GEOG470

Spatial Data Algorithms

Prerequisite: GEOG276 or permission of instructor. Jointly offered with: GEOG770. Credit only granted for: CMSC498Q, CMSC788I, GEOG470, GEOG498I, GEOG770, or GEOG788I. Formerly: GEOG498I. Geometric primitives and algorithms for discrete and continuous spatial data processing. Point data representation and analysis: spatial data structures, neighbor finding and range queries, clustering algorithms. Terrain modeling: grids and TINs, algorithms and data structures for building and querying TINs, gridding and interpolation. Terrain analysis: segmentation through watershed computation, algorithms for visibility computation. Applications to LiDAR data processing and analysis for forest management, urban modeling, and coastal data mapping.

Spring 2026

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Spring 2025

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Past Semesters

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During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.05 between 78 students*

GEOG470 Grade Distribution+-05101520253035404550556065% of studentsABCDFWother
A-: 24.36%
A: 24.36%
A+: 11.54%
B-: 3.85%
B: 12.82%
C-: 6.41%
C: 5.13%
D-: 1.28%
F: 3.85%
W: 6.41%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.