Examinando por Materia "Land use"

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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.
Dinámica de la cobertura y uso de la tierra en Chalamarca, Chota, Cajamarca
(Universidad Nacional Autónoma de Chota, 2023-12-26) Lumba Huamán, Eduar Nann; Tarrillo Cieza, Deyner; Mírez Rubio, Yolmer; Chávez Collantes, Azucena; Chávez Juanito, Yuli Anabel; Sánchez Rojas, Alfonso; Elera Gonzales, Duberli Geomar
Las actividades naturales y antrópicas causan cambios continuos en la cobertura terrestre, que impactan en la sociedad, clima, biodiversidad, ciclos hidrológicos y ecosistemas. Los datos de sensoramiento remoto representan un componente clave para identificar la variación de los diferentes tipos de coberturas. El objetivo en este trabajo fue analizar el cambio de cobertura y uso de la tierra en el distrito de Chalamarca, durante el período 2000-2020. Se utilizó la metodología Corine Land Cover en los niveles I, II y III mediante el uso de imágenes Landsat en la plataforma Google Earth Engine. Se identificó cambios de cobertura y uso de la tierra en 9 571,58 ha, que representa el 53,82% del área de estudio. Se clasificaron ocho tipos de cobertura vegetal: tejido urbano continuo, cultivos transitorios, pastos, bosque plantado, vegetación herbácea, vegetación arbustiva, afloramientos rocosos y tierra desnuda. Las categorías que mostraron mayor incremento fueron: bosques plantados 2 642,82 ha (14,85%), cultivos transitorios 848,05 ha (4,77%) y pastos 322,20 ha (1,81%). Por el contrario, las clases de cobertura que disminuyeron fueron vegetación herbácea 2 943,94 ha (-16,50%) y arbustal 909,55 ha (-5,55%). La expansión de la frontera agrícola, el sobrepastoreo y el establecimiento de nuevas viviendas son los factores que influyeron en el cambio de cobertura y uso de la tierra en el distrito de Chalamarca en el periodo 2000-2020. En conclusión, se generó un cambio del 53,82% de cambio de cobertura y uso de la tierra en el distrito de Chalamarca durante el periodo 2000-2020.
Effectiveness of protected areas in containing the loss of Peruvian Amazonian forests
(Elsevier, 2025-01-11) Rojas Briceño, Nilton B.; Cajas Bravo, Verónica; Pasquel Cajas, Alexander; Guzman Valqui, Betty Karina; Silva López, Jhonsy O.; Veneros, Jaris; García, Ligia
Peruvian Amazonian Forests (PAF), vital for biodiversity, climate, and human well-being, lost 2.92M ha during 2001-2022, mainly due to anthropogenic activities. This prompted strategies to conserve and protect the PAF, such as land use and natural resource restrictions, with natural protected areas (NPAs) being the main strategy. This study evaluated the effectiveness of 41 NPAs in containing deforestation in the PAF by analyzing national spatial data. An Effectiveness Index (EI) was constructed by adding five standardized parameters: (1) the percentage of deforested area (DA%) and (2) its annual rate of change (DAr) between 2000 and 2022 inside each NPA, (3) the difference in DAr between NPAs and their surrounding areas, (4) their corresponding ecoregions, and (5) the entire PAF. In 2000, the DA% was 7.15% of the PAF, increasing to 10.88% in 2022. NPAs showed lower DAr than their surrounding areas and ecoregions, except for five NPAs. Of the 41 NPAs, nine were non-effective (EI≤3), 31 moderately effective (3
Landsat images and GIS techniques as key tools for historical analysis of landscape change and fragmentation
(Elsevier, 2024-07-28) Gómez Fernández, Darwin; Salas López, Rolando; Zabaleta Santisteban, Jhon Antony; Medina Medina, Angel J.; Goñas Goñas, Malluri; Silva López, Jhonsy O.; Oliva Cruz, Manuel; Rojas Briceño, Nilton B.
Monitoring and evaluation of landscape fragmentation is important in numerous research areas, such as natural resource protection and management, sustainable development, and climate change. One of the main challenges in image classification is the intricate selection of parameters, as the optimal combination significantly affects the accuracy and reliability of the final results. This research aimed to analyze landscape change and fragmentation in northwestern Peru. We utilized accurate land cover and land use (LULC) maps derived from Landsat imagery using Google Earth Engine (GEE) and ArcGIS software. For this, we identified the best dataset based on its highest overall accuracy, and kappa index; then we performed an analysis of variance (ANOVA) to assess the differences in accuracies among the datasets, finally, we obtained the LULC and fragmentation maps and analyzed them. We generated 31 datasets resulting from the combination of spectral bands, indices of vegetation, water, soil and clusters. Our analysis revealed that dataset 19, incorporating spectral bands along with water and soil indices, emerged as the optimal choice. Regarding the number of trees utilized in classification, we determined that using between 10 and 400 decision trees in Random Forest classification doesn't significantly affect overall accuracy or the Kappa index, but we observed a slight cumulative increase in accuracy metrics when using 100 decision trees. Additionally, between 1989 and 2023, the categories Artificial surfaces, Agricultural areas, and Scrub/ Herbaceous vegetation exhibit a positive rate of change, while the categories Forest and Open spaces with little or no vegetation display a decreasing trend. Consequently, the areas of patches and perforated have expanded in terms of area units, contributing to a reduction in forested areas (Core 3) due to fragmentation. As a result, forested areas smaller than 500 acres (Core 1 and 2) have increased. Finally, our research provides a methodological framework for image classification and assessment of landscape change and fragmentation, crucial information for decision makers in a current agricultural zone of northwestern Peru.
Migration patterns and land use by immigrants under a changing frontier society in the Peruvian Amazon
(Japan Soc Tropical Ecology, 2014-09-01) Ichikawa, Masahiro; Ricse Tembladera, Auberto; Ugarte, Julio; Kobayashi, Shigeo
One of main factors identified as explaining forest loss and degradation in the Selva (the Peruvian Amazon) is the migration of people from the Sierra (Andes highlands), where agricultural conditions are severe, to forest areas in the Selva in search of new land. This paper aims at clarifying the characteristics and process of migration based on interviews with local people near Pucallpa, Ucayali Department, where forest loss and degradation has advanced in recent decades. In the study area, forest loss and degradation progressed by commercial logging after construction of a road connecting between Lima and Pucallpa in 1943. After logging, stock-farming companies and immigrants entered the area, and land uses other than high forest have been expanding. Today, the study area is occupied by people who have immigrated since the 1960s. Many of them earned income by logging until the 1980s, while today almost of them make a livelihood by agriculture, stock farming, or tree planting. As a result of these economic activities, there are substantial areas of mixed shrubs and grass in the study area today. This paper clarifies two points. First, the majority of immigrants were born not in the Sierra, but in the Selva, for instance as part of the expanding population in the Departments of San Martin and Amazonas. The main stream of migration is from parts of the Selva where immigrants had started reclamation in earlier days to other parts of the Selva with still abundant forests (such as the study area). Second, most migrants were not born in a rural area, but in Pucallpa, a developing urban area in the Selva. Pucallpa is also an important place for step migrants who stayed there for a while and worked temporarily before immigrating to the study area. The urban area has gained an important role in migration to forests in the Selva as a place of birth of migrants and for its function in step migration.