Automatic generation of hillside units and topographic profiles, based on a digital terrain model, in the municipality of La Vega, Cauca

Los análisis de morfométricos de los diferentes tipos de modelo digitales de terreno con los que contamos hoy en día son una herramienta que cada día se vuelve más valiosa para el desarrollo de los diferentes proyectos de infraestructura urbana, así mismo como para los planes de ordenamiento territorial de cada uno de los municipios, con el fin de emplear estos elementos que cada día con los avances tecnológicos mejoran, se propone la siguiente metodología con el fin de generar unidades de laderas y perfiles de terreno que permitan realizar distintos tipos de análisis, fundamentalmente movimientos en masa los cuales pueden ser causales de avenidas torrenciales o derrumbes que causen diferentes tipos de afectaciones en el municipio y puedan incluso costar vidas humanas, en el desarrollo de este documento veremos cómo se desarrolla por medio del software ArcGIS, los insumos necesarios para realizar los diferentes estudios de forma rápida y adecuada.The morphometric analysis of the different types of digital terrain models that we have today is a tool that is becoming more valuable every day for the development of different urban infrastructure projects, as well as for the land use plans of each of the municipalities, in order to use these elements that improve every day with technological advances, the following methodology is proposed in order to generate slope units and terrain profiles that allow different types of analysis, mainly mass movements which can cause torrential floods or landslides that cause different types of damage in the municipality and can even cost human lives, in the development of this document we will see how it is developed through ArcGIS software, the necessary inputs to perform the different studies quickly and properly.Especializació

Real-Time Mapping Using Stereoscopic Vision Optimization

This research focuses on efficient methods of generating 2D maps from stereo vision in real-time. Instead of attempting to locate edges between objects, we make the assumption that the representative surfaces of objects in a view provide enough information to generate a map while taking less time to locate during processing. Since all real-time vision processing endeavors are extremely computationally intensive, numerous optimization techniques are applied to allow for a real-time application: horizontal spike smoothing for post-disparity noise, masks to focus on close-proximity objects, melding for object synthesis, and rectangular fitting for object extraction under a planar assumption. Additionally, traditional image transformation mechanisms such as rotation, translation, and scaling are integrated. Results from our research are an encouraging 10Hz with no vision post processing and accuracy up to 11 feet. Finally, vision mapping results are compared to simultaneously collected sonar data in three unique experimental settings