Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

There was an error with your search parameters. Please clear your search and try again.

1 to 4 of 4 Results
Jul 11, 2023
Vallejo Orti, Miguel; Negussie, Kaleb; Corral, Eva; Höfle, Bernhard; Bubenzer, Olaf, 2023, "Multi Profile Curvature Analysis (MPCA) algorithm for gully detection using TanDEM X Digital elevation model.", https://doi.org/10.11588/data/A4KGYJ, heiDATA, V1
Characterization of micro-terrain features has been explored to detect convex and concave features in the terrain. The analysis of first and second derivatives of a function fitted to the terrain is a frequently used resource to describe terrain characteristics and to undertake G...
Feb 19, 2024
Vallejo Orti, Miguel; Anders, Katharina; Ajali, Oliubikum; Bubenzer, Olaf; Höfle, Bernhard, 2024, "Integrating VGI contributions for gully mapping using Kalman filter and machine learning", https://doi.org/10.11588/data/UHSQG0, heiDATA, V1, UNF:6:dbfZe/C8CmWXcBEZJg2RPw== [fileUNF]
The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of...
Dec 13, 2023
Vallejo Orti, Miguel; Negussie, Kaleb; Corral, Eva; Höfle, Bernhard; Bubenzer, Olaf, 2023, "Gully detection with Inverse Morphological Reconstruction Algorithm [data]", https://doi.org/10.11588/data/PXDR4M, heiDATA, V1
Characterization of micro-terrain features has been explored to detect gully objects in the terrain. An adaptation to the morphological reconstruction operator is implemented to detect gullies instead of buildings or other man-made structures. This operator can be configured to d...
Jan 16, 2024
Vallejo Orti, Miguel; Castillo, Carlos; Zahs, Vivien; Bubenzer, Olaf; Höfle, Bernhard, 2023, "Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]", https://doi.org/10.11588/data/NSMM6P, heiDATA, V2, UNF:6:KVUhApCn+Ker99oncknXzA== [fileUNF]
This code implements the TimeSeriesForest algorithm to classify different types of changes in gully environments. i)gully topographical change, ii)no change outside gully, iii) no change inside gully, and iv) non-topographical change. The algorithm is specifically designed for ti...
Add Data

Sign up or log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.