LAND COVER CHANGE DETECTION NEAR SMALL WATER BODIES BASED ON RGB UAV DATA: CASE STUDY OF THE POND BAROCH, CZECH REPUBLIC
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F22%3A39918949" target="_blank" >RIV/00216275:25410/22:39918949 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5194/isprs-archives-XLIII-B3-2022-617-2022" target="_blank" >http://dx.doi.org/10.5194/isprs-archives-XLIII-B3-2022-617-2022</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5194/isprs-archives-XLIII-B3-2022-617-2022" target="_blank" >10.5194/isprs-archives-XLIII-B3-2022-617-2022</a>
Alternative languages
Result language
angličtina
Original language name
LAND COVER CHANGE DETECTION NEAR SMALL WATER BODIES BASED ON RGB UAV DATA: CASE STUDY OF THE POND BAROCH, CZECH REPUBLIC
Original language description
Monitoring changes of land cover near water bodies and water bodies themselves represents a part of environment protection and management. The management can be done at the global or local level. The local level requires more detailed data, which can be collected i.e. by means of aircraft or UAV. The paper describes a case study focused on the utilization of UAV-based RGB data to monitor land cover near the pond Baroch, which is located in the Czech Republic, near the city of Pardubice. The area is specific - it is a small pond accompanied by several smaller pools and connecting canals and surrounded by meadows (often watered), reeds, bushes and some trees Used data were collected by authors by in advance planned flights in August, September, October, November, and December 2021. Support Vector Machine, Maximum Likelihood, Random Trees, and Deep Learning are used as methods to process data and detect land cover changes. Manually interpreted data are used as reference data. Because of the nature of the data (only R, G, and B bands), classification into bare land, the water, vegetation, dry vegetation, and wet vegetation classes only was used. Very high heterogeneity of the observed area, availability of RGB bands only, and very high spatial resolution (1,9 cm per pixel) led to isolated cells.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science
ISBN
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ISSN
1682-1750
e-ISSN
2194-9034
Number of pages
7
Pages from-to
617-623
Publisher name
International Society for Photogrammetry and Remote Sensing
Place of publication
GOTTINGEN
Event location
Nice
Event date
Jun 6, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000855647800087