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Jannes Muenchow
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Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data
P Schratz, J Muenchow, E Iturritxa, J Richter, A Brenning
Ecological Modelling 406, 109-120, 2019
454*2019
Geocomputation with R
R Lovelace, J Nowosad, J Muenchow
Chapman and Hall/CRC, 2019
2182019
Landslide susceptibility near highways is increased by 1 order of magnitude in the Andes of southern Ecuador, Loja province
A Brenning, M Schwinn, AP Ruiz-Páez, J Muenchow
Natural Hazards and Earth System Sciences 15 (1), 45-57, 2015
1172015
Mapping tree species vulnerability to multiple threats as a guide to restoration and conservation of tropical dry forests
T Fremout, E Thomas, H Gaisberger, K Van Meerbeek, J Muenchow, ...
Global Change Biology 26 (6), 3552-3568, 2020
862020
Geomorphic process rates of landslides along a humidity gradient in the tropical Andes
J Muenchow, A Brenning, M Richter
Geomorphology 139, 271-284, 2012
572012
The performance of landslide susceptibility models critically depends on the quality of digital elevation models
J Brock, P Schratz, H Petschko, J Muenchow, M Micu, A Brenning
Geomatics, Natural Hazards and Risk 11 (1), 1075-1092, 2020
502020
Predictive mapping of species richness and plant species' distributions of a Peruvian fog oasis along an altitudinal gradient
J Muenchow, A Bräuning, EF Rodríguez, H von Wehrden
Biotropica, 2013
402013
Reviewing qualitative GIS research—Toward a wider usage of open‐source GIS and reproducible research practices
J Muenchow, S Schäfer, E Krüger
Geography Compass 13 (6), e12441, 2019
362019
RQGIS: Integrating R with QGIS for Statistical Geocomputing
J Muenchow, P Schratz, A Brenning
The R Journal 9 (2), 409-428, 2017
362017
Soil texture and altitude, respectively, largely determine the floristic gradient of the most diverse fog oasis in the Peruvian desert
J Muenchow, S Hauenstein, A Bräuning, R Bäumler, EF Rodríguez, ...
Journal of Tropical Ecology 29 (5), 427-438, 2013
362013
A review of ecological gradient research in the Tropics: identifying research gaps, future directions, and conservation priorities
J Muenchow, P Dieker, J Kluge, M Kessler, H von Wehrden
Biodiversity and Conservation 27, 273-285, 2018
292018
Coupling ordination techniques and GAM to spatially predict vegetation assemblages along a climatic gradient in an ENSO‐affected region of extremely high climate variability
J Muenchow, H Feilhauer, A Bräuning, EF Rodríguez, F Bayer, ...
Journal of Vegetation Science, 2013
262013
Woody vegetation of a Peruvian tropical dry forest along a climatic gradient depends more on soil than annual precipitation
J Muenchow, H von Wehrden, EF Rodríguez, RA Rodríguez, F Bayer, ...
Erdkunde, 241-248, 2013
212013
Climatic cycles and gradients of the El Niño core region in North Peru
R Rollenbeck, F Bayer, J Münchow, M Richter, R Rodriguez, N Atarama
Advances in Meteorology 2015 (1), 750181, 2015
152015
An ecological paradox: high species diversity and low position of the upper forest line in the A ndean D epression
T Peters, A Braeuning, J Muenchow, M Richter
Ecology and Evolution 4 (11), 2134-2145, 2014
152014
RPyGeo: ArcGIS geoprocessing via python
A Brenning, F Polakowski, M Becker
URL: https://CRAN. R-project. org/package= RPyGeo, 2018
122018
Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?
P Schratz, J Muenchow, E Iturritxa, J Cortés, B Bischl, A Brenning
Remote Sensing 13 (23), 4832, 2021
92021
Qualitative forschung und geographische informationssysteme
S Schäfer, J Muenchow, B Harnisch
Sozialraum erforschen: Qualitative methoden in der geographie, 167-180, 2018
62018
Package ‘tmap’
M Tennekes, J Nowosad, J Gombin, S Jeworutzki, K Russell, R Zijdeman, ...
42023
Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru
J Muenchow, P Dieker, T Böttcher, J Brock, G Didenko, T Fremout, ...
Ecography 43 (12), 1878-1890, 2020
42020
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Articles 1–20