Detecting Impervious Cover with Artificial Lighting in Astronaut Photography from the International Space Station

Impervious cover continues to pose a threat to flood-prone regions, especially the ones in dense urban areas. Mapping the location of impervious surface becomes vital to properly managing drainage and runoff in a city, along with the health of fluvial ecosystems. Kotarba and Aleksandrowicz, in 2016, tested the ability of nighttime astronaut imagery from the International Space Station (ISS) to detect impervious cover. The artificial lighting emitted from a city’s nightscape is used as a proxy for imperviousness. This paper expands on their research by focusing on the nightscape in San Antonio, TX from December 2015, and by observing the effect the camera look angle has on impervious surface detection. Analysis was done by comparing the ISS light intensity imagery to 2016 National Land Cover Database (NLCD) Degree of Imperviousness ground reference data on the basis of low, medium, and high urban density. Difference images between reclassified ISS images and the NLCD reference data for low, medium, and high imperviousness were calculated with up to 49% kappa accuracy, a moderate agreement. ISS images’ overall accuracy increased with the growth of the threshold for urban density although the kappa statistic was highest with the smallest threshold for imperviousness. ISS photographs classified dense urban areas correctly but failed to correctly classify poorly lit impervious surfaces such as rural roadways, residential neighborhoods, and airport runways. ISS imagery had a high producer’s accuracy, particularly with lower thresholds for imperviousness, meaning that the likelihood is high that impervious cover detected by the ISS is actually impervious cover. Overall, ISS imagery detects impervious surfaces moderately well and may be more accurate due to the imperfect nature of the ground reference data.

Name thesis:degree_name

Masters of Applied Geography

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Geographic Information Science

Grantor

Texas State University

Year dc:date.issued

2020

Author dc:creator

• Johnson, Bradley

Advisor dc:contributor.advisor

• Currit, Nathan Allen

Committee member dc:contributor.committeemember

• Yuan, Yihong

• impervious cover
• artificial lighting
• astronaut photography
• international space station
• San Antonio

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10877/11988

OAI identifier oai:identifier

oai:digital.library.txst.edu:10877/11988