GIS&T Body of Knowledge //rusa.maharashtra.gov.in/mediarusa/pdf/2019-07-31... · Web view2019/07/31...

R A S H T R I Y A U C H C H A T A R S H I K S H A B H I Y A N (R U S A)

COURSE CONTENT

FOR UNIVERSITIES AND ALL AFFILIATED COLLEGES

R A S H T R I YA U C H C H A T A R S H I K S HA AB H I YAN (R U S A)

State Project Directorate, RUSA, Office AddressUnit no.2, 18th Floor, Centre One, World Trade

Centre, Colaba Mumbai 400005

1

Syllabus for Core Course of Geo-Spatial Technologies

Programmes: UndergraduateSemester : IVCredits: 3 creditsTotal Hours: 60Mode: Theory: 3 hrs, Lab:2 hrsCourse Prerequisites: None

Course Outcome: 1. Describe the common terms and definitions of GIS

2. Discuss different GIS data and Data acquisition Technologies

3. Get knowledge about different GIS trends and technologies.

4. Discuss the relevant spatial computing systems and techniques for working with geospatial

data. Apply GIS concepts to solve real world problems.

5. Critically evaluate spatial computing software and systems and determine whether they have

been applied in appropriate ways

Methodology: Class Room Teaching + Lab Hands on, online resources

Recommended:

Set up a learning environment like moodle (for learning resources, uploading assignments, on-

line collaborations and online evaluations

Peer evaluation, presentations, Collaborative learning

Exams and make-up exams policy : flexible

Attendance standards : flexible

2

Course Outline: Geo-Spatial Technologies

1Introduction to GIS : Definitions, Evolution, Components and Objectives

2Geo-Spatial data : Types of geographic data (spatial data with attributes and non-spatial

data), levels of measurements, Concepts of space and time, layers coverage, Spatial data

models, Representation of geographic features in vector, raster data models, Concept of

vertices , point, lines, polygons, and topology, Computer representation for storing spatial

data

3Data acquisition : GPS , History, types, navigation systems and applications

4GPS Trends & Technology: Brief introduction to,Web Based GIS, Enterprise GIS, Mobile

GIS,3-D Visualization and Fly through, Open GIS.

5Application of GIS (Examples) : Watershed Studies, Flood Studies, Ground water Studies,

Health and nutrition geography , Utility Studies, Security and Defense Studies, Urban ( solid

waste management, livability) and infrastructure Studies.

Modalities of assessment

Continuous assessment: Exams, Quizzes, Assignments and Mini projects

Mid semester examination: Quizzes, Assignments and Mini projects

End semester assessment : Project and examination

Reading List:

GIS&T Body of Knowledge https://gistbok.ucgis.org/

Introduction to GIS : http://www.gise.cse.iitb.ac.in/wiki/images/3/3a/

Introduction_to_map_GIS.pdf

Python Geospatial Development - Third Edition by Erik Westra ,May 2016

http://link.springer.com/book/10.1007/978-3-319-25691-7

Google's Earth Engine

Text Books:

1. Longley, P. A., Goodchild, M. F., Maguire, D. J., Rhind, D. W. (2002): Geographical Informa-

tion Systems and Science, John Wiley & Sons, Chichester

2. Lo, C. P., Yeung, A. W. (2002): Concepts Techniques of Geographical Information Systems,

Prentice-Hall of India, New Delhi

3. Chang, K. T. (2008): Introduction to Geographic Information Systems, Avenue of the Americas,

McGraw-Hill, New York

Reference books:

3

http://earthengine.google.com/


http://www.gise.cse.iitb.ac.in/wiki/images/3/3a/Introduction_to_map_GIS.pdf


1. Korte, G. B. (2001): The GIS Book, Onward Press, Bangalore

2. Demers, M. N. (2000): Fundamentals of Geographic Information Systems, John Wiley and

Sons, New Delhi

3. Burrough, P. A. and McDonnell, R. A. (2000): Principles of Geographical Information Systems,

Oxford University Press, New York

4. Heywood, I., Cornelisus, S., Carver, S. (2011): An Introduction to Geographical Information

Systems, Pearson Education, New Delhi

5. Ahmed, E. L. Rabbany (2002): Introduction to Global Positioning Systems, Artech House, Bo-

ston

6. Sarda, N.L., Acharya, P.S and Sen, S (2019) Geospatial Infrastructure, Applications and Tech-

nologies: India Case Studies, Springer Singapore

4

Recommended Laboratory Assignments on Geo-Spatial Technologies

Objectives:

1. To understand the technology tools used for Geospatial Technologies

2. Provide the students with fundamental concepts and introduce some current technologies of

Geographic Information Systems

3. To offer learning situations and problem solving opportunities from real life including mobile

apps( use of and tweaking/customizing, not full-fledged development) , desktop GIS and Web

GIS.

Methodology: Teaching + Experimentation in Lab Sessions

Recommended:

Domain focus should be incorporated. For example, Insurance domain, Water planning,

Town-planning.


Incentive for uploading projects online

Experiments/ Practical List

1 Installation of QGIS

2 lab includes to perform following tasks:

Task 1 – Learn to work with QGIS Browser.

Task 2 – Become familiar with geospatial data models.

Task 3 – Viewing geospatial data in QGIS Desktop.

3 lab includes to perform following tasks:

Task 1 – Add data, organize map layers and set map projections.

Task 2 – Style data layers.

Task 3 – Compose map deliverable.

4 Creating Dynamic Maps in QGIS Using Python

5 Accessing the Map Canvas, Changing Map Units, and Iterating over Layers

6 lab to perform the following tasks:

Task 1 – Data Preparation

Task 2 – Querying and Extracting Subsets of Data

Task 3 – Buffering and Clipping Data

Task 4 – Preparing a Map

7 Understanding Remote Sensing and Analysis using QGIS

5

Lab Reference books/Software manual:

1. Kurt Menke, Richard Smith Jr., Luigi Pirelli and John van Hoesen (2015) Mastering QGIS

Pakt Publishing.

6

Syllabus for Core Course of Spatial and Graph Databases Undergraduate Programmes: Under-

graduate

Semester : V

Credits: 3 credits

Total Hours: 60

Mode: Theory: 3 hrs, Lab:2 hrs

Course Prerequisites : Geo Spatial technologies

Course Outcome:1. Describe the common terms and definitions of spatial data & databases 2. Discuss different data models3. Get knowledge about spatial query languages.

4. Apply spatial databases concepts to solve real world problems.

Methodology: Class Room Teaching + Lab Hands on

Recommended:






7

Course Outline: Spatial Databases

1Introduction to spatial databases : Requirement of spatial databases , DBMS

Support for Geospatial Data, Users in SDBMS, Example of SDBMS

2Spatial Concepts and Data Models : Geographic Space Modelling, Spatial Data

Formats and Exchange Standards,Three step database design, Extending ER model

with spatial constraints

3Spatial Query Language : Standard database query languages, Extending SQL for

spatial data, Object relational SQL

4Spatial Storage and Indexing : Brief introduction to spatial data storage,

Definition of spatial indexing, Different techniques for indexing spatial data

5Query Processing and Optimization : Introduction to spatial query processing,

Evaluation of spatial operations, Query Optimization techniques

6Trends in Spatial Databases : Database support for field entities, Content based

retrieval, Introduction to spatial data-warehouses, System Integration, Big

geospatial data platforms





Reading List:

A Gentle Introduction to GIS https://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/

data_capture.html

https://www.e-education.psu.edu/geog585/syllabus#top

https://www.youtube.com/watch?v=EUUWUUDjU4o postgis

Books:

1. Spatial Databases: A Tour 1st Edition, Shashi Shekhar, Sanjay Chawla

2. Spatial Databases: with Application to GIS, Rigaux et al, Morgan Kaufmanm (or the other

popular book in the field: Spatial Databases: A Tour, Shekhar and Chawla, Prentice-Hall);

Reference books:

8

https://www.youtube.com/watch?v=EUUWUUDjU4o

https://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/data_capture.html


Recommended Laboratory Assignments on Spatial and Graph Databases

Objectives:

1. To understand the database concepts and tools used for Geospatial Technologies

2. To understand design and modelling the Spatial problems

3. To understand and execute complex queries on spatial databases.


Recommended:


Town-planning.



Sr.

No


1 A. Installation of Postgres, PostGIS and QGIS, pgAdmin

B. Ice cream entrepreneurs Jen have opened business and now need a database to track or-

ders. When taking an order they record the customer's name, the details of the order such

as the flavors and quantities of ice cream needed, the date the order is needed and the de-

livery address. Their database needs to help them answer two important questions:

1. Which orders are due to be shipped within the next two days?

2. Which flavors must be produced in greater quantities?

Implement a Database Design for above scenario.

2 Introduction to Postgres's graphical interface: pgAdmin

A. Create a new schema,

B. Load data from a shapefile

C. Create a new table

D. Load data using the COPY command

E. Write queries in pgAdmin

3 Query-Writing Assignment

4 Spatial Select Queries

5 PostGIS Geometry Types Queries.

A. Create a new empty spatial table

9

Sr.

No


B. Add rows to the spatial table

C. Create and populate a table of linestrings

D. Create and populate a table of polygons

E. 3- and 4-dimensional geometries

F. Multipart geometries

G. Mixing geometries

6 Add PostGIS data to QGIS

Quantum GIS (QGIS, pronounced kyü'-jis) is a free and open-source desktop GIS package

view the tables we created and populated in the previous Assignments

7 PostgreSQL provides several index types: B-tree, R-tree, Hash, and GiST. Each index type

uses a different algorithm that is best suited to different types of queries. Create a

database execute all index type queries and measure the performance.

8 Write queries on following using following Spatial Relationship Functions : ST_Contains(),

ST_Within(), ST_Covers(), ST_CoveredBy(), ST_Intersects(), ST_Disjoint(),

ST_Overlaps(), ST_Touches(), ST_Dwithin(), ST_DFullyWithin()

9 Write queries on following using following Spatial Measurement Functions : ST_Area(),

ST_Centroid(), ST_Distance(), ST_Distance_Spheroid() and ST_Distance_Sphere(),

ST_Length(), ST_Length_Spheroid(), ST_Length3D(), ST_Length3D_Spheroid(),

ST_Perimeter(), ST_Perimeter3D()


1. Regina O. Obe and Leo S. Hsu (2015): PostGIS in Action, Manning Publications


Pakt Publishing.

10

Syllabus for Core Course of Introduction to Geospatial Data Analytics

Programmes: Undergraduate

Semester : VI

Credits: 3 credits

Total Hours: 60

Mode: Theory: 3 hrs, Lab:2 hrs

Course Prerequisites : Geospatial Technologies

Course Outcome:

The student should be able to

1. Understand the spatial data types

2. Understand principles of visual and statistical analysis with geospatial data

3. To comprehend the effective reporting of geospatial analysis


Recommended:






Course Outline:

1Introduction: Data & Spatial Data Analysis, Types of Spatial Data, The Spatial

Data Matrix, Spatial Autocorrelation, The Tyranny of Spatial Data.

2Map based analytics: Visualizing spatial processes in maps, Developing readable

maps and interactive analysis. Fundamental data analytics principles.

Communicating with maps.

11

3Methods Spatial Interaction Data: The General Spatial Interaction Model,

Maximum Likelihood estimation of the Poisson Spatial Interaction Model,

Generalization of Poisson Model of Spatial Interaction

4Models for Spatial Interaction Data: Visualizing & Exploring Spatial Interaction

data, The General Spatial Interaction Model, Functional Specifications & the

method of Ordinary least Square Regression.

5Spatial Interaction Models & Spatial Dependence: The Independence Spatial

Interaction Model in Matrix Notation, Econometric Extension to the Independence

Spatial Interaction Model, Spatial Filtering Versions of Spatial Interaction Models

Text Books:

1. "Geospatial Data and Analysis" by Bill Day, Jon Bruner, Aurelia Moser Publisher: O'Reilly Me-

dia, Inc. ISBN: 9781491984314

2. Menno-Jan Kraak, F.J. Ormeling (2013) Cartography: Visualization of Spatial Data, Routledge

Publishing.

3. Michael J de Smith, Michael F Goodchild, Paul A Longley (2007) Geospatial Analysis: A Com-

prehensive Guide to Principles, Techniques and Software Tools, Troubador Publishing.

4. Michael Dorman (2014) Learning R for Geospatial Analysis, Packt Publishing.





12

Recommended Laboratory Assignments on Geospatial Data Analytics

Objectives :

To understand the geospatial data tools

To understand the analytical tools

Ability use analytic tools for analysis

Ability to visualise and interpret the analysis


Recommended:


Town-planning.




1 Creating and manipulating spatial data using R

2 Logistic Regression implementation in R

3 Multinomial Logistic Regression with Categorical Response Variables at 3 Levels

using R

4 Unsupervised Classification using QGIS and Grass GIS

5 Supervised Classification using QGIS and Grass GIS

6 Interpolating Point Data using QGIS

7 Nearest Neighbor Analysis using QGIS



Pakt Publishing.

2. Guy Lansley and James Cheshire (2016) An Introduction to Spatial Data Analysis in R avail-

able on http://www.spatialanalysisonline.com

13

Syllabus for Core Course of WebGIS, Geospatial Programming and Visualization

Semester V

Credits: 3 credits

Total Hours: 60

Mode: Theory Class+ Lab

Theory: 3 hrs, Lab:2 hrs

Prerequisites: Geo-Spatial Technologies

Course Outcome:

1. To understand programming tools in geospatial applications

2. To understand spatial databases and representations on web

3. Able to make programming in WebGIS

4. Able to implement geospatial applications

Methodology: Class Room Teachingc + Lab Hands on

Recommended:






Course Outline:

1Building the web: HTML, CSS, and Javascript : Learn how to build the

structure and content of a web page with HTML, Apply styling rules with CSS, and

automate and script the page with javascript/jquery, Learn javascript basics: strings,

numbers, arrays, objects,, functions, loops, etc.

14

2Mapping with Leaflet.js ( or openlayers.js) : Use the leaflet.js library to add a

map element to a website, Add basemaps, markers, and controls to your map,

Explore advanced techniques and features of leaflet, including choropleth

mapping/dynamic styling, leaflet plugins, events, etc.

3Spatial Data for the Web : Understand how data is stored, moved and organized

for integration into a web map. e.g geoserver , Explore data sources and techniques

for transforming/preparing data for use in web maps., Add vector data to a leaflet.js

map . Tiling of data. Styles of spatial features.

4GIS data access and manipulation with Python: Data storage and retrieval in

QGIS, Reading vector attribute data, Accessing data fields, Reading through

records, Retrieving records using an attribute query , Retrieving records using a

spatial query, Writing vector attribute data, Updating existing records, Inserting

new records, Working with rasters

5Web Application Development for Geospatial: Building a Web Map, Turning

Your Map into an App, Embedding a Map, Configuring an App Based on a

Template, Creating an App with the Web AppBuilder, use of geonode as a stack

Text Books:

1. Introduction to web programming for GIS applications by Michael Miller

2. Web mapping by Prof. Dr. Martin Breunig

3. Web Mapping and Geospatial Web Services: An Introduction by Emmanuel Stefanakis

References :

1. www.geonode.org

2. www.geoserver.org





Practical : Recommended Laboratory Assessment

1 Write a Page Using XHTML and CSS

2 UCreate Your First 2D Map of your hometown and Post the map containing

your hometown to your e-portfolio use openlayers or leaflet

15

http://www.geoserver.org/

http://www.geonode.org/

https://www.e-education.psu.edu/geog485/node/64

https://www.e-education.psu.edu/geog485/node/64

3Creating An Interactive Map With Leaflet and OpenStreetMap

4 Update the web page which is created in assignment no2 to include choropleth

mapping/dynamic styling

5 Find which cities have at least two park within their boundaries.Mark the

"HasTwoParkAndRides" field as "True" for all cities that have at least two park

and calculate the percentage of cities that have at least two park within their

boundaries and print this for the user using Python

6 You have been provided two things:

A text file StatePoints.txt containing the coordinates of a state

boundary.

An empty polygon shapefile that uses a geographic coordinate system.

write a Python script that reads the text file and creates a state boundary

polygon out of the coordinates.

7 Turn Map into an App using geonode

16

Syllabus for Electives Course of Geo-Informatics and Spatial Computing Programmes: Undergraduate Semester : V/VI, ElectiveCredits: 3 creditsTotal Hours: 60Mode: Theory: 3 hrs, Lab:2 hrsCourse Prerequisites: None Course Outcome:

1. Describe the theoretical foundations of geospatial data and its various representations

2. Select and use the appropriate spatial computing technologies and systems to solve any of a

variety of real-world problems

3. Build integrated applications that combine geographic data and applications for processing

that data

4. Understand, create, and apply semantic descriptions of geographic data which can then be

used for searching, integrating, and sharing geographic knowledge

5. Discuss the relevant spatial computing systems and techniques for working with geospatial

data

6. Apply relevant spatial computing techniques to solve spatial problems

7. Critically evaluate spatial computing software and systems and determine whether they have

been applied in appropriate ways

Methodology: Class Room Teachingc + Lab Hands on

Recommended:






17

Course Outline: Geo-Informatics and Spatial Computing

1Introduction to basics of spatial data, representations of spatial data, structured spatial data,

unstructured spatial data, streaming data, coordinate systems, datum, projections, etc.

Introduction to real-world spatial computing problems and challenges in using traditional GI

systems

2Structured Spatial Data: Introduction to capabilities of spatial systems that handle large

spatial datasets Online Spatial Data: online GIS software and datasets, with a focus on

Google Maps, Bing Maps, and Google Earth

3Machine-Understandable Spatial Data: Introduction to methods and applications for

representing and reasoning about geospatial data using the infrastructure of the Semantic

Web, Introduction to research and techniques for creating and using geospatial linked data

4Unstructured Spatial Data: Introduction to new methods and applications for linking

addresses to locations, Introduction to methods and applications for linking textual

information to geographic locations

5Advanced Spatial Computing: Introduction to advanced techniques for handling spatial data,

including spatial data mining, reasoning, and streaming





Reading List:


data_capture.html

Text Books:

1. Clarke K C (2011) Getting Started with Geographic Information Systems (Fifth Edition). Up-

per Saddle Creek, NJ: Prentice Hall

2. Drive your research with Open Source GIS https://www.osgeo.org/initiatives/geo-for-

all/drive-research-open-source-gis/

18

https://www.osgeo.org/initiatives/geo-for-all/drive-research-open-source-gis/

https://www.osgeo.org/initiatives/geo-for-all/drive-research-open-source-gis/



Practical's : Recommended Laboratory Assignment

Objectives :

Given the fact that students of MA (Geography) and MSc (Geography) have rich knowledge

of geography, but

To understand the technology tools used for Geospatial Technologies

Provide the students with fundamental concepts and introduce some current technologies of

Geographic Information Systems (GIS)

To offer learning situations and problem solving opportunities from real life including mobile

apps( use of and tweaking/customizing, not full-fledged development) , desktop GIS and Web

GIS.


Recommended:

Domain focus should be incorporated. For example, Insurance domain, Water planning, Solid

Waste Management, Town-planning ( DP).



Exp Lab/Experiment

1 Registering and using Google earth engine resources

2 Introduction to Google earth engine editor

3 Writing a simple program in google earth engine using Javascript

4 Introduction to linking addresses to locations using google earth engine

5 Simple classification of data using google earth engine

19

Syllabus for Electives on Course in Geospatial Big data analytics and cloud computing

Program : Undergraduate

Semester VII

Credits: 3 credits

Total Hours: 60




Course Outcome:

1. To understand big data concepts

2. To understand cloud concepts

3. To able to understand geospatial cloud applications deployment

4. To able to perform geospatial analysis methodologies

Course Outcome:

The main objectives of this course are:

1. To train the students with geospatial technologies (preferably open source softwares, like Geonode,

geoserver, Geospark, HIVE, Spatial Hadoop) through hands-on experiences in solving real-life or

nearly real-life problems in above sectors.

2. To analyse geospatial data using open source platforms with large size.

3. To enable the converging global trends in geo-awareness, geo-enablement, geo-technologies,

citizen science, and storytelling towards enabling societal dialogue.

4. To describe the common terms and definitions of GIS, Discuss different GIS data acquisition

Technologies, and Get knowledge about different GIS trends and technologies.

5. Apply GIS concepts to solve real world problems.


Recommended:



20




Course Outline:

1 Introduction to Geographic Information and Big Data: Introduction to GIS as

big data ,Characteristics of Geospatial Data as big data, Different types of geospa-

tial big data

2 Parallel Computation of Algorithm on GPU with large volume of spatial Data,

MMDBM Algorithm, Distributed File Systems and Computations

3 Big Data Scientific Workflows in the Cloud Challenges and Future Prospects

4 Survey of geospatial big data platform: Introduction to various big data

platforms, Spatial Hadoop, Geospark, Geomessa, Hive spatial, geonode,

5 Geospatial Big Data, Analytics : Challenges, Applications and Potential

Text Books:

1. Cloud Computing for Geospatial Big Data Analytics, Editors: Das, H., Barik, R.K., Dubey,

H., Roy, D.S. (Eds.), Springer

2. Jiang Zhe and Shashi Shekhar (2017) Spatial Big Data Science Classification Techniques for

Earth Observation Imagery. Springer

Reference books:

1. Chris Eaton, Dirk Deroos, Tom Deutsch et al., “Understanding Big Data”, McGrawHIll, 2012.

2. Eric Siegel, Thomas H. Davenport, “Predictive Analytics: The Power to Predict Who Will

Buy", Bye, Lie, or Die”, Wiley, 2013.

3. http://cran.r-project.org/doc/manuals/R-intro.html





21

Recommended Laboratory Assignments on Geospatial Big data analytics and cloud computing

Objectives :

1. To be able to do understand cloud services

2. To be able to operate cloud applications

3. To be able to operate geospatial cloud applications

4. To be able to perform analytics on geospatial datasets


Recommended:


Town-planning.



Recommended Laboratory Assessment

1 To install and configure spatial Hadoop on Linux

2 To execute Gzip compression algorithms on spatial Hadoop

3 To implement R index algorithms on spatial hadoop on geospatial data

4 To implement KNN on spatial Hadoop

5 To implement range queries on spatial Hadoop

6 To install and configure Geospark on Linux

7 To execute Gzip compression algorithms on Geospark

8 To implement R index algorithms on Geospark on geospatial data

9 To implement KNN on Geospark

10 To implement range queries on Geospark


1. Jiang Zhe and Shashi Shekhar (2017) Spatial Big Data Science Classification Techniques for

Earth Observation Imagery. Springer

22

Syllabus for Electives Course in Advance course on geospatial technologies.

Program : Postgraduate

Semester II

Credits: 4 credits

Total Hours: 80




Course Objectives

The main objectives of this course are:

● To create human resource with proven expertise in geospatial technologies who are able to act

as enablers of the technology as well as design solutions employing spatial thinking

● Using case based studies and hands on experience, create the capacity to design and

implement systems that harness the evolving potential of geospatial data and applications.

● Through on the job learning with industry and public service organisations, provide students

to real-world experience, thereby building confidence and ensuring necessary exposure for

students to transition into practitioners


Unit Topics & Sub Topics Hrs

1 Geospatial Applications and components of GIS

Location centric workflows, Applications of geospatial technologies, components of

GIS, modern GIS, GIS as a part of mainstream IT.

10

2 Spatial Data, Databases and Programming

Introduction to spatial data, need for spatial databases, creating and using spatial

data, introduction to scripting. Automating geospatial processes.

SQL code, Python Scripting

14

23

3 Geo-visualization, thematic mapping and scripting

Creating spatial displays. Maps as extended graphs, visual analytics through maps,

introduction to digital cartography.

R, R packages/Spatial Analyst

14

4 Spatial statistics, analytics for spatial data science

Introductory spatial statistics and its applications, GIS and other spatial data for data

science. Spatial autocorrelation, variation and interpolation. Spatial inference

Cartographic reports, mapmaking (digitizing, raster-vec), neogeogrphy

12

5 Web -GIS and Mobile GIS

(spatial) Data sharing on the web, standard map interfaces on the web, crowd

mobile-gis and its applications, trade-offs in relation to mobile and web mapping.

Geonode, R

14

Text books;

1. Introduction to web programming for GIS applications by Michael Miller

2. Web mapping by Prof. Dr. Martin Breunig

24

Lab Work/ Experiments

Sr. No Lab/Experiment Hrs

1Geospatial Applications and components of GIS, OGC standards, Open Source

GIS

20

2*Data Acquisition

20

4 Spatial Data, Databases and Programming 30

5 *Geovisualization, thematic mapping and scripting 20

6 Spatial statistics, analytics for spatial data science 20

7 *System integration, geospatial project lifecycle, project planning 10

Web -GIS and Mobile GIS 15

Spatial Mini Project 45

25

References / Further Reading List :


data_capture.html

UCGIS Body of Knowledge

o Old:http://www.aag.org/galleries/publications-files/GIST_Body_of_knowledge.pdf

o New : http://gistbok.ucgis.org/

Tutorials online : https://goo.gl/gPrB9T ( some documents and some links)

Introduction to GIS : http://www.gise.cse.iitb.ac.in/wiki/images/3/3a/

Introduction_to_map_GIS.pdf

Python Geospatial Development - Third Edition by Erik Westra ,May 2016


https://www.e-education.psu.edu/geog585/syllabus#top

https://www.youtube.com/watch?v=EUUWUUDjU4o postgis

https://www.geos.ed.ac.uk/~gisteac/gis_book_abridged/

https://www.youtube.com/watch?v=08LS7XZWzPE web mapping on Windows

Industry, Software :

Next-Generation Google Maps : https://tinyurl.com/bbhvdk o

https://viewer.nationalmap.gov/launch/

ISRO’s GIS : http://bhuvan.nrsc.gov.in/map/bhuvan/bhuvan2d.php

Opensource framework for GIS : www.geoshape.org

26

http://www.geoshape.org/

http://bhuvan.nrsc.gov.in/map/bhuvan/bhuvan2d.php

https://viewer.nationalmap.gov/launch/

https://tinyurl.com/bbhvdko

https://www.youtube.com/watch?v=08LS7XZWzPE

https://www.youtube.com/watch?v=EUUWUUDjU4o




https://goo.gl/gPrB9T

http://gistbok.ucgis.org/

http://www.aag.org/galleries/publications-files/GIST_Body_of_knowledge.pdf



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