# Mapping Mountain Landforms and Its Dynamics: Study Cases in Tropical Environments
## 3 Procedures, Material and Methods
### Material and Methods
#### 3.3.2 UAV Parameters, Imagery Acquisition, Photogrammetric Processing, and Outputs  
We present results regarding the use of UAVs in fluvial geomorphology, giving new insights into tropical river behavior, with a spatial high-resolution component. We used a low-cost UAV commercial model to map and monitor changes in this challenging environment, as traditional remote-sensing sources cannot give quality topographic information and imagery due to (i) vegetation coverage, and (ii) cloudiness.  
The river reach was surveyed with a UAV platform (DJI Phantom 4 V.2) carrying a RGB camera of 1\" CMOS 20M effective pixel resolution. The UAV was used for automated photogrammetric flights. The flight missions were programmed with an Android mobile application, DroneDeploy. Within the app, the flight velocity, extension, altitude, and front-side overlap (<80%) were programmed according to the environmental conditions. Since the surveyed sites are mountainous, the flight parameters were adapted to dense vegetation and high atmospheric humidity conditions, meaning low-altitude flights (>100 m from the takeoff site), and low velocity (>10 km/s) for the safety of the aircraft. Planning and executing the photogrammetric flight took under 20 min. Thirty-seven images were taken at 70 m flight altitude from the takeoff site. The flights surveyed 2.5 hectares. The photogrammetric processing produced an orthomosaic with a resolution of 2.6 cm/pixel and a DSM with a resolution of 10.6 cm/pixel. Two flights were performed with the same flight parameters. The first observation was executed on 14 August 2017 and the second on 21 September 2017.  
To map the high-resolution fluvial geomorphology and change detection, the digital imagery obtained from the automated flight routes was centered on developing 3D surface models (DSM), elevation models (DEM), and 2D photogrammetric orthomosaics, using the structure from motion algorithm [63]. The method uses a set of covered images to produce densified point clouds to generate the elevation products [64]. The digital imagery was processed on the software Agisoft Photoscan 1.4.0. The SfM is based on a sequential step that assembles the images. Firstly, digital camera adjustments and ground control points (GCPs) were calibrated in the initial steps. Imagery arrangement of the images derives a scarce cloud that derives from the corresponding point process. The ground control points were surveyed with a Trimble R8s GNSS receiver and an Android mobile device during each flight mission in the same location. The locations were marked with spray paint, and corresponded to large boulders and nearby trees located in the survey area. Afterwards, the dense point cloud was created from the scarce cloud. Later, the densified point cloud was classified into separate points relating to ground, vegetation, or other structures.  
The DSM, DEM and orthomosaic were used to map the fluvial geomorphology of the river reach. The photointerpretation of the digital outputs allowed the accurate delineation of the fluvial geomorphological features and the calculation of the morphological and morphometric data. Comparing both photogrammetric flights and using a Maximum Likelihood Classification on ArcMap 10.7 allowed the detection of accurate changes in the river, such as boulder transport, accretion, erosion, tree falling and turbulence changes within the channel [65]. Using the classification method proposed by [PERSON] [66], and [PERSON] et al. [67], channel morphology was analyzed for this single-thread, straight reach.