Model:DeltaClassification: Difference between revisions

Revision as of 09:14, 10 April 2020

Also known as	DeltaClassification
Model type	Tool
Model part of larger framework
Note on status model
Date note status model

Incorporated models or components:

Spatial dimensions	2D
Spatial extent	Landscape-Scale
Model domain	Coastal
One-line model description	Geometry classification of delta islands
Extended model description	This tool provides a method for extracting information on the nature and spatial extent of active geomorphic processes across deltas from the geometry of islands and the channels around them using machine learning. The method consists of a two-step ensemble unsupervised machine learning algorithm that clusters islands into spatially continuous zones based on morphological metrics computed on remotely sensed imagery

Keywords:	machine learning, delta landforms,

Supported platforms	Linux, Mac OS
Other platform
Programming language	Python
Other program language
Code optimized	Single Processor
Multiple processors implemented
Nr of distributed processors
Nr of shared processors
Start year development	2017
Does model development still take place?	No
If above answer is no, provide end year model development	2019
Code development status	As is, no updates are provided
When did you indicate the 'code development status'?	2020
Model availability	As code
Source code availability (Or provide future intension)	Through CSDMS repository
Source web address
Source csdms web address
Program license type	BSD or MIT X11
Program license type other
Memory requirements	n/a
Typical run time	n/a

Describe input parameters	Geometric parameters on delta shapes derived from satellite data
Input format	ASCII
Other input format
Describe output parameters	classification of groups of similar zones within a delta system
Output format	ASCII
Other output format	maps
Pre-processing software needed?	No
Describe pre-processing software
Post-processing software needed?	No
Describe post-processing software
Visualization software needed?	No
If above answer is yes
Other visualization software

Describe processes represented by the model	Tool is used to regionalize a study area into zones with 'common physical characteristics' with the underlying aim of differentiating areas of influence of various physical processes. Regionalization attempts to aggregate spatial units or observations into clusters based on spatial continuity as well as attribute similarity. Geometry metrics are derived from satellite data analysis and include a.o. island area, island aspect ratio, island fractal dimension, and surrounding channel metric, channel width, channel sinousity, number of outflow channels, convexity.
Describe key physical parameters and equations	The key methods used are: 1) Feature normalization and principal component analysis 2) Spatial clustering using GEOSOM algorithm 3) Hierarchical agglomerative clustering to built nested clusters
Describe length scale and resolution constraints	Methods has been applied to data set of 100's of individual delta islands derived from Landsat satellite data (30-60m resolution).
Describe time scale and resolution constraints	Mapview at a given time
Describe any numerical limitations and issues	n/a Limitations on the method do occur when delta systems consist of only a few islands, then the input dataset of geometric parameters becomes too small for the machine learning methods.

Describe available calibration data sets	Proof of concept was applied for the Ganges-Brahmaputra delta system
Upload calibration data sets if available:
Describe available test data sets	Test data was slightly updated from a published dataset by Passalacqua, P., Lanzoni, S., Paola, C., and Rinaldo, A.: Geomorphic signatures of deltaic processes and vegetation: The Ganges- Brahmaputra-Jamuna case study, Journal of Geophysical Research: Earth Surface, 118, 1838–1849, 2013.
Upload test data sets if available:
Describe ideal data for testing

Do you have current or future plans for collaborating with other researchers?	no

Is there a manual available?	No
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Model website if any
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Featured publication(s)	Year	Model described	Type of Reference	Citations
Perignon, Mariela; Adams, Jordan; Overeem, Irina; Passalacqua, Paola; 2020. Dominant process zones in a mixed fluvial-tidal delta are morphologically distinct. . (View/edit entry)	2020	DeltaClassification	Model overview	3
Perignon, M.C.; 2020. csdms-contrib/DeltaClassification: First release of DeltaClassification (Version v1.0). , , . 10.5281/zenodo.3926763 (View/edit entry)	2020	DeltaClassification	Source code ref.	0
See more publications of DeltaClassification