The research area of the data set is the 5km long river course between Luc en diois and reconbeau jansac in France and its surrounding geomorphic environment. The width of the river course is between 10-200M. The river bed is mainly composed of loose sandstone, gravel and pebbles. The river course is wide and shallow with small curvature. There is no dike along the river, the river course is not fixed and moves rapidly, and the vegetation on both sides of the river course is dense.
The data set consists of two parts: one is orthophoto data, the other is DEM. There are ten GeoTIFF format data files in total. The geographic coordinate system is rgf93 ﹐ Lambert ﹐ 93. The orthophoto clearly shows the river and vegetation and other related landforms. The spatial resolution is 0.1M, and the pixel depth is 8-bit integer. The pixel depth of DEM compressed data is 32-bit floating-point type, and the spatial resolution is 0.2m/0.3m. The elevation of the whole area is between 480m and 580m. Taking the data of 2006 as an example, the orthophoto data is named as 2006dr ô me.tif, and the DEM data is named as 2006dr ô me dem.tif.
Original data: the UAV image data is the image obtained by CNRS (Centre National de la recherche Scientifique) in 2005-2009 from the UAV remote sensing monitoring of Dr ô me. The data is obtained by using the UAV (pixy The system is equipped with a high-definition camera to obtain a high overlap, high-resolution, true color digital image covering the whole research area, and the image format is JPEG.
SFM (structure from motion) data processing flow: the main processing flow is as follows: (1) in order to ensure the accuracy of image data processing, carry out preliminary quality detection on the image, remove the image with serious distortion, blur, abnormality and not in the study area, and import the pre-processing remote sensing image of unmanned aerial vehicle into photoscan. (2) The matching points of overlapped images are calculated, the position of each image is estimated, and sparse point cloud is generated. (3) Import the ground control points with precise geographical coordinates, transform the data from the image space coordinate system to the real world space coordinate system, further optimize the model and obtain the real space location of the camera and sparse point cloud. (4) Calculate depth information and generate dense point cloud. (5) Generating Orthophoto Image and DEM with spatial geographic coordinate information, the resolution size and projection type can be adjusted when outputting, and the data can be outputted.
This dataset is mainly used for quality control by the following means:
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CSTR:11738.11.ncdc.nieer.2020.1383
10.12072/ncdc.nieer.db3168.2023