Geomatics Engineering (GE)

Go through the latest GATE 2022 syllabus for Geomatics Engineering here. All sections and topics of the paper are covered in detail.

Candidates appearing for the Graduate Aptitude Test in Engineering (GATE) 2022 Exam with  Geomatics Engineering (Code: GE) as their subject paper can refer to the detailed syllabus provided below. Geomatics Engineering is one of the 29 optional papers in the exam. The syllabus is divided into two parts  – Part A and Part B (Sections 1 and 2).

PART A: Common

Engineering Mathematics – Surveying measurements, Accuracy, Precision, Most probable value,

Errors and their adjustments, Regression analysis, Correlation coefficient, Least square adjustment,

Statistical significant value, Chi square test.

Remote Sensing – Basic concept, Electromagnetic spectrum, Spectral signature, Resolutions-

Spectral. Spatial, Temporal and Radiometric, Platforms and Sensors, Remote Sensing Data

Products – PAN, Multispectral, Microwave, Thermal, Hyperspectral, Visual and digital interpretation

methods

GNSS – Principle used, Components of GNSS, Data collection methods, DGPS, Errors in

observations and corrections.

GIS – Introduction, Data Sources, Data Models and Data Structures, Algorithms, DBMS, Creation of

Databases (spatial and non-spatial), Spatial analysis – Interpolation, Buffer, Overlay, Terrain

Modeling and Network analysis.

PART B: Section I

Maps – Importance of maps to engineering projects, Types of maps, Scales and uses, Plotting

accuracy, Map sheet numbering, Coordinate systems- Cartesian and geographical, map projections,

map datum – MSL, Geoid, spheroid, WGS-84.

Land Surveying – Various Levels, Levelling methods, Compass, Theodolite and Total Station and

their uses, Tachometer, Trigonometric levelling, Traversing, Triangulation and Trilateration.

Aerial Photogrammetry – Types of photographs, Flying height and scale, Relief (height)

displacement, Stereoscopy, 3-D Model, Height determination using Parallax Bar, Digital Elevation

Model (DEM), Slope.PART B: Section II

Data Quantization and Processing – Sampling and quantization theory, Principle of Linear System,

Convolution, Continuous and Discrete Fourier Transform.

Digital Image Processing – Digital image characteristics: image histogram and scattergram and

their significance, Variance-Covariance matrix, Correlation matrix and their significance.

Radiometric and Geometric Corrections – Registration and Resampling techniques.

Image Enhancement – Contrast Enhancement: Linear and Non-linear methods; Spatial Enhancement: Noise and Spatial filters

Image Transformation – Principal Component Analysis (PCA), Discriminant Analysis, Color

transformations (RGB – IHS, CMYK), Indices (Ratios, NDVI, NDWI).

Image Segmentation and Classification – Simple techniques.