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The Corchal “El Mono Hernández” Fauna and Flora Sanctuary is a protected area located in northern Colombia and is home to the Pterocarpus officinalis forest. In this area, however, this forest cover is declining due to natural causes associated with a change in the hydrosedimentological dynamics. Multitemporal assessment was performed to quantify t...
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... was coccobacilli shaped and gram negative, UTB-161 was rod shaped and gram positive and UTB-162 was rod shaped and gram negative. All strains isolated from Half Moon Island presented positive catalase and oxidase reactions, nitrate reduction and negative reactions and were negative for H 2 S. The characteristics of these isolates are listed in Table 1. ...Similar publications
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Tropical forests of Colombia have one of the highest deforestation rates in the world. The humid forest of the Magdalena valley region is one of the ecosystems with the highest risk of landscape transformation, despite being home to many endemic and threatened species. The aim of this study was to evaluate the role of a Peasant Reserve Zone in the...
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... In the past, forest monitoring primarily relied on field surveys, a method that is costly and time-consuming, and in some areas, it is difficult to implement due to spatial or topographical constraints [9]. With the development of satellite sensor technology, high-resolution remote sensing satellite imagery offers a wide coverage range, which can effectively reduce the need for field surveys and provide the capability for periodic monitoring. ...
Severe forest fires caused by extremely high temperatures have resulted in devastating disasters in the natural forest reserves of New South Wales, Australia. Traditional forest research methods primarily rely on manual field surveys, which have limited generalization capabilities. In order to monitor forest ecosystems more comprehensively and maintain the stability of the regional forest ecosystem, as well as to monitor post-disaster ecological restoration efforts, this study employed high-resolution remote sensing imagery and proposed a semantic segmentation architecture named CCE-UNet. This architecture focuses on the precise identification of forest coverage while simultaneously monitoring the distribution of water resources in the area. This architecture utilizes the Contextual Information Fusion Module (CIFM) and introduces the dual attention mechanism strategy to effectively filter background information and enhance image edge features. Meanwhile, it employs a multi-scale feature fusion algorithm to maximize the retention of image details and depth information, achieving precise segmentation of forests and water bodies. We have also trained seven semantic segmentation models as candidates. Experimental results show that the CCE-UNet architecture achieves the best performance, demonstrating optimal performance in forest and water body segmentation tasks, with the MIoU reaching 91.07% and the MPA reaching 95.15%. This study provides strong technical support for the detection of forest and water body coverage in the region and is conducive to the monitoring and protection of the forest ecosystem.