Linda See
Linda See
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Cited by
Cited by
HydroTest: a web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts
CW Dawson, RJ Abrahart, LM See
Environmental Modelling & Software 22 (7), 1034-1052, 2007
Mapping global cropland and field size
S Fritz, L See, I McCallum, L You, A Bun, E Moltchanova, M Duerauer, ...
Global change biology 21 (5), 1980-1992, 2015
Contribution of citizen science towards international biodiversity monitoring
M Chandler, L See, K Copas, AMZ Bonde, BC López, F Danielsen, ...
Biological conservation 213, 280-294, 2017
Mapping local climate zones for a worldwide database of the form and function of cities
B Bechtel, PJ Alexander, J Böhner, J Ching, O Conrad, J Feddema, ...
ISPRS International Journal of Geo-Information 4 (1), 199-219, 2015
Comparing neural network and autoregressive moving average techniques for the provision of continuous river flow forecasts in two contrasting catchments
RJ Abrahart, L See
Hydrological processes 14 (11‐12), 2157-2172, 2000
Agent-based models of geographical systems
AJ Heppenstall, AT Crooks, LM See, M Batty
Springer Science & Business Media, 2011
Global livestock production systems
TP Robinson, PK Thornton, GN Francesconi, RL Kruska, F Chiozza, ...
FAO and ILRI, 2011
Geo-Wiki: An online platform for improving global land cover
S Fritz, I McCallum, C Schill, C Perger, L See, D Schepaschenko, ...
Environmental Modelling & Software 31, 110-123, 2012
Farming and the geography of nutrient production for human use: a transdisciplinary analysis
M Herrero, PK Thornton, B Power, JR Bogard, R Remans, S Fritz, ...
The Lancet Planetary Health 1 (1), e33-e42, 2017
Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting
RJ Abrahart, F Anctil, P Coulibaly, CW Dawson, NJ Mount, LM See, ...
Progress in Physical Geography 36 (4), 480-513, 2012
Data preprocessing for river flow forecasting using neural networks: wavelet transforms and data partitioning
B Cannas, A Fanni, L See, G Sias
Physics and Chemistry of the Earth, Parts A/B/C 31 (18), 1164-1171, 2006
Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information
L See, P Mooney, G Foody, L Bastin, A Comber, J Estima, S Fritz, N Kerle, ...
ISPRS International Journal of Geo-Information 5 (5), 55, 2016
Data-driven modelling: concepts, approaches and experiences
D Solomatine, LM See, RJ Abrahart
Practical hydroinformatics, 17-30, 2009
Highlighting continued uncertainty in global land cover maps for the user community
S Fritz, L See, I McCallum, C Schill, M Obersteiner, M Van der Velde, ...
Environmental Research Letters 6 (4), 044005, 2011
Calibration of a fuzzy cellular automata model of urban dynamics in Saudi Arabia
K Al-Ahmadi, L See, A Heppenstall, J Hogg
Ecological complexity 6 (2), 80-101, 2009
Land consolidation in Cyprus: why is an integrated planning and decision support system required?
D Demetriou, J Stillwell, L See
Land use policy 29 (1), 131-142, 2012
Citizen science and the United Nations sustainable development goals
S Fritz, L See, T Carlson, MM Haklay, JL Oliver, D Fraisl, R Mondardini, ...
Nature Sustainability 2 (10), 922-930, 2019
Identifying and quantifying uncertainty and spatial disagreement in the comparison of Global Land Cover for different applications
S Fritz, L See
Global Change Biology 14 (5), 1057-1075, 2008
Crime reduction through simulation: An agent-based model of burglary
N Malleson, A Heppenstall, L See
Computers, environment and urban systems 34 (3), 236-250, 2010
Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments
RJ Abrahart, L See
Hydrology and Earth System Sciences 6 (4), 655-670, 2002
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