rel="nofollow" href="https://doi.org/10.3390/su71115570">10.3390/su71115570.
27 Gamba, P., and Houshmand, B. (2002). Joint analysis of SAR, LIDAR and aerial imagery for simultaneous extraction of land cover, DTM and 3D shape of buildings. International Journal of Remote Sensing 23(20): 4439–4450. doi:10.1080/01431160110114952.
28 Gamba, P., Dell'Acqua, F., and Dasarathy, B.V. (2005). Urban remote sensing using multiple data sets: past, present, and future. Information Fusion 6: 319–326. doi:10.1016/j.inffus.2005.02.007.
29 Geiß, C., Leichtle, T., Wurm, M., Pelizari, P.A., Standfuß, I., Zhu, X.X., So, E., Siedentop, S., Esch, T., and Taubenbock, H. (2019). Large‐area characterization of urban morphology—mapping of built‐up height and density using TanDEM‐X and Sentinel‐2 data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12(8): 2912–2927. doi:10.1109/JSTARS.2019.2917755.
30 Golovinskiy, A., Kim, V.G., and Funkhouser, T. (2009). Shape‐based recognition of 3D point clouds in urban environments. IEEE 12th International Conference on Computer Vision 2154–2161. doi:10.1109/ICCV.2009.5459471.
31 Groisman, P., Shugart, H., Kicklighter, D., Henebry, G., Tchebakova, N., Maksyutov, S., Monier, E., Gutman, G., Gulev, S., Qi, J., Prishchepov, A., Kukavskaya, E., Porfiriev, B., Shiklomanov, A., Loboda, T., Shiklomanov, N., Nghiem, S., Bergen, K., Albrechtová, J., Chen, J., Shahgedanova, M., Shvidenko, A., Speranskaya, N., Soja, A., de Beurs, K, Bulygina, O., McCarty, J., Zhuang, Q., and Zolina, O. (2017). Northern Eurasia future initiative (NEFI): facing the challenges and pathways of global change in the 21st century. Progress in Earth and Planetary Science 4: 41. doi:10.1186/s40645‐017‐0154‐5.
32 Gutman, G., Janetos, A.C., Justice, C.O., Moran, E.F., Mustard, J.F., Rindfuss, R.R., Skole, D., Turner, B.L. (eds.) (2004). Land Change Science: Observing, Monitoring and Understanding Trajectories of Change on the Earth's Surface. New York: Kluwer Academic.
33 Habib, A.F., Kersting, J., McCaffrey, T.M., and Jarvis, A.M.Y. (2008). Integration of LiDAR and airborne imagery for realistic visualization of 3D urban environments. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVII (Part B2): 617–623.
34 Henderson, F.M., and Xia, Z.G. (1998). Radar applications in urban analysis, settlement detection and population analysis. In: Henderson, F.M., Lewis, A.J. (eds.), Principles and Applications of Imaging Radar 733–768. New York: Wiley.
35 Imhoff, M.L., Zhang, P., Wolfe, R.E., and Bounoua, L. (2010). Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sensing of Environment 114(3): 504–513. doi:10.1016/j.rse.2009.10.008.
36 Jacobson, M.Z., Nghiem, S.V., Sorichetta, A., and Whitney, N. (2015). Ring of impact from the mega‐urbanization of Beijing between 2000 and 2009. Journal of Geophysical Research: Atmospheres 120: 5740–5756. doi:10.1002/2014JD023008.
37 Jacobson, M.Z., Nghiem, S.V., and Sorichetta, A. (2019). Short‐term impacts of the megaurbanizations of New Delhi and Los Angeles between 2000 and 2009. Journal of Geophysical Research: Atmospheres 124: 35–56. doi:10.1029/2018JD029310.
38 JPL (Jet Propulsion Laboratory) (2006). QuikSCAT Science Data Product user's Manual. Jet Propulsion Laboratory Document D‐18053‐RevA. Pasadena, CA: NASA Jet Propulsion Laboratory, California Institute of Technology.
39 Kaufmann, R.K., Seto, K.C., Schneider, A., Liu, Z., Zhou, L., and Wang, W. (2007). Climate response to rapid urban growth: evidence of a human‐induced precipitation deficit. Journal of Climate 20(10): 2299–2306. doi:10.1175/JCLI4109.1.
40 Leinenkugel, P., Esch, T., and Kuenzer, C. (2011). Settlement detection and impervious surface estimation in the Mekong Delta using optical and SAR remote sensing data. Remote Sensing of Environment 115(12): 3007–3019. doi:10.1016/j.rse.2011.06.004.
41 Li, M., Koks, E., Taubenböck, H., and van Vliet, J. (2020). Continental‐scale mapping and analysis of 3D building structure. Remote Sensing of Environment 245: 111859. doi:10.1016/j.rse.2020.111859.
42 Lukac, N., Seme, S., Zlaus, D., Stumberger, G., and Zalik, B. (2014). Building roofs potential assessment based on LiDAR (light detection and ranging) data. Energy 66: 598–609. doi:10.1016/j.energy.2013.066.
43 Marin, C., Bovolo, F., and Bruzzone, L. (2015). Building change detection in multitemporal very high resolution SAR images. IEEE Transactions on Geoscience and Remote Sensing 53(5): 2664–2682. doi:10.1109/TGRS.2014.2363548.
44 Masek, J.G., Lindsay, F.E., and Goward, S.N. (2000). Dynamics of urban growth in the Washington DC metropolitan area, 1973‐1996, from Landsat observations. International Journal of Remote Sensing 21(18): 3473–3486. doi:10.1080/014311600750037507.
45 Masetti, M., Nghiem, S.V., Sorichetta, A., Stevennazi, S., Fabbri, P., Pola, M., Filippini, M., and Brakenridge, G.R. (2015). Investigating urban changes and environmental impacts in Italy. Eos, Earth & Space Science News 96(21): 13–16.
46 Mathews, A.J., and Frazier, A.E. (2017). Unmanned aerial systems. In: J.P. Wilson (ed.), The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2017). Ithaca, NY: University Consortium for Geographic Information Science (UCGIS). doi:10.22224/gistbok/2017.2.4.
47 Mathews, A.J., Frazier, A.E., Nghiem, S.V., Neumann, G., and Zhao, Y. (2019). Satellite scatterometer estimation of urban built‐up volume: validation with airborne lidar data. International Journal of Applied Earth Observation and Geoinformation 77: 100–107. doi:10.1016/j.jag.2019.01.004.
48 Moussavi, M.S., Abdalati, W., Scambos, T., and Neuenschwander, A. (2014). Applicability of an automatic surface detection approach to micro‐pulse photon‐counting lidar altimetry data: implications for canopy height retrieval from future ICESat‐2 data. International Journal of Remote Sensing 35: 5263–5279. doi:10.1080/01431161.2014.939780.
49 Myint, S.W., Gober, P., Brazel, A., Grossman‐Clarke, S., and Weng, Q. (2011). Per‐pixel vs. object‐based classification of urban land cover extraction using high spatial resolution imagery. Remote Sensing of Environment 115(5): 1145–1161. doi:10.1016/j.rse.2010.12.017.
50 NASEM (National Academies of Sciences, Engineering, and Medicine) (2018). Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space. Washington, DC: The National Academies Press. doi:10.17226/24938.
51 Nghiem, S.V., and van Zyl, J.J. (1997). Theory for polarimetric interferometry. Proceedings of Progress in Electromagnetics Research Symposium (Cambridge, MA) 205.
52 Nghiem, S.V., Balk, D., Rodriguez, E., Neumann, G., Sorichetta, A., Small, C., and Elvidge, C. (2009). Observations of urban and suburban environments with global satellite scatterometer data. ISPRS Journal of Photogrammetry and Remote Sensing 64(4): 367–380.
53 Nghiem,