Examinando por Autor "Salas Lopez, Rolando"

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Analyzing urban expansion and land use dynamics in Bagua Grande and Chachapoyas using cloud computing and predictive modeling
(Springer Nature, 2024-09-26) Barboza, Elgar; Turpo, Efrain Y.; Salas Lopez, Rolando; Silva López, Jhonsy O.; Cruz Luis, Juancarlos Alejandro; Vásquez, Héctor V.; Purohit, Sanju; Aslam, Muhammad; Tariq, Aqil
Urban growth and Land Use/Land Cover (LULC) changes have increased in recent decades due to anthropogenic activities. This study explored past and projected future LULC changes and urban growth patterns in the Bagua Grande and Chachapoyas districts using Landsat imagery, cloud computing, and predictive models for 1990 to 2031. The analysis of satellite images was grouped into four time periods (1990–2000, 2000–2011, 2011–2021 and 2021–2031). The Google Earth Engine (GEE) cloud-based system facilitated the classification of Landsat 5 ETM (1990, 2000, and 2011) and Landsat 8 OLI (2021) images using the Random Forest (RF) model. A simulation model integrating Cellular Automata (CA) and an Artificial Neural Network (ANN) Multilayer Perceptron (MLP) in the MOLUSCE plugin of QGIS was used to forecast urban sprawl to 2031. The resulting maps showed an overall accuracy (OA) of over 92%. A decrease in forested area was observed, from 20,807.97 ha in 1990 to 14,629.44 ha in 2021 in Bagua Grande and from 7,796.08 ha to 3,598.19 ha in Chachapoyas. In contrast, urban areas experienced a significant increase, from 287.49 to 1,128.77 ha in Bagua Grande and from 185.65 to 924.50 ha in Chachapoyas between 1990 and 2021. By 2031, the urban area of Bagua Grande is expected to increase from 1,128.77 to 1,459.25 ha (29%) in a southeast, south, southwest, west, and northwest direction. Chachapoyas expanded from 924.50 to 1138.05 ha (23%) in the southwest, north, northeast, and southeast directions. The study presents an analytical method integrating cloud processing, GIS, and change simulation modeling to evaluate urban growth spatio-temporal patterns and LULC changes. This approach effectively identified the main LULC changes and trends in the study area. In addition, potential urbanization areas are highlighted where there are still opportunities for developing planned and managed urban settlements.
Suitability of the Amazonas region for beekeeping and its future distribution under climate change scenarios
(Elsevier, 2025-02-17) Gómez Fernández, Darwin; García, Ligia; Silva López, Jhonsy O.; Veneros Guevara, Jaris; Arellanos Carrión, Erick; Salas Lopez, Rolando; Goñas Goñas, Malluri; Atalaya Marin, Nilton; Oliva Cruz, Manuel; Rojas Briceño, Nilton B.
Beekeeping plays an important role in global food production and the conservation of wild species. However, determining territorial suitability and future distribution under climate change scenarios is a relatively under-studied area in Peru. This study assessed the beekeeping suitability of the Amazonas region and its variation under climate change scenarios in two projected periods (2041-2060 and 2081-2100), according to Shared Socioeconomic Pathways (SSP). The methodological framework integrated the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS), and the Hadley Centre Global Earth Model - Global Coupled configuration 3.1 (HadGEM3-GC31-LL) was used for future climate analysis. The beekeeping suitability of the region was determined based on eleven criteria: four climatic, three topographic, and four environmental. The results indicate that beekeeping suitability is distributed as follows: 3.4% (1417.90 km²) with 'High' suitability, 79.2% (33,318.61 km²) with 'Moderate' suitability, 17.2% (7230.26 km²) with 'Marginal' suitability, and 0.2% (83.64 km²) as 'Not suitable'. Moreover, the average temperature across the region is projected to increase by approximately 3 °C under the SSP2-4.5 scenario and between 6 °C and 8 °C under the SSP5-8.5 scenario during the projected periods. Precipitation will decrease in the northern part of the region, while the southwestern part will experience an increase. In the highly suitable beekeeping area, a temperature increases up to 10.8 °C is expected, with frequent variations around 3 °C to 8 °C, affecting more than 500 km². Additionally, a reduction in precipitation up to 311 mm/year is projected, with predominant variations ranging from -49.5 to 32.8 mm/year over approximately 600 km². Therefore, it is suggested to implement strategies to mitigate these upcoming challenges, particularly if the modeled economic development under the SSPs continues. This study modeled and mapped areas with present conditions suitable for beekeeping and future climate behavior. The modeling aims to guide beekeepers and local authorities in developing sustainable practices and implementing preventive measures to address future climatic challenges.