activity
20172022
most citedPoverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning

51 citations · 126 across the 7 of their papers we have counts for

collaborators

15 papers

eess.IV20228 cited

Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution

Yutong He, William Zhang, Chenlin Meng +3

Automated tracking of urban development in areas where construction information is not available became possible with recent advancements in machine learning and remote sensing. Un…

cs.CV20216 cited

Wildfire smoke plume segmentation using geostationary satellite imagery

Jeff Wen, Marshall Burke

Wildfires have increased in frequency and severity over the past two decades, especially in the Western United States. Beyond physical infrastructure damage caused by these wildfir…

cs.SI202116 cited

Using Localized Twitter Activity for Red Tide Impact Assessment

A. Skripnikov, N. Wagner, J. Shafer +3

Red tide blooms of the dinoflagellate Karenia brevis (K. brevis) produce toxic coastal conditions that can impact marine organisms and human health, while also affecting local econ…

cs.CY2020

Using satellite imagery to understand and promote sustainable development

Marshall Burke, Anne Driscoll, David B. Lobell +1

Accurate and comprehensive measurements of a range of sustainable development outcomes are fundamental inputs into both research and policy. We synthesize the growing literature th…

cs.CV2020

Predicting Livelihood Indicators from Community-Generated Street-Level Imagery

Jihyeon Lee, Dylan Grosz, Burak Uzkent +4

Major decisions from governments and other large organizations rely on measurements of the populace's well-being, but making such measurements at a broad scale is expensive and thu…

cs.CV2020

Efficient Poverty Mapping using Deep Reinforcement Learning

Kumar Ayush, Burak Uzkent, Kumar Tanmay +3

The combination of high-resolution satellite imagery and machine learning have proven useful in many sustainability-related tasks, including poverty prediction, infrastructure meas…