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Part 1: Document Description
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Citation |
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Title: |
Gully detection with Inverse Morphological Reconstruction Algorithm [data] |
Identification Number: |
doi:10.11588/data/PXDR4M |
Distributor: |
heiDATA |
Date of Distribution: |
2023-12-13 |
Version: |
1 |
Bibliographic Citation: |
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 |
Citation |
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Title: |
Gully detection with Inverse Morphological Reconstruction Algorithm [data] |
Identification Number: |
doi:10.11588/data/PXDR4M |
Authoring Entity: |
Vallejo Orti, Miguel (Heidelberg University, Institute of Geography) |
Negussie, Kaleb (Namibia University of Science and Technology) |
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Corral, Eva (University of Huelva) |
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Höfle, Bernhard ((3D Geospatial Data Processing Group, Institute of Geography, Heidelberg University, Germany)) |
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Bubenzer, Olaf ((Institute of Geography, Heidelberg University, Germany)) |
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Distributor: |
heiDATA |
Access Authority: |
Vallejo Orti, Miguel |
Holdings Information: |
https://doi.org/10.11588/data/PXDR4M |
Study Scope |
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Keywords: |
Earth and Environmental Sciences |
Topic Classification: |
gully erosion, digital elevation models, automatic detection |
Abstract: |
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 different gully depths and widths. The algorithm is based on successive geodesic dilations applied on a moving kernel. The geodesic dilation uses a mask (shifted copy of the original terrain) to generate a reconstructed surface, which ultimately can be subtracted from the original terrain to produce off-terrain elements or gully zones. Thus, the algorithm uses as inputs the original DEM, and a predefined height (mask shift) and width (kernel size) in meters, to customize the minimum detectable gully by the operator. |
Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
Vallejo Orti, M.; Negussie, K.; Corral-Pazos-de-Provens, E.; Höfle, B.; Bubenzer, O. Comparison of Three Algorithms for the Evaluation of TanDEM-X Data for Gully Detection in Krumhuk Farm (Namibia). Remote Sens. 2019, 11, 1327. doi: 10.3390/rs11111327 |
Identification Number: |
10.3390/rs11111327 |
Bibliographic Citation: |
Vallejo Orti, M.; Negussie, K.; Corral-Pazos-de-Provens, E.; Höfle, B.; Bubenzer, O. Comparison of Three Algorithms for the Evaluation of TanDEM-X Data for Gully Detection in Krumhuk Farm (Namibia). Remote Sens. 2019, 11, 1327. doi: 10.3390/rs11111327 |
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IMR_report.txt |
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Example of Output data |
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text/plain |
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inverse_morphological_reconstruction.py |
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Code |
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text/plain |
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MetaData_inverse_morphological_reconstuction.txt |
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Code Metadata |
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text/plain |
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points_dem3.txt |
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Example of Input data |
Notes: |
text/plain |