3D Spatial Data Processing

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1 to 10 of 94 Results

Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Jul 24, 2023 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, V1, 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...
Metadata_TSF.txt Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Plain Text - 4.1 KB - MD5: 32877e41621e27231bae303eda9f5d19 Documentation
Prediction_VH_Kunene-1.csv Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Comma Separated Values - 1.7 MB - MD5: 2059b5ada7e507f6a7148a75118b19a6 Data
Prediction_VH_Kunene-2.tab Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Tabular Data - 7.6 MB - 55 Variables, 12422 Observations - UNF:6:KVUhApCn+Ker99oncknXzA== Data
Prediction_VH_Kunene.csv Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Comma Separated Values - 95.8 KB - MD5: e7610e57ac4f1415f3d11a64963c8181 Data
target_very_big_Kunene_VH.csv Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Comma Separated Values - 7.7 MB - MD5: 923572a230d9fd56a22c4db0c40c8c86 Data
time_series_forest.py Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Python Source Code - 6.5 KB - MD5: 3e159b643fbeb7a266a39e997a0f80d9 Code
training_VH_Kunene.csv Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data] Comma Separated Values - 3.4 MB - MD5: a241c5fa94335ceb6bb16b6eba3528ec Data
Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code] Jul 20, 2023 Zahs, Vivien; Anders, Katharina; Kohns, Julia; Stark, Alexander; Höfle, Bernhard, 2023, "Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code]", https://doi.org/10.11588/data/D3WZID, heiDATA, V1 Automatic damage assessment by analysing UAV-derived 3D point clouds provides fast information on the damage situation after an earthquake. However, the assessment of different damage grades is challenging given the variety in damage characteristics and limited transferability of...
building_models_post_event_damage_grade3_generic.zip Jul 20, 2023 - Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code] ZIP Archive - 9.5 GB - MD5: 71093af0413740aeecc28c761c281115 Data

Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Jul 24, 2023

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, V1, 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...

Metadata_TSF.txt

Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Plain Text - 4.1 KB -

Documentation

Prediction_VH_Kunene-1.csv

Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Comma Separated Values - 1.7 MB -

Data

Prediction_VH_Kunene-2.tab

Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Tabular Data - 7.6 MB - 55 Variables, 12422 Observations -

Data

Prediction_VH_Kunene.csv

Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Comma Separated Values - 95.8 KB -

Data

target_very_big_Kunene_VH.csv

Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Comma Separated Values - 7.7 MB -

Data

time_series_forest.py

Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Python Source Code - 6.5 KB -

Code

training_VH_Kunene.csv

Jul 24, 2023 - Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]

Comma Separated Values - 3.4 MB -

Data

Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code]

Jul 20, 2023

Zahs, Vivien; Anders, Katharina; Kohns, Julia; Stark, Alexander; Höfle, Bernhard, 2023, "Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code]", https://doi.org/10.11588/data/D3WZID, heiDATA, V1

Automatic damage assessment by analysing UAV-derived 3D point clouds provides fast information on the damage situation after an earthquake. However, the assessment of different damage grades is challenging given the variety in damage characteristics and limited transferability of...

building_models_post_event_damage_grade3_generic.zip

Jul 20, 2023 - Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code]

ZIP Archive - 9.5 GB -

Data

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