Deep Learning Application for Biodiversity Conservation and Educational Tourism in Natural Reserves DOI Creative Commons
Marco Flórez, Óscar Becerra, Eduardo Carrillo

et al.

ISPRS International Journal of Geo-Information, Journal Year: 2024, Volume and Issue: 13(10), P. 358 - 358

Published: Oct. 11, 2024

Natural reserves, such as the Santurbán Moor in Colombia, are ecologically important but face significant threats from activities like mining and agriculture. Preserving biodiversity these ecosystems is essential for maintaining ecological balance promoting sustainable tourism practices. Identifying plant species reserves accurately challenging due to environmental variability similarities, complicating conservation efforts educational promotion. This study aims create assess a mobile application based on deep learning, called FloraBan, autonomously identify natural enhancing encouraging The employs EfficientNet Lite4 model, trained comprehensive dataset of images taken various field conditions. Designed work offline, particularly useful remote areas. model evaluation revealed an accuracy exceeding 90% classifying images. FloraBan was effective under lighting conditions complex backgrounds, offering detailed information about each species, including scientific name, family, status. ability function without internet connectivity benefit, especially isolated regions reserves. represents notable improvement automated identification, supporting botanical research preserve Moor. Additionally, it encourages responsible practices, which align with sustainability goals, providing tool both tourists conservationists.

Language: Английский

Functional Diversity and Ecosystem Services of Birds in Productive Landscapes of the Colombian Amazon DOI Creative Commons
Jenniffer Tatiana Díaz-Cháux, Alexander Velásquez Valencia, Alejandra Martínez‐Salinas

et al.

Diversity, Journal Year: 2025, Volume and Issue: 17(5), P. 305 - 305

Published: April 23, 2025

The expansion of anthropogenic activities drives changes in the composition, structure, and spatial configuration natural landscapes, influencing both taxonomic functional diversity bird communities. This pattern is evident Colombian Amazon, where agricultural livestock has altered ecological dynamics, avifaunal assemblages, provision regulating ecosystem services. study analyzed influence agroforestry (cocoa-based systems—SAFc) silvopastoral systems (SSP) on birds their potential impact services eight productive landscape mosaics within Amazon. Each mosaic consisted a 1 km2 grid, which seven types vegetation cover were classified, metrics calculated. Bird communities surveyed through visual observations mist-net captures, during traits measured. Additionally, guilds assigned to each species based literature review. Five multidimensional indices computed, along with community-weighted means per guild. A total 218 recorded across land-use systems. richness, abundance, diversity—as well as composition guilds—varied according cover. Functional increased containing closed patches symmetrical configurations. Variations linked low redundancy, may also lead differences such biological pest control seed dispersal—both are critical for regeneration connectivity rural landscapes. In conclusion, contributes resilience landscapes Amazonian systems, highlighting need management that promotes structural heterogeneity sustain connectivity.

Language: Английский

Citations

0

Adaptive management of mountain ecosystems based on carbon sequestration: Based on the “state-flow-utility” framework DOI Creative Commons
Chuhan Wang, Boyan Li, Jing Li

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 168, P. 112703 - 112703

Published: Oct. 21, 2024

Language: Английский

Citations

3

Deep Learning Application for Biodiversity Conservation and Educational Tourism in Natural Reserves DOI Creative Commons
Marco Flórez, Óscar Becerra, Eduardo Carrillo

et al.

ISPRS International Journal of Geo-Information, Journal Year: 2024, Volume and Issue: 13(10), P. 358 - 358

Published: Oct. 11, 2024

Natural reserves, such as the Santurbán Moor in Colombia, are ecologically important but face significant threats from activities like mining and agriculture. Preserving biodiversity these ecosystems is essential for maintaining ecological balance promoting sustainable tourism practices. Identifying plant species reserves accurately challenging due to environmental variability similarities, complicating conservation efforts educational promotion. This study aims create assess a mobile application based on deep learning, called FloraBan, autonomously identify natural enhancing encouraging The employs EfficientNet Lite4 model, trained comprehensive dataset of images taken various field conditions. Designed work offline, particularly useful remote areas. model evaluation revealed an accuracy exceeding 90% classifying images. FloraBan was effective under lighting conditions complex backgrounds, offering detailed information about each species, including scientific name, family, status. ability function without internet connectivity benefit, especially isolated regions reserves. represents notable improvement automated identification, supporting botanical research preserve Moor. Additionally, it encourages responsible practices, which align with sustainability goals, providing tool both tourists conservationists.

Language: Английский

Citations

1