SH
Member Since 2008
Solomon M. Hsiang
Professor, University of California Berkeley
AGU Research
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Combining Modern High Resolution Satellite Imagery with Historical Aerial Photography to Map Changes in Population Distribution
SCIENCE AND APPLICATIONS ENABLED BY REMOTE SENSING DATA FUSION AND TIME SERIES ANALYSIS II POSTER
biogeosciences | 15 december 2023
Joel Ferguson, Trinetta Chong, Hannah Druckenmille...
We are currently constructing the first sub-national measures of population for more than 60 countries across the developing world between 1939 and 19...
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Chapter 19 - Economics - The Fifth National Climate Assessment
THE FIFTH NATIONAL CLIMATE ASSESSMENT: RISKS, IMPACTS, AND RESPONSES POSTER
science and society | 12 december 2023
Simon Greenhill, Solomon M. Hsiang, Jeremy Martini...
This poster is part of the Fifth National Climate Assessment (NCA5) poster series. NCA5 Chapter 19 - Economics outlines the myriad ways that climate c...
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Developing high resolution, historical land cover maps in Africa using deep learning and an aerial photography archive
ADVANCES IN CHARACTERIZING AND MONITORING LAND SYSTEM CHANGE USING REMOTE SENSING DATA IV ORAL
biogeosciences | 12 december 2023
Hikari Murayama, Trinetta Chong, Hannah Druckenmil...
Land cover maps are imperative to understanding how urban areas have expanded, how forests have recovered under conservation laws, and how the introdu...
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A window back in time: Combining aerial photography and machine learning to map urban change over the 20th century
APPLICATIONS OF MACHINE LEARNING AND DEEP LEARNING TO ADDRESS ENVIRONMENTAL CHALLENGES AND SUSTAINABLE DEVELOPMENT GOALS III ORAL
global environmental change | 12 december 2023
Simon Greenhill, Trinetta Chong, Hannah Druckenmil...
The recent explosion in the availability and quality of satellite imagery, in combination with advances in machine learning, are revolutionizing Earth...
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Global high-resolution estimates of the United Nations Human Development Index using satellite imagery and machine learning
UNION SESSION: BEYOND THE BLACK BOX—ADVANCING GEO-ML BY INCORPORATING CONTEXT WITH SPECIALIZED ARCHITECTURES, BENCHMARK DATASETS, AND TAILORED NOTIONS OF INTERPRETABILITY I ORAL
union sessions | 11 december 2023
Jonathan Proctor, Luke Sherman, Hannah Druckenmill...
The United Nations Human Development Index (HDI) is arguably the most widely used alternative to gross domestic product for measuring national develop...
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DSCIM-Coastal v1.1: An Open-Source Data Integration and Modeling Platform for Global Impacts of Sea Level Rise
EVERYONE, EVERYTHING, EVERYWHERE: SPATIAL DATA FOR SUSTAINABLE DEVELOPMENT AND ENVIRONMENTAL JUSTICE APPLICATIONS I POSTER
informatics | 11 december 2023
Ian W. Bolliger, Nicholas J. Depsky, Daniel P. All...
Sea level rise (SLR) may impose substantial economic costs to coastal communities worldwide, but characterizing its global impact remains challenging ...
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Labor Disutility in a Warmer World: The Impact of Climate Change on the Global Workforce
ADVANCES IN ESTIMATES OF ECONOMIC DAMAGES FROM CLIMATE CHANGE TO SUPPORT UPDATED SOCIAL COST OF GREENHOUSE GAS CALCULATIONS AND IMPACTS ON WATER AND AIR POLLUTION III POSTER
global environmental change | 14 december 2022
Ashwin Rode, Rachel Baker, Tamma Carleton, Anthony...
This paper develops the first globally comprehensive and empirically grounded estimates of worker disutility due to future temperature increases cause...
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Throwing caution to the wind: Common instrumental variables approaches to causal analysis of air pollution are flawed
CONNECTING CAUSE AND EFFECT IN ANALYSES OF COUPLED HUMAN AND GEOPHYSICAL SYSTEMS: THE EARLY TO MODERN ANTHROPOCENE I ORAL
global environmental change | 14 december 2022
Andrew Wilson, Jaecheol Lee, Solomon M. Hsiang
Instrumental variables (IVs) are a common approach for causal identification in applied econometrics. The IV strategy involves isolating plausibly ran...
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