Zobrazeno 1 - 10
of 273
pro vyhledávání: '"O. Hellwich"'
Publikováno v:
Hydrology and Earth System Sciences, Vol 27, Pp 4551-4562 (2023)
In the context of global warming, an increase in atmospheric aridity and global dryland expansion under the future climate has been expected in previous studies. However, this conflicts with observed greening over drylands and the insignificant incre
Externí odkaz:
https://doaj.org/article/ee353f25e60a4473b7522d7c08521c3f
Publikováno v:
Biogeosciences, Vol 20, Pp 2727-2741 (2023)
Using statistical methods that do not directly represent the causality between variables to attribute climate and plant traits as controlling ecosystem functions may lead to biased perceptions. We revisited this issue using a causal graphical model,
Externí odkaz:
https://doaj.org/article/40aab9fe303b4bcda539c52b40b3baca
Autor:
H. Shi, G. Luo, O. Hellwich, M. Xie, C. Zhang, Y. Zhang, Y. Wang, X. Yuan, X. Ma, W. Zhang, A. Kurban, P. De Maeyer, T. Van de Voorde
Publikováno v:
Hydrology and Earth System Sciences, Vol 26, Pp 4603-4618 (2022)
With the rapid accumulation of water flux observations from global eddy-covariance flux sites, many studies have used data-driven approaches to model water fluxes, with various predictors and machine learning algorithms used. However, it is unclear h
Externí odkaz:
https://doaj.org/article/489b1a1733514245bdabe734541a4128
Autor:
H. Shi, G. Luo, O. Hellwich, M. Xie, C. Zhang, Y. Zhang, Y. Wang, X. Yuan, X. Ma, W. Zhang, A. Kurban, P. De Maeyer, T. Van de Voorde
Publikováno v:
Biogeosciences, Vol 19, Pp 3739-3756 (2022)
Net ecosystem exchange (NEE) is an important indicator of carbon cycling in terrestrial ecosystems. Many previous studies have combined flux observations and meteorological, biophysical, and ancillary predictors using machine learning to simulate the
Externí odkaz:
https://doaj.org/article/1838d097c6da46278c3a48c98b251cb9
Autor:
H. Shi, G. Luo, H. Zheng, C. Chen, O. Hellwich, J. Bai, T. Liu, S. Liu, J. Xue, P. Cai, H. He, F. U. Ochege, T. Van de Voorde, P. de Maeyer
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 901-925 (2021)
The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian networ
Externí odkaz:
https://doaj.org/article/e5865596f074491aa6037f54978d16d6
Autor:
R. Hänsch, O. Hellwich
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-3, Pp 105-112 (2018)
Random Forests have continuously proven to be one of the most accurate, robust, as well as efficient methods for the supervised classification of images in general and polarimetric synthetic aperture radar data in particular. While the majority of pr
Externí odkaz:
https://doaj.org/article/a70cd8fd80ff4588ad92e448502c80fd
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-2-W4, Pp 243-250 (2017)
Multi-view stereo has been shown to be a viable tool for the creation of realistic 3D city models. Nevertheless, it still states significant challenges since it results in dense, but noisy and incomplete point clouds when applied to aerial images. 3
Externí odkaz:
https://doaj.org/article/4d28ad0ee2614388acd135e9286166a0
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol III-7, Pp 235-242 (2016)
In this paper, we introduce a method to detect and reconstruct building parts from tomographic Synthetic Aperture Radar (SAR) airborne data. Our approach extends recent works in two ways: first, the radiometric information is used to guide the extrac
Externí odkaz:
https://doaj.org/article/e60622e90d524c579e0ffb4c33379732
Autor:
R. Hänsch, O. Hellwich
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol III-7, Pp 263-270 (2016)
The automatic classification of land cover types from hyperspectral images is a challenging problem due to (among others) the large amount of spectral bands and their high spatial and spectral correlation. The extraction of meaningful features, that
Externí odkaz:
https://doaj.org/article/87da72f2b40a4b73931c3f0cc8902d27
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol III-3, Pp 43-50 (2016)
The task to compute 3D reconstructions from large amounts of data has become an active field of research within the last years. Based on an initial estimate provided by structure from motion, bundle adjustment seeks to find a solution that is optimal
Externí odkaz:
https://doaj.org/article/4aa61d7d84f64aaa98540e39339148f4