Browsing by Autor "Yuri Sandoval Montes"

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    Descending Mountain Routes Future: the North Yungas and Făgăraș Geosystem's Comparative Study
    (2018) Mihai Voda; Yuri Sandoval Montes
    The Yungas region geographical position on the Eastern slopes of Cordillera Real and the Fgra Mountains East-West alignment generated unique Geosystems. A single gravel road links La Paz with Amazonia Boliviana: El Camino de la Muerte and only one road crosses the Fgra Mountains: the Transfgran. Mountain roads networks are connecting communities and their resources all over the world. This research is adding value to the old mountain roads systems using the new technical Geography advances and transforming them in tourist sites. The cultural ecosystem services have a growing popularity that can be valorized for the locals benefits if managed accordingly. This paper focuses on the special descending sections identification and assessment for the mountain recreational activities development. The North Yungas and the Fgra areas represent unique Geosystems from the Bolivian Andes and the Romanian Mountains, analyzed using Geomedia techniques. Here we show that our Death Road model can securely allow tourist access, increase locals' livelihood and protect mountain environments. Our research results prove that the South American Geosystem`s unique attributes can constitute a functional reference for a considerable number of world`s mountain routes future sustainable development.
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    Evaluación de segmentación en imágenes de dron para identificación de majo (Oenocarpus bataua), asai (Euterpe precatoria Mart.) y palmera común (Phoenix dactylifera) en tres comunidades del municipio de San Buenaventura
    (2025) Yuri Sandoval Montes; Luis Ernesto Cuenca Usmayo; Javier Nuñez Villalba
    La falta de información sobre la distribución espacial de majo (Oenocarpus bataua), asai (Euterpe precatoria Mart.) y palmera común (Phoenix dactylifera) dificulta su conservación y manejo sostenible. Este estudio tuvo como objetivo determinar dicha distribución mediante técnicas de segmentación, evaluando la precisión de tres softwares para identificar la herramienta más efectiva. eCognition logró una precisión geométrica superior (PSE mínimo: 0.021), ajustando eficazmente los límites de las coronas foliares, lo que permitió cuantificar las especies de majo “15 en San Silvestre, 10 en UMSA-Tumupasa y 250 en El Infierno”, asai “444 en El Infierno” y palmera común “84 en San Silvestre, 123 en UMSA-Tumupasa y 229 en El Infierno”.