LAND COVER CHANGE DETECTION NEAR SMALL WATER BODIES BASED ON RGB UAV DATA: CASE STUDY OF THE POND BAROCH, CZECH REPUBLIC

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

LAND COVER CHANGE DETECTION NEAR SMALL WATER BODIES BASED ON RGB UAV DATA: CASE STUDY OF THE POND BAROCH, CZECH REPUBLIC

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

LAND COVER CHANGE DETECTION NEAR SMALL WATER BODIES BASED ON RGB UAV DATA: CASE STUDY OF THE POND BAROCH, CZECH REPUBLIC

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science

ISBN

—

ISSN

1682-1750

e-ISSN

2194-9034

Počet stran výsledku

7

Strana od-do

617-623

Název nakladatele

International Society for Photogrammetry and Remote Sensing

Místo vydání

GOTTINGEN

Místo konání akce

Nice

Datum konání akce

6. 6. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000855647800087