Software

Caution: this software is provided "as-is". Read the manual before using.

Subsidence evaluation tool

This tool was developed as a standalone program to be run either as an executable or within the MATLAB environment. The development is hosted on GitHub. The main project can be found here while the official releases can be found here.

Algorithm description: This [.pdf] is an Accepted Manuscript of an article published in International Journal of Remote Sensing on 18 Sep 2013, available online: http://www.tandfonline.com/10.1080/01431161.2013.833357.

Add-in version for ArcGIS

Same subsidence evaluation tool for use within the ArcGIS environment. This is just a prototype to be further developed. Some users have reported problems with some version of ArcGIS that cause the environment to hang.

The development is hosted on GitHub. The main project can be found here while the official releases can be found here.


ArcGIS toolboxes

Bridge Movement Analysis

This tool takes a shapefile of bridges and colors them based on displacement data over time. Points are first filtered by height to make sure that they are on the bridge. After filtering, if any point moves greater than the warning threshold (inches/year) then the bridge status is set to WARNING. If any point moves greater than the critical threshold (inches/month) then the bridge status is set to CRITICAL. These thresholds have default values but may be user adjusted. If there are no problematic points, the bridge status is set to GOOD. The data are noisy, so a running average of calculated velocities is taken to perform the analysis.

The status IDs and bridge coordinates are printed to the output attribute table. A symbology layer is required as input to allow the tool to color the bridges based on status ID - red for CRITICAL, yellow for WARNING, and green for GOOD. When the tool has completed running, if a CRITICAL bridge was found, the tool will zoom to that location. Otherwise, coordinates and the status for each bridge appear in a pop-up window (when running the tool in foreground) and in the output table.

The development is hosted on GitHub. The main project can be found here while the official releases can be found here.

Coherent motion analysis

The 'Coherent Motion' tool of a noisy time-series data is based on a statistical trend detection procedure, Theil-Sen trend map. In this algorithm, a median trend is computed of an uniform or nonuniform time series. It is entirely a point-based operation; therefore no geological structural analysis is needed.

The 'Coherent Motion' tool takes a feature layer with point feature class as input and gives two separate output layers.

The first output layer exhibits the absolute value of linear trend of each point in the input layer. The trends are colored encoded in the symbology layer based on warning threshold and critical threshold.

The second output layer shows a set of polygons based on a group of points that are determined within a specified scale and that has absolute trend value more than warning threshold. This tool automatically save a shapefile for the polygon featureclass in the background. The polygons are colored based on another input symbology layer. As an example, a red polygon indicates that there exists at least one point that has an absolute trend value more than the critical threshold. The minimum number of points that are allowed to form a polygon within the scale is set as '3' within the script.

The development is hosted on GitHub. The main project can be found here while the official releases can be found here.

Road smoothness

The road smoothness analysis of a noisy time-series data is based on the smoothness computation on a graph, It is a region-based operation, not a point-based one. A graph is constructed using a couple of points that lie within a certain scale. Therefore, using the change of scale both global and local deformation information can be computed.

The road smoothness analysis takes a feature layer with point feature class as input and gives two separate output layers.

The first output layer exhibits the absolute value smoothness of a road. The smoothness values are colored encoded in the symbology layer based on warning threshold and critical threshold.

The second output layer shows a set of polygons based on a group of points. This tool automatically save a shapefile for the polygon featureclass in the background. The polygons are colored based on another input symbology layer. As an example, a red polygon indicates that smoothness value of the entire polygon is above a critical threshold. The minimum number of points that are allowed to form a polygon within the scale is set as '3' within the script.

The development is hosted on GitHub. The main project can be found here while the official releases can be found here.


GISque

This repository contains a set of python tools generated and used during the project.

Once again, these scripts are provided "as-is".


Surface reconstruction

MATLAB implementation of mosaicked, thin-plate spline surface reconstruction. Example included.

The development is hosted on GitHub. The main project can be found here while the official releases can be found here.


GIS Export

MATLAB routines which export polygon risk information into Google Earth and ArcGIS. ArcGIS export requires the mapping toolbox.

The development is hosted on GitHub. The main project can be found here while the official releases can be found here.

Topic revision: r8 - 18 Jan 2016, AndreaVaccari
 
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