# Mapping Mountain Landforms and Its Dynamics: Study Cases in Tropical Environments
## 1 Introduction  
Cartography has become an essential instrument for scientific research. In a broad sense, cartography includes any activity in which the representation and use of maps has a basic interest, encompassing a group of techniques that reduces the spatial characteristics of a large area to expose it in the form of a map and to be observable [1] Geomorphological maps are an important factor in the prevention of natural risks such as floods, landslides, subsidence, volcanic and coastal hazards, among many others. In addition, geomorphological mapping is key to representing the distribution of landforms and the processes relating to their geographic environments. These maps are critical for studies related to the cryosphere, as well as for volcanic and structural terrains, providing constant new knowledge of its processes and changing dynamics. There are several methodological procedures for geomorphological mapping. However, high mountain environments usually have a greater variety of geological formations, landforms, and soils. Moreover, many of these areas are inaccessible or difficult to access for fieldwork purposes. According to [PERSON] [2], the more complex the terrain, the larger the variety of colors and symbols needed for its mapping. Thus, there is a probability that the chosen legend does not have enough elements to represent all the features of the study area. Therefore, more symbology elements are needed in many cases. Topographic data calculation is key for several geomorphic applications, especially landform monitoring and evolution [3]. To monitor these landforms, structure from motion (SfM) is a photogrammetric approach that has become popular over recent years. SfM is a low-cost technique of 3D reconstruction of landforms, it automatically solves, by using iterative calculation algorithms, the problems of camera placing and scene arrangement,using common features in multiple overlapping images. Moreover, despite the fact that the automatic geographic determination has increased in the last years [4; 5], there is a continuous need to classify, delineate and check in the field the obtained morphologies according to their genesis, dynamics, evolution, and age [6; 7]. However, it is challenging to obtain remote sensing images with the same sensor type and spatial resolution [8]. During the last decade, the proliferation of unmanned aerial vehicles (UAVs), also called unoccupied aerial vehicles or remotely piloted aircraft systems (RPAS) [9], has resulted in the production of high-quality aerial imaging and high-precision digital elevation models (DEM). UAV are remotely controlled vehicles such as fixed-wing planes, helicopters, or multi-rotor platforms [10; 11]. All this, together with the wide availability of high quality satellite images, has facilitated the observation and the monitoring of mountain landforms. Moreover, remotely-sensed data resolution is elemental in modern glacial settings. Spatial resolutions proportionate the landform size that can be mapped, and the research scope [12]. The treatment of UAV images may be accomplished with structure from motion (SfM) photogrammetry techniques, with any available software. Multitemporal UAV imagery will enable the measurement of the current state of potential landforms or the monitoring of them within short timescales (e.g., [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24], among many others). To work with all these data, GIS software packages offer several tools for visualizing, manipulating and analyzing large amounts of remote sensing-and geomorphological data (e.g., [12; 25; 26; 27]). These techniques can be applied to a wide range of studies, such as geomorphological, (e.g., [28; 29; 30; 31]), and glaciological, (e.g., [32; 33; 34; 35; 36]). There are a great diversity of landforms in high mountain areas, which are the result of intense processes related to deglaciation [30; 37]. We hypothesize that a mountain geomorphology mapping protocol is a key tool in a warming-world scenario.