DocumentCode
3461
Title
Quantifying Contribution of Land Use Types to Nighttime Light Using an Unmixing Model
Author
Xi Li ; Linlin Ge ; Xiaoling Chen
Author_Institution
State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China
Volume
11
Issue
10
fYear
2014
fDate
Oct. 2014
Firstpage
1667
Lastpage
1671
Abstract
In this study, a model is developed to quantify the land use contribution to nighttime light using coarse-resolution nighttime light imagery and fine-resolution land use data. We assumed that the nighttime light of a region can be represented by a linear combination of land use areas, with its nighttime light intensity (NLI) as coefficient. Based on an unmixing strategy, the NLI of each land use type was estimated. The Berlin City and MA State were used as study areas. For the Berlin City, we made use of nighttime light imagery from the Suomi National Polar-orbiting Partnership and the land use maps with 52 classes as data sets for analysis, and we used a nighttime aerial photograph to derive reference data. For the MA State, we made use of nighttime light imagery from the Defense Meteorological Satellite Program´s Operational Linescan System and the land use maps with 33 classes as data sets for analysis, and we used a nighttime photograph from the International Space Station to derive reference data. The reference NLI data were correlated with the estimated NLI data, and the R2 values of Berlin and Massachusetts were 0.7277 and 0.7982, respectively, proving that the proposed model is effective.
Keywords
geophysical image processing; image representation; image resolution; land use; photography; Berlin City; Defense Meteorological Satellite Program; International Space Station; MA State; Massachusetts; NLI; Suomi National Polar-orbiting partnership; coarse-resolution nighttime light imagery; fine-resolution land use data; image representation; land use contribution quantify; nighttime aerial photograph; nighttime light intensity; operational linescan system; unmixing model; Cities and towns; Data models; Image resolution; Remote sensing; Satellites; Sociology; Statistics; Land use; nighttime light; nonnegative least square (NLS); remote sensing; unmixing;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2014.2304496
Filename
6747967
Link To Document