Subpixel urban mapping over the conterminous U.S. (CONUS) using S-NPP VIIRS

Huiran Jin

doi:10.1109/IGARSS.2019.8900580

Subpixel urban mapping over the conterminous U.S. (CONUS) using S-NPP VIIRS

Huiran Jin

School of Applied Engr and Tech

Research output: Contribution to conference › Paper › peer-review

Abstract

A random forest regression model was developed to estimate subpixel urban percentage using the Visible Infrared Imaging Radiometer Suite (VIIRS) data and high quality calibration information derived from the National Land Cover Database (NLCD) 2011. Accuracy assessment resulted in a mean absolute error of 3.57% and a root mean square error of 8.50%. A wall-to-wall map of urban land use across the conterminous U. S. (CONUS) in 2012 was produced, demonstrating the utility of VIIRS observations for urban mapping at regional to larger scales.

Original language	English (US)
Pages	1903-1906
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS.2019.8900580
State	Published - 2019
Event	39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan Duration: Jul 28 2019 → Aug 2 2019

Conference

Conference	39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Country/Territory	Japan
City	Yokohama
Period	7/28/19 → 8/2/19

All Science Journal Classification (ASJC) codes

Computer Science Applications
General Earth and Planetary Sciences

Keywords

CONUS
Random forest
Subpixel mapping
Urban percentage
VIIRS

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10.1109/IGARSS.2019.8900580

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abstract = "A random forest regression model was developed to estimate subpixel urban percentage using the Visible Infrared Imaging Radiometer Suite (VIIRS) data and high quality calibration information derived from the National Land Cover Database (NLCD) 2011. Accuracy assessment resulted in a mean absolute error of 3.57% and a root mean square error of 8.50%. A wall-to-wall map of urban land use across the conterminous U. S. (CONUS) in 2012 was produced, demonstrating the utility of VIIRS observations for urban mapping at regional to larger scales.",

keywords = "CONUS, Random forest, Subpixel mapping, Urban percentage, VIIRS",

author = "Huiran Jin",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 ; Conference date: 28-07-2019 Through 02-08-2019",

year = "2019",

doi = "10.1109/IGARSS.2019.8900580",

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AB - A random forest regression model was developed to estimate subpixel urban percentage using the Visible Infrared Imaging Radiometer Suite (VIIRS) data and high quality calibration information derived from the National Land Cover Database (NLCD) 2011. Accuracy assessment resulted in a mean absolute error of 3.57% and a root mean square error of 8.50%. A wall-to-wall map of urban land use across the conterminous U. S. (CONUS) in 2012 was produced, demonstrating the utility of VIIRS observations for urban mapping at regional to larger scales.

KW - CONUS

KW - Random forest

KW - Subpixel mapping

KW - Urban percentage

KW - VIIRS

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T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019

Y2 - 28 July 2019 through 2 August 2019

ER -

Subpixel urban mapping over the conterminous U.S. (CONUS) using S-NPP VIIRS

Abstract

Conference

All Science Journal Classification (ASJC) codes

Keywords

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