Spatial Data Mining

~ Sakthi, 2nd year, B.E. Geoinformatics

Have you ever wondered how the engineers recover files that have been deleted from our phones? They use a technique known as data mining. Data mining is the process of extraction of useful, implicit and previously unknown data from large databases. In the recent years databases have gone through tremendous advancements. One such advancement is spatial database. They are complex databases in which data are represented by spatial data types and associated by means of spatial relations Along with the improvements in data mining, spatial data mining has also had developments like spatial reasoning, spatial data structures, computational geometry and so more. Other than just extracting knowledge from large spatial databases, the spatial data mining methods is also primarily used to understand those databases and the spatial relationships among those objects One of the widely used approaches for spatial data analysis is the Statistical approach It has been well researched; thus, many algorithms exist that efficiently handle numerical data and come up with realistic models of spatial phenomena. But these modelling processes are so complex that only experts with good statistical knowledge are able to work with them. Furthermore, this approach is not able to model nonlinear data properly Hence the need for more efficient data mining techniques was felt and machine learning is the result of that It is the technique of training a system to learn from the examples and solve problems on its own It’s highly effective when systems are trained to extract spatial data from very large and complex datasets by feeding it examples of known spatial objects along with some of the spatial relationships between them Another popular approach is the Spatial Cluster Analysis which has also been modified for use of data mining Apart from these, there are image databases, mostly obtained through remote sensing techniques Spatial data mining algorithms are also used here to analyse the grid arrays in one or more spectral ranges. Data mining is a new field that began only after the 1980s. Currently spatial data mining is done by considering the databases as relational databases But advanced approaches like Object Oriented database approach are refining them, so suitable methods for spatial data mining should also be developed in due course of time

LET’s QUAKE THE PLATES: Seismic wave Prediction

When dark night sky rumbles, floor beneath your shoes begins to shake and structures fall upon you. You can’t hear anything; you can’t see anything It’s just you, struggling to survive, waiting for someone to save you This is not just a nightmare; it happens in real – an earthquake An Earthquake is caused by a shift in tectonic plates These plates have been moving for millions of years, but when they struck at their edges due to friction, a stress occurs at the edge. When stress overcomes friction, it causes an earthquake, resulting in immense release of energy. Earthquakes can be a result of anthropogenic activities too Mining activities result in disruption of the crust, leading to seismic movements Gallons of water stored in dams and reservoirs create pressure along the fault line and reach the magma, creating vapour pressure beneath the crustal plates These phenomena cause instability in mass balance of tectonic plates. Geographic Information System (GIS) can be used henceforth to analyze the instability in mass distribution and tectonic activities over the plates. This instability in plates also causes foreshock (aseismic slip), a mini earthquake (magnitude around 3 4 in Richter Scale) that precedes a larger earthquake in the same location, like a caution signal GIS mapping and satellite data can assist in collecting useful data related to foreshocks, strains/stress on the plates and some previous tectonic activities in the fault line, using which an algorithm can be generated to model earthquakes and predict them in near future. Hence, Remote sensing and GIS is the need of the hour for earthquake prediction and disaster management

If you’re a current B.E. Geoinformatics student, get good exposure beyond regular classes and exams; look out for the various opportunities that you can explore. This column might guide you with finding the right internships in India as well as in abroad, that you can pursue during your undergraduate course.

Internships can be taken primarily in the 2nd and the pre-final year of undergraduate, with major internship opportunities available for the pre-final years.

Within India

● Hexamap Solutions

● M S Swaminathan Research Foundation (MSSRF, Tharamani)

● National Centre for Coastal Research (NCCR), National Institute of Ocean Technology (NIOT)

● Red Networks Telecom Pvt Ltd

● IIT Bombay – Center of Studies in Resources Engineering (CSRE)

● Indian Institute of Remote Sensing (IIRS), Dehradun –minimum project duration: 3 months

● IIT Kanpur – Students Undergraduate Research Graduate Excellence (SURGE) summer program

● IIT Roorkee – SPARK summer internship

● IISER Kolkata – Summer Student Research Programme (GI Application-oriented research work, particularly earth sciences)

● Indian Academ y of Sciences – Summer Research Fellowship Programme (SRFP) – for both engineering and theoretical sciences

Internships Abroad

• Globalink Research Internship – MITACS: 12-week research internship with Canadian University facult y member guides

• DAAD, German y

• Lunar and Planetary Institute, Houston, Texas, USA –specificall y for Planetary Remote Sensing

• Nan yang Technological University (NTU), Singapore Summer internship program

• RIPS, University of California Los Angeles (UCLA) – Program, Research in Industrial Projects for Students (RIPS)

• California Institute of Technology – SURF programme (Summer Undergraduate Research Fellowship)

• Charpak Internship Program, France – for duration of 1 to 2 months at a French University/Institution

What’s in store after undergraduate?

Following the undergraduate course, there are broadly two ways to go – placements or higher studies. Getting jobs is further categorized as getting placed in core Geoinformatics industries, or in IT or other field companies The scope of SPATIA is restricted to giving exposure for Geoinformatics, hence focus is on placement opportunities in course-core companies.

PLACEMENT DOORS: - Geoinformatics course holds a lot of job opportunities in the industry, some of them are listed here:

• Environmental Systems Research Institute (ESRI) – core GIS compan y, mapping and anal ytics; HQ in California, USA

• Hexagon, HQ in Stockholm, Sweden

• Hexamap Solutions

• RedLeaf Technologies Pvt Ltd – providing geospatial products and solutions to various sectors

• L&T Mindtree – HQ at Bangalore

• BIRDSCALE, Chennai – particularl y for inspection, airborne LiDAR mapping, customized drone manufacture and software development

• Swiss Re

• Trimble - HQ in Colorado, USA

• kCube, Chennai – application development services, professional training in GIS and remote sensing

• Infomap

HIGHER STUDIES: - Unique courses like Geoinformatics have tremendous scope in research areas, with applications in almost every field of study. With such a vast window of opportunity to excel, pursuing higher studies (Masters and preferably a PhD) is surely an excellent way to go:

Masters in India: Masters in India primarily requires the clearing of entrance exams like GATE, TANCET and other university-specific entrance exams

• M.E. Remote sensing and Geomatics, Anna University –through TANCET exam

Through GATE exam,

• IIT Bombay – CSRE, M.Tech.

• IIT Delhi – Centre for Atmospheric Sciences

• IIT Kanpur – M Tech Geoinformatics

• IIT Roorkee – M.Tech Geomatics Engineering

• IIT ISM Dhanbad – M Tech Geomatics

• IIST Thiruvananthapuram – M Tech in Geoinformatics

• NIT Surathkal – Dept of Water Resources and Ocean Engineering – Remote sensing and G IS

• Delhi Technological University (DTU) – M Tech in Geoinformatics (Dept. of Civil Engineering)

Masters Overseas:

• University of Twente, ITC, Netherlands – Facult y of Geo-information Science and Earth Observation

• Georgia Institute of Technology, Georgia, USA

• Stanford Universit y, USA – Civil and Environmental Engineering, School of Earth, Energy and Environmental Sciences

• Massachusetts Institute of Technology, USA – Dept of Civil and Environmental Engineering

• ETH Zurich, Switzerland

• University of Michigan, USA – Rackham Graduate School – good for RS and GIS along with atmospheric sciences

• University of Toronto, Canada

• University College London – Core GIS

• Ohio State University, USA – specificall y good for pursuing Geodes y

Higher studies in abroad requires a couple of entrance exams, aptitude tests and English proficiency tests to be taken, which differs with each universit y’s guidelines The common exams include: TOEFL and IELTS (For English Proficiency), GRE (General and Subject), assessing one’s logical and anal ytical abilities along with a bit of subject knowledge