George Azzari
George Azzari
Research Associate - Stanford University
Verified email at - Homepage
Cited by
Cited by
Using publicly available satellite imagery and deep learning to understand economic well-being in Africa
C Yeh, A Perez, A Driscoll, G Azzari, Z Tang, D Lobell, S Ermon, M Burke
Nature communications 11 (1), 2583, 2020
Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques
S Wang, G Azzari, DB Lobell
Remote sensing of environment 222, 303-317, 2019
Smallholder maize area and yield mapping at national scales with Google Earth Engine
Z Jin, G Azzari, C You, S Di Tommaso, S Aston, M Burke, DB Lobell
Remote sensing of environment 228, 115-128, 2019
Landsat-based classification in the cloud: An opportunity for a paradigm shift in land cover monitoring
G Azzari, DB Lobell
Remote Sensing of Environment 202, 64-74, 2017
Weakly supervised deep learning for segmentation of remote sensing imagery
S Wang, W Chen, SM Xie, G Azzari, DB Lobell
Remote Sensing 12 (2), 207, 2020
Tile2vec: Unsupervised representation learning for spatially distributed data
N Jean, S Wang, A Samar, G Azzari, D Lobell, S Ermon
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3967-3974, 2019
Towards fine resolution global maps of crop yields: Testing multiple methods and satellites in three countries
G Azzari, M Jain, DB Lobell
Remote Sensing of Environment 202, 129-141, 2017
Rapid characterization of vegetation structure with a Microsoft Kinect sensor
G Azzari, ML Goulden, RB Rusu
Sensors 13 (2), 2384-2398, 2013
Eyes in the sky, boots on the ground: Assessing satellite‐and ground‐based approaches to crop yield measurement and analysis
DB Lobell, G Azzari, M Burke, S Gourlay, Z Jin, T Kilic, S Murray
American Journal of Agricultural Economics 102 (1), 202-219, 2020
Improving the accuracy of satellite-based high-resolution yield estimation: A test of multiple scalable approaches
Z Jin, G Azzari, DB Lobell
Agricultural and forest meteorology 247, 207-220, 2017
Satellite detection of cover crops and their effects on crop yield in the Midwestern United States
CA Seifert, G Azzari, DB Lobell
Environmental Research Letters 13 (6), 064033, 2018
Mapping smallholder yield heterogeneity at multiple scales in Eastern Africa
Z Jin, G Azzari, M Burke, S Aston, DB Lobell
Remote Sensing 9 (9), 931, 2017
Poverty prediction with public landsat 7 satellite imagery and machine learning
A Perez, C Yeh, G Azzari, M Burke, D Lobell, S Ermon
arXiv preprint arXiv:1711.03654, 2017
Satellite detection of rising maize yield heterogeneity in the US Midwest
DB Lobell, G Azzari
Environmental Research Letters 12 (1), 014014, 2017
Satellite mapping of tillage practices in the North Central US region from 2005 to 2016
G Azzari, P Grassini, JIR Edreira, S Conley, S Mourtzinis, DB Lobell
Remote Sensing of Environment 221, 417-429, 2019
Quantifying fire‐wide carbon emissions in interior Alaska using field measurements and Landsat imagery
BM Rogers, S Veraverbeke, G Azzari, CI Czimczik, SR Holden, ...
Journal of Geophysical Research: Biogeosciences 119 (8), 1608-1629, 2014
Semi-supervised multitask learning on multispectral satellite images using wasserstein generative adversarial networks (gans) for predicting poverty
A Perez, S Ganguli, S Ermon, G Azzari, M Burke, D Lobell
arXiv preprint arXiv:1902.11110, 2019
The impact of agricultural interventions can be doubled by using satellite data
M Jain, P Rao, AK Srivastava, S Poonia, J Blesh, G Azzari, AJ McDonald, ...
Nature Sustainability 2 (10), 931-934, 2019
Eyes in the sky, boots on the ground: assessing satellite-and ground-based approaches to crop yield measurement and analysis in Uganda
DB Lobell, G Azzari, M Burke, S Gourlay, Z Jin, T Kilic, S Murray
World Bank Policy Research Working Paper, 2018
From sunlight to seed: Assessing limits to solar radiation capture and conversion in agro-ecosystems
JIR Edreira, S Mourtzinis, G Azzari, JF Andrade, SP Conley, D Lobell, ...
Agricultural and Forest Meteorology 280, 107775, 2020
The system can't perform the operation now. Try again later.
Articles 1–20