Lara A. Arroyo

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Understanding fire is essential to improving forest management strategies. More specifically, an accurate knowledge of the spatial distribution of fuels is critical when analyzing, modelling and predicting fire behaviour. First, we review the main concepts and terminology associated with forest fuels and a number of fuel type classifications. Second, we(More)
Most current coral reef management is supported by mapping and monitoring limited in record length and spatial extent. These deficiencies were addressed in a multidisciplinary study of cyclone impacts on Aboré Reef, New-Caledonia. Local knowledge, high thematic-resolution maps, and time-series satellite imagery complemented classical in situ monitoring(More)
We compared the E-test to the broth microdilution method for testing the susceptibility of 115 clinical isolates of Acinetobacter baumannii to colistin. Twenty-two (19.1%) strains were resistant to colistin and 93 (80.8%) strains were susceptible according to the reference broth microdilution method. A categorical agreement of 98.2% was found, with only two(More)
[1] Knowledge of fuel load and composition is critical in fighting, preventing, and understanding wildfires. Commonly, the generation of fuel maps from remotely sensed imagery has made use of medium-resolution sensors such as Landsat. This paper presents a methodology to generate fuel type maps from high spatial resolution satellite data through(More)
This research presents a time-effective approach for mapping streambed and riparian zone extent from high spatial resolution LiDAR derived products, i.e. digital terrain model, terrain slope and plant projective cover. Geographic object based image analysis (GEOBIA) has proven useful for feature extraction from high spatial resolution image data because of(More)
The objectives of this research were to: (1) develop rule sets in Definiens Developer 7® for mapping and monitoring riparian zone land-cover classes within two QuickBird images; and (2) compare the results of four object-oriented and pixel-based change detection approaches. Two QuickBird images, atmospherically corrected to at-surface reflectance, were(More)
Forest structure characterisation approaches using LiDAR data and object-based image analysis remain scarce to forestry agencies as these automated procedures usually require the use of expensive software and highly skilled analysts. The integration of forest expert opinion into semi-automated approaches would simplify the access of forest managers to new(More)
Vegetation communities are traditionally mapped from aerial photography interpretation. Other semi-automated methods include pixeland object-based image analysis. While these methods have been used for decades, there is a lack of comparative research. We evaluated the cost-effectiveness of seven approaches to map vegetation communities in a northern(More)
Although geographic object based image analysis (GEOBIA) has been successfully applied to derive local maps (1-10s km) from very high spatial resolution (VHR) image data (pixels < 1.0 x 1.0 m), its potential for automatically mapping large areas remains unknown. The aim of this study was to create and apply a GEOBIA method to automatically map land cover(More)
Wildland fires are one of the factors causing the deepest disturbances on the natural environment and severely threatening many ecosystems, as well as economic welfare and public health. Having accurate and up-to-date fuel type maps is essential to properly manage wildland fire risk areas. This research aims to assess the viability of combining Geographic(More)
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