Follow
Catherine Lilian Nakalembe
Catherine Lilian Nakalembe
Assistant Professor, University of Maryland
Verified email at umd.edu - Homepage
Title
Cited by
Cited by
Year
Strengthening agricultural decisions in countries at risk of food insecurity: The GEOGLAM Crop Monitor for Early Warning
I Becker-Reshef, C Justice, B Barker, M Humber, F Rembold, R Bonifacio, ...
Remote Sensing of Environment 237, 111553, 2020
882020
A review of satellite-based global agricultural monitoring systems available for Africa
C Nakalembe, I Becker-Reshef, R Bonifacio, G Hu, ML Humber, ...
Global food security 29, 100543, 2021
522021
Agricultural land use change in Karamoja Region, Uganda
C Nakalembe, J Dempewolf, C Justice
Land Use Policy 62, 2-12, 2017
522017
Cropharvest: A global dataset for crop-type classification
G Tseng, I Zvonkov, CL Nakalembe, H Kerner
Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021
362021
Rapid response crop maps in data sparse regions
H Kerner, G Tseng, I Becker-Reshef, C Nakalembe, B Barker, B Munshell, ...
arXiv preprint arXiv:2006.16866, 2020
312020
Learning to predict crop type from heterogeneous sparse labels using meta-learning
G Tseng, H Kerner, C Nakalembe, I Becker-Reshef
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
302021
Characterizing agricultural drought in the Karamoja subregion of Uganda with meteorological and satellite-based indices
C Nakalembe
Natural Hazards 91 (3), 837-862, 2018
262018
Urgent and critical need for sub-Saharan African countries to invest in Earth observation-based agricultural early warning and monitoring systems
C Nakalembe
Environmental Research Letters 15 (12), 121002, 2020
162020
Validation of automatically generated global and regional cropland data sets: the case of Tanzania
JC Laso Bayas, L See, C Perger, C Justice, C Nakalembe, J Dempewolf, ...
Remote Sensing 9 (8), 815, 2017
15*2017
Street2sat: A machine learning pipeline for generating ground-truth geo-referenced labeled datasets from street-level images
M Paliyam, C Nakalembe, K Liu, R Nyiawung, H Kerner
ICML 2021 Workshop on Tackling Climate Change with Machine Learning, 2021
112021
Field-level crop type classification with k nearest neighbors: A baseline for a new Kenya smallholder dataset
H Kerner, C Nakalembe, I Becker-Reshef
arXiv preprint arXiv:2004.03023, 2020
112020
Considerations for AI-EO for agriculture in Sub-Saharan Africa
C Nakalembe, H Kerner
Institute of Physics, 2023
92023
Annual and in-season mapping of cropland at field scale with sparse labels
G Tseng, H Kerner, C Nakalembe, I Becker-Reshef
Proceedings of the Thirty-fourth Conference on Neural Information Processing …, 2020
92020
Enhancing access and usage of earth observations in environmental decision-making in eastern and southern africa through capacity building
S Shukla, D Macharia, GJ Husak, M Landsfeld, CL Nakalembe, ...
Frontiers in Sustainable Food Systems 5, 504063, 2021
72021
Cropharvest: a global satellite dataset for crop type classification
G Tseng, I Zvonkov, C Nakalembe, H Kerner
Neural Information Processing Systems (NeurIPS), 2021
72021
Sowing seeds of food security in africa
C Nakalembe, C Justice, H Kerner, C Justice, I Becker-Reshef
Eos (Washington. DC) 102, 2021
72021
A review of satellite-based global agricultural monitoring systems available for Africa, Glob. Food Secur., 29, 100543
C Nakalembe, I Becker-Reshef, R Bonifacio, G Hu, ML Humber, ...
52021
How accurate are existing land cover maps for agriculture in Sub-Saharan Africa?
H Kerner, C Nakalembe, A Yang, I Zvonkov, R McWeeny, G Tseng, ...
arXiv preprint arXiv:2307.02575, 2023
42023
Discovering inclusivity in remote sensing: Leaving no one behind
KE Joyce, CL Nakalembe, C Gómez, G Suresh, K Fickas, M Halabisky, ...
Frontiers in Remote Sensing 3, 869291, 2022
42022
Limitations of remote sensing in assessing vegetation damage due to the 2019–2021 desert locust upsurge
EC Adams, HB Parache, E Cherrington, WL Ellenburg, V Mishra, R Lucey, ...
Frontiers in Climate 3, 714273, 2021
42021
The system can't perform the operation now. Try again later.
Articles 1–20