fabianfassnacht Goto Github PK

1_laserscanning_lidr

avi_carotenoids

bayesiantools

General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

biomass

R-Codes for RSE manuscript "Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass"

cauquenes

R-scripts entitled "Using Multi-Sensor Data to Derive a Landscape-Level Biomass Map Covering Multiple Vegetation Types"

cloud_compare_3dfin

Basic tutorial for the 3DFin workflow in CloudCompare

cloudcompare_basics_1

esdl

ESDL report

fabianfassnacht.github.io

homepage

gam_best_subset_selection

Best subset selection for a model with a given number of predictors using exhausitive search

modisreproj

batch process reprojection of modis files

multi_scale_remote_sensing

Calculate landscape metrics in R based on a land-cover classification of Sentinel-2

phenology_analysis

planetary_science_rs_tutorial_1_download_landsat_s2

pytorch_unet_geotiff_tutorial

A tutorial explaining how to run a unet segmentation in PyTorch using Geotiffs as input

qgis_tutorial4

qgis_tutorial5

qgis_tutorial6

qgis_tutorial7

qgis_tutorial8

qgis_tutorial_1

qgis_tutorial_2

qgis_tutorial_3

qgis_tutorial_9

reforse

GeForse - Generating Syntethic Forest Remote Sensing Data

sentinel-download

Automated download of Sentinel-2 L1C data from ESA (through wget) :http://olivierhagolle.github.io/Sentinel-download

speciesrichness-glmvsrf-lidar

R-codes for: Lopatin, J., Dolos, K., Hernández, J., Galleguillos, M., Fassnacht, F. E. (2016): Comparing Generalized Linear Models and random forest to model vascular plant species richness using LiDAR data in a natural forest in central Chile. Remote Sensing of Environment 173, pp. 200–210. 10.1016/j.rse.2015.11.029

svh

scripts doing some simple experiments related to the spectral variability hypothesis

tibet_landsat

Code to process NDVI time series for the Tibetan Plateau

treemortality