# ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371: Introduction to Environmental Remote Sensing | UW–Madison [View on UW Courses](https://uwcourses.com/courses/ENVIRST_GEOG_GEOSCI_GLE_LANDARC_371) ## Dataset ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ### repository twangodev/uwcourses ### schema version 6 ### importer version 7 ### projection id 52a78527ff09011d88cb04c7d43867d9fbfec2930bf1dd2ec359ebd2844e0b07 ### observed at 2026-09-07T15:55:43.033547+00:00 ### built at 2026-09-10T19:50:42.743001+00:00 ### courses 8951 ### current instructors 5754 ### limited false ### terms * 1272 * 1264 * 1262 * 1254 * 1252 * 1244 * 1242 * 1234 * 1232 * 1224 * 1222 * 1212 * 1204 * 1202 * 1194 * 1192 * 1184 * 1182 * 1174 * 1172 * 1164 * 1162 * 1154 * 1152 * 1144 * 1142 * 1134 * 1132 * 1124 * 1122 * 1114 * 1112 * 1104 * 1102 * 1094 * 1092 * 1084 * 1082 * 1074 * 1072 ### term 1272 ### departments | subject | count | | --------- | ----- | | AAE | 90 | | ABT | 20 | | ACCTIS | 36 | | ACTSCI | 14 | | AFAERO | 10 | | AFRICAN | 87 | | AFROAMER | 71 | | AGROECOL | 21 | | AMERIND | 53 | | ANAT\&PHY | 7 | | ANATOMY | 2 | | ANESTHES | 8 | | ANSCI | 57 | | ANTHRO | 95 | | ART | 125 | | ARTED | 10 | | ARTHIST | 121 | | ASIALANG | 129 | | ASIAN | 109 | | ASIANAM | 28 | | ASTRON | 38 | | ATMOCN | 69 | | BIOCHEM | 51 | | BIOCORE | 10 | | BIOLOGY | 14 | | BIOMDSCI | 18 | | BME | 66 | | BMI | 41 | | BMOLCHEM | 10 | | BOTANY | 69 | | BSE | 44 | | C\&ESOC | 73 | | CBE | 48 | | CHEM | 101 | | CHICLA | 52 | | CIVENGR | 133 | | CLASSICS | 47 | | CNP | 10 | | CNSRSCI | 50 | | COMARTS | 137 | | COMPBIO | 15 | | COMPLIT | 11 | | COMPSCI | 138 | | COUNPSY | 78 | | CRB | 19 | | CS\&D | 71 | | CSCS | 40 | | CURRIC | 193 | | DANCE | 93 | | DERM | 8 | | DS | 88 | | DYSCI | 35 | | ECE | 155 | | ECON | 145 | | EDPOL | 114 | | EDPSYCH | 97 | | ELPA | 70 | | EMA | 53 | | EMERMED | 17 | | ENGL | 206 | | ENTOM | 40 | | ENVIRST | 148 | | EP | 15 | | EPD | 67 | | ESL | 16 | | F\&WECOL | 60 | | FAMMED | 22 | | FINANCE | 50 | | FOLKLORE | 40 | | FOODSCI | 43 | | FRENCH | 63 | | GEN\&WS | 145 | | GENBUS | 72 | | GENECSLR | 17 | | GENETICS | 60 | | GEOG | 113 | | GEOSCI | 83 | | GERMAN | 82 | | GLE | 48 | | GNS | 38 | | GREEK | 27 | | HDFS | 41 | | HEBR-BIB | 13 | | HEBR-MOD | 10 | | HISTORY | 233 | | HISTSCI | 56 | | HONCOL | 13 | | ILS | 43 | | INFOSYS | 9 | | INTEGART | 7 | | INTEGSCI | 22 | | INTER-AG | 18 | | INTER-HE | 11 | | INTER-LS | 22 | | INTEREGR | 16 | | INTLBUS | 21 | | INTLST | 50 | | ISYE | 83 | | ITALIAN | 53 | | JEWISH | 56 | | JOURN | 88 | | KINES | 128 | | LACIS | 26 | | LANDARC | 61 | | LATIN | 24 | | LAW | 120 | | LEGALST | 48 | | LINGUIS | 35 | | LIS | 89 | | LITTRANS | 78 | | LSC | 52 | | M\&ENVTOX | 7 | | MARKETNG | 62 | | MATH | 153 | | MDGENET | 8 | | ME | 130 | | MEDHIST | 43 | | MEDICINE | 60 | | MEDIEVAL | 32 | | MEDPHYS | 39 | | MEDSC-M | 29 | | MEDSC-V | 41 | | MHR | 68 | | MICROBIO | 45 | | MILSCI | 16 | | MM\&I | 22 | | MOLBIOL | 6 | | MS\&E | 59 | | MUSIC | 165 | | MUSPERF | 126 | | NAVSCI | 20 | | NE | 44 | | NEURODPT | 11 | | NEUROL | 7 | | NEURSURG | 4 | | NTP | 11 | | NURSING | 111 | | NUTRSCI | 65 | | OBS\&GYN | 18 | | OCCTHER | 39 | | ONCOLOGY | 14 | | OPHTHALM | 5 | | OTM | 43 | | PATH | 34 | | PATH-BIO | 29 | | PEDIAT | 26 | | PHARMACY | 31 | | PHILOS | 77 | | PHMCOL-M | 11 | | PHMPRAC | 45 | | PHMSCI | 60 | | PHYASST | 37 | | PHYSICS | 88 | | PHYSIOL | 3 | | PHYTHER | 37 | | PLANTSCI | 52 | | PLPATH | 35 | | POLISCI | 192 | | POPHLTH | 58 | | PORTUG | 33 | | PSYCH | 101 | | PSYCHIAT | 22 | | PUBAFFR | 54 | | PUBLHLTH | 23 | | RADIOL | 11 | | REALEST | 41 | | RELIGST | 90 | | RHABMED | 9 | | RMI | 24 | | RP\&SE | 102 | | S\&APHM | 17 | | SCANDST | 73 | | SLAVIC | 89 | | SOC | 149 | | SOCWORK | 87 | | SOILSCI | 46 | | SPANISH | 83 | | SRMED | 21 | | STAT | 94 | | STDYABRD | 52 | | STS | 8 | | SURGERY | 25 | | SURGSCI | 33 | | THEATRE | 91 | | URBRPL | 60 | | UROLOGY | 5 | | ZOOLOGY | 89 | ## course ### run id 20260907T155543-ce3781c4 ### semester 1272 ### observed at 2026-09-07 15:55:43.033547+00:00 ### record version id 661223bd12eced955945c8c5fa39c2c87d122ed248de68aeeeedbfcf9a0787d5 ### course id ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371 ### course uid course\_093fa77b2a5a91704aafc99c ### catalog version id c99ebb9118705c21d9f8dd1bc522e02a8eae1c3c42b06a0b2cd32f6039560f6b ### course number 371 ### subjects * ENVIRST * GEOG * GEOSCI * GLE * LANDARC ### title INTRODUCTION TO ENVIRONMENTAL REMOTE SENSING ### description Introduction to the Earth as viewed from above, focusing on use of aerial photography and satellite imagery to study the environment. Includes physical processes of electromagnetic radiation, data types and sensing capabilities, methods for interpretation, analysis and mapping, and applications. ### requirements text (Sophomore standing andMATH 113,114, or 171), graduate/professional standing, or member of Engineering Guest Students ### credit offering ids None recorded. ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 8570c63493ff4eaa0c966a937c8d40847ddb560334cce2a14121ef283e882654 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Introduction to environmental remote sensing using aerial photography and satellite imagery to study the Earth. ### llm topics * Physical processes of electromagnetic radiation * Data types and sensing capabilities * Interpretation, analysis, and mapping methods ### llm skills * Interpretation, analysis, and mapping of environmental data * Use of aerial photography and satellite imagery ### llm assumed background * Algebra and trigonometry skills ### llm search phrases * remote sensing introduction * aerial photography interpretation * satellite imagery analysis * electromagnetic radiation sensing * environmental mapping methods ### llm requirements status needs\_review ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash f4df37bfb53805064e04d3272d0de37f249332dda8dcea1aacf1f9ffffd3b5d7 #### course id ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371 #### current instructors None recorded. #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered false #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Recent recorded grades — Spring 2024: 3.04 GPA, 33.3% A/AB (n=27 letter grades); Spring 2025: 3.10 GPA, 43.3% A/AB (n=30 letter grades); Spring 2026: 3.02 GPA, 51.9% A/AB (n=27 letter grades). ```json { "citations": [ { "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "c85b125b-6258-3048-a050-5a69eebf4e3f", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1244", "type": "grade" }, { "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "c85b125b-6258-3048-a050-5a69eebf4e3f", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "c85b125b-6258-3048-a050-5a69eebf4e3f", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" 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"total": 44, "source_aliases": [ "ENVIRST/F&WECOL/GEOG/GEOSCI/GLE/LANDARC 371", "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "course_uid": "course_093fa77b2a5a91704aafc99c", "term_id": "1162", "term_name": "Fall 2015", "instructors": [ "ANNEMARIE SCHNEIDER", "Annemarie Schneider" ], "a": 7, "ab": 7, "b": 7, "bc": 0, "c": 1, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 1, "total": 24, "source_aliases": [ "ENVIRST/F&WECOL/GEOG/GEOSCI/GLE/LANDARC 371", "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "course_uid": "course_093fa77b2a5a91704aafc99c", "term_id": "1172", 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"ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "course_uid": "course_093fa77b2a5a91704aafc99c", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "ANNEMARIE SCHNEIDER", "Annemarie Schneider" ], "a": 9, "ab": 0, "b": 11, "bc": 0, "c": 6, "d": 1, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 28, "source_aliases": [ "ENVIRST/F&WECOL/GEOG/GEOSCI/GLE/LANDARC 371", "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "course_uid": "course_093fa77b2a5a91704aafc99c", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "ANNEMARIE SCHNEIDER", "Annemarie Schneider" ], "a": 13, "ab": 0, "b": 10, "bc": 2, "c": 3, "d": 0, "f": 2, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 30, "source_aliases": [ "ENVIRST/F&WECOL/GEOG/GEOSCI/GLE/LANDARC 371", "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371", "course_uid": "course_093fa77b2a5a91704aafc99c", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Annemarie Schneider" ], "a": 11, "ab": 3, "b": 5, "bc": 2, "c": 3, "d": 1, "f": 2, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 27, "source_aliases": [ "ENVIRST/GEOG/GEOSCI/GLE/LANDARC 371" ] } ] ``` ### statistics #### gpa 3.119 #### graded 293 #### counts * 106 * 28 * 93 * 10 * 40 * 8 * 8 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_093fa77b2a5a91704aafc99c-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_093fa77b2a5a91704aafc99c-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_093fa77b2a5a91704aafc99c-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_093fa77b2a5a91704aafc99c-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_093fa77b2a5a91704aafc99c-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_093fa77b2a5a91704aafc99c-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.1194539249146755 #### count 293 #### university ##### size 4120 ##### gpa Percentile 5 ##### count Percentile 74 ##### median Count 124 ##### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 12 | false | | 2.8–3.2 | 316 | true | | 3.2–3.6 | 1159 | false | | 3.6–4.0 | 2632 | false | #### departments ```json [ { "subject": "ENVIRST", "comparison": { "size": 95, "gpaPercentile": 6, "countPercentile": 67, "medianCount": 177, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 10, "current": true }, { "range": "3.2–3.6", "count": 33, "current": false }, { "range": "3.6–4.0", "count": 51, "current": false } ] } }, { "subject": "GEOG", "comparison": { "size": 65, "gpaPercentile": 5, "countPercentile": 72, "medianCount": 115, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 6, "current": true }, { "range": "3.2–3.6", "count": 28, "current": false }, { "range": "3.6–4.0", "count": 30, "current": false } ] } }, { "subject": "GEOSCI", "comparison": { "size": 32, "gpaPercentile": 32, "countPercentile": 65, "medianCount": 238.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 11, "current": true }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 5, "current": false } ] } }, { "subject": "GLE", "comparison": { "size": 20, "gpaPercentile": 21, "countPercentile": 79, "medianCount": 93.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 6, "current": true }, { "range": "3.2–3.6", "count": 7, "current": false }, { "range": "3.6–4.0", "count": 7, "current": false } ] } }, { "subject": "LANDARC", "comparison": { "size": 26, "gpaPercentile": 8, "countPercentile": 88, "medianCount": 91.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 3, "current": true }, { "range": "3.2–3.6", "count": 7, "current": false }, { "range": "3.6–4.0", "count": 15, "current": false } ] } } ] ``` ### terms #### 1152 ##### term 1152 ##### gpa 3.1931818181818183 ##### count 44 ##### university ###### size 918 ###### gpa Percentile 28 ###### count Percentile 27 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 33 | false | | 2.8–3.2 | 227 | true | | 3.2–3.6 | 371 | false | | 3.6–4.0 | 286 | false | ##### departments ```json [ { "subject": "ENVIRST", "comparison": { "size": 26, "gpaPercentile": 52, "countPercentile": 24, "medianCount": 83.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 2, "current": false }, { "range": "2.8–3.2", "count": 13, "current": true }, { "range": "3.2–3.6", "count": 6, "current": false }, { "range": "3.6–4.0", "count": 5, "current": false } ] } }, { "subject": "GEOG", "comparison": { "size": 20, "gpaPercentile": 37, "countPercentile": 26, "medianCount": 60, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 8, "current": true }, { "range": "3.2–3.6", "count": 8, "current": false }, { "range": "3.6–4.0", "count": 3, "current": false } ] } }, { "subject": "GEOSCI", "comparison": { "size": 16, "gpaPercentile": 73, "countPercentile": 27, "medianCount": 57.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 2, "current": false }, { "range": "2.8–3.2", "count": 10, "current": true }, { "range": "3.2–3.6", "count": 2, "current": false }, { "range": "3.6–4.0", "count": 2, "current": false } ] } }, { "subject": "GLE", "comparison": null }, { "subject": "LANDARC", "comparison": null } ] ``` #### 1162 ##### term 1162 ##### gpa 3.4318181818181817 ##### count 22 ##### departments | subject | comparison | | ------- | ---------- | | ENVIRST | | | GEOG | | | GEOSCI | | | GLE | | | LANDARC | | #### 1172 ##### term 1172 ##### gpa 2.913793103448276 ##### count 29 ##### departments | subject | comparison | | ------- | ---------- | | ENVIRST | | | GEOG | | | GEOSCI | | | GLE | | | LANDARC | | #### 1182 ##### term 1182 ##### gpa 3.310344827586207 ##### count 29 ##### departments | subject | comparison | | ------- | ---------- | | ENVIRST | | | GEOG | | | GEOSCI | | | GLE | | | LANDARC | | #### 1192 ##### term 1192 ##### gpa 2.814814814814815 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | ENVIRST | | | GEOG | | | GEOSCI | | | GLE | | | LANDARC | | #### 1202 ##### term 1202 ##### gpa 3.074074074074074 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | ENVIRST | | | GEOG | | | GEOSCI | | | GLE | | | LANDARC | | #### 1234 ##### term 1234 ##### gpa 3.2903225806451615 ##### count 31 ##### university ###### size 1188 ###### gpa Percentile 21 ###### count Percentile 3 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 3 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 144 | false | | 3.2–3.6 | 374 | true | | 3.6–4.0 | 650 | false | ##### departments ```json [ { "subject": "ENVIRST", "comparison": { "size": 35, "gpaPercentile": 21, "countPercentile": 6, "medianCount": 75, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 6, "current": false }, { "range": "3.2–3.6", "count": 8, "current": true }, { "range": "3.6–4.0", "count": 20, "current": false } ] } }, { "subject": "GEOG", "comparison": { "size": 20, "gpaPercentile": 26, "countPercentile": 0, "medianCount": 86, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 4, "current": false }, { "range": "3.2–3.6", "count": 9, "current": true }, { "range": "3.6–4.0", "count": 6, "current": false } ] } }, { "subject": "GEOSCI", "comparison": null }, { "subject": "GLE", "comparison": null }, { "subject": "LANDARC", "comparison": null } ] ``` #### 1244 ##### term 1244 ##### gpa 3.037037037037037 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | ENVIRST | | | GEOG | | | GEOSCI | | | GLE | | | LANDARC | | #### 1254 ##### term 1254 ##### gpa 3.1 ##### count 30 ##### university ###### size 1289 ###### gpa Percentile 7 ###### count Percentile 0 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 128 | true | | 3.2–3.6 | 379 | false | | 3.6–4.0 | 765 | false | ##### departments ```json [ { "subject": "ENVIRST", "comparison": { "size": 39, "gpaPercentile": 8, "countPercentile": 0, "medianCount": 73, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 3, "current": true }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 25, "current": false } ] } }, { "subject": "GEOG", "comparison": { "size": 22, "gpaPercentile": 10, "countPercentile": 0, "medianCount": 73, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 2, "current": true }, { "range": "3.2–3.6", "count": 5, "current": false }, { "range": "3.6–4.0", "count": 14, "current": false } ] } }, { "subject": "GEOSCI", "comparison": { "size": 11, "gpaPercentile": 0, "countPercentile": 0, "medianCount": 86, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 3, "current": true }, { "range": "3.2–3.6", "count": 5, "current": false }, { "range": "3.6–4.0", "count": 3, "current": false } ] } }, { "subject": "GLE", "comparison": null }, { "subject": "LANDARC", "comparison": { "size": 11, "gpaPercentile": 0, "countPercentile": 0, "medianCount": 48, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 1, "current": true }, { "range": "3.2–3.6", "count": 2, "current": false }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.0185185185185186 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | ENVIRST | | | GEOG | | | GEOSCI | | | GLE | | | LANDARC | | ### benchmarks #### all ##### school ###### size 4120 ###### gpa 3.6586405556993498 ###### top Share 81.81019846428565 ###### count 124 ##### ENVIRST ###### size 95 ###### gpa 3.594517005848932 ###### top Share 77.66163665381767 ###### count 177 ##### GEOG ###### size 65 ###### gpa 3.55903356740939 ###### top Share 76.12255298610839 ###### count 115 ##### GEOSCI ###### size 32 ###### gpa 3.3408320129249858 ###### top Share 61.2135967107706 ###### count 238.5 ##### GLE ###### size 20 ###### gpa 3.42221688715575 ###### top Share 65.25570849426728 ###### count 93.5 ##### LANDARC ###### size 26 ###### gpa 3.5688382815521695 ###### top Share 78.66043470091945 ###### count 91.5 #### terms ##### 1152 ###### school ###### size 918 ###### gpa 3.408733538594633 ###### top Share 66.06693005846735 ###### count 65 ###### ENVIRST ###### size 26 ###### gpa 3.2887810672539186 ###### top Share 57.82041568457323 ###### count 83.5 ###### GEOG ###### size 20 ###### gpa 3.2886723887363396 ###### top Share 57.6790762666065 ###### count 60 ###### GEOSCI ###### size 16 ###### gpa 3.1133622666098173 ###### top Share 45.502003791012335 ###### count 57.5 ##### 1162 ###### school ###### size 954 ###### gpa 3.43726781345039 ###### top Share 68.05645304987395 ###### count 64.5 ###### ENVIRST ###### size 23 ###### gpa 3.4014159683803316 ###### top Share 65.57341826434005 ###### count 128 ###### GEOG ###### size 18 ###### gpa 3.3176420835103957 ###### top Share 60.81158305120385 ###### count 79.5 ###### GEOSCI ###### size 13 ###### gpa 3.0969919052891512 ###### top Share 44.17120890690046 ###### count 83 ##### 1172 ###### school ###### size 991 ###### gpa 3.465129042641772 ###### top Share 69.42600667567366 ###### count 67 ###### ENVIRST ###### size 24 ###### gpa 3.4070567845053272 ###### top Share 65.41628909745516 ###### count 85.5 ###### GEOG ###### size 16 ###### gpa 3.3601991654243832 ###### top Share 63.20012922722716 ###### count 81.5 ###### GEOSCI ###### size 12 ###### gpa 3.332469037218154 ###### top Share 60.983357038393144 ###### count 74 ##### 1182 ###### school ###### size 1025 ###### gpa 3.474159360325319 ###### top Share 70.34861441764347 ###### count 69 ###### ENVIRST ###### size 27 ###### gpa 3.3518833054291157 ###### top Share 62.139516370734285 ###### count 134 ###### GEOG ###### size 20 ###### gpa 3.453345625277811 ###### top Share 69.04243509767332 ###### count 68.5 ###### GEOSCI ###### size 14 ###### gpa 3.2749466933418137 ###### top Share 54.68273808359606 ###### count 64 ##### 1192 ###### school ###### size 1077 ###### gpa 3.50327634323125 ###### top Share 72.44641925727845 ###### count 67 ###### ENVIRST ###### size 29 ###### gpa 3.4591452833640997 ###### top Share 69.39432045184823 ###### count 65 ###### GEOG ###### size 21 ###### gpa 3.436453371088323 ###### top Share 69.30075813293759 ###### count 73 ###### GEOSCI ###### size 13 ###### gpa 3.2616249441842324 ###### top Share 55.69237807550567 ###### count 65 ##### 1202 ###### school ###### size 1102 ###### gpa 3.5102605987403313 ###### top Share 72.78244569053733 ###### count 68 ###### ENVIRST ###### size 27 ###### gpa 3.443810915169906 ###### top Share 67.51593481001147 ###### count 91 ###### GEOG ###### size 18 ###### gpa 3.456671683161845 ###### top Share 67.85126625248914 ###### count 62 ###### GEOSCI ###### size 12 ###### gpa 3.2900356120117817 ###### top Share 57.229039635187995 ###### count 102.5 ##### 1234 ###### school ###### size 1188 ###### gpa 3.5799441677552393 ###### top Share 77.18256448537606 ###### count 65 ###### ENVIRST ###### size 35 ###### gpa 3.562190005068061 ###### top Share 74.74595421679987 ###### count 75 ###### GEOG ###### size 20 ###### gpa 3.443558312357458 ###### top Share 69.37000071893554 ###### count 86 ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### ENVIRST ###### size 40 ###### gpa 3.609333958752014 ###### top Share 78.44870523269554 ###### count 71 ###### GEOG ###### size 22 ###### gpa 3.5303428750158634 ###### top Share 74.39280835537028 ###### count 72 ###### LANDARC ###### size 11 ###### gpa 3.689508024262557 ###### top Share 85.3718775905583 ###### count 41 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### ENVIRST ###### size 39 ###### gpa 3.6271091837384972 ###### top Share 80.50128090125337 ###### count 73 ###### GEOG ###### size 22 ###### gpa 3.5765534265131054 ###### top Share 77.77119788550397 ###### count 73 ###### GEOSCI ###### size 11 ###### gpa 3.4683975607136763 ###### top Share 71.36857364724828 ###### count 86 ###### LANDARC ###### size 11 ###### gpa 3.691055422837633 ###### top Share 85.70846372417932 ###### count 48 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### ENVIRST ###### size 39 ###### gpa 3.6234319124309753 ###### top Share 80.66171436378418 ###### count 70 ###### GEOG ###### size 24 ###### gpa 3.5370488567946716 ###### top Share 76.3701545252745 ###### count 69.5 ## instructor Trends ```json [ { "uid": "instructor_234794bfea356012b6077041", "name": "ANNEMARIE SCHNEIDER", "count": 293, "terms": [ { "term": "1152", "count": 44, "sections": 1, "gpa": 3.1931818181818183 }, { "term": "1162", "count": 22, "sections": 1, "gpa": 3.4318181818181817 }, { "term": "1172", "count": 29, "sections": 1, "gpa": 2.913793103448276 }, { "term": "1182", "count": 29, "sections": 1, "gpa": 3.310344827586207 }, { "term": "1192", "count": 27, "sections": 1, "gpa": 2.814814814814815 }, { "term": "1202", "count": 27, "sections": 1, "gpa": 3.074074074074074 }, { "term": "1234", "count": 31, "sections": 1, "gpa": 3.2903225806451615 }, { "term": "1244", "count": 27, "sections": 1, "gpa": 3.037037037037037 }, { "term": "1254", "count": 30, "sections": 1, "gpa": 3.1 }, { "term": "1264", "count": 27, "sections": 1, "gpa": 3.0185185185185186 } ] } ] ``` ## following | code | title | | --------------------------- | -------------------------------------------- | | CIVENGR/ENVIRST/LANDARC 556 | REMOTE SENSING DIGITAL IMAGE PROCESSING | | ENVIRST 931 | REMOTE SENSING FOR INTERNATIONAL DEVELOPMENT | | ENVIRST 956 | ADVANCED ENVIRONMENTAL REMOTE SENSING | | ENVIRST 971 | ENVIRONMENTAL SENSING TECHNOLOGIES |