TSTools is a plugin for QGIS (version 2.0+) that helps visualize remote sensing time series by linking time series dataset models (objects that describe and characterize the time series) with user interface tools designed to harmonize the spatial and temporal dimensions of these large datasets.
Read the Quickstart to see the plugin in action
This plugin has not been uploaded to the main QGIS plugin repository so installation will need to be done manually.
In most cases, the QGIS Python plugins folder will be located in your home directory within the ".qgis2/python/plugins" folder. Any plugins you have installed previously will be located here. For more information, see this excellent answer on Stack Exchange.
- Install QGIS and the required Python libraries (see requirements section below)
- Download the file "tstools.zip" from this repository on Github.
- Unzip the ZIP file to find the "tstools" folder.
- Copy this "tstools" folder into your QGIS Python plugins directory (see above for where this is located)
- Launch QGIS and open the Plugin Manage dialog (Plugins menu -> Manage and Install Plugins)
- Check the box next to "TSTools" to enable the plugin
Two new icons will be added to the plugins toolbar. These icons have the letters "TS" in capital red colored letters. To initialize a timeseries dataset within the plugin, click the icon without the crosshair symbol. Point this dialog to your timeseries and configure any additional options before clicking "Okay". To retrieve the timeseries for any given pixel, add an image from your timeseries to QGIS using the "Images" tab and click the "TS" icon with the crosshairs to replace your current map tool with the "TSTools" map tool.
An example dataset for this plugin is located here: https://github.com/ceholden/landsat_stack
To help out people who find the installation of this software is not so straightforward (e.g., it is more difficult on Windows than Linux), I have created a virtual machine of the 14.04 LTS Xubuntu distribution with everything installed. This virtual machine contains a full stack of softwares - GDAL, Python, QGIS, NumPy, SciPy, etc. - that are required to use the plugin. The virtual machine is formatted as a VirtualBox image and I would recommend you to use VirtualBox to run the virtual machine. VirtualBox is a free and open source softare that can create and host virtual machines and is comparable to commercial solutions such as VMWare or Parallels.
The virtual machine has been exported to a VirtualBox appliance and uploaded to my university department's anonymous FTP server:
ftp://ftp-earth.bu.edu/ceholden/TSTools/
Please see the included README for further instructions. A md5sum of the virtual disk appliance is provided for confirming the file transfer integrity.
Python (2.7.x tested)
Numpy (1.7.x tested)
GDAL (1.10.0 tested)
- For reading CCDC results: Scipy (0.12.0 tested)
- For live plotting with YATSM (CCDC / BFAST inspired clone or hybrid): see https://github.com/ceholden/yatsm
To help develop this plugin, you will need QGIS, Python, and the Qt developer tools for Python (for building). The Qt dependencies are available on Ubuntu in the "pyqt4-dev-tools" package.
Time series fit from Zhe Zhu's CCDC
- Click a plot point and open corresponding image in QGIS
- Adjust X and Y plot limits
- Turn on or off model results
- Export image as PNG, EPS, etc.
