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1
objeto de conferencia
Publicado 2022
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Dry forests are home to large amounts of biodiversity, are providers of ecosystem services, and control the advance of deserts. However, globally, these ecosystems are being threatened by various factors such as climate change, deforestation, and land use and land cover (LULC). The objective of this study was to identify the dynamics of LULC changes and the factors associated with the transformations of the dry forest in the Tumbes region (Peru) using Google Earth Engine (GEE). For this, the annual collection of Sentinel 2 (S2) satellite images of 2017 and 2021 was analyzed. Six types of LULC were identified, namely urban area (AU), agricultural land (AL), land without or with little vegetation (LW), water body (WB), dense dry forest (DDF), and open dry forest (ODF). Subsequently, we applied the Random Forest (RF) method for the classification. LULC maps reported accuracies greater than ...
2
artículo
Publicado 2024
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Dry forests are ecosystems of great importance worldwide, but in recent decades they have been affected by climate change and changes in land use. In this study, we evaluated land use and land cover changes (LULC) in dry forests in Peru between 2017 and 2021 using Sentinel-2 images, and cloud processing with Machine Learning (ML) models. The results reported a mapping with accuracies above 85% with an increase in bare soil, urban areas and open dry forest, and reduction in the area of crops and dense dry forest. Protected natural areas lost 2.47% of their conserved surface area and the areas with the greatest degree of land use impact are located in the center and north of the study area. The study provides information that can help in the management of dry forests in northern Peru.
3
artículo
Publicado 2022
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Fire is one of the significant drivers of vegetation loss and threat to Amazonian landscapes. It is estimated that fires cause about 30% of deforested areas, so the severity level is an important factor in determining the rate of vegetation recovery. Therefore, the application of remote sensing to detect fires and their severity is fundamental. Radar imagery has an advantage over optical imagery because radar can penetrate clouds, smoke, and rain and can see at night. This research presents algorithms for mapping the severity level of burns based on change detection from Sentinel-1 backscatter data in the southeastern Peruvian Amazon. Absolute, relative, and Radar Forest Degradation Index (RDFI) predictors were used through singular polarization length (dB) patterns (Vertical, Vertical-VV and Horizontal, Horizontal-HH) of vegetation and burned areas. The Composite Burn Index (CBI) determ...
4
tesis de grado
Publicado 2024
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El presente proyecto analiza los principales factores de la deserción universitaria y plantea un modelo de análisis predictivo aplicando Machine Learning para detectar de manera temprana casos de deserción. Actualmente, la deserción universitaria es un problema que no solo afecta al estudiante, sino a las familias, universidad y sociedad. Como consecuencias, la pérdida de un profesional genera pérdidas en las inversiones de las universidad y disminución de investigación y producción científica. Con el apoyo de los algoritmos de Machine Learning, el proyecto identifica casos de deserción con la finalidad que las universidades actúen lo más antes posible. Tras analizar investigaciones similares, se realizó un Benchmarking de los algoritmos potencialmente aplicables. Finalmente, el proyecto desarrolla un modelo de análisis predictivo aplicando el algoritmo Random Forest (RF)....
5
artículo
Forensic microbiology enables, among other applications, the estimation of the post-mortem interval (PMI), the identification of individuals, and the location of crime scenes through microbiome analysis and the geolocation of biological remains. Artificial intelligence (AI), together with new sequencing techniques, has revolutionized this field, markedly improving the accuracy and speed of forensic analyses. In this study, a systematic review was conducted following PRISMA guidelines. Databases such as PubMed, Scopus, Web of Science, and Google Scholar were searched using keywords related to forensic microbiology, IA, and PMI. Inclusion criteria included studies published in English or Spanish, regardless of the publication date. Exclusion criteria included duplicate studies or those that did not address the thanatomicrobiome analysis using AI tools. After the search and selection proces...
