Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891484 | PMC |
http://dx.doi.org/10.3390/s19225020 | DOI Listing |
Plants (Basel)
January 2025
Departamento de Ciencias Jurídicas, Universidad Técnica Particular de Loja, Loja 1101608, Ecuador.
Epiphytic bryophytes are an important component in terms of the diversity and functioning of montane forests known as biodiversity hotspots. Bryophytes are highly dependent on their external environments because they are sensitive to environmental changes related to disturbance, fragmentation, air pollution, and climate change. The richness and composition of bryophytes in remnants of primary and secondary forests were analyzed, where the richness and cover were recorded on trunk bases of 120 trees.
View Article and Find Full Text PDFAnimals (Basel)
January 2025
College of Forestry, Central South University of Forestry and Technology, Changsha 410004, China.
Climate change and human disturbance are critical factors affecting the habitat distribution of wild animals, with implications for management strategies such as protecting migration corridors, habitat restoration, and species conservation. In the Hupingshan National Nature Reserve (NNR), Reeve's muntjac () is a key prey species for the South China tiger (), which is extinct in the wild and targeted for reintroduction by the Chinese government. Thus, understanding the habitat distribution and abundance of Reeve's muntjac is essential to ensure the survival and sustainability of reintroduced tiger populations.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Royal Danish Library, Special Collections, Søren Kierkegaards Plads. 1, 1221, Copenhagen K, Denmark.
Historical topographical maps contain valuable, spatially and thematically detailed information about past landscapes. Yet, for analyses of landscape dynamics through geographical information systems, it is necessary to "unlock" this information via map processing. For two study areas in northern and central Jutland, Denmark, we apply object-based image analysis, vector GIS, colour image segmentation, and machine learning processes to produce machine-readable layers for the land use and land cover categories forest, wetland, heath, dune sand, and water bodies from topographic maps from the late nineteenth century.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Wildlife Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Mississippi State, MS, 39762-9690, USA.
The increasing trend in land surface temperature (LST) and the formation of urban heat islands (UHIs) has emerged as a persistent challenge for urban planners and decision-makers. The current research was carried out to study the land use and land cover (LULC) changes and associated LST patterns in the planned city (Kabul) and the unplanned city (Jalalabad), Afghanistan, using Support Vector Machine (SVM) and Landsat data from 1998 to 2018. Future changes in LULC and LST were predicted for 2028 and 2038 using Cellular Automata-Markov (CA-Markov) and Artificial Neural Network (ANN) models.
View Article and Find Full Text PDFTicks Tick Borne Dis
January 2025
Department of Health, Sport and Bioscience. University of East London, Water Lane, Stratford E15 4LZ, United Kingdom. Electronic address:
The interplay of biotic and abiotic factors driving Ixodes ricinus abundance trends are not fully understood. Machine learning (ML) approaches are being increasingly used to explore this and predict future abundance patterns of this species, however, the studies focusing on this to date have had limitations (including short study duration, limited sample size, narrow geographical range and use of a single ML model). This study was undertaken to address these limitations by applying 11 predictive ML models (across three data clustering techniques) to a large I.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!