Remote Sensing—Methods and Applications

Session Submission Type: Full Paper Panel

Session Description

Earth observation with satellite imagery has experienced explosive growth over the past decade as new satellite-mounted sensors proliferate and image-as-data methods expand the uses for the petabytes of publicly available data those sensors produce. Now every location on Earth is observed by public satellites on a daily basis by satellites with varying spatial, spectral, and temporal resolution. This explosion of data allows researchers to precisely and frequently measure outcomes which were previously only available Through expensive on the ground measurement. This panel highlights recent methods for and applications of satellite imagery as a data source in political science. In the first paper Bluhm, Lessmann and Schaudt study the economic effects of gaining or losing subnational capital status using daytime and nighttime satellite imagery. Kikuta and Kamahara use satellite-measured forest cover test whether a new environmental code introduced after the “Great War of Africa” was able to reduce the deforestation associated with mining. In the third paper Kim, Naoi and Sasaki test whether differences in trade agreements are associated with electoral institutions using remotely sensed data on concentration of agricultural commodities and product-level data on trade agreements. Finally Sanford provides and validates best practices for using satellite data for measurement and discusses how to use unique sources of variation in the data for causal inference.

Sub Unit

• Division 8: Political Methodology

Individual Presentations

• The Political Geography of Cities - Richard Bluhm, Leibniz University Hannover

• Environmental Protection after Civil War: Mining and Deforestation in the DRC - Kyosuke Kikuta, Japan External Trade Organization; Yuta Kamahara, Yokohama National University

• Geographic Concentration and Agricultural Trade Liberalization - In Song Kim, Massachusetts Institute of Technology; Megumi Naoi, University of California, San Diego; Tomoya Sasaki, MIT

• Remote Sensing: Measurement and Causal Inference - Luke Sanford, Yale University

Chair

• Michelle Torres Rice University

Discussant

• Carl Müller-Crepon Oxford University