List of Courses/ Semester
Course Objective : This course aims at introducing concept, principles and applications of Geographic Information Systems (GIS). Course also aims to develop the skill of using software and other tools of GIS in students.
Learning Outcomes:
The students on the completion of the course will be able to :
1. Explain and communicate the concept of various kind of maps and geospatial data
2. Develop, edit and update geospatial data
3. Create digital maps, apply projections and other characteristics of mapping
4. Integrate various kind of data from various sources and analyse the same using GIS concept and tools
5. Apply the knowledge and skill for various applications
Prerequisite: None
Course Objective : This course provides students foundations of Remote Sensing (RS) theory, RS image processing techniques and applications. Specific objectives of this course are: i) to provide background knowledge and understanding of principles of RS and RS systems; ii) to enhance students’ capacity to interpret images and extract information on the earth surface from multi-resolution imagery at multi-scale level; iii) to acquire skills on basic image processing and classification techniques; iv) to enable critical, spatial and temporal thinking on Remote Sensing for real-world applications.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Critically compare different EO systems taking into account the essence of the observed phenomena.
2. Evaluate different EO data and select the more appropriate under limited observation condition.
3. Carry out effective and accurate geometric and atmospheric corrections to reduce observation distortions.
4. Apply basic procedures of digital image processing for RS image enhancement analysis.
5. Conduct accurate automatic or semi-automatic geo-information extraction from remotely sensed imagery.
6. Carry out independent scientific remote sensing research or professional RS assignments.
Prerequisite: None
Course Objective :
The objective of this course aims at providing students with knowledge and in-depth understanding of techniques in digital image processing for remote sensing data analysis. This course emphasizes on implementation of algorithms as computer programs. The techniques taught in this course have application in several fields dealing with image data.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Explain the image data handling in memory and file system
2. Interpret the C programming source code for image processing
3. Apply the principle of image processing as the automate data processing procedure for remote sensing data analysis, resampling and DEM processing
4. Apply the principle of image processing on huge image files by using High Performance Computing (HPC) and General-purpose computing on Graphics Processing Units (GPGPU) environment
5. Develop new algorithms for image processing and conduct scientific Remote Sensing research
Prerequisite: None
Course Objective : This course aims at providing practical knowledge and in-depth understanding of of the Remote Sensing. Through practical applications and real-world examples, students will be provided with necessary skills to generate and analyze high-level remote sensing products.
Specific objectives are: i) to train students on remote sensing data type and formats, imagery products and their availability; ii) to give insights on processing methods and techniques for handling radiometric and geometric properties of remotely sensed; iii) to give principles and methods of multi-resolutions and multi-spectral data fusion, multitemporal processing and accuracy assessment; iv) to develop data processing automation through batch processing.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Explain and communicate quantitative remote-sensing principles and integrate different tools for remote sensing data analysis.
2. Perform image corrections and enhancements and generate high-level remote sensing products.
3. Manipulate and process RS data using manual and automated techniques
4. Critically compare different type of remote sensing data products and analysis technique and select the more appropriate to solve a real-world problem.
Prerequisite: AT76.03 Remote Sensing
Course Objective: The course conveys the basics of terrestrial and satellite digital photogrammetry. It aims at providing basic photogrammetry concept, procedures and processing task. Insights on products quality and error analysis are also considered and explained with various methods. Basic concepts of terrestrial and aerial laser scanning will be also given.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Comprehend basic concepts of digital photogrammetry (including terrestrial, aerial and satellite photogrammetry)
2. Explain photogrammetric processing principles and methods
3. Generate digital ortho-products (orthophotos, digital elevation models, building, point clouds) from multi-source photogrammetric data and evaluate the results
4. Identify the role of relief displacement, evaluate elevation data products and assess their use for a range of applications
Pre-requisite: None
Course Objective:
This course is designed to provide fundamental knowledge and theories of microwave remote sensing. The fundamentals of electromagnetics, both real aperture and synthetic aperture radar systems will be introduced including physical principles.
Learning Outcomes :
The Students upon successful completion would be able to:
1. Identify the fundamental of interactive of electromagnetic radiation with matter
2. Compare difference type of microwave remote sensing (real aperture and synthetic aperture radar system) and apply the principle of remote sensing measuring the essence of phenomena
3. Apply principle of digital image processing for enhancing and analysis the microwave remote sensing
4. Conduct scientific microwave remote sensing research
Prerequisite: None
Course Objective: The objective of this course aims at providing knowledge and understandings of the RS/GIS and Computer Mapping Technology (CMT). It also provides more in-depth knowledge and skills for applications of the technologies and relevant service innovations.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Explain and communicate fundamentals concepts of cartography, map generalization and map design.
2. Identify and distinguish new mapping technologies such as GNSS, INS, laser range scanning, global earth observation, mobile mapping, UAV, web mapping.
3. Formulate scientific questions about geographical big data analysis.
Pre-requisite: None
Course Objective: This course aims at providing advance knowledge in discrete and continuous spatial data understanding and analysis. Students will also be exposed to advance modeling techniques, exploratory spatial data analysis, interpolation techniques, terrain modeling, and geostatistical analysis.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Analyze the discrete and continuous databases
2. Identify and communicate the mathematical, statistical, logical and cartographic modeling methods
3. Rank and compute weights for decision making for planning and site suitability
4. Analyze patterns, trends and hotspots, and find spatial auto-correlations in different multi-criteria phenomenon.
5. Use the concept of geospatial analysis and modeling tools in GIS software such as ArcGIS, Quantum GIS
6. Develop applications in various areas for Urban planning and management, Disaster Risk Management, Agriculture, Health
Pre-requisite: AT76.01 Geographic Information Systems
Course Objective: This course aims at providing advance knowledge in spatial data understanding, analysis and programming skill in GIS environment. Students will also be exposed to advance geoprocessing and modeling techniques, exploratory geostatistical analysis and spatial data analysis to impart advance knowledge of programming, customization and automation in GIS.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Perform object-oriented programming tasks in GIS using Python;
2. Analyze GIS-model interactions and design procedures for modeling with GIS;
3. Develop their own tools for geospatial analysis;
4. Develop GIS-based models in Python for various applications integrated with ArcGIS;
5. Describe general software engineering concepts and good programming methods and practices; and
6. Critically evaluate different methodologies for developing applications in GIS; x
Pre-requisite: AT76.01 Geographic Information Systems
Course Objective: This course imparts knowledge about Data Modeling for Geospatial Information. It also aims to prepare students for more in-depth training in understanding what model and modeling is, what object orientation and UML is, how to describe UML diagram, and what ISO and OGC standard is.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Identify and communicate concepts of data model and modeling.
2. Understand object orientation and UML, UML diagram.
3. Distinguish and evaluate Spatial and Temporal Schema, Application Schema, Metadata Schema, etc.
4. Develop understanding of international standards such as ISO.
Pre-requisite: None
Course Objective: The objective of this course aims at providing students with knowledge and understanding about Web GIS technology. The client and server architecture of Web GIS will be taught as well.
Learning Outcomes :
It is expected that student will be able to (during and at the end of this course):
1. Classify the Web GIS architecture
2. Design the Web GIS application based-on the data specification, functionalities requirement and client platform
3. Publish vector, raster data and spatial analysis as the standard OGC Web Services and develop Web GIS application
4. Comprehend and apply OGC Web Services for integrated framework
Prerequisite: None
Course Objective: The objective of this course aims at providing students with practical utilization of Free and Open Source Software (FOSS) for data manipulation, management and analysis of remote sensing images and GIS data. Students will be trained to able to use and integrate FOSS to make comprehensive system which provides powerful functionalities at very affordable cost.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Describe the new opportunities for indigenous Geoinformatics software industries using Free and Open Source Software
2. Conduct data manipulation and data management for pre-processing procedure
3. Perform geospatial analysis using Free and Open Source Software
4. Comprehend and integrate various Free and Open Source Software for geospatial analysis
Prerequisite: None
Course Objective: The objective of this course aims at providing basic introduction and concept of spatial information engineering with an insight into both academic knowledge and practical skills at the entry level. It also addresses the basic and history of geospatial information, location-based service, GNSS, space technology and IoT.
Learning Outcomes:
The Students on the completion of this course would be able to:
- Identify and communicate basic concept of spatial information engineering such as monitoring and observation method, data analysis and handling, data interoperability.
- Develop understanding of how to process and analyze spatial data, how to utilize it, and how to combine it with the spatial designs and rules of society.
- Comprehend and integrate various technology in spatial information.
Pre-requisite: None
Course Objective: The objective of this course aims to provide the fundamentals of spatial data processing and analysis, including data pre-processing, exploration of data input, visualization and manipulation, Software customization and development. It also addresses the basis of data processing using spatial databases both in database design, implementation and management.
Learning Outcomes :
The students on the completion of this course would be able to:
1. Use software to conduct basic data processing and analysis on geospatial data.
2. Publish and visualize output/result on geospatial data visualization tools.
3. Identify and communicate concept of big data and data processing for large-scale.
4. Apply data processing techniques to process and analysis spatial trajectory data.
5. Process and analyse data using database system.
Pre-requisite: None
Course Objective: This course aims at providing students with ideas of Geospatial Modeling on environmental issues including sustainable development and ecosystem management from community scale to global, as well as basic practical skills to develop geospatial models for the purpose. Course Objective: This course aims at providing students with ideas of Geospatial Modeling on environmental issues including sustainable development and ecosystem management from community scale to global, as well as basic practical skills to develop geospatial models for the purpose.
Learning Outcomes :
The students on the completion of this course would be able to :
1. Utilize the basic functions of GIS and the fundamental procedures for Remote Sensing data processing to develop geospatial models.
2. Apply geospatial modeling for environmental issues including sustainable development and ecosystem management.
3. Acquire practical skills for GIS operation and Remote Sensing image processing for geospatial modeling on environmental issues.
4. Acquire practical skills to develop geospatial models for environmental issues.
Prerequisite: None
Course Objective: The objectives of this course are: i) to provide background knowledge and understanding of principles of InSAR; iii) to acquire skills on basic InSAR and DInSAR image processing and analysis as well as basic knowledge on main limitations and error sources of these techniques; iv) to enable critical, spatial and temporal thinking on InSAR for real-world applications.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Evaluate critically the principles of INSAR and DInSAR systems
2. Search and download relevant SAR data required for a certain InSAR and DInSAR –based project/purpose.
3. Perform basic signal processing techniques for InSAR and DInSAR imaging using publicly available software packages and SAR data.
4. Visually interpret in a qualitative way InSAR and DInSAR output images and interferograms.
5. Gain insight into the strengths and limitations InSAR and DInSAR systems and
applications.
Prerequisite: None
Course Objective: The objective of this course aims at providing students with knowledge and understanding about Location-Based Services (LBSs) technology. The fundamentals and operation of LBSs will be taught to obtain an understanding of its systems and methods. The key technology of various positioning method will be trained. Additionally, the course will also cover related technologies of Indoor Positioning, Augmented Reality and navigation systems
Learning Outcomes :
The students upon successful completion of this course will be able to:
1. Explain the fundamentals and operation of LBSs system and methods
2. Identify the suitable position method with various constraints and purpose
3. Identify the new opportunities by using the LBSs technology for solving the problems
Prerequisite: None
Course Objective: The objective of this course aims at providing students with knowledge and understanding about Unmanned Aerial Vehicle (UAV) technology. Additionally, students will learn how UAV are utilized in earth observation, agriculture and 3D mapping.
Learning Outcomes :
The students upon successful completion of this course will be able to:
1. Identify and demonstrate principles and operation of UAV, its system components and applications
2. Perform UAV data processing and perform products generation for earth observation and 3D mapping
3. Design the flight plan of UAV observation for specific type of applications.
Prerequisite: None
Course Objective: The objective of this course is to prepare the student for their research at AIT in Geoinformatics and to develop statistical skills. Students will be introduced with research methods and steps in research design relevant to Geoinformatics research. The course will cover scientific reading and writing,
including proposal and thesis writing in AIT. Additionally, the objective is also to introduce statistical methods for analyzing spatial and non-spatial data.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Efficiently read and analyze any scientific document
2. Identify effective ways of writing scientific reports, including journal articles, thesis, research proposals etc.
3. Learn how to present research in an effective way in front of a crowd and deliver the message commendably
4. Describe and apply basic statistical analysis, types and applications
5. Distinguish several statistical tools in remote sensing and GIS analysis and their applicability in practical applications
Prerequisite: None
Course Objective: The aim of this course is to introduce the principles of the Global Navigation Satellite Systems (GNSS), Satellite Positioning, GNSS Signal Structures and to demonstrate its applications to various aspects of location-based services and geospatial sciences.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Understand fundamental theory and applications of radio navigation with the Multi-GNSS.
2. Develop understanding of satellite orbit theory, GNSS signal structure, point positioning with pseudorange, real-time kinematic positioning with carrier phase, dilution of precision and atmospheric effect on GNSS signals.
3. Perform calculation on position, Dilution of precision (DOP) using RTKLIB
Pre-requisite: None
Course Objective: This course provides the principles of spacecraft dynamics and basic control technics of spin-stabilized satellites. It includes fundamental mathematics and dynamics which are necessary to understand the spacecraft’s behavior in space. The objectives of this course are to give a basic working knowledge of vector algebra and matrices as well as the rigid-body dynamics and control theory.
Learning Outcomes:
The students on the completion of the course would be able to:
1. Obtain a basic knowledge of vector algebra and matrices.
2. Critically evaluate and apply principles of spacecraft dynamics and control techniques.
3. Explain the attitude maneuvers of rigid spacecraft.
4. Control the spin-stabilized satellites.
Prerequisite: None
Rationale: This course will focus on new trends, concepts and essential technologies used for disease surveillance, hotspot mapping and healthcare planning. It is based on theory and hands on learning methodlogies. Current and future satellites for environmental observations specifically related to health applications, mapping of disease locations, diseases’ transmission in tropical and sub-tropical regions, ecological and use of environmental/ social/ economic data for predicting disease, freely available tools and techniques for emergency response will be discussed.
Catalog Description: GIS concepts. Disease surveillance, Hotspots, Health databases – standards and creation, Data manipulation and Geoprocessing for disease data analysis. Statistical analysis for health application, Disease trends. Disease risk mapping, Satellite Navigation for trauma Assistance, Risk Mapping.
Prerequisite: AT76.01 or any course related to GIS
Course Objective:
This course introduces the principles lying behind remote sensing of water, concentrating on water quality. Main objective of the course is to gain a basic and practical understanding, and linkages of remote sensing concepts with and coastal, estuarine, and inland water bodies. The major focus remains on practical knowledge over theories to learn how remote sensing tools and methods work. A variety of tools and techniques for real applications will be introduced through explained tutorials, including image interpretation, image enhancement, atmospheric corrections, band ratio, extraction of optically active constituents, and time series analysis. Participants will gain experience to download, handle and analyse data from variety of earth observation sources.
Learning Outcomes:
The students on the completion of this course would be able to:
1. Understanding of the interactions of radiation with the earth’s water surface and atmosphere.
2. Understanding and applying best practices for advanced atmospheric correction and extraction of optical properties of water.
3. Understanding and basic interpretation skills, the strengths and limitations of remotes sensing-derived water quality and quantity products.
Prerequisite: None but the AT7603 Remote Sensing is preferable
