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Quantum GIS Trainings at NIRD Jaipur Centre, India |
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The National Institute of Rural Development (NIRD) is an Apex institute of Ministry of Rural Development, Government of India. Headquarter is located at Hyderabad city of India and it has three sub centres at Guwahati, Jaipur and Patna city. Jaipur city is capital of Rajasthan State (North Western side of country). The NIRD Jaipur Centre is actively involved in short (mostly 5 days including one-day handheld GPS survey and local visit) residential GIS trainings for middle level government officials of North Indian States. Reputed NGOs and Scholars are also trained if interested. Trainings are fully sponsored by NIRD and participants are to bear only their travel expenses.
The author is working in NIRD Jaipur centre as an Assistant Professor and coordinating GIS and Watershed related trainings at the centre. Initially at the time of his posting at Headquarter of NIRD at Hyderabad, he was involved in GIS trainings with commercial software like ArcGIS and ERDAS. After getting opportunity of a two days training on QuantumGIS at IIT Madras in 2009, it was felt that the Open Source GIS can fulfil the need of Rural Development sector of India. The version learnt in training was QGIS 1.0.2. The training feedback was provided to seniors and it was recommended to introduce QGIS in further trainings but apprehensions were there in accepting the software in mainstream of trainings. Software was then pursued for the personal use for one year and its new versions were checked for the enhanced functionalities. During this whenever author was course coordinator in training, he used QGIS in trainings for introduction and feedbacks.
QGIS is used for all GIS training courses
Figure 1: QGIS training course at NIRD Jaipur Centre
Since creation of NIRD Jaipur centre, only QuantumGIS is being used for all GIS trainings at the centre. Further it is being messaged and advised in all trainings that no commercial GIS software should be purchased at District (administrative unit in India after Nation and State) and below, if real requirement is not felt and this saving may be used for purchase of hardware like GPSs, computers etc.
There is a question why QGIS only when other software like uDig, MapWindow, gvSIG, GRASS are also there. The answer lies in the facts that QGIS is an OSGeo incubated project, less complex, its development is very fast and associated with huge community of users and developers and lastly authors expertise. With its latest version of 1.8, software is capable of satisfying the all needs of grass root rural development executors in India with satisfying the present queries and wishes for future.
The applications of software during training are generally concentrated on Watershed and Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS) as these two are land based flagships of Government of India. Local Open Source Raster and Vector data are used in exercises. Participants are encouraged to come with their own or departmental data if available to work. Training is provided in lab equipped with 15 computers of i5, 8GB RAM and Windows7 OS. Per training number of trainees remains between 20-30.
Figure 2: Conducted QGIS training courses and participants
General topics covered are basic introduction to the GIS and QGIS software , major tool bars, plug-in structure, geo-referencing, creation/editing of vector data, clip (Raster/Vector), merge, terrain analysis, contours, .csv to .shp layer, .shp to .kml and vice versa, handling GPS data, Interpolation, table editing/query, field calculator, print composer etc. and some basic analysis on vector data. Apart from introduction to various help links available, a LinkedIn group for participants has been created for post training support.
Number of QGIS Based trainings conducted by author with participants’ details is shown in the table:
Success
Every month training is conducted with 20-30 participants so this number is increasing every month. Training feedbacks are remaining very positive and encouraging. Certificates are provided to the participants after completion of training.
Presently handouts are being supplied to the participants in hard copy and tutorial, software and practice data in soft copies but plan is there to create DVDs containing screen-recorded lectures/demo of various topics in Hindi and English language. In future certificate and diploma programmes may also be initiated.
Author
This article was contributed in July 2012 by H K Solanki, Assistant professor, NIRD Jaipur centre, Website: http://www.nird.org.in
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Amurum forest reserve habitat and avifauna mapping with QGIS in Nigeria |
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Amurum forest reserve is located near the city of Jos, Plateau state, Nigeria. It was established in conjunction with the initiation of the A.P. Leventis Ornithological Research Institute (APLORI) for the purpose of natural conservation, education and research. APLORI is hosted by the Department of Zoology at the University of Jos. Yearly a group of approximately eight highly motivated students from all over Nigeria obtain training in conservation biology, statistics (with R) and as of 2011 GIS as well. During two weeks in December 2011 we studied basic GIS concepts and applied those with QGIS for various conservation purposes. In this article we describe the way in which we used QGIS to map the habitats and its determinants of Amurum reserve and how the basic habitat maps were used to obtain strata for the purpose of efficiently determining the spatial distribution of the avifauna including the biodiversity.
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| Training Group |
Mapping elevation, hill shade, slope and habitats
1) Mapping elevation and groundtruthing: We downloaded (free) elevation data originating from the NASA Shuttle Radar Topographic Mission (SRTM) for the area in which Amurum is located. (Information about the global elevation data set can be found here: http://www.cgiar-csi.org/data/elevation/item/45-srtm-90m-digital-elevation-database-v41).
2) The GdalTools were used to merge original data sets and to clip a smaller area containing the reserve so that the raster data sets remained relatively small. By means of GPS we collected elevations at various locations in the reserve.
3) Overall, the elevations of the SRTM data set corresponded well to the gps-collected elevations. Terrain models in GdalTools were used to calculate hills hades and slopes for the area. These variables are important from an ecological point of view because they are strongly associated with the type of habitat.
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| QGIS screenshot |
4) Since we intended to develop a good-looking map, we interpolated the original (clipped) elevation map to obtain a higher resolution map. We used the warp tool in GdalTools. By means of the contour tool we obtained smooth contour lines.
5) Coordinates of the boundary of the reserve were obtained by walking along the boundaries of the reserve with a GPS. The waypoints and tracks stored in the GPS were smoothly imported using the GPS Tools. The imported waypoints and tracks were used to construct a polygon shapefile. The tracks inside the reserve were mapped in a similar fashion.
6) We were able to quickly and precisely construct a habitat map of Amurum using a Google satellite image which we got into the workspace with the Openlayers plugin. The reserve has three types of distinct habitat: Savannah, Gallery forest and Rocky outcrop. On the basis of the satellite image we used the editor to draw polygons demarcating the three habitats. Setting the snapping options correctly allowed the construction of non-overlapping polygons.
Mapping bird distributions and diversity
The habitat maps were used to generate random locations. The area of the various types of habitat were used to generate a number of locations proportional to the surface of each habitat type (stratification).
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| Training Group |
The random points in fTools were used for this purpose. All the locations were visited during two mornings by four groups of students (2 per group) giving a total of 38 random locations dispersed throughout the reserve. The observation data were entered in a spreadsheet and analyzed using R. In addition, the Shannon-Wiener diversity index was calculated using R. After merging the location file with the resulting observation data it was exported as a csv file which was loaded into QGIS using the “Add delimited text layer” tool. On the basis of the above mentioned layers a map was constructed presenting some of the most important landscape features and avian diversity of the Amurum reserve.
Conclusion
Overall, the course was a great success. We - a group of students with no previous GIS experience - enjoyed working with QGIS a lot. Within just two weeks time we were able to develop an extremely useful map of the reserve. Amongst others, the extents of the various habitats were determined which allows for stratification and thus for better estimates of abundances of various kinds of organisms. Basically we are now able to do better ecological research using QGIS as an open source platform.
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| QGIS map: Diversity of Amurum Forest Reserve |
Authors
Abengowe Elmond Chiadikaobi, Adeyanju Temidayo Esther, Akiemen Nerioya, Albert Malangale Tauje, Azi Abok Joel, Echude Daniel, Eelke Folmer, Nwaogu Chima Josiah, Onoja Joseph Daniel, Yadok Biplang Godwill |
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QGIS at high school - the urban green spaces in Rada Tilly coastal town, Chubut province, Argentina |
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Introduction
In our region, Argentinean Patagonia, we have very few references about the application of GIS in High School for the construction of geographical knowledge as a mean to face territorial and environmental issues. The case of the urban green spaces in Rada Tilly coastal town analyzed by QuantumGIS, tends to demonstrate a methodology of an academic exercise that can project, with important reaches, as formative instances related to the geographical reasoning in students of 12th grade of the Abraham Lincoln School.
We started by the observation (inventory), digitizing the cadastral blocks and the green areas (tree´s canopy) using Google Earth satellite images. As a conceptual framework, we lectured about cartographic design, satellite images reading and interpretation, and specially, location analysis to contrast the situation (in m2) of the urban green spaces by inhabitant in Rada Villa coastal town, with values suggested by the World Health Organization -WHO- (a minimum of 9 m2 of green areas, by person, in urban areas).
About the project
The main objective of the experience was to lecture the 12th grade students, in the implementation of a GIS as tool to optimize and enhance the management of spatial information, and to provide a support to the decision making process.
Specific objectives:
- Student´s appropriation of a local issue (the Rada Tilly´s green areas related the 9m2 by inhabitant proposed by WHO) from a geographical perspective through GIS tools.
- Usage of GIS as a technical tool to validate of socio-spatial hypothesis.
- Verification of the viability of capture, processing, storage, analysis, recovery and updating of spatial data using a FOSS QuantumGIS.
Methodology:
To generate the project we continue the following methodology:
- Practical and theoretical lectures; mainly about the usage of QGIS and the benefits of urban green spaces and its territorial implications.
- Cartographic modeling, vector layers definition, development of GIS databases.
- Field work (trees data records and GPS locations).
- Vector digitizing of urban cadastral blocks and the tree´s canopies, using a Google Earth (GeoEye) image. In order to consider the amount inhabitants by cadastral block, we assigned an average value of 4 inhabitants by plot.
- Results presentation through thematic cartography.
Attribute table of “blocks” vector layer.
Conclusion
Based in the projection of an average value of 4 inhabitants by cadastral plot, we estimated that the current (2010) urban population Rada Tilly would go up to around 9.600 inhabitants. These people reside in 209 blocks and they represent 157.6 hectares. The average population density would be of 61 inhabitants by hectare.
The total inventoried green areas grow up to 150.736 m2 (15 hectares). Reason why we can consider that the green area by inhabitant in the study area is 15.7 m2 (the WHO suggested value is 9m2 of green area by inhabitant). This value proves a very favorable situation, as far as the environmental benefits, that trees offer to the inhabitants in this marine coastal town.
Distribution of urban green spaces (green) and population density by blocks (white to brown) at Rada Tilly coastal town, Chubut Provinc, Argentina.
Although the project was an academic exercise of High School, we deeply value the inventory´s results obtained by QGIS. Students worked with all academic rigor and seriousness, showing appropriation of the thematic (urban green spaces) and also of the tool (QGIS). It was a very enriching experience for them and also for the educational staff involved.
After the project experience we can assure that the FOSS QuantumGIS is an extremely recommendable alternative for capture, processing, storage, analysis, recovery and updating of spatial data, in fast and efficient form. We have such a positive impression of the software that we will start the use of QGIS in our university courses, replacing GIS Proprietary software that we have being using.
Authors
This article was contributed in September 2011 by Mauro Novara and Alberto Vázquez from Argentina.
 Mauro Novara is Professor of Territorial Information Systems course. Lecturer and researcher of National University of Patagonia San Juan Bosco, Faculty of Humanities and Social Sciences. Geography Department. Comodoro Rivadavia, Chubut Province, Argentina.
 Prof. Alberto Vázquez is a graduate teaching assistant of Territorial Information Systems course. National University of Patagonia San Juan Bosco, Faculty of Humanities and Social Sciences. Geography Department. Comodoro Rivadavia, Chubut Province, Argentina.
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QGIS and GRASS in Local Government Bushfire Hazard Mapping |
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Introduction
The Southern Downs Regional Council (SDRC) is a small-to-medium sized local government in south east Queensland, Australia. The council region, mainly the southern part, suffers from major bushfires. Bushfire is a real and present concern for the residents and landowners in the Southern Downs Region, and has resulted in the loss of life and property.
This project will allow the council and the people of the region to be more aware of the risk and to allow for better decision making in the future.
The Project
As bushfire is not only a problem for SDRC but also for the whole of Queensland, the state government requires that each local government identifies the bushfire hazard in their area via the State Planning Policy 1/03 Mitigating the Adverse Impacts of Flood, Bushfire and Landslide [1]. This kind of job would normally be done using consultants but was instead done by the council itself using a combination of QGIS and GRASS.
The GIS side of the project project was broken down into 6 main steps
- Slope assessment and mapping
- Aspect assessment and mapping
- Vegetation assessment and mapping
- Combining scores to identify the severity of bushfire hazard
- Field verification and qualitative assessment
- Final Maps
The use of QGIS and GRASS
QGIS, using the GRASS plugin, was selected as it provided the tools needed to complete the job and the interaction between QGIS and GRASS made it easy to process the raster maps and present them in a meaningful way to users. SDRC uses MapInfo for its main GIS system, however MapInfo’s addons were not as powerful as GRASS GIS for raster processing.
The QGIS GRASS plugin was used to import 5 meter contours of the whole region into GRASS which were then converted into a contour raster map using r.surf.contour. A slope and aspect map were then generated using r.slope.aspect from the raster contour map. Categories were assigned to different slope and aspect ranges and given a hazard risk sore. Vegetation areas were also given different risk scores. All the resulting raster maps were then combined using mapcalc and given a final risk hazard score. The risk scores are then divided into three main categories: high; medium; and low.
The final part of the process was field verification via the rural fire service. After the review process, QGIS was used to print the final maps for presentation.
As all GRASS commands can be run from the command line, all the commands that were needed to generate the bushfire hazard maps were recorded, for documentation purposes and for if the maps needed to be regenerated some time in the future.
Conclusion
Overall QGIS, together with the GRASS plugin, provided a great experience and a great final outcome for the council doing their own bushfire hazard mapping. The GRASS plugin provides a very easy to use interface to GRASS through QGIS. As QGIS is able to open the GRASS raster format natively, integration is very seamless and maps can be made with ease.
The project won an encouragement award at the Queensland Planning Institute of Australia state planning awards in 2010 [2]
References:
[1] http://www.emergency.qld.gov.au/publications/spp/
[2]http://digital.crowtherblayne.com.au/default.aspx?xml=crowther_pia.xml
Author
This article was contributed in January 2011 by Nathan Woodrow. Nathan is a GIS officer at the Southern Downs Regional Council and is studying an associates degree in Spatial Science at University of Souther Queensland
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