3D Spatial Data Processing

Data publications of the 3D Spatial Data Processing Group at the Institute of Geography at Heidelberg University.

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1 to 10 of 121 Results

Integrating VGI contributions for gully mapping using Kalman filter and machine learning 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...
Cross_Training_Integration.zip Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning ZIP Archive - 1.9 MB - MD5: 4833cdc615e69607bd51b49cfff7ea9d
Kalman_filter_integration.py Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning Python Source Code - 23.7 KB - MD5: 9b1919e5bf0dcdcf8e3d68eec4a25fdd Code
MetaData_Integrating_lines_kalman.txt Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning Plain Text - 2.7 KB - MD5: 3592aa831001b5a26154a7ba6c3109fd
reference_left.tab Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning Tabular Data - 31.6 KB - 8 Variables, 463 Observations - UNF:6:dbfZe/C8CmWXcBEZJg2RPw==
Reporting_Lines_combination_left_UAV.txt Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning Plain Text - 7.0 KB - MD5: 9b20b45da9830b79f92dc506546496f1
Self_Training_Integration.zip Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning ZIP Archive - 3.9 MB - MD5: 96697ceeebf0cca5a98e4c07ffbdd54a
UAV_Left.zip Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning ZIP Archive - 15.4 KB - MD5: 6001d045b9acf3b143b7df82c4ca0c89
Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation Jan 18, 2024 Weiser, Hannah; Ulrich, Veit; Winiwarter, Lukas; Esmorís, Alberto M.; Höfle, Bernhard, 2024, "Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation", https://doi.org/10.11588/data/UUMEDI, heiDATA, V1, UNF:6:9U7BGTgjjsWd1GduT1qXjA== [fileUNF] This dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have a...
AcePse_SP02_04_2019-08-23_q2_TLS-on_c.laz Jan 18, 2024 - Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation Unknown - 78.2 MB - MD5: 984abea0c7e1e0ebacfa92bf974a101e

Integrating VGI contributions for gully mapping using Kalman filter and machine learning

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...

Cross_Training_Integration.zip

Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning

ZIP Archive - 1.9 MB -

Kalman_filter_integration.py

Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning

Python Source Code - 23.7 KB -

Code

MetaData_Integrating_lines_kalman.txt

Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning

Plain Text - 2.7 KB -

reference_left.tab

Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning

Tabular Data - 31.6 KB - 8 Variables, 463 Observations -

Reporting_Lines_combination_left_UAV.txt

Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning

Plain Text - 7.0 KB -

Self_Training_Integration.zip

Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning

ZIP Archive - 3.9 MB -

UAV_Left.zip

Feb 19, 2024 - Integrating VGI contributions for gully mapping using Kalman filter and machine learning

ZIP Archive - 15.4 KB -

Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation

Jan 18, 2024

Weiser, Hannah; Ulrich, Veit; Winiwarter, Lukas; Esmorís, Alberto M.; Höfle, Bernhard, 2024, "Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation", https://doi.org/10.11588/data/UUMEDI, heiDATA, V1, UNF:6:9U7BGTgjjsWd1GduT1qXjA== [fileUNF]

This dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have a...

AcePse_SP02_04_2019-08-23_q2_TLS-on_c.laz

Jan 18, 2024 - Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation

Unknown - 78.2 MB -

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