@article{75bdd5f9cf184eda8c31502c534b306e,
title = "Satellite scatterometer estimation of urban built-up volume: Validation with airborne lidar data",
abstract = " Accurately mapping urban infrastructure and extent is a high priority for resource management and service allocation as well as for addressing environmental, socioeconomic, and geopolitical concerns. Most available data products only document surficial (two-dimensional) land use and land cover (LULC), yet a substantial component of urban growth occurs in the vertical dimension. Light detection and ranging (lidar) data offer the potential for monitoring three-dimensional (3D) change, but the extreme lack of systematic lidar coverage worldwide inflicts considerable gaps in both spatial and temporal coverage. Satellite scatterometer (radar) data may serve as an alternative data source for characterizing urban growth and development in both the horizontal and vertical directions. The accuracy of these radar-based datasets for estimating building volumes remains to be validated quantitatively. For nine U.S. cities, we test whether scatterometer data can be used to estimate 3D urban built-up volume. We found strong, linear correlations between the lidar-derived and radar-derived building volume estimates for all cities with r 2 values as high as 0.98 when using spatial trend analysis. Given the high expense that limits lidar data acquisition to small areas at sporadic points in time, satellite scatterometer data provide a breakthrough method for monitoring both vertical growth and horizontal expansion of cities across the world with a continuous decadal time scale. ",
keywords = "Built-up volume, Dense sampling method, Land cover, Land use, Lidar, Radar",
author = "Mathews, {Adam J.} and Frazier, {Amy E.} and Nghiem, {Son V.} and Gregory Neumann and Yun Zhao",
note = "Funding Information: This material is based upon work supported by the National Aeronautics and Space Administration (NASA) under Grant No. NNX15AK42A issued through Oklahoma NASA EPSCoR to A.J. Mathews and A.E. Frazier in collaboration with the NASA Jet Propulsion Laboratory (JPL). The research carried out at the JPL (S.V. Nghiem and G. Neumann), California Institute of Technology, was supported by the NASA Land Cover/Land Use Change (LCLUC) Program and in part by the NASA Earth Science R&A Program. The authors wish to thank the Army Geospatial Center for providing the lidar data used in this study. Additionally, we appreciate the efforts of Emily A. Ellis, K. Colton Flynn, and Gustavo A. Ovando-Montejo in processing the lidar datasets. Availability of the data used in this study: QuikSCAT satellite data from the NASA JPL ( https://podaac.jpl.nasa.gov ) and lidar data from the Army Geospatial Center with permission ( https://www.agc.army.mil ). Funding Information: This material is based upon work supported by the National Aeronautics and Space Administration (NASA) under Grant No. NNX15AK42A issued through Oklahoma NASA EPSCoR to A.J. Mathews and A.E. Frazier in collaboration with the NASA Jet Propulsion Laboratory (JPL). The research carried out at the JPL (S.V. Nghiem and G. Neumann), California Institute of Technology, was supported by the NASA Land Cover/Land Use Change (LCLUC) Program and in part by the NASA Earth Science R&A Program. The authors wish to thank the Army Geospatial Center for providing the lidar data used in this study. Additionally, we appreciate the efforts of Emily A. Ellis, K. Colton Flynn, and Gustavo A. Ovando-Montejo in processing the lidar datasets. Availability of the data used in this study: QuikSCAT satellite data from the NASA JPL (https://podaac.jpl.nasa.gov) and lidar data from the Army Geospatial Center with permission (https://www.agc.army.mil). Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",
year = "2019",
month = may,
doi = "10.1016/j.jag.2019.01.004",
language = "English (US)",
volume = "77",
pages = "100--107",
journal = "International Journal of Applied Earth Observation and Geoinformation",
issn = "1569-8432",
publisher = "Elsevier",
}