Publications

Weng, Q., Liu, H., Liang, B. and D. Lu. 2008 (expected). The spatial variations of urban land surface temperatures: pertinent factors, zoning effect, and seasonal variability. Submitted to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS). Accepted on Dec. 17, 2007 .

Rajasekar, U. and Weng, Q. 2009 (expected) . Application of association rule mining for e xploring the relationship between urban land surface temperature and biophysical/social parameters. Submitted to Photogrammetric Engineering & Remote Sensing. Accepted on Dec. 11, 2007 .

Liu, H. and Q. Weng. 2009 (expected) . Scaling-up effect on the relationship between landscape pattern and land surface temperature. Submitted to Photogrammetric Engineering & Remote Sensing . Accepted on Nov. 14, 2007.

Weng, Q., Hu, X., and H. Liu. 2009 (expected). Estimating impervious surfaces using linear spectral mixture analysis with multi-temporal ASTER images. Submitted to International Journal of Remote Sensing. Accepted on Oct. 5, 2007.

Liang, B. and Weng, Q. 2008 (expected). A multi-scale analysis of census-based land surface temperature variations and determinants in Indianapolis, United States. Journal of Urban Planning and Development. Accepted September 20, 2007.

Liu, H. and Q. Weng. 2008 (expected). Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, U.S.A. Environmental Monitoring and Assessment.. Accepted August 31, 2007.

Weng, Q. and Lu, D. 2008 (expected). Sub-pixel analysis of urbanization effects on the interactions between land surface temperature and vegetation cover in Indianapolis, U.S.A. International Journal of Applied Earth Observation and Geoinformation . Accepted May 24, 2007.

Weng, Q., Hu, X. and D. Lu. 2008 (expected). Extracting impervious surface from medium spatial resolution multispectral and hyperspectral imagery: a comparison. Submitted to International Journal of Remote Sensing. on August 7, 2006. Accepted on May 12, 2007.

Melesse, A., Weng, Q., Thenkabail, P., and Senay, G. 2007. Remote sensing sensors and applications in environmental resources mapping and modeling. Sensors, 7 :  3209-3241 . 

Weng, Q., Liu, H. and D. Lu. 2007. Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States. Urban Ecosystems. 10(2): 1083-8155 (Print) 1573-1642 (Online).

Lu, D. and Weng, Q. 2006. Use of impervious surface in urban land use classification. Remote Sensing of Environment, 102(1-2): 146-160.

Lu, D. and Weng, Q. 2006. Spectral mixture analysis of ASTER imagery for examining the relationship between thermal features and biophysical descriptors in Indianapolis, Indiana. Remote Sensing of Environment, 104(2): 157-167.

Weng, Q., Lu, D. and B. Liang. 2006. Urban surface biophysical descriptors and land surface temperature variations. Photogrammetric Engineering & Remote Sensing, 72(11): 1275-1286.

Research Findings, 2006-07

Refereed Papers

Lu, D. and Weng, Q. 2006. Use of impervious surface in urban land use classification. Remote Sensing of Environment, 102(1-2): 146-160.

 Results showed that the integration of fraction images and surface temperature provided substantially improved impervious surface image. Accuracy assessment indicated that the root-mean-square error and system error yielded 9.22% and 5.68%, respectively, for the impervious surface image. The overall classification accuracy of 83.78% for five urban land-use classes was obtained.

Lu, D. and Weng, Q. 2006. Spectral mixture analysis of ASTER imagery for examining the relationship between thermal features and biophysical descriptors in Indianapolis, Indiana. Remote Sensing of Environment, 104(2): 157-167.

Results indicate that impervious surface was positively correlated with while vegetation negatively correlated with land surface temperature. Hot objects displayed a more significant role in influencing land surface temperature patterns than cold objects.

Weng, Q., Lu, D. and B. Liang. 2006. Urban surface biophysical descriptors and land surface temperature variations. Photogrammetric Engineering & Remote Sensing, 72(11): 1275-1286.

Results indicate that fraction images derived from spectral mixture analysis were effective for quantifying the urban morphology and for providing reliable measurements of biophysical variables such as vegetation abundance, soil, and impervious surface. An examination of land surface temperature (LST) variations within census block groups and their relationships with the compositions of land use and land cover (LULC) types, biophysical descriptors, and other relevant spatial data shows that LST possessed a weaker relation with the LULC compositions than with other variables (including urban biophysical descriptors, remote sensing biophysical variables, GIS-based impervious surface variables, and population density).

Weng, Q., Liu, H. and D. Lu. 2007 (expected). Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States. Urban Ecosystem. Accepted February 23, 2007.

Landscape metrics were found useful in examining the relationship between the land use and land cover and land surface temperature maps for deepening understanding of their interactions. Further research should be directed to the theoretical and applied implications of describing such relationships.

Book Chapters

Weng, Q. and D. Lu. 2006. Sub-pixel analysis of urban landscapes. In Weng, Q. and D. Quattrochi (eds.): Urban Remote Sensing. Boca Raton, FL: CRC/Taylor & Francis, pp. 71-90.

 Vegetation-Impervious surface-Soil model can provide an effective approach for characterizing urban landscape patterns by defining standardized component surfaces, and provide a physically based solution to quantifying spatial and temporal changes in urban landscape compositions. The V-I-S model may further act as a link between urban landscape components and remote sensing spectral data via the spectral unmixing model.

Lu, D. and Weng, Q. 2007. Mapping urban impervious surfaces from medium and high spatial resolution multispectral imagery. In Weng, Q. (ed.): Remote Sensing of Impervious Surfaces. Boca Raton, FL: CRC/Taylor & Francis, pp.--. Forthcoming.

The objective of this research is compare the advantages and disadvantages for extracting impervious surfaces from multispectral Landsat ETM+ image and from IKONOS data.

Refereed Papers in Progress

Weng, Q. and D. Lu. 2006. Landscape as a continuum: an examination of the urban landscape structures and dynamics of Indianapolis city. Under Review.

Results indicate that the Vegetation-Impervious surface-Soil model can provide an effective approach for characterizing urban landscape patterns by defining standardized component surfaces, and provide a physically based solution to quantifying spatial and temporal changes in urban landscape compositions. The V-I-S model may further act as a link between urban landscape components and remote sensing spectral data via the spectral unmixing model. Our study suggests that linear spectral mixture analysis provided a suitable technique to detect and map urban component surfaces in repetitive and consistent ways, and to decompose the spectral mixtures of medium resolution satellite imagery. Thus, a more realistic description and quantification of the true nature of urban landscapes is possible, as compared with conventional methods.

Weng, Q. and Lu, D. 2006. Sub-pixel analysis of urbanization effects on the interactions between land surface temperature and vegetation cover in Indianapolis, U.S.A. Accepted.

 Results indicate that multi-temporal fraction images were effective for quantifying the dynamics of urban morphology and for deriving a reliable measurement of environmental variables. Urbanization created an evolved inverse relationship between impervious and vegetation coverage, and brought about new LST patterns because of LST’s correlations with these environmental variables.

Liang, B. and Weng, Q. 2006. A multi-scale analysis of census-based land surface temperature variations and determinants in Indianapolis, Indiana. Under Review.

Land surface temperatures data of Indianapolis city, United States, were used to examine census-based variations and to model their numerical relationships with urban morphology. Selected variables for the urban morphology include Normalized Difference Vegetation Index, buildings, roads, and water bodies. Correlation analysis and stepwise regression modeling at each census level were performed. The sensitivity of the relationship to aggregation and thus the scale effect of Modifiable Areal Unit Problem were examined.

Weng, Q., Hu, X. and D. Lu. 2006. Extracting impervious surface from medium spatial resolution multispectral and hyperspectral imagery: a comparison. Submitted to International Journal of Remote Sensing . Accepted. pdf

In this paper, impervious surface fraction images were directly extracted from EO-1 Hyperion and ALI images by applying a fully constraint linear spectral mixture analysis. General methods for estimating and mapping urban impervious surfaces from medium resolution satellite imagery were explored.

Lu, D. and Q. Weng. 2006. Extraction of urban impervious surfaces from IKONOS imagery. Under Review.

The objective is to explore the approach to extract impervious surface areas from IKONOS data, through the use of a hybrid approach based on the combination of decision tree classifier and unsupervised classification in order to extract the dark impervious surface and other shadowed impervious surface areas.

Weng, Q., Liu, H., Liang, B. and D. Lu. 2006. The spatial variations of urban land surface temperatures: pertinent factors, zoning effect, and seasonal variability. Under Review.

This study aimed to analyze the spatial patterns of LSTs and to explore factors contributing to the LST variations in the City of Indianapolis, the United States. The potential factors were grouped into the categories of LULC composition, biophysical conditions, intensity of human activities, and landscape pattern. Statistical analyses were conducted to determine the relative importance of each group of the variables. Moreover, the spatial variations of LST were examined at both the residential and general zoning levels, so that the environmental effect of urban planning on LST may be assessed. By analyzing the mean and standard deviation values of normalized LSTs, the seasonal dynamics of LST were finally studied.

Liu, H. and Q. Weng. 2006. Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, U.S.A. Under Review.

This paper intended to examine the seasonal variations in the relationship between landscape pattern and land surface temperature based on a case study of Indianapolis, United States. The integration of remote sensing, GIS, and landscape ecology methods was used in this study. Four Terra’s ASTER images were used for the analysis.

Rajasekar, U. and Weng, Q. 2006. Urban heat island monitoring and analysis by data mining of MODIS imageries. Under Revision.

A procedure for monitoring of the urban heat is developed and experimented over selected location from the Indiana State, United States. Nine counties in the central Indiana were selected and the urban heat island patterns were modeled. 200 day and night relatively cloud free land surface temperature (LST) images of the year 2005 developed from Moderate Resolution Imaging Spectroradiometer (MODIS) imageries were used to estimate the urban heat island parameters.

Liu, H. and Q. Weng. 2006. Scaling-up effect on the relationship between landscape pattern and land surface temperature. Under Review.

The objective of this paper is to examine the scaling-up effect on the relationship between landscape pattern and land surface temperature. Every LULC and LST image was resampled to eight spatial scales: 15, 30, 60, 90, 120, 250, 500, and 1000 m. The scaling-up effect on the spatial and ecological characteristics of landscape patterns and LSTs were examined by the use of landscape metrics. An optimal spatial resolution was then determined on the basis of the minimum distance in landscape metric space.

Liang, B. and Weng, Q. 2006. Estimating Scale-dependent Land Surface Temperature - Vegetation Density Relationship Using Image Fusion. Under Review.

With the utilization of three types of images collected by Landsat ETM+, ASTER, and IKONOS sensors, this study investigates the scale-dependent relationship between land surface temperature (LST) and vegetation abundance in the Marion County, Indiana, USA.

Papers in Proceedings and Technical Reports

Liu, H. and Q. Weng. 2006. Seasonal urban thermal patterns based on land surface temperatures measured from ASTER imagery. Proceedings of 2006 ASPRS Annual Convention, Reno, Nevada, May 1-5. Unpaginated CD-ROM (12 pages).

The relationship between land use and land cover (LULC) and land surface temperatures varied with seasons.

Weng, Q., Lu, D. and B. Liang. 2007. Spatial variations of urban land surface temperatures. Proceedings of 2007 Urban Remote Sensing Joint Event, Paris, France, April 11-13. Unpaged CD-ROM (6 pages).

The causes of spatial variations in land surface temperatures in urban areas were analyzed.

Research Findings, 2005-06

Refereed Papers

Lu, D. and Weng, Q. 2006. Use of impervious surface in urban land use classification. Remote Sensing of Environment., Accepted.

Results showed that the integration of fraction images and surface temperature provided substantially improved impervious surface image. Accuracy assessment indicated that the root-mean-square error and system error yielded 9.22% and 5.68%, respectively, for the impervious surface image. The overall classification accuracy of 83.78% for five urban land-use classes was obtained.

Lu, D. and Weng, Q. 2006. Spectral mixture analysis of ASTER imagery for examining the relationship between thermal features and biophysical descriptors in Indianapolis, Indiana. Remote Sensing of Environment., Accepted.

Results indicate that impervious surface was positively correlated with while vegetation negatively correlated with land surface temperature. Hot objects displayed a more significant role in influencing land surface temperature patterns than cold objects.

Weng, Q., Lu, D. and B. Liang. 2006. Urban surface biophysical descriptors and land surface temperature variations. Photogrammetric Engineering & Remote Sensing., Accepted.

Results indicate that fraction images derived from spectral mixture analysis were effective for quantifying the urban morphology and for providing reliable measurements of biophysical variables such as vegetation abundance, soil, and impervious surface. An examination of land surface temperature (LST) variations within census block groups and their relationships with the compositions of land use and land cover (LULC) types, biophysical descriptors, and other relevant spatial data shows that LST possessed a weaker relation with the LULC compositions than with other variables (including urban biophysical descriptors, remote sensing biophysical variables, GIS-based impervious surface variables, and population density).

Book Chapters

Weng, Q. and D. Lu. 2006. Sub-pixel analysis of urban landscapes. In Weng, Q. and D. Quattrochi (eds.): Urban Remote Sensing. Boca Raton, FL: CRC/Taylor & Francis, pp.--. Forthcoming.

Vegetation-Impervious surface-Soil model can provide an effective approach for characterizing urban landscape patterns by defining standardized component surfaces, and provide a physically based solution to quantifying spatial and temporal changes in urban landscape compositions. The V-I-S model may further act as a link between urban landscape components and remote sensing spectral data via the spectral unmixing model.

Refereed Papers in Progress

Weng, Q. and D. Lu. 2006. Landscape as a continuum: an examination of the urban landscape structures and dynamics of Indianapolis city. Under Review.

Results indicate that the Vegetation-Impervious surface-Soil model can provide an effective approach for characterizing urban landscape patterns by defining standardized component surfaces, and provide a physically based solution to quantifying spatial and temporal changes in urban landscape compositions. The V-I-S model may further act as a link between urban landscape components and remote sensing spectral data via the spectral unmixing model. Our study suggests that linear spectral mixture analysis provided a suitable technique to detect and map urban component surfaces in repetitive and consistent ways, and to decompose the spectral mixtures of medium resolution satellite imagery. Thus, a more realistic description and quantification of the true nature of urban landscapes is possible, as compared with conventional methods.

 Weng, Q., Liu, H. and D. Lu. 2005. Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States. Submitted to Urban Ecosystems. Under Review.

Landscape metrics were found useful in examining the relationship between the land use and land cover and land surface temperature maps for deepening understanding of their interactions. Further research should be directed to the theoretical and applied implications of describing such relationships.

Papers in Proceedings and Technical Reports

Liu, H. and Q. Weng. 2006. Seasonal urban thermal patterns based on land surface temperatures measured from ASTER imagery. Proceedings of 2006 ASPRS Annual Convention, Reno, Nevada, May 1-5. Unpaginated CD-ROM (12 pages).

The relationship between land use and land cover (LULC) and land surface temperatures varied with seasons.