References
Campbell, James B., and Randolph H. Wynne. 2011. Introduction to
Remote Sensing, Fifth Edition. Guilford Press.
Christian Ginzler. 2021. “Vegetation Height Model NFI.” https://doi.org/10.16904/1000001.1.
Dwyer, John L., David P. Roy, Brian Sauer, Calli B. Jenkerson, Hankui K.
Zhang, and Leo Lymburner. 2018. “Analysis Ready Data: Enabling
Analysis of the Landsat Archive.” Remote Sensing 10 (9):
1363. https://doi.org/10.3390/rs10091363.
Eggimann, Sven. 2022. “Expanding Urban Green Space with
Superblocks.” Land Use Policy 117 (June): 106111. https://doi.org/10.1016/j.landusepol.2022.106111.
Frantz, David. 2019. “FORCELandsat + Sentinel-2
Analysis Ready Data and Beyond.” Remote Sensing 11 (9):
1124. https://doi.org/10.3390/rs11091124.
Fu, Yongyong, Kunkun Liu, Zhangquan Shen, Jinsong Deng, Muye Gan, Xinguo
Liu, Dongming Lu, and Ke Wang. 2019. “Mapping Impervious Surfaces
in TownRural Transition Belts Using China’s
GF-2 Imagery and Object-Based Deep CNNs.” Remote Sensing
11 (3): 280. https://doi.org/10.3390/rs11030280.
Gupta, Saurabh Kumar, and Arvind Chandra Pandey. 2021. “Spectral
Aspects for Monitoring Forest Health in Extreme Season Using
Multispectral Imagery.” The Egyptian Journal of Remote
Sensing and Space Science 24 (3, Part 2): 579–86. https://doi.org/10.1016/j.ejrs.2021.07.001.
Hadjimitsis, D. G., G. Papadavid, A. Agapiou, K. Themistocleous, M. G.
Hadjimitsis, A. Retalis, S. Michaelides, N. Chrysoulakis, L. Toulios,
and C. R. I. Clayton. 2010. “Atmospheric Correction for Satellite
Remotely Sensed Data Intended for Agricultural Applications: Impact on
Vegetation Indices.” Natural Hazards and Earth System
Sciences 10 (1): 89–95. https://doi.org/10.5194/nhess-10-89-2010.
“Historic Environment.” n.d. https://www.cityoflondon.gov.uk/services/planning/cityoflondon.gov.uk/services/planning/historic-environment.
Holloway, Jacinta, and Kerrie Mengersen. 2018. “Statistical
Machine Learning Methods and Remote Sensing for Sustainable Development
Goals: A Review.” Remote Sensing 10 (9): 1365. https://doi.org/10.3390/rs10091365.
Huang, C., L. S. Davis, and J. R. G. Townshend. 2002. “An
Assessment of Support Vector Machines for Land Cover
Classification.” International Journal of Remote Sensing
23 (4): 725–49. https://doi.org/10.1080/01431160110040323.
Jovanović, Dušan, Milan Gavrilović, Dubravka Sladić, Aleksandra
Radulović, and Miro Govedarica. 2021. “Building Change Detection
Method to Support Register of Identified Changes on Buildings.”
Remote Sensing 13 (16): 3150. https://doi.org/10.3390/rs13163150.
Lausch, Angela, Stefan Erasmi, Douglas J. King, Paul Magdon, and Marco
Heurich. 2016. “Understanding Forest Health with Remote Sensing
-Part IA Review of Spectral Traits, Processes and
Remote-Sensing Characteristics.” Remote Sensing 8 (12):
1029. https://doi.org/10.3390/rs8121029.
Lawrence, Rick L., and Christopher J. Moran. 2015. “The
AmericaView Classification Methods Accuracy Comparison Project: A
Rigorous Approach for Model Selection.” Remote Sensing of
Environment 170 (December): 115–20. https://doi.org/10.1016/j.rse.2015.09.008.
Lechner, Alex M., Giles M. Foody, and Doreen S. Boyd. 2020.
“Applications in Remote Sensing to Forest Ecology and
Management.” One Earth 2 (5): 405–12. https://doi.org/10.1016/j.oneear.2020.05.001.
Lewis, Simon L., David P. Edwards, and David Galbraith. 2015.
“Increasing Human Dominance of Tropical Forests.”
Science 349 (6250): 827–32. https://doi.org/10.1126/science.aaa9932.
Li, Congcong, Jie Wang, Lei Wang, Luanyun Hu, and Peng Gong. 2014.
“Comparison of Classification Algorithms and Training Sample Sizes
in Urban Land Classification with Landsat Thematic Mapper
Imagery.” Remote Sensing 6 (2): 964–83. https://doi.org/10.3390/rs6020964.
“Living Textbook | Relative Atmospheric Correction | by ITC,
University of Twente.” n.d. https://ltb.itc.utwente.nl/498/concept/81688.
Maxwell, Aaron E., Timothy A. Warner, and Fang Fang. 2018.
“Implementation of Machine-Learning Classification in Remote
Sensing: An Applied Review.” International Journal of Remote
Sensing 39 (9): 2784–2817. https://doi.org/10.1080/01431161.2018.1433343.
Nieuwenhuijsen, Mark J., and Haneen Khreis. 2016. “Car Free
Cities: Pathway to Healthy Urban Living.” Environment
International 94 (September): 251–62. https://doi.org/10.1016/j.envint.2016.05.032.
Pekel, Jean-François, Andrew Cottam, Noel Gorelick, and Alan S. Belward.
2016. “High-Resolution Mapping of Global Surface Water and Its
Long-Term Changes.” Nature 540 (7633): 418–22. https://doi.org/10.1038/nature20584.
Suel, Esra, John W. Polak, James E. Bennett, and Majid Ezzati. 2019.
“Measuring Social, Environmental and Health Inequalities Using
Deep Learning and Street Imagery.” Scientific Reports 9
(1): 6229. https://doi.org/10.1038/s41598-019-42036-w.
Tamiminia, Haifa, Bahram Salehi, Masoud Mahdianpari, Lindi Quackenbush,
Sarina Adeli, and Brian Brisco. 2020a. “Google Earth Engine for
Geo-Big Data Applications: A Meta-Analysis and Systematic
Review.” ISPRS Journal of Photogrammetry and Remote
Sensing 164 (June): 152–70. https://doi.org/10.1016/j.isprsjprs.2020.04.001.
———. 2020b. “Google Earth Engine for Geo-Big Data Applications: A
Meta-Analysis and Systematic Review.” ISPRS Journal of
Photogrammetry and Remote Sensing 164 (June): 152–70. https://doi.org/10.1016/j.isprsjprs.2020.04.001.
Tang, Zixia, Mengmeng Li, and Xiaoqin Wang. 2020. “Mapping Tea
Plantations from VHR Images Using OBIA and Convolutional Neural
Networks.” Remote Sensing 12 (18): 2935. https://doi.org/10.3390/rs12182935.
Wang, Lei, Yang Chen, Luliang Tang, Rongshuang Fan, and Yunlong Yao.
2018. “Object-Based Convolutional Neural Networks for Cloud and
Snow Detection in High-Resolution Multispectral Imagers.”
Water 10 (11): 1666. https://doi.org/10.3390/w10111666.
Xofis, Panteleimon, and Konstantinos Poirazidis. 2018. “Combining
Different Spatio-Temporal Resolution Images to Depict Landscape Dynamics
and Guide Wildlife Management.” Biological Conservation
218 (February): 10–17. https://doi.org/10.1016/j.biocon.2017.12.003.