Comparison of Earth Observing-1 ALI and Landsat ETM+ for crop identification and yield prediction in Mexico. - David B. Lobell; Gregory Asner (IEEE Trans. Geosci. Remote. Sens., 2003)

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping. - Sang Michael Xie; Neal Jean; Marshall Burke; David B. Lobell; Stefano Ermon (AAAI, 2016)

Mapping Smallholder Wheat Yields and Sowing Dates Using Micro-Satellite Data. - Meha Jain; Amit K. Srivastava; Balwinder Singh; Rajiv K. Joon; Andrew McDonald; Keitasha Royal; Madeline C. Lisaius; David B. Lobell (Remote. Sens., 2016)

Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data. - Jiaxuan You; Xiaocheng Li; Melvin Low; David B. Lobell; Stefano Ermon (AAAI, 2017)

Monitoring Ethiopian Wheat Fungus with Satellite Imagery and Deep Feature Learning. - Reid Pryzant; Stefano Ermon; David B. Lobell (CVPR Workshops, 2017)

Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning. - Anthony Perez 002; Christopher Yeh; George Azzari; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2017)

Hierarchical Modeling of Seed Variety Yields and Decision Making for Future Planting Plans. - Huaiyang Zhong; Xiaocheng Li; David B. Lobell; Stefano Ermon; Margaret L. Brandeau (CoRR, 2017)

Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa. - Zhenong Jin; George Azzari; Marshall Burke; Stephen Aston; David B. Lobell (Remote. Sens., 2017)

Deep Transfer Learning for Crop Yield Prediction with Remote Sensing Data. - Anna X. Wang; Caelin Tran; Nikhil Desai; David B. Lobell; Stefano Ermon (COMPASS, 2018)

Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning. - Barak Oshri; Annie Hu; Peter Adelson; Xiao Chen 014; Pascaline Dupas; Jeremy Weinstein; Marshall Burke; David B. Lobell; Stefano Ermon (KDD, 2018)

Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data. - Neal Jean; Sherrie Wang; Anshul Samar; George Azzari; David B. Lobell; Stefano Ermon (AAAI, 2019)

Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery. - Wenjie Hu; Jay Harshadbhai Patel; Zoe-Alanah Robert; Paul Novosad; Samuel Asher; Zhongyi Tang; Marshall Burke; David B. Lobell; Stefano Ermon (AIES, 2019)

Semantic Segmentation of Crop Type in Africa: A Novel Dataset and Analysis of Deep Learning Methods. - Rose M. Rustowicz; Robin Cheong; Lijing Wang; Stefano Ermon; Marshall Burke; David B. Lobell (CVPR Workshops, 2019)

Learning to Interpret Satellite Images using Wikipedia. - Burak Uzkent; Evan Sheehan; Chenlin Meng; Zhongyi Tang; Marshall Burke; David B. Lobell; Stefano Ermon (IJCAI, 2019)

Predicting Economic Development using Geolocated Wikipedia Articles. - Evan Sheehan; Chenlin Meng; Matthew Tan; Burak Uzkent; Neal Jean; Marshall Burke; David B. Lobell; Stefano Ermon (KDD, 2019)

Semi-Supervised Multitask Learning on Multispectral Satellite Images Using Wasserstein Generative Adversarial Networks (GANs) for Predicting Poverty. - Anthony Perez 002; Swetava Ganguli; Stefano Ermon; George Azzari; Marshall Burke; David B. Lobell (CoRR, 2019)

Learning to Interpret Satellite Images in Global Scale Using Wikipedia. - Burak Uzkent; Evan Sheehan; Chenlin Meng; Zhongyi Tang; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2019)

Farm Parcel Delineation Using Spatio-temporal Convolutional Networks. - Han Lin Aung; Burak Uzkent; Marshall Burke; David B. Lobell; Stefano Ermon (CVPR Workshops, 2020)

Meta-Learning for Few-Shot Land Cover Classification. - Marc Rußwurm; Sherrie Wang; Marco Körner 001; David B. Lobell (CVPR Workshops, 2020)

Landsat-Based Reconstruction of Corn and Soybean Yield Histories in the United States Since 1999. - David B. Lobell; Walter T. Dado; Jillian M. Deines; Stefania Di Tommaso; Sherrie Wang (IGARSS, 2020)

Generating Interpretable Poverty Maps using Object Detection in Satellite Images. - Kumar Ayush; Burak Uzkent; Marshall Burke; David B. Lobell; Stefano Ermon (IJCAI, 2020)

Farmland Parcel Delineation Using Spatio-temporal Convolutional Networks. - Han Lin Aung; Burak Uzkent; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2020)

Efficient Poverty Mapping using Deep Reinforcement Learning. - Kumar Ayush; Burak Uzkent; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2020)

Predicting Livelihood Indicators from Crowdsourced Street Level Images. - Jihyeon Janel Lee; Dylan Grosz; Sicheng Zeng; Burak Uzkent; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2020)

Using satellite imagery to understand and promote sustainable development. - Marshall Burke; Anne Driscoll; David B. Lobell; Stefano Ermon (CoRR, 2020)

High-Resolution Soybean Yield Mapping Across the US Midwest Using Subfield Harvester Data. - Walter T. Dado; Jillian M. Deines; Rinkal Patel; Sang-Zi Liang; David B. Lobell (Remote. Sens., 2020)

Sight for Sorghums: Comparisons of Satellite- and Ground-Based Sorghum Yield Estimates in Mali. - David B. Lobell; Stefania Di Tommaso; Calum You; Ismael Yacoubou Djima; Marshall Burke; Talip Kilic (Remote. Sens., 2020)

Weakly Supervised Deep Learning for Segmentation of Remote Sensing Imagery. - Sherrie Wang; William Chen; Sang Michael Xie; George Azzari; David B. Lobell (Remote. Sens., 2020)

Mapping Crop Types in Southeast India with Smartphone Crowdsourcing and Deep Learning. - Sherrie Wang; Stefania Di Tommaso; Joey Faulkner; Thomas Friedel; Alexander Kennepohl; Rob Strey; David B. Lobell (Remote. Sens., 2020)

Efficient Poverty Mapping from High Resolution Remote Sensing Images. - Kumar Ayush; Burak Uzkent; Kumar Tanmay; Marshall Burke; David B. Lobell; Stefano Ermon (AAAI, 2021)

Predicting Livelihood Indicators from Community-Generated Street-Level Imagery. - Jihyeon Janel Lee; Dylan Grosz; Burak Uzkent; Sicheng Zeng; Marshall Burke; David B. Lobell; Stefano Ermon (AAAI, 2021)

Geography-Aware Self-Supervised Learning. - Kumar Ayush; Burak Uzkent; Chenlin Meng; Kumar Tanmay; Marshall Burke; David B. Lobell; Stefano Ermon (ICCV, 2021)

Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis. - Yutong He; Dingjie Wang; Nicholas Lai; William Zhang 004; Chenlin Meng; Marshall Burke; David B. Lobell; Stefano Ermon (NeurIPS, 2021)

SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning. - Christopher Yeh; Chenlin Meng; Sherrie Wang; Anne Driscoll; Erik Rozi; Patrick Liu; Jihyeon Janel Lee; Marshall Burke; David B. Lobell; Stefano Ermon (NeurIPS Datasets and Benchmarks, 2021)

Two Shifts for Crop Mapping: Leveraging Aggregate Crop Statistics to Improve Satellite-based Maps in New Regions. - Dan M. Kluger; Sherrie Wang; David B. Lobell (CoRR, 2021)

Combining GEDI and Sentinel-2 for wall-to-wall mapping of tall and short crops. - Stefania Di Tommaso; Sherrie Wang; David B. Lobell (CoRR, 2021)

Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach. - Chenxi Lin; Liheng Zhong; Xiao-Peng Song; Jinwei Dong; David B. Lobell; Zhenong Jin (CoRR, 2021)

Scalable deep learning to identify brick kilns and aid regulatory capacity. - Jihyeon Janel Lee; Nina R. Brooks; Fahim Tajwar; Marshall Burke; Stefano Ermon; David B. Lobell; Debashish Biswas; Stephen P. Luby (Proc. Natl. Acad. Sci. USA, 2021)

Twice Is Nice: The Benefits of Two Ground Measures for Evaluating the Accuracy of Satellite-Based Sustainability Estimates. - David B. Lobell; Stefania Di Tommaso; Marshall Burke; Talip Kilic (Remote. Sens., 2021)

Using Sentinel-1, Sentinel-2, and Planet Imagery to Map Crop Type of Smallholder Farms. - Preeti Rao; Weiqi Zhou; Nishan Bhattarai; Amit K. Srivastava; Balwinder Singh; Shishpal Poonia; David B. Lobell; Meha Jain (Remote. Sens., 2021)

IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling. - Chenlin Meng; Enci Liu; Willie Neiswanger; Jiaming Song; Marshall Burke; David B. Lobell; Stefano Ermon (AAAI, 2022)

Understanding economic development in rural Africa using satellite imagery, building footprints and deep models. - Amna Elmustafa; Erik Rozi; Yutong He; Gengchen Mai; Stefano Ermon; Marshall Burke; David B. Lobell (SIGSPATIAL/GIS, 2022)

SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery. - Yezhen Cong; Samar Khanna; Chenlin Meng; Patrick Liu; Erik Rozi; Yutong He; Marshall Burke; David B. Lobell; Stefano Ermon (NeurIPS, 2022)

Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution. - Yutong He; William Zhang 004; Chenlin Meng; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2022)

Mapping Sugarcane in Central India with Smartphone Crowdsourcing. - Ju Young Lee; Sherrie Wang; Anjuli Jain Figueroa; Rob Strey; David B. Lobell; Rosamond L. Naylor; Steven M. Gorelick (Remote. Sens., 2022)

Unlocking Large-Scale Crop Field Delineation in Smallholder Farming Systems with Transfer Learning and Weak Supervision. - Sherrie Wang; François Waldner; David B. Lobell (Remote. Sens., 2022)

Building Coverage Estimation with Low-resolution Remote Sensing Imagery. - Enci Liu; Chenlin Meng; Matthew Kolodner; Eun Jee Sung; Sihang Chen; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2023)

Annual Field-Scale Maps of Tall and Short Crops at the Global Scale Using GEDI and Sentinel-2. - Stefania Di Tommaso; Sherrie Wang; Vivek Vajipey; Noel Gorelick; Rob Strey; David B. Lobell (Remote. Sens., 2023)

Canopy Height Mapping for Plantations in Nigeria Using GEDI, Landsat, and Sentinel-2. - Angela Tsao; Ikenna Nzewi; Ayodeji Jayeoba; Uzoma Ayogu; David B. Lobell (Remote. Sens., 2023)

HarvestNet: A Dataset for Detecting Smallholder Farming Activity Using Harvest Piles and Remote Sensing. - Jonathan Xu; Amna Elmustafa; Liya Weldegebriel; Emnet Negash; Richard Lee; Chenlin Meng; Stefano Ermon; David B. Lobell (AAAI, 2024)

DiffusionSat: A Generative Foundation Model for Satellite Imagery. - Samar Khanna; Patrick Liu; Linqi Zhou; Chenlin Meng; Robin Rombach; Marshall Burke; David B. Lobell; Stefano Ermon (ICLR, 2024)

GeoLLM: Extracting Geospatial Knowledge from Large Language Models. - Rohin Manvi; Samar Khanna; Gengchen Mai; Marshall Burke; David B. Lobell; Stefano Ermon (ICLR, 2024)

Large Language Models are Geographically Biased. - Rohin Manvi; Samar Khanna; Marshall Burke; David B. Lobell; Stefano Ermon (ICML, 2024)

ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts. - Samar Khanna; Medhanie Irgau; David B. Lobell; Stefano Ermon (CoRR, 2024)