Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Thorsten Hoeser"'
Autor:
Thorsten Hoeser, Claudia Kuenzer
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 112, Iss , Pp 102957- (2022)
With the promotion of renewable energy production and a planned phaseout of fossil fuels until 2040, the offshore wind energy sector has expanded and will continue to increase its capacity in the upcoming decades. This study presents a novel approach
Externí odkaz:
https://doaj.org/article/c0a5c20bbf024cc2b56f5f04a257ea8d
Autor:
Jennifer Kriese, Thorsten Hoeser, Sarah Asam, Patrick Kacic, Emmanuel Da Ponte, Ursula Gessner
Publikováno v:
Remote Sensing, Vol 14, Iss 17, p 4327 (2022)
The Paraguayan Chaco is one of the most rapidly deforested areas in Latin America, mainly due to cattle ranching. Continuously forested windbreaks between agricultural areas and forest patches within these areas are mandatory to minimise the impact t
Externí odkaz:
https://doaj.org/article/d0d80241cf054c5db8ff55395929b8b3
Autor:
Zhiyuan Wang, Felix Bachofer, Jonas Koehler, Juliane Huth, Thorsten Hoeser, Mattia Marconcini, Thomas Esch, Claudia Kuenzer
Publikováno v:
Land, Vol 11, Iss 8, p 1174 (2022)
In the past decades, various Earth observation-based time series products have emerged, which have enabled studies and analysis of global change processes. Besides their contribution to understanding past processes, time series datasets hold enormous
Externí odkaz:
https://doaj.org/article/2b0310ebc2c14cac843f31352153343f
Publikováno v:
Remote Sensing, Vol 12, Iss 18, p 3053 (2020)
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by investigating aggregated classes. The increase in data with a very high spatial resolution enables investigations on a fine-grained feature level which can hel
Externí odkaz:
https://doaj.org/article/56aade2b0b4243b1b45a6839cc85dc15
Autor:
Thorsten Hoeser, Claudia Kuenzer
Publikováno v:
Remote Sensing, Vol 12, Iss 10, p 1667 (2020)
Deep learning (DL) has great influence on large parts of science and increasingly established itself as an adaptive method for new challenges in the field of Earth observation (EO). Nevertheless, the entry barriers for EO researchers are high due to
Externí odkaz:
https://doaj.org/article/0819112878e1428ea73537d5582c2a24
Autor:
Gessner, Jennifer Kriese, Thorsten Hoeser, Sarah Asam, Patrick Kacic, Emmanuel Da Da Ponte, Ursula
Publikováno v:
Remote Sensing; Volume 14; Issue 17; Pages: 4327
The Paraguayan Chaco is one of the most rapidly deforested areas in Latin America, mainly due to cattle ranching. Continuously forested windbreaks between agricultural areas and forest patches within these areas are mandatory to minimise the impact t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::346a2e8a5dea22981a69923ce5943e90
Autor:
Kuenzer, Zhiyuan Wang, Felix Bachofer, Jonas Koehler, Juliane Huth, Thorsten Hoeser, Mattia Marconcini, Thomas Esch, Claudia
Publikováno v:
Land; Volume 11; Issue 8; Pages: 1174
In the past decades, various Earth observation-based time series products have emerged, which have enabled studies and analysis of global change processes. Besides their contribution to understanding past processes, time series datasets hold enormous
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::8538e79a2ed5b53deadacceb2776c2eb
Autor:
Koehler, Jonas1 (AUTHOR) jonas.koehler@dlr.de, Bauer, André2 (AUTHOR), Dietz, Andreas J.1 (AUTHOR), Kuenzer, Claudia1,3 (AUTHOR)
Publikováno v:
Remote Sensing. Sep2022, Vol. 14 Issue 18, pN.PAG-N.PAG. 30p.
Autor:
Hoeser, Thorsten1 (AUTHOR) thorsten.hoeser@dlr.de, Feuerstein, Stefanie1 (AUTHOR), Kuenzer, Claudia1,2 (AUTHOR)
Publikováno v:
Earth System Science Data. 2022, Vol. 14 Issue 9, p4251-4270. 20p.