Fall 2026

Remote Sensing Digital Image Processing

CIVENGR/ENVIRST/LANDARC 556 teaches techniques for the enhancement, quantification, and processing of remote sensing imagery from various sensors.

offering recorded3 credits
Recorded instructors · Fall 2026 Mutlu Ozdogan

Summary

1 / 4

Recent recorded grades — Fall 2023: 3.97 GPA, 100.0% A/AB (n=17 letter grades); Fall 2024: 3.95 GPA, 94.7% A/AB (n=19 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=14 letter grades).

Grade history

average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

LAND ARC/​ENVIR ST/​G L E/​GEOG/​GEOSCI 371, graduate/professional standing, or member of Engineering Guest Students (or FW ECOL 371 prior to Summer 2026)

CIVENGR/ENVIRST/LANDARC 556

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Fall 2026

Recent recorded grades — Fall 2023: 3.97 GPA, 100.0% A/AB (n=17 letter grades); Fall 2024: 3.95 GPA, 94.7% A/AB (n=19 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=14 letter grades).

Historical instructors & teaching patterns

MUTLU OZDOGAN is recorded teaching in Fall 2008, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 200
LAB 301Classroom Instruction0 / 200
LEC 001Classroom Instruction17 / 200
LAB 301Classroom Instruction17 / 200
LEC 001Classroom Instruction0 / 200
LAB 301Classroom Instruction0 / 200

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records

Student experience

the class

Recent recorded grades — Fall 2023: 3.97 GPA, 100.0% A/AB (n=17 letter grades); Fall 2024: 3.95 GPA, 94.7% A/AB (n=19 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=14 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Applications in agriculture, forestry, geology, soils, water quality, and urban planning.

Skills

  • Enhancement and quantification of remote sensing imagery.
  • Processing and analyzing data from airborne and satellite sensors.
  • Quantitative analysis of data from photography, electro-optical scanners, satellite systems, radar, and passive microwave systems.

Grades

Latest available · Fall 2025— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2025

More grade details Grade mix, volume & source data

Not enough comparable courses for Fall 2026 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Selected offering source records
CIVENGR/ENVIRST/LANDARC 556 · Fall 2026

Remote Sensing Digital Image Processing

Recorded 2026-09-07
CIVENGR/ENVIRST/LANDARC 556 · Fall 2026

Remote Sensing Digital Image Processing

Recorded 2026-09-07
CIVENGR/ENVIRST/LANDARC 556 · Fall 2026

Remote Sensing Digital Image Processing

Recorded 2026-09-07
Raw records
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    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:240:007356",
    "course_id": "CIVENGR/ENVIRST/LANDARC 556",
    "course_uid": "course_eb3e68351d835c43865c6150",
    "term_id": "1272",
    "source_course_id": "007356",
    "source_subject_id": "240",
    "title": "Remote Sensing Digital Image Processing",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Every Other Spring"
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:360:007356",
    "course_id": "CIVENGR/ENVIRST/LANDARC 556",
    "course_uid": "course_eb3e68351d835c43865c6150",
    "term_id": "1272",
    "source_course_id": "007356",
    "source_subject_id": "360",
    "title": "Remote Sensing Digital Image Processing",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Every Other Spring"
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:520:007356",
    "course_id": "CIVENGR/ENVIRST/LANDARC 556",
    "course_uid": "course_eb3e68351d835c43865c6150",
    "term_id": "1272",
    "source_course_id": "007356",
    "source_subject_id": "520",
    "title": "Remote Sensing Digital Image Processing",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Every Other Spring"
  }
]
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "1cafe2024df97d13872aafd33949dae12c6fe158fb22fb30d707f28f6dce4aec",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}