Akpona Okujeni
Akpona Okujeni
Humboldt-Universität zu Berlin, Geography Department, Geomatics Lab
Подтвержден адрес электронной почты в домене geo.hu-berlin.de
Название
Процитировано
Процитировано
Год
CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands
U Rascher, G Agati, L Alonso, G Cecchi, S Champagne, R Colombo, ...
Biogeosciences 6 (7), 1181-1198, 2009
1442009
The EnMAP-Box—A toolbox and application programming interface for EnMAP data processing
S van der Linden, A Rabe, M Held, B Jakimow, PJ Leitão, A Okujeni, ...
Remote Sensing 7 (9), 11249-11266, 2015
1422015
Support vector regression and synthetically mixed training data for quantifying urban land cover
A Okujeni, S van der Linden, L Tits, B Somers, P Hostert
Remote Sensing of Environment 137, 184-197, 2013
1082013
Extending the vegetation–impervious–soil model using simulated EnMAP data and machine learning
A Okujeni, S van der Linden, P Hostert
Remote Sensing of Environment 158, 69-80, 2015
572015
Influence of neighbourhood information on ‘Local Climate Zone’mapping in heterogeneous cities
ML Verdonck, A Okujeni, S van der Linden, M Demuzere, R De Wulf, ...
International Journal of Applied Earth Observation and Geoinformation 62 …, 2017
432017
A comparison of advanced regression algorithms for quantifying urban land cover
A Okujeni, S Van der Linden, B Jakimow, A Rabe, J Verrelst, P Hostert
Remote Sensing 6 (7), 6324-6346, 2014
362014
Monitoring natural ecosystem and ecological gradients: Perspectives with EnMAP
PJ Leitão, M Schwieder, S Suess, A Okujeni, LS Galvão, S Linden, ...
Remote Sensing 7 (10), 13098-13119, 2015
282015
Mapping patterns of urban development in Ouagadougou, Burkina Faso, using machine learning regression modeling with bi-seasonal Landsat time series
F Schug, A Okujeni, J Hauer, P Hostert, JØ Nielsen, S van der Linden
Remote Sensing of Environment 210, 217-228, 2018
272018
Ensemble Learning From Synthetically Mixed Training Data for Quantifying Urban Land Cover With Support Vector Regression
A Okujeni, S van der Linden, S Suess, P Hostert
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017
262017
A Novel Spectral Library Pruning Technique for Spectral Unmixing of Urban Land Cover
J Degerickx, A Okujeni, MD Iordache, M Hermy, S van der Linden, ...
Remote Sensing 9 (6), 565, 2017
222017
Using class probabilities to map gradual transitions in shrub vegetation from simulated EnMAP data
S Suess, S van der Linden, A Okujeni, PJ Leitão, M Schwieder, P Hostert
Remote Sensing 7 (8), 10668-10688, 2015
222015
Subpixel Mapping of Urban Areas Using EnMAP Data and Multioutput Support Vector Regression
J Rosentreter, R Hagensieker, A Okujeni, R Roscher, PD Wagner, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017
202017
Import vector machines for quantitative analysis of hyperspectral data
S Suess, S van der Linden, PJ Leitão, A Okujeni, B Waske, P Hostert
IEEE Geoscience and Remote Sensing Letters 11 (2), 449-453, 2014
202014
Sensing of photosynthetic activity of crops
U Rascher, A Damm, S van der Linden, A Okujeni, R Pieruschka, ...
Precision Crop Protection-the Challenge and Use of Heterogeneity, 87-99, 2010
202010
Imaging Spectroscopy of Urban Environments
S van der Linden, A Okujeni, F Canters, J Degerickx, U Heiden, P Hostert, ...
Surveys in Geophysics, 1-18, 2018
192018
Characterizing 32 years of shrub cover dynamics in southern Portugal using annual Landsat composites and machine learning regression modeling
S Suess, S van der Linden, A Okujeni, P Griffiths, PJ Leitão, M Schwieder, ...
Remote Sensing of Environment 219, 353-364, 2018
162018
Image SVM classification, application manual: Image SVM version 2.0
S Van der Linden, A Rabe, A Okujeni, P Hostert
Humboldt-Universität zu Berlin, Germany, 2009
162009
Image SVM classification
S Van der Linden, A Rabe, A Okujeni, P Hostert
Application Manual: image SVM version 2, 2009
152009
Generalizing machine learning regression models using multi-site spectral libraries for mapping vegetation-impervious-soil fractions across multiple cities
A Okujeni, F Canters, SD Cooper, J Degerickx, U Heiden, P Hostert, ...
Remote Sensing of Environment 216, 482-496, 2018
142018
Berlin-Urban-Gradient dataset 2009-An EnMAP Preparatory Flight Campaign (Datasets)
A Okujeni, S Van Der Linden, P Hostert
GFZ Data Services, 2016
132016
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Статьи 1–20