Examinando por Materia "GIS"

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Multicriteria evaluation and remote sensing approach to identifying degraded soil areas in northwest Peru
(Taylor & Francis Group, 2024-12-23) Arce Inga, Marielita; Atalaya Marin, Nilton; Barboza Castillo, Elgar; Tarrillo Julca, Ever; Chuquibala Checan, Beimer; Tineo Flores, Daniel; Fernandez Zarate, Franklin Hitler; Cruz Luis, Juancarlos Alejandro; Goñas Goñas, Malluri; Gómez Fernández, Darwin
Soil is a vital nonrenewable resource characterized by rapid degradation and slow regeneration processes. In this study, soil degradation in Jaén and San Ignacio was assessed via a multicriteria evaluation approach combined with remote sensing (RS) data. Nine factors were analyzed classified three categories: environmental, topographic, and edaphological factors. The results revealed that the slope (59.07%) was the main influencing factor, followed by land use and land cover (LULC) (56.36%). The degradation map revealed that 83.48% of the area exhibited moderate degradation, 14.49% low degradation, and 1.56% high degradation. The districts of Pomahuaca and San José de Lourdes demonstrated the largest areas of moderate degradation, accounting for 13.71% and 22.54%, respectively. Bellavista and Huarango exhibited the largest areas of very high degradation, accounting for 0.27% and 0.08%, respectively. The (AHP) method and RS data were employed to assess soil degradation, highlighting the need for sustainable soil restoration and conservation strategies.
Spatial patterns of diversity and genetic erosion of traditional cassava (Manihot esculenta Crantz) in the Peruvian Amazon: An evaluation of socio-economic and environmental indicators
(Springer Nature, 2007-02-23) Willemen, Louise; Scheldeman, Xavier; Soto Cabellos, Víctor; Rafael Salazar, Simón; Guarino, Luigi
This study evaluates quantitatively the suitability of the use of site-specific socio-economic and environmental data as indicators to rapidly assess patterns of diversity and genetic erosion risk in cassava. Socio-economic data as well as farmers’ estimation of genetic erosion were collected in the study area, the Ucayali region of the Peruvian Amazon, through interviews with 285 cassava farmers in 50 communities, while diversity was assessed based on agromorphological characterization of 295 cassava accessions. Using multivariate regression analyses, 50 and 45% of the variation in respectively diversity and genetic erosion estimation could be explained by a selected set of socio-economic and environmental indicators. In both regression models four out of the total of 38 variables proved to contribute significantly (at p < 0.10 level). Additionally, the study revealed that farmers are a good direct source of information on the diversity present at community level, which can contribute to the development of methodologies to assess diversity more rapidly. The results of this study are valuable for the development of models to rapidly assess diversity dynamics in large areas.