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During the past three decades, various methods have been developed to improve the classification accuracy in very high resolution (< 2 m) satellite data. This study's main goal was to evaluate and select the most suitable classification approach for detecting deadwood potentially useful for energy projects that would satisfy part of the demand for heating in the area. We compare five classification approaches using a WorldView-2 (Digital Global, Ins) standard, an orthorectified image of the Aysén region of the Chilean Patagonia. The five classifiers were evaluated and selecting the best one was carried out through a confusion matrix and Kappa coefficient. The results showed that the two non-parametric classifiers used (neural net and support vector machine) offered the best performance (98%) and the best Kappa coefficient (0.97). We conclude that it is essential to promote the development of innovative projects in native forests by local owners can contribute, to the formulation of public policies that directly benefit the Aysén region's inhabitants. [Display omitted] • Successful mapping of deadwood in a second-growth native forest • The basis for future estimation of the usable volume of biomass from deadwood • NN and SVM are the recommended methods for detecting deadwood. • Successful use of historical VHR images [ABSTRACT FROM AUTHOR]

A water vulnerability assessment was performed on the Río Grande-Lagos de Montebello watershed, in southeastern region of Chiapas, Mexico. This is a karstic environment highlighted by well-preserved lakes, close to Guatemala border. We used multicriteria analysis to identify areas vulnerable to water contamination at subbasin scale using geographic information system and spatial analysis. Potential contamination sources were georeferenced and overlapped with precipitation and slope layers to identify areas prone to contaminant transport and infiltration. The results showed that both irrigation and rainfed agriculture were the main contamination sources, followed by wastewater discharge. Supported by land use and forest change analysis, agricultural activities were the most important drivers of change. A water vulnerability map at subbasin scale is presented as an outcome, which enables the ranking of water contamination potential in presence of different contamination sources using the weighted sum and linear normalization methods. Two subbasins were identified within the most vulnerable categories, Comitán and El Triunfo. No previous water vulnerability analyses have been performed for this region. We propose this vulnerability map as a decision-making tool for sustainable water management at watershed scale in areas with scarce information and increasing water quality degradation processes. • The studied region is one of the most important water sources in Mexico. • We identify different exposure levels to contamination in vulnerable rural area. • Multicriteria analysis showed irrigation and rainfed agriculture as main drivers of contamination. • This karst watershed is vulnerable to contamination due to agricultural activities. • GIS provided a way to analyze factors impacting watershed vulnerability. [ABSTRACT FROM AUTHOR]

[Display omitted] • Litterbags of a mixture of leaves, hand net, and corer was the compared techniques. • We got 540 samples in five forested wetlands temporary and permanent for one year. • Richness and diversity were higher with a hand net, followed by litterbags, and corer. • nMDS and ANOSIM separating two macroinvertebrate assemblages in respect to techniques. • We reinforce findings from the joint use of two techniques, hand net, and corer. Forest wetlands are biodiversity hotspots that perform functions of vital ecological importance, but they are among the world's most threatened ecosystems. Due to their high diversity of habitats and species, the study of their benthic macroinvertebrate communities is challenging, and there is no consensus on which sampling methods allow a better representation of these communities. Here we compared the performance of 3 sampling methods (hand net, corer and litterbags) in 2 temporary and 3 permanent forested wetlands in southern Chile, which were bimonthly sampled throughout a year, with 108 samples per wetland. Our results indicated that the greatest abundance and diversity were collected with the hand net, followed by the litterbags and the corer. The composition of communities collected by the hand net and litterbags were more similar between them than that of communities collected by the corer (where Chironomidae and Oligochaeta were common). We suggest that the combined use of the hand net and corer could provide a good representation of macroinvertebrate communities in forest wetlands, as they would allow recording most of the diversity, including taxa that are both sensitive and tolerant to stressors. [ABSTRACT FROM AUTHOR]