satélite constitui uma solução interessante e com boa relação custo-benefício para a vigilância e monitorização das áreas terrestres e marinhas do Arquipélago dos Acores. Há, contudo, algumas variáveis que condicionam o pleno aproveitamento desta tecnologia a nível regional, como por exemplo a quase constante nebulosidade que impede a obtenção frequente e periódica de imagens óticas por parte da missão espacial de DR mais importante e antiga a nível global: o Programa Landsat da NASA/USGS (EUA), cujas imagens recolhidas são disponibilizadas gratuitamente. As alternativas (menos económicas) que permitem de algum modo contornar estas condicionantes passam assim quer pela aquisição de imagens óticas de sensores comerciais (com pedidos “a la carte”), quer pela execução de levantamentos aéreos (seja com avião, seja com drones – a tendência mais recente e mais económica). […].info:eu-repo/semantics/publishedVersio

Conservation strategies for island - the "Park Island" of Pico (Azores)

É apresentado o conceito de Parque ilha e desenvolvido uma metodologia de caracterização e avaliação dos sistemas ecológicos em contexto insula

Challenges and opportunities of implementing a ,mobile bank in Portugal by Altice Group

This research intends to provide a deeper overview of the market challenges and opportunities of establishing a mobile bank in Portugal by Altice Group, through the investigation of the main forces that are disrupting the industry, combining with a market research through an online questionnaire that adds evidence in those findings and provides deeper view of the Portuguese market. With this research the company is able to understand how it can add value to the industry and which future business model is proposed

Sustainable Development and Environmental Conservation in the Outermost European Regions

The Outermost European Regions (OERs) are geographic areas which are part of a European Union Member State, but situated outside continental Europe. All OERs except French Guiana are islands or archipelagos. They face several challenges to full development – remoteness, insularity, terrain and climate constraints, economic dependence and a narrow range of exportable commodities or services. Nevertheless, the European Commission advocates for these regions the assumption of a new paradigm: turning their natural and socioeconomic handicaps into assets. This strategy makes the sustainable development and environmental conservation strategies and policies of OERs especially challenging in scientific, technical and political terms. This Island Studies Journal special section on Sustainable Development and Environmental Conservation in the Outermost European Regions includes five articles that describe, analyse and address directly social-ecological systems’ issues in insular Portuguese and Spanish OERs (Azores and Canaries, respectively). These studies propose novel concepts, strategies and models aiming towards designing and implementing better and more cost-effective sustainability and environmental conservation policies in these remote European regions

Resource Communication : ForestAz - Using Google Earth Engine and Sentinel data for forest monitoring in the Azores Islands (Portugal)

AIM OF STUDY: ForestAz application was developed to (i) map Azorean forest areas accurately through semiautomatic supervised classification; (ii) assess vegetation condition (e.g., greenness and moisture) by computing and comparing several spectral indices; and (iii) quantitatively evaluate the stocks and dynamics of aboveground carbon (AGC) sequestrated by Azorean forest areas. AREA OF STUDY: ForestAz focuses primarily on the Public Forest Perimeter of S. Miguel Island (Archipelago of the Azores, Portugal), with about 3808 hectares. MATERIAL AND METHODS: ForestAz was developed with Javascript for the Google Earth Engine platform, relying solely on open satellite remote sensing data, as Copernicus Sentinel-1 (Synthetic Aperture Radar) and Sentinel-2 (multispectral). MAIN RESULTS: By accurately mapping S. Miguel island forest areas using a detailed species-based vegetation mapping approach; by allowing frequent and periodic monitoring of vegetation condition; and by quantitatively assessing the stocks and dynamics of AGC by these forest areas, this remote sensing-based application may constitute a robust and low-cost operational tool able to support local/regional decision-making on forest planning and management. RESEARCH HIGHLIGHTS: This collaborative initiative between the University of the Azores and the Azores Regional Authority in Forest Affairs was selected to be one of the 99 user stories by local and regional authorities described in the catalog edited by the European Commission, the Network of European Regions Using Space Technologies (NEREUS Association), and the European Space Agency (ESA).info:eu-repo/semantics/publishedVersio

A systematic literature review

Barriguinha, A., Neto, M. D. C., & Gil, A. (2021). Vineyard yield estimation, prediction, and forecasting: A systematic literature review. Agronomy, 11(9), 1-27. [1789]. https://doi.org/10.3390/agronomy11091789Purpose—knowing in advance vineyard yield is a critical success factor so growers and winemakers can achieve the best balance between vegetative and reproductive growth. It is also essential for planning and regulatory purposes at the regional level. Estimation errors are mainly due to the high inter-annual and spatial variability and inadequate or poor performance sampling methods; therefore, improved applied methodologies are needed at different spatial scales. This paper aims to identify the alternatives to traditional estimation methods. Design/methodology/approach—this study consists of a systematic literature review of academic articles indexed on four databases collected based on multiple query strings conducted on title, abstract, and keywords. The articles were reviewed based on the research topic, methodology, data requirements, practical application, and scale using PRISMA as a guideline. Findings—the methodological approaches for yield estimation based on indirect methods are primarily applicable at a small scale and can provide better estimates than the traditional manual sampling. Nevertheless, most of these approaches are still in the research domain and lack practical applicability in real vineyards by the actual farmers. They mainly depend on computer vision and image processing algorithms, data-driven models based on vegetation indices and pollen data, and on relating climate, soil, vegetation, and crop management variables that can support dynamic crop simulation models. Research limitations—this work is based on academic articles published before June 2021. Therefore, scientific outputs published after this date are not included. Originality/value—this study contributes to perceiving the approaches for estimating vineyard yield and identifying research gaps for future developments, and supporting a future research agenda on this topic. To the best of the authors’ knowledge, it is the first systematic literature review fully dedicated to vineyard yield estimation, prediction, and forecasting methods.publishersversionpublishe

The spectralrao-monitoring Python package : A RAO's Q diversity index-based application for land-cover/land-use change detection in multifunctional agricultural areas

Monitoring multifunctional agricultural areas is paramount to ensure their cost-effective management. The remote sensing-based detection of land-cover/land-use (LCLU) changes and analysis of vegetation dynamics constitute a relevant indicator to support robust monitoring schemes, allowing the control of agri-environmental conditions and enforcing related measures and policies. The Rao's Q diversity index (RaoQ) is frequently used to measure functional diversity in ecology, thanks to the textural analysis of the environment. This paper aims to develop and provide an open-source Python application whose workflow may constitute a RaoQ-based LCLU change monitoring tool for multifunctional agricultural areas. Here, a use case is presented for detecting and mapping LCLU changes leveraging the free and open access Landsat 8 (L8) satellite data. The workflow is organized in four main stages: (1) data processing; (2) Normalized Difference Vegetation Index (NDVI) calculation; (3) RaoQ calculation; and (4) detection and mapping of LCLU changes through thresholding of RaoQ. Three methodological approaches were developed (RaoC – “classic” RaoQ; RaoMD – “multidimensional” RaoQ, and “classic + multidimensional” RaoQ) with overall accuracies ranging from 0.88 to 0.92. An example of an agri-environmental monitoring decision-support framework based on spectralrao-monitoring is presented. The application is easily reproducible, and the code is fully available and utilizable with other sensors at different resolutions to support monitoring other types of agricultural areas.During the conception and primary development of this research idea, author A. Gil was funded by FCT (Portuguese National Foundation for Science and Technology) under a postdoctoral fellowship (SFRH/BPD/100017/2014) and a subsequent Assistant Researcher contract (Decree-Law 57/2017).info:eu-repo/semantics/publishedVersio