Case Studies

Enhancing the Use of Python in GIS and Remote Sensing

Session Type: 
Poster
Presenter(s): 
Nathan Jennings, American River College/Opticks

This abstract outlines the development of a geographic information systems (GIS) Programming and Remote Sensing course at American River College using Python and Opticks (http://opticks.org) open source image processing software for use with remotely sensed imagery. The author has developed a fully on-line GIS course and text for developing and using Python for ArcGIS in addition to developing and using the Opticks Python scripting extension for a remote sensing course. The ability to use Python in both open source and commercial GIS and remote sensing software is becoming common place and a skill this is widely sought after. This paper will describe some of the knowledge, abilities, and skill sets that employers are seeking and how the author has developed the courses and texts using Python and Opticks in GIS and remote sensing to help students build these skills.

See www.jenningsplanet.com and http://opticks.org for more information.

Speaker Bio: 

Adjunct GIS Professor, American River College, Sacramento, CA
Sr. GIS Analyst, City of Sacramento, Sacramento, CA
Principal, JenningsPlanet, GIS Consulting
Opticks, Contributor-Collaborator-Mentor

The Oklahoma/Kansas cyberCommons: An Ecological Informatics Research Laboratory

Session Type: 
Poster
Presenter(s): 
Mr Jonah Duckles, University of Oklahoma
Mr Mark Stacy
Mr Brian Cremeans

Integrative ecological research efforts often collapses under the weight of the massive amounts of data they hope to integrate. We share our approach to addressing this by building a loosely-coupled data and analysis toolkit. This toolkit draws heavily from from FOSS4G, OGC services and open standards to enhance scientific analysis capabilities. We share several examples where we organize, process, enhance and expose spatiotemporal datasets, such as: 1) weather radar reflectivity data before quality control, used to classify biological targets; 2) archives of earth observing remote sensing satellite imagery and derrived products; 3) regional carbon flux modeling. We show the FOSS4G tools we draw upon and how we've arranged them into a system to meet our research goals.

Speaker Bio: 

Jonah is a member of the Eco-Informatics group at the University of Oklahoma. Eco-Informatics embeds IT professionals with ecological scientists to enhance research capabilities.

Embracing Web 2.0 and GIS to Enhance Public Participation in Science

Session Type: 
Poster
Presenter(s): 
Mr Shaun Langley, Michigan State University

Recent decades have seen a dramatic shift towards transdisciplinary research. Such projects require a unique integration of skill and communication. The integration of academic disciplines resulting from these endeavors creates a unique challenge, particularly for data management and analysis. The explosion in availability of spatial data has further exacerbated this problem as researchers and the public alike are enticed by the utility of such data sets. With the advent of Web 2.0, the public is becoming increasingly interested in GIS and data exploration, often for no purpose other than personal edification. At the same time, researchers are showing a greater appreciation for “indigenous knowledge” and it’s ability to provide unique insight into old questions. Volunteered GIS (VGI) has been successful at engaging non-scientists in scientific exploits, though often with little or no methodology or purpose. Participatory GIS (PGIS) has sought to enhance the relationship between researchers and the public in order to solve problems; however it is often of limited utility for the researcher and even more frequently lacking a technical aspect.

Recent advances in technology and spatial analysis, in conjunction with a greater technological understanding by the public, make it possible to revisit a cooperative relationship between researchers and non-scientists. The availability of mobile devices and wireless communication permit the public to be more involved in research activities to a greater degree than in the past. Furthermore, the accuracy of these devices is rapidly improving, allowing us to address old questions of uncertainty and error in data collections. Such cooperation between researchers and the public integrates themes common to VGI and PGIS, to bring about a new paradigm in GIScience.

Speaker Bio: 

I am a doctoral student in Geography at Michigan State University. My research focuses on adapting new computing technologies for use in an academic context.

Development of QGIS plugin for an user friendly management of climatological data in Italy

Session Type: 
Poster
Presenter(s): 
Dr Tiziana De Filippis, National Research Council - Institute of Biometeorology
PerInd Leandro Rocchi
Giulio Castagnini
Fabio Straccali

The study of potential dangerous events due to extreme meteorological conditions such as hail, wind and rainfall has been made at national scale in order to define a synthetic index representing the climatological hazard for administrative units in cartographic form.

The aims of this work is to provide the insurance companies and decision makers with user friendly Open GIS tools for analysis of meteorological parameters at a municipality scale over Italy.
qSIGAV is a plugin developed in Python that is able to change the “look and feel” of QuantumGIS environment to provide a user friendly GUI and functions to perform queries on the results of climatological study.

After plugin’s installation, qSIGAV controls several components of qGIS through its API and the QgisInterface Class in order to change menu entries, functions, graphical entities obtaining a full customized GIS system.

A DBmanager component allows the users to update, insert, delete all shape files and the associated legends of climatological themes, dataset that in qGIS are manage by SQLite3 engine.

Moreover a wizard helps the user to choose the region, domain and layer to be visualized on QGIS main view. Other tools have been developed to facilitate the insurance agents in join insurance indexes with climatological data.

All system elements as well as datasets, system database, customized functions, qGIS application have been encapsulated into a personalized setup using NSIS, an Open Source system for Windows Installer creation.

qSIGAV is a complete Open Source project that opens new perspectives for developers and GIS experts for implementing more flexible and customable GIS system applications.

Speaker Bio: 

Permanent researcher at the Institute of Biometeorology - National Research Council. She focused her interests on SDI and Web GIS applications using Open Source solutions.

 

Analysis of medium and small scale Digital Surface Models with respect to slope and aspect

Session Type: 
Poster
Presenter(s): 
Prof Maria Antonia Brovelli, Politecnico di Milano, DIIAR, Polo regionale di Como
Eng Sara Lucca

The work is about preliminary analysis for DSM errors distribution evaluation.

Three digital models were taken in consideration: the SRTM DSM (step around 90m), the ASTER DSM (step around 30m) and the DSM provided by Lombardia Region (step 2m).
The analysis was performed in an area including the walled city of Como and part of the Como province around; in the chosen area a LiDAR dataset, provided by the Lombardia Region, was also available.

At first the LiDAR data were filtered in order to compute a DTM and a DSM characterized by a higher spatial resolution (step of 2m) so they were used as ground truth, considering that he nominal vertical accuracy of the dataset is about 20 cm.

All digital models were three-dimensionally readjusted using points from the LiDAR dataset to remove 3D effects with a Matlab software developed at the Geomatic Laboratory of the Politecnico di Milano.

Once removed three-dimensional effects from the LiDAR derived digital model, 33 classes were obtained from the combination of four slope classes and eight aspect classes (the last class corresponds to flat terrain).

The digital models from SRTM and ASTER as well as the Lombardia Region DSM were compared with respect to the 33 classes in order to evaluate, through two-way ANOVA (Analisys Of VAriance), the dependency on slope or aspect that may be due to survey geometry or to the way a model was generated.

Before and after the readjustment procedure the RMSE between the models and the DSM from LiDAR were computed to evaluate accuracy variations.

In the last part of the work possible DSM errors depending on terrain coverage were evaluated using terrain coverage information DUSAF obtained from Regione Lombardia.

Speaker Bio: 

Degree with honors in Physics, PHD in Geodesy. Vice rector of Polytechnic of Milan with responsability for the Como Campus. Professor of GIS and Internet GIS.

 

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