Access the full text.
Sign up today, get DeepDyve free for 14 days.
R. Daniels, T. Boden, D. Easterling, T. Karl, E. Mason, P. Hughes, D. Bowman (1996)
United States Historical Climatology Network (US HCN) monthly temperature and precipitation data
K. Gallo, Alan Mcnab, T. Karl, Jesslyn Brown, J. Hood, J. Tarpley (1993)
The use of NOAA AVHRR data for assessment of the urban heat island effectJournal of Applied Meteorology, 32
J. Eidenshink (1992)
The 1990 conterminous U. S. AVHRR data setPhotogrammetric Engineering and Remote Sensing, 58
T. Karl, H. Diaz, G. Kukla (1988)
Urbanization: Its Detection and Effect in the United States Climate RecordJournal of Climate, 1
T. Stohlgren, T. Chase, R. Pielke, .. Sr, T. Kittel, J. Baron (1998)
Evidence that local land use practices influence regional climate, vegetation, and stream flow patterns in adjacent natural areasGlobal Change Biology, 4
L. Stowe (1991)
Cloud and aerosol products at NOAA/NESDISGlobal and Planetary Change, 4
T. Oke (1973)
City size and the urban heat islandAtmospheric Environment, 7
C. Elvidge, K. Baugh, E. Kihn, H. Kroehl, E. Davis, C. Davis (1997)
Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumptionInternational Journal of Remote Sensing, 18
J. Voogt, T. Oke (1997)
Complete urban surface temperaturesJournal of Applied Meteorology, 36
J. Townshend, C. Justice, D. Skole, J. Malingreau, J. Cihlar, P. Teillet, F. Sadowski, S. Ruttenberg (1994)
The 1 km resolution global data set: needs of the International Geosphere Biosphere Programme†International Journal of Remote Sensing, 15
T. Owen (1998)
Using DMSP-OLS light frequency data to categorize urban environments associated with US climate observing stationsInternational Journal of Remote Sensing, 19
M. Roth, T. Oke, W. Emery (1989)
Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatologyInternational Journal of Remote Sensing, 10
S. Changnon (1992)
Inadvertent Weather Modification in Urban Areas: Lessons for Global Climate ChangeBulletin of the American Meteorological Society, 73
C. Elvidge, K. Baugh, E. Kihn, H. Kroehl, E. Davis (1997)
Mapping City Lights With Nighttime Data from the DMSP Operational Linescan SystemPhotogrammetric Engineering and Remote Sensing, 63
J. Monteith, T. Oke (1979)
Boundary Layer Climates.Journal of Applied Ecology, 17
K. Gallo, J. Tarpley (1996)
The comparison of vegetation index and surface temperature composites for urban heat-island analysisInternational Journal of Remote Sensing, 17
M. Imhoff, W. Lawrence, D. Stutzer, C. Elvidge (1997)
A Technique for Using Composite DMSP/OLS "City Lights"Satellite Data to Map Urban AreaRemote Sensing of Environment, 61
T. Loveland, A. Belward (1997)
The IGBP-DIS global 1km land cover data set, DISCover: First resultsInternational Journal of Remote Sensing, 18
K. Gallo, D. Easterling, T. Peterson (1996)
The influence of land use/land cover on climatological values of the diurnal temperature rangeJournal of Climate, 9
K. Gallo, T. Owen, D. Easterling, P. Jamason (1999)
Temperature Trends of the U.S. Historical Climatology Network Based on Satellite-Designated Land Use/Land CoverJournal of Climate, 12
J. Price (1990)
Using spatial context in satellite data to infer regional scale evapotranspirationIEEE Transactions on Geoscience and Remote Sensing, 28
(1986)
Urban warming
T. Carlson (1986)
Regional‐scale estimates of surface moisture availability and thermal inertia using remote thermal measurements, 1
D. Cayan, A. Douglas (1984)
Urban Influences on Surface Temperatures in the Southwestern United States during Recent DecadesJournal of Applied Meteorology and Climatology, 23
Monthly and seasonal relationships between urban––rural differences in minimum, maximum, and average temperatures measured at surface-based observation stations were compared to satellite-derived Advanced Very High Resolution Radiometer estimates of a normalized difference vegetation index (NDVI) and surface radiant temperature ( T sfc ). The relationships between surface- and satellite-derived variables were developed during 1989––91 and tested on data acquired during 1992––93. The urban––rural differences in air temperature were linearly related to urban––rural differences in the NDVI and T sfc . A statistically significant but relatively small (less than 40%%) amount of the variation in these urban––rural differences in air temperature the urban heat island (UHI) bias was associated with variation in the urban––rural differences in NDVI and T sfc . A comparison of the satellite-based estimates of the UHI bias with population-based estimates of the UHI bias indicated similar levels of error. The use of satellite-derived data may contribute to a globally consistent method for analysis of the urban heat island bias.
Journal of Applied Meteorology – American Meteorological Society
Published: Apr 17, 1998
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.