Item talk:Q264910
From geokb
{
"USGS Publications Warehouse": {
"@context": "https://schema.org",
"@type": "Article",
"additionalType": "Journal Article",
"name": "Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images",
"identifier": [
{
"@type": "PropertyValue",
"propertyID": "USGS Publications Warehouse IndexID",
"value": "70252794",
"url": "https://pubs.usgs.gov/publication/70252794"
},
{
"@type": "PropertyValue",
"propertyID": "USGS Publications Warehouse Internal ID",
"value": 70252794
},
{
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.3389/frsen.2024.1305991",
"url": "https://doi.org/10.3389/frsen.2024.1305991"
}
],
"journal": {
"@type": "Periodical",
"name": "Frontiers in Remote Sensing",
"volumeNumber": "5",
"issueNumber": null
},
"inLanguage": "en",
"isPartOf": [
{
"@type": "CreativeWorkSeries",
"name": "Frontiers in Remote Sensing"
}
],
"datePublished": "2024",
"dateModified": "2024-04-05",
"abstract": "Introduction:\u00a0Information on spatial patterns of water depth in river channels is valuable for numerous applications, but such data can be difficult to obtain via traditional field methods. Ongoing developments in remote sensing technology have enabled various image-based approaches for mapping river bathymetry; this study evaluated the potential to retrieve depth from multispectral images acquired by an uncrewed aircraft system (UAS).Methods:\u00a0More specifically, we produced depth maps for a 4\u00a0km reach of a clear-flowing, relatively shallow river using an established spectrally based algorithm, Optimal Band Ratio Analysis. To assess accuracy, we compared image-derived estimates to direct measurements of water depth. The field data were collected by wading and from a boat equipped with an echo sounder and used to survey cross sections and a longitudinal profile. We partitioned our study area along the Sacramento River, California, USA, into three distinct sub-reaches and acquired a separate image for each one. In addition to the typical, self-contained, per-image depth retrieval workflow, we also explored the possibility of exporting a relationship between depth and reflectance calibrated using data from one site to the other two sub-reaches. Moreover, we evaluated whether sampling configurations progressively more sparse than our full field survey could still provide sufficient calibration data for developing robust depth retrieval models.Results:\u00a0Our results indicate that under favorable environmental conditions like those observed on the Sacramento River during low flow, accurate, precise depth maps can be derived from images acquired by UAS, not only within a sub-reach but also across multiple, adjacent sub-reaches of the same river.Discussion:\u00a0Moreover, our findings imply that the level of effort invested in obtaining field data for calibration could be significantly reduced. In aggregate, this investigation suggests that UAS-based remote sensing could facilitate highly efficient, cost-effective, operational mapping of river bathymetry at the reach scale in clear-flowing streams.",
"description": "1305991, 16 p.",
"publisher": {
"@type": "Organization",
"name": "Frontiers Media"
},
"author": [
{
"@type": "Person",
"name": "Legleiter, Carl J. cjl@usgs.gov",
"givenName": "Carl J.",
"familyName": "Legleiter",
"email": "cjl@usgs.gov",
"identifier": {
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0003-0940-8013",
"url": "https://orcid.org/0000-0003-0940-8013"
},
"affiliation": [
{
"@type": "Organization",
"name": "WMA - Integrated Modeling and Prediction Division",
"url": "https://www.usgs.gov/mission-areas/water-resources"
},
{
"@type": "Organization",
"name": "National Research Program - Central Branch",
"url": "https://www.usgs.gov/centers/arizona-water-science-center"
}
]
},
{
"@type": "Person",
"name": "Harrison, Lee R.",
"givenName": "Lee R.",
"familyName": "Harrison",
"affiliation": [
{
"@type": "Organization",
"name": "University of California, Santa Barbara, CA"
}
]
}
],
"funder": [
{
"@type": "Organization",
"name": "WMA - Observing Systems Division",
"url": "https://www.usgs.gov/mission-areas/water-resources"
}
],
"spatialCoverage": [
{
"@type": "Place",
"additionalType": "country",
"name": "United States",
"url": "https://geonames.org/4074035"
},
{
"@type": "Place",
"additionalType": "state",
"name": "California"
},
{
"@type": "Place",
"additionalType": "unknown",
"name": "Sacramento River",
"url": "https://geonames.org/5389630"
},
{
"@type": "Place",
"geo": [
{
"@type": "GeoShape",
"additionalProperty": {
"@type": "PropertyValue",
"name": "GeoJSON",
"value": {
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"properties": {},
"geometry": {
"coordinates": [
[
[
-122.5,
40
],
[
-122.5,
39
],
[
-121.75,
39
],
[
-121.75,
40
],
[
-122.5,
40
]
]
],
"type": "Polygon"
}
}
]
}
}
},
{
"@type": "GeoCoordinates",
"latitude": 39.5,
"longitude": -122.125
}
]
}
]
},
"OpenAlex": {
"_id": "https://openalex.org/w4393944857",
"abstract_inverted_index": {
"Introduction:": [
0
],
"Information": [
1
],
"on": [
2,
223
],
"spatial": [
3
],
"patterns": [
4
],
"of": [
5,
73,
99,
166,
253,
265,
294
],
"water": [
6,
100
],
"depth": [
7,
50,
66,
158,
171,
208,
232
],
"in": [
8,
30,
268,
301
],
"river": [
9,
41,
78,
295
],
"channels": [
10
],
"is": [
11
],
"valuable": [
12
],
"for": [
13,
39,
68,
148,
205,
272
],
"numerous": [
14
],
"applications,": [
15
],
"but": [
16,
247
],
"such": [
17
],
"data": [
18,
104,
176,
204,
271
],
"can": [
19,
234
],
"be": [
20,
235,
275
],
"difficult": [
21
],
"to": [
22,
48,
96,
120,
153,
180
],
"obtain": [
23
],
"via": [
24
],
"traditional": [
25
],
"field": [
26,
103,
197,
270
],
"methods.": [
27
],
"Ongoing": [
28
],
"developments": [
29
],
"remote": [
31,
285
],
"sensing": [
32,
286
],
"technology": [
33
],
"have": [
34
],
"enabled": [
35
],
"various": [
36
],
"image-based": [
37
],
"approaches": [
38
],
"mapping": [
40,
293
],
"bathymetry;": [
42
],
"this": [
43,
280
],
"study": [
44,
131
],
"evaluated": [
45,
187
],
"the": [
46,
134,
154,
164,
181,
224,
254,
263,
298
],
"potential": [
47
],
"retrieve": [
49
],
"from": [
51,
110,
177,
237
],
"multispectral": [
52
],
"images": [
53,
238
],
"acquired": [
54,
144,
239
],
"by": [
55,
107,
240
],
"an": [
56,
80,
115
],
"uncrewed": [
57
],
"aircraft": [
58
],
"system": [
59
],
"(UAS).": [
60
],
"Methods:": [
61
],
"More": [
62
],
"specifically,": [
63
],
"we": [
64,
92,
161,
186
],
"produced": [
65
],
"maps": [
67,
233
],
"a": [
69,
74,
111,
125,
145,
168,
245
],
"4": [
70
],
"km": [
71
],
"reach": [
72,
299
],
"clear-flowing,": [
75
],
"relatively": [
76
],
"shallow": [
77
],
"using": [
79,
175
],
"established": [
81
],
"spectrally": [
82
],
"based": [
83
],
"algorithm,": [
84
],
"Optimal": [
85
],
"Band": [
86
],
"Ratio": [
87
],
"Analysis.": [
88
],
"To": [
89
],
"assess": [
90
],
"accuracy,": [
91
],
"compared": [
93
],
"image-derived": [
94
],
"estimates": [
95
],
"direct": [
97
],
"measurements": [
98
],
"depth.": [
101
],
"The": [
102
],
"were": [
105
],
"collected": [
106
],
"wading": [
108
],
"and": [
109,
118,
124,
143,
172
],
"boat": [
112
],
"equipped": [
113
],
"with": [
114
],
"echo": [
116
],
"sounder": [
117
],
"used": [
119
],
"survey": [
121,
198
],
"cross": [
122
],
"sections": [
123
],
"longitudinal": [
126
],
"profile.": [
127
],
"We": [
128
],
"partitioned": [
129
],
"our": [
130,
195,
259
],
"area": [
132
],
"along": [
133
],
"Sacramento": [
135,
225
],
"River,": [
136
],
"California,": [
137
],
"USA,": [
138
],
"into": [
139
],
"three": [
140
],
"distinct": [
141
],
"sub-reaches": [
142,
252
],
"separate": [
146
],
"image": [
147
],
"each": [
149
],
"one.": [
150
],
"In": [
151,
278
],
"addition": [
152
],
"typical,": [
155
],
"self-contained,": [
156
],
"per-image": [
157
],
"retrieval": [
159,
209
],
"workflow,": [
160
],
"also": [
162,
248
],
"explored": [
163
],
"possibility": [
165
],
"exporting": [
167
],
"relationship": [
169
],
"between": [
170
],
"reflectance": [
173
],
"calibrated": [
174
],
"one": [
178
],
"site": [
179
],
"other": [
182
],
"two": [
183
],
"sub-reaches.": [
184
],
"Moreover,": [
185,
258
],
"whether": [
188
],
"sampling": [
189
],
"configurations": [
190
],
"progressively": [
191
],
"more": [
192
],
"sparse": [
193
],
"than": [
194
],
"full": [
196
],
"could": [
199,
274,
287
],
"still": [
200
],
"provide": [
201
],
"sufficient": [
202
],
"calibration": [
203,
273
],
"developing": [
206
],
"robust": [
207
],
"models.": [
210
],
"Results:": [
211
],
"Our": [
212
],
"results": [
213
],
"indicate": [
214
],
"that": [
215,
262,
283
],
"under": [
216
],
"favorable": [
217
],
"environmental": [
218
],
"conditions": [
219
],
"like": [
220
],
"those": [
221
],
"observed": [
222
],
"River": [
226
],
"during": [
227
],
"low": [
228
],
"flow,": [
229
],
"accurate,": [
230
],
"precise": [
231
],
"derived": [
236
],
"UAS,": [
241
],
"not": [
242
],
"only": [
243
],
"within": [
244
],
"sub-reach": [
246
],
"across": [
249
],
"multiple,": [
250
],
"adjacent": [
251
],
"same": [
255
],
"river.": [
256
],
"Discussion:": [
257
],
"findings": [
260
],
"imply": [
261
],
"level": [
264
],
"effort": [
266
],
"invested": [
267
],
"obtaining": [
269
],
"significantly": [
276
],
"reduced.": [
277
],
"aggregate,": [
279
],
"investigation": [
281
],
"suggests": [
282
],
"UAS-based": [
284
],
"facilitate": [
288
],
"highly": [
289
],
"efficient,": [
290
],
"cost-effective,": [
291
],
"operational": [
292
],
"bathymetry": [
296
],
"at": [
297
],
"scale": [
300
],
"clear-flowing": [
302
],
"streams.": [
303
]
},
"apc_list": {
"value": 1900,
"currency": "USD",
"value_usd": 1900,
"provenance": "doaj"
},
"apc_paid": {
"value": 1900,
"currency": "USD",
"value_usd": 1900,
"provenance": "doaj"
},
"authorships": [
{
"author_position": "first",
"author": {
"id": "https://openalex.org/A5017833403",
"display_name": "Carl J. Legleiter",
"orcid": "https://orcid.org/0000-0003-0940-8013"
},
"institutions": [],
"countries": [],
"is_corresponding": false,
"raw_author_name": "Carl J. Legleiter",
"raw_affiliation_strings": [],
"affiliations": []
},
{
"author_position": "last",
"author": {
"id": "https://openalex.org/A5014682581",
"display_name": "Lee R. Harrison",
"orcid": "https://orcid.org/0000-0002-5219-9280"
},
"institutions": [],
"countries": [],
"is_corresponding": false,
"raw_author_name": "Lee R. Harrison",
"raw_affiliation_strings": [],
"affiliations": []
}
],
"best_oa_location": {
"is_oa": true,
"landing_page_url": "https://doi.org/10.3389/frsen.2024.1305991",
"pdf_url": "https://www.frontiersin.org/articles/10.3389/frsen.2024.1305991/pdf?isPublishedV2=False",
"source": {
"id": "https://openalex.org/S4210194326",
"display_name": "Frontiers in Remote Sensing",
"issn_l": "2673-6187",
"issn": [
"2673-6187"
],
"is_oa": true,
"is_in_doaj": true,
"is_core": true,
"host_organization": "https://openalex.org/P4310320527",
"host_organization_name": "Frontiers Media",
"host_organization_lineage": [
"https://openalex.org/P4310320527"
],
"host_organization_lineage_names": [
"Frontiers Media"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
},
"biblio": {
"volume": "5",
"issue": null,
"first_page": null,
"last_page": null
},
"citation_normalized_percentile": {
"value": 0.999834,
"is_in_top_1_percent": true,
"is_in_top_10_percent": true
},
"cited_by_api_url": "https://api.openalex.org/works?filter=cites:W4393944857",
"cited_by_count": 1,
"cited_by_percentile_year": {
"min": 88,
"max": 95
},
"concepts": [
{
"id": "https://openalex.org/C174943157",
"wikidata": "https://www.wikidata.org/wiki/Q810826",
"display_name": "Bathymetry",
"level": 2,
"score": 0.9496318
},
{
"id": "https://openalex.org/C173163844",
"wikidata": "https://www.wikidata.org/wiki/Q1761440",
"display_name": "Multispectral image",
"level": 2,
"score": 0.90326965
},
{
"id": "https://openalex.org/C62649853",
"wikidata": "https://www.wikidata.org/wiki/Q199687",
"display_name": "Remote sensing",
"level": 1,
"score": 0.7154997
},
{
"id": "https://openalex.org/C127162648",
"wikidata": "https://www.wikidata.org/wiki/Q16858953",
"display_name": "Channel (broadcasting)",
"level": 2,
"score": 0.66289806
},
{
"id": "https://openalex.org/C2778755073",
"wikidata": "https://www.wikidata.org/wiki/Q10858537",
"display_name": "Scale (ratio)",
"level": 2,
"score": 0.6262414
},
{
"id": "https://openalex.org/C127313418",
"wikidata": "https://www.wikidata.org/wiki/Q1069",
"display_name": "Geology",
"level": 0,
"score": 0.4469718
},
{
"id": "https://openalex.org/C41008148",
"wikidata": "https://www.wikidata.org/wiki/Q21198",
"display_name": "Computer science",
"level": 0,
"score": 0.36653483
},
{
"id": "https://openalex.org/C39432304",
"wikidata": "https://www.wikidata.org/wiki/Q188847",
"display_name": "Environmental science",
"level": 0,
"score": 0.3499036
},
{
"id": "https://openalex.org/C58640448",
"wikidata": "https://www.wikidata.org/wiki/Q42515",
"display_name": "Cartography",
"level": 1,
"score": 0.33525798
},
{
"id": "https://openalex.org/C205649164",
"wikidata": "https://www.wikidata.org/wiki/Q1071",
"display_name": "Geography",
"level": 0,
"score": 0.2909311
},
{
"id": "https://openalex.org/C111368507",
"wikidata": "https://www.wikidata.org/wiki/Q43518",
"display_name": "Oceanography",
"level": 1,
"score": 0.23008737
},
{
"id": "https://openalex.org/C76155785",
"wikidata": "https://www.wikidata.org/wiki/Q418",
"display_name": "Telecommunications",
"level": 1,
"score": 0.10033882
}
],
"corresponding_author_ids": [],
"corresponding_institution_ids": [],
"countries_distinct_count": 0,
"counts_by_year": [
{
"year": 2024,
"cited_by_count": 1
}
],
"created_date": "2024-04-05",
"datasets": [],
"display_name": "Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images",
"doi": "https://doi.org/10.3389/frsen.2024.1305991",
"fulltext_origin": "pdf",
"fwci": 1.855,
"grants": [],
"has_fulltext": true,
"id": "https://openalex.org/W4393944857",
"ids": {
"openalex": "https://openalex.org/W4393944857",
"doi": "https://doi.org/10.3389/frsen.2024.1305991"
},
"indexed_in": [
"crossref"
],
"institutions_distinct_count": 0,
"is_paratext": false,
"is_retracted": false,
"keywords": [],
"language": "en",
"locations": [
{
"is_oa": true,
"landing_page_url": "https://doi.org/10.3389/frsen.2024.1305991",
"pdf_url": "https://www.frontiersin.org/articles/10.3389/frsen.2024.1305991/pdf?isPublishedV2=False",
"source": {
"id": "https://openalex.org/S4210194326",
"display_name": "Frontiers in Remote Sensing",
"issn_l": "2673-6187",
"issn": [
"2673-6187"
],
"is_oa": true,
"is_in_doaj": true,
"is_core": true,
"host_organization": "https://openalex.org/P4310320527",
"host_organization_name": "Frontiers Media",
"host_organization_lineage": [
"https://openalex.org/P4310320527"
],
"host_organization_lineage_names": [
"Frontiers Media"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
}
],
"locations_count": 1,
"mesh": [],
"ngrams_url": "https://api.openalex.org/works/W4393944857/ngrams",
"open_access": {
"is_oa": true,
"oa_status": "gold",
"oa_url": "https://www.frontiersin.org/articles/10.3389/frsen.2024.1305991/pdf?isPublishedV2=False",
"any_repository_has_fulltext": false
},
"primary_location": {
"is_oa": true,
"landing_page_url": "https://doi.org/10.3389/frsen.2024.1305991",
"pdf_url": "https://www.frontiersin.org/articles/10.3389/frsen.2024.1305991/pdf?isPublishedV2=False",
"source": {
"id": "https://openalex.org/S4210194326",
"display_name": "Frontiers in Remote Sensing",
"issn_l": "2673-6187",
"issn": [
"2673-6187"
],
"is_oa": true,
"is_in_doaj": true,
"is_core": true,
"host_organization": "https://openalex.org/P4310320527",
"host_organization_name": "Frontiers Media",
"host_organization_lineage": [
"https://openalex.org/P4310320527"
],
"host_organization_lineage_names": [
"Frontiers Media"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
},
"primary_topic": {
"id": "https://openalex.org/T11164",
"display_name": "Mapping Forests with Lidar Remote Sensing",
"score": 0.9997,
"subfield": {
"id": "https://openalex.org/subfields/2305",
"display_name": "Environmental Engineering"
},
"field": {
"id": "https://openalex.org/fields/23",
"display_name": "Environmental Science"
},
"domain": {
"id": "https://openalex.org/domains/3",
"display_name": "Physical Sciences"
}
},
"publication_date": "2024-04-04",
"publication_year": 2024,
"referenced_works": [
"https://openalex.org/W1852156094",
"https://openalex.org/W1969566724",
"https://openalex.org/W1974610360",
"https://openalex.org/W1977886272",
"https://openalex.org/W1990174871",
"https://openalex.org/W2004804317",
"https://openalex.org/W2009396719",
"https://openalex.org/W2060552827",
"https://openalex.org/W2067653716",
"https://openalex.org/W2068990297",
"https://openalex.org/W2142454868",
"https://openalex.org/W2152686492",
"https://openalex.org/W2743445409",
"https://openalex.org/W2796112747",
"https://openalex.org/W2807808709",
"https://openalex.org/W2907525308",
"https://openalex.org/W2924949734",
"https://openalex.org/W2960407059",
"https://openalex.org/W2994984469",
"https://openalex.org/W3014967572",
"https://openalex.org/W3048166052",
"https://openalex.org/W3048895281",
"https://openalex.org/W3088182663",
"https://openalex.org/W3127117956",
"https://openalex.org/W3167782070",
"https://openalex.org/W3193886938",
"https://openalex.org/W4289950742",
"https://openalex.org/W4311178372",
"https://openalex.org/W4321200408",
"https://openalex.org/W4378619255"
],
"referenced_works_count": 30,
"related_works": [
"https://openalex.org/W773765100",
"https://openalex.org/W4386617716",
"https://openalex.org/W4318664220",
"https://openalex.org/W4313058144",
"https://openalex.org/W3152163876",
"https://openalex.org/W2793357704",
"https://openalex.org/W2738763808",
"https://openalex.org/W2622615123",
"https://openalex.org/W2351842833",
"https://openalex.org/W2184765375"
],
"sustainable_development_goals": [],
"title": "Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images",
"topics": [
{
"id": "https://openalex.org/T11164",
"display_name": "Mapping Forests with Lidar Remote Sensing",
"score": 0.9997,
"subfield": {
"id": "https://openalex.org/subfields/2305",
"display_name": "Environmental Engineering"
},
"field": {
"id": "https://openalex.org/fields/23",
"display_name": "Environmental Science"
},
"domain": {
"id": "https://openalex.org/domains/3",
"display_name": "Physical Sciences"
}
},
{
"id": "https://openalex.org/T10577",
"display_name": "Ecological Dynamics of Riverine Landscapes",
"score": 0.9969,
"subfield": {
"id": "https://openalex.org/subfields/2303",
"display_name": "Ecology"
},
"field": {
"id": "https://openalex.org/fields/23",
"display_name": "Environmental Science"
},
"domain": {
"id": "https://openalex.org/domains/3",
"display_name": "Physical Sciences"
}
},
{
"id": "https://openalex.org/T13282",
"display_name": "Automatic Road Extraction from Remote Sensing Images",
"score": 0.9877,
"subfield": {
"id": "https://openalex.org/subfields/2212",
"display_name": "Ocean Engineering"
},
"field": {
"id": "https://openalex.org/fields/22",
"display_name": "Engineering"
},
"domain": {
"id": "https://openalex.org/domains/3",
"display_name": "Physical Sciences"
}
}
],
"type": "article",
"type_crossref": "journal-article",
"updated_date": "2024-08-11T09:17:15.753788",
"versions": []
}
}
