Name: University of Potsdam - Remote Sensing - Earth Surface Processes Group (UP-RS-ESP)
Type: Organization
Bio: This is repository contains scripts, codes, and models relevant for the analysis of remote sensing data and earth surface processes
University of Potsdam - Remote Sensing - Earth Surface Processes Group (UP-RS-ESP)'s Projects
Analysis of Distributions from Digital Elevation Models (ADDEM)
Scripts to process SPOT6/7 (or other satellite) imagery with the Ames Stereo Pipeline (https://github.com/NeoGeographyToolkit/StereoPipeline)
Python module to work with bounded power-law (BPL) distributed random variables.
ChanGeom - Channel Geometry, River Width, and along-stream distance extraction from KML
Codes pertinent for the analysis for remote sensing or earth-surface data
Python C-extension for memory efficient and multithreaded Pearson product-moment correlation coefficient estimation using OpenMP
Digital Elevation Model (DEM) and KnickZone-Picker (KZP) Analyzer (http://onlinelibrary.wiley.com/doi/10.1002/2017JF004250/full)
Connected Components (CC) from longitudinal river profiles for debris flow mapping
Matlab code for DEM noise analysis using 2D DFT
Digital Elevation Model Networks
Tools for the estimation of surface area of digital terrain models (DTMs) and its effect on slope distributions
Flow accumulation on TINs of point-cloud data
Voxelize a point-cloud variable via Gaussian kernel interpolation to voxel centers
GPU Gaussian kernel density estimation
Manuals (Markdown, PDF) for Python, Remote-Sensing Software, and SSH installation
GNSS Collection and Post-Processing with RTKLIB
Geometric based filtering of ICESat-2 ATL03 data for ground profile retrieval in Quebrada del Toro, Argentina
The Sparse Vegetation Detection Algorithm (SVDA) for ICESat-2 data
Laspy based lidar waveform reading
Comparison of KDTree implementations for Lidar PointClouds (PC)
Multiple Flow Direction (MFD) flow routing after Freeman (1991)
MinGrid creates a gridded DEM from point clouds by the minimum elevation per grid cell
Python module to compute the Mann-Kendall test for trend in time series data
Calculating the Moraine Age from Cosmogenic Nuclide Boulder Ages using a Gaussian Mixture Model
MSc Remote Sensing, geoInformation, and Visualization at the University of Potsdam
Normalize time series by quantile normalization to the normal distribution.