Browsing by Author "Goovaerts, Pierre"
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- Developing an index for forest productivity mapping - A case study for maritime pine production regulation in PortugalPublication . Mestre, Susana Candeias; Alegria, C.M.M.; Albuquerque, M.T.D.; Goovaerts, PierreProductivity is very dependent on the environmental and biotic factors present at the site where the forest species of interest is present. Forest site productivity is usually assessed using empirical models applied to inventory data providing discrete predictions. While the use of GIS-based models enables building a site productivity distribution map. Therefore, the aim of this study was to derive a productivity index using multivariate statistics and coupled GIS-geostatistics to obtain a forest productivity map. To that end, a study area vastly covered by naturally regenerated forests of maritime pine in central Portugal was used. First, a productivity index (PI) was built based on Factorial Correspondence Analysis (FCA) by incorporating a classical site index for the species and region (Sh25 - height index model) and GIS-derived environmental variables (slope and aspect). After, the PI map was obtained by multi-Gaussian kriging and used as a GIS layer to evaluate maritime pine areas by productivity class (e.g., low, intermediate and high). In the end, the area control method was applied to assess the size and the number of compartments to establish by productivity class. The management compartments of equal productivity were digitized as GIS layer and organized in a temporal progression of stands’ age regularly available for cutting each year during a 50-year schedule. The methodological approach developed in this study proved that can be used to build forest productivity maps which are crucial tools to support forest production regulation.
- Modelação da produtividade de povoamentos de pinheiro bravo (Pinus pinaster Aiton) na região Centro de Portugal, através de técnicas de geoestatística e de ferramentas SIGPublication . Mestre, Susana Candeias; Alegria, C.M.M.; Albuquerque, M.T.D.; Goovaerts, PierreO presente estudo permitiu desenvolver uma nova abordagem à quantificação da produtividade florestal, tradicionalmente avaliada de forma pontual ao nível dos povoamentos, para uma representação contínua obtida como uma superfície de krigagem, o que permitirá incorporar essa informação em SIG como um nível temático para a análise e planeamento espacial da gestão florestal.
- A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold explorationPublication . Goovaerts, Pierre; Albuquerque, M.T.D.; Antunes, I.M.H.R.This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R2=0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold's paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization.
- A spatial statistical approach for sedimentary gold exploration: a portuguese case studyPublication . Goovaerts, Pierre; Albuquerque, M.T.D.; Antunes, I.M.H.R.This paper describes the mapping of gold content in the surroundings of abandoned gold mines located in central Portugal. In 1988, 376 samples were collected and analyzed for 22 elements. Gold (Au) was measured only inside the gold mines and its value was predicted at other locations using linear regression (R2=0.46 ) and four metals (Fe, As, Mn and W) which are known to be mostly associated with the local gold’s paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential Gaussian simulation. Each simulated map then underwent a local cluster analysis to identify areas of significantly low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated likelihood. The distribution of the hot-spots and cold-spots shows a clear enrichment in Au along the Erges River.