Browsing by Author "Tassi, Andrea"
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- A low-cost Sentinel-2 data and Rao’s Q diversity index-based application for detecting, assessing and monitoring coastal land-cover/land-use changes at high spatial resolutionPublication . Tassi, Andrea; Gil, Artur José FreireCoastal zones in small oceanic islands as the Archipelago of the Azores (Portugal) are very sensitive territories severely threatened by climate change, natural disasters, biological invasions, infrastructure and tourism development, and also agriculture intensification. Land-cover/land-use changes are one of the most relevant indicators for monitoring and assessing coastal spatial planning and management policies in insular territories. This paper describes the application of a low-cost Rao's Q diversity index-based remote sensing tool able to provide a systematic and accurate coastal land-cover/land-use monitoring system in small oceanic islands, using free and open access Sentinel-2 multispectral satellite data and Terceira island (Archipelago of the Azores, Portugal) as the case-study area. Results indicate that about 7% (∼300 hectares) of Terceira Island's coastal zone (∼4290 hectares) have changed their land-cover/ land-use between March 2017 and December 2018 (21 months). Agricultural areas (4.1%), urban areas (2.1%) and bare soil areas (0.6%) are the categories showing more relevant changes.
- Monitorização semiautomática da orla costeira terrestre dos Açores com base em deteção remota por satélitePublication . Gil, Artur José Freire; Tassi, AndreaO solo é um recurso escasso e não renovável em qualquer território, mas este constrangimento ganha muito maior relevância em pequenas ilhas como as do Arquipélago dos Açores, nas quais é fundamental gerir e conservar este recurso insubstituível, de modo a assegurar maior autossuficiência alimentar e maior resiliência as alterações climáticas e catástrofes naturais, possibilitando assim um desenvolvimento cada vez mais sustentável. A orla costeira e usualmente a zona de cada ilha sujeita a maiores pressões, quer as ditas "naturais" (erosão da orla costeira, movimentos de vertente, proliferação de espécies de plantas exóticas invasoras, etc.), quer as decorrentes diretamente da presença e atividade humana (núcleos urbanos, áreas de agricultura mais intensiva e desenvolvimento de infraestruturas turísticas, industriais, portuárias e recreativas, etc.), causando uma degradação acelerada da ocupação e uso do solo costeiros (recuo da orla costeira, perda de solo com capacidade agroflorestal, diminuição da biodiversidade, poluição costeira, etc.). […].
- The spectralrao-monitoring Python package : A RAO's Q diversity index-based application for land-cover/land-use change detection in multifunctional agricultural areasPublication . Tassi, Andrea; Massetti, Andrea; Gil, Artur José FreireMonitoring 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.