A labor-free index-guided semantic segmentation approach for urban vegetation mapping from high-resolution true color imagery

References

• Abdollahi, Abolfazl, and Biswajeet Pradhan. 2021. “Urban Vegetation Mapping from Aerial Imagery Using Explainable AI (XAI).” Sensors 21 (14), doi:10.3390/s21144738.
   PubMed Web of Science ®Google Scholar
• Ahern, Jack. 2011. “From Fail-Safe to Safe-to-Fail: Sustainability and Resilience in the New Urban World.” Landscape and Urban Planning 100 (4): 341–343. doi:10.1016/j.landurbplan.2011.02.021.
   Web of Science ®Google Scholar
• Almeer, Mohamed H. 2012. “Vegetation Extraction from Free Google Earth Images of Deserts Using a Robust BPNN Approach in HSV Space.” International Journal of Advanced Research in Computer and Communication Engineering 1 (3): 134–140.
   Google Scholar
• Audebert, Nicolas, Bertrand Le Saux, and Sébastien Lefèvre. 2018. “Beyond RGB: Very High Resolution Urban Remote Sensing with Multimodal Deep Networks.” ISPRS Journal of Photogrammetry and Remote Sensing 140: 20–32. doi:10.1016/j.isprsjprs.2017.11.011.
   Web of Science ®Google Scholar
• Badrinarayanan, Vijay, Ankur Handa, and Roberto Cipolla. 2015. “SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling.” http://arxiv.org/abs/1505.07293.
   Google Scholar
• Baker, Fraser, Claire L. Smith, and Gina Cavan. 2018. “A Combined Approach to Classifying Land Surface Cover of Urban Domestic Gardens Using Citizen Science Data and High Resolution Image Analysis.” Remote Sensing 10 (4): 537. doi:10.3390/rs10040537.
   Web of Science ®Google Scholar
• Bannari, A., D. Morin, F. Bonn, and A. R. Huete. 1995. “A Review of Vegetation Indices.” Remote Sensing Reviews 13 (1–2): 95–120. doi:10.1080/02757259509532298.
   Google Scholar
• Barwise, Yendle, and Prashant Kumar. 2020. “Warming and Drying Over the Central Himalaya Caused by an Amplification of Local Mountain Circulation.” Npj Climate and Atmospheric Science 3 (1): 1–19. doi:10.1038/s41612-019-0105-5.
   Web of Science ®Google Scholar
• Bendig, Juliane, Kang Yu, Helge Aasen, Andreas Bolten, Simon Bennertz, Janis Broscheit, Martin L. Gnyp, and Georg Bareth. 2015. “Combining UAV-Based Plant Height from Crop Surface Models, Visible, and Near Infrared Vegetation Indices for Biomass Monitoring in Barley.” International Journal of Applied Earth Observation and Geoinformation 39: 79–87. doi:10.1016/j.jag.2015.02.012.
   Web of Science ®Google Scholar
• Blicharska, Malgorzata, Richard J. Smithers, Grzegorz Mikusiński, Patrik Rönnbäck, Paula A. Harrison, Måns Nilsson, and William J. Sutherland. 2019. “Biodiversity’s Contributions to Sustainable Development.” Nature Sustainability 2 (12): 1083–1093. doi:10.1038/s41893-019-0417-9.
   Web of Science ®Google Scholar
• Bressan, Patrik Olã, José Marcato Junior, José Augusto Correa Martins, Maximilian Jaderson de Melo, Diogo Nunes Gonçalves, Daniel Matte Freitas, Ana Paula Marques Ramos, et al. 2022. “Semantic Segmentation with Labeling Uncertainty and Class Imbalance Applied to Vegetation Mapping.” International Journal of Applied Earth Observation and Geoinformation 108 (January), doi:10.1016/j.jag.2022.102690.
   PubMedGoogle Scholar
• Cao, Yinxia, and Xin Huang. 2022. “A Coarse-to-Fine Weakly Supervised Learning Method for Green Plastic Cover Segmentation Using High-Resolution Remote Sensing Images.” ISPRS Journal of Photogrammetry and Remote Sensing 188 (April): 157–176. doi:10.1016/j.isprsjprs.2022.04.012.
   Google Scholar
• Cao, Rui, Wei Tu, Cuixin Yang, Qing Li, Jun Liu, Jiasong Zhu, Qian Zhang, Qingquan Li, and Guoping Qiu. 2020. “Deep Learning-Based Remote and Social Sensing Data Fusion for Urban Region Function Recognition.” ISPRS Journal of Photogrammetry and Remote Sensing 163 (February): 82–97. doi:10.1016/j.isprsjprs.2020.02.014.
   Google Scholar
• Chen, Liang Chieh, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam. 2018. “Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11211 LNCS: 833–851. doi:10.1007/978-3-030-01234-2_49.
   Google Scholar
• De Carvalho, Roberta Mendonça, and Claudio Fabian Szlafsztein. 2019. “Urban Vegetation Loss and Ecosystem Services: The Influence on Climate Regulation and Noise and Air Pollution.” Environmental Pollution 245: 844–852. doi:10.1016/j.envpol.2018.10.114.
   PubMed Web of Science ®Google Scholar
• Duhl, Tiffany R., Alex Guenther, and Detlev Helmig. 2012. “Estimating Urban Vegetation Cover Fraction Using Google Earth® Images.” Journal of Land Use Science 7 (3): 311–329. doi:10.1080/1747423X.2011.587207.
   Google Scholar
• Fang, Hong, Yuchun Wei, Hong Luo, and Qi Hu. 2019. “Detection of Building Shadow in Remote Sensing Imagery of Urban Areas with Fine Spatial Resolution Based on Saturation and Near-Infrared Information.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12 (8): 2695–2706. doi:10.1109/JSTARS.2019.2917605.
   Web of Science ®Google Scholar
• Feng, Quanlong, Jiantao Liu, and Jianhua Gong. 2015. “UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis.” Remote Sensing 7 (1): 1074–1094. doi:10.3390/rs70101074.
   Web of Science ®Google Scholar
• Ferreira, Carla S.S., Rory P.D. Walsh, and António J.D. Ferreira. 2018. “Degradation in Urban Areas.” Current Opinion in Environmental Science & Health 5: 19–25. doi:10.1016/j.coesh.2018.04.001.
   Google Scholar
• Fisher, Adrian, Neil Flood, and Tim Danaher. 2016. “Comparing Landsat Water Index Methods for Automated Water Classification in Eastern Australia.” Remote Sensing of Environment, 167–182. doi:10.1016/j.rse.2015.12.055.
   Web of Science ®Google Scholar
• Ge, Yong, Xining Zhang, Peter M. Atkinson, Alfred Stein, and Lianfa Li. 2022. “Geoscience-Aware Deep Learning: A New Paradigm for Remote Sensing.” Science of Remote Sensing 5 (March): 100047. doi:10.1016/j.srs.2022.100047.
   Google Scholar
• Gelan, Eshetu, and Yared Girma. 2022. “Urban Green Infrastructure Accessibility for the Achievement of SDG 11 in Rapidly Urbanizing Cities of Ethiopia.” GeoJournal 87 (4): 2883–2902. doi:10.1007/s10708-021-10404-7.
   Web of Science ®Google Scholar
• Gitelson, Anatoly A., Yoram J. Kaufman, Robert Stark, and Don Rundquist. 2002. “Novel Algorithms for Remote Estimation of Vegetation Fraction.” Remote Sensing of Environment 80 (1): 76–87. doi:10.1016/S0034-4257(01)00289-9.
   Web of Science ®Google Scholar
• Hobbie, Sarah E., Jacques C. Finlay, Benjamin D. Janke, Daniel A. Nidzgorski, Dylan B. Millet, and Lawrence A. Baker. 2017. “Contrasting Nitrogen and Phosphorus Budgets in Urban Watersheds and Implications for Managing Urban Water Pollution.” Proceedings of the National Academy of Sciences 114 (16): 4177–4182. doi:10.1073/pnas.1618536114.
   PubMed Web of Science ®Google Scholar
• Huete, A. 1988. “A Soil-Adjusted Vegetation Index (SAVI).” Remote Sensing of Environment 25 (3): 295–309. doi:10.1016/0034-4257(88)90106-X.
   Web of Science ®Google Scholar
• Huete, A., K. Didan, T. Miura, E. P. Rodriguez, X. Gao, and L. G. Ferreira. 2002. “Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices.” Remote Sensing of Environment 83 (1): 195–213. doi:10.1016/S0034-4257(02)00096-2.
   Web of Science ®Google Scholar
• Lecun, Yann, Yoshua Bengio, and Geoffrey Hinton. 2015. “Deep Learning.” Nature 521 (7553): 436–444. doi:10.1038/nature14539.
   PubMed Web of Science ®Google Scholar
• Li, Yansheng, Wei Chen, Yongjun Zhang, Chao Tao, Rui Xiao, and Yihua Tan. 2020. “Accurate Cloud Detection in High-Resolution Remote Sensing Imagery by Weakly Supervised Deep Learning.” Remote Sensing of Environment 250 (December 2019): 112045. doi:10.1016/j.rse.2020.112045.
   Google Scholar
• Li, Xiaoxiao, and Guofan Shao. 2013. “Object-Based Urban Vegetation Mapping with High-Resolution Aerial Photography as a Single Data Source.” International Journal of Remote Sensing 34 (3): 771–789. doi:10.1080/01431161.2012.714508.
   Web of Science ®Google Scholar
• Long, Jonathan, Evan Shelhamer, and Trevor Darrell. 2015. “Fully Convolutional Networks for Semantic Segmentation.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3431–3440.
   Google Scholar
• Louhaichi, Mounir, Michael M. Borman, and Douglas E. Johnson. 2001. “Spatially Located Platform and Aerial Photography for Documentation of Grazing Impacts on Wheat.” Geocarto International 16 (1): 65–70. doi:10.1080/10106040108542184.
   Google Scholar
• Neyns, Robbe, and Frank Canters. 2022. “Mapping of Urban Vegetation with High-Resolution Remote Sensing: A Review.” Remote Sensing 14 (4), doi:10.3390/rs14041031.
   Web of Science ®Google Scholar
• Nowak, David J., and Daniel E. Crane. 2002. “Carbon Storage and Sequestration by Urban Trees in the USA.” Environmental Pollution 116 (3): 381–389. doi:10.1016/S0269-7491(01)00214-7.
   PubMed Web of Science ®Google Scholar
• Nutsford, D., A. L. Pearson, and S. Kingham. 2013. “An Ecological Study Investigating the Association Between Access to Urban Green Space and Mental Health.” Public Health 127 (11): 1005–1011. doi:10.1016/j.puhe.2013.08.016.
   PubMed Web of Science ®Google Scholar
• Otsu, Nobuyuki. 1979. “A Threshold Selection Method from Gray-Level Histograms.” IEEE Transactions on Systems, Man, and Cybernetics 9 (1): 62–66.
   Web of Science ®Google Scholar
• Pettorelli, Nathalie, Jon Olav Vik, Atle Mysterud, Jean Michel Gaillard, Compton J. Tucker, and Nils Chr Stenseth. 2005. “Using the Satellite-Derived NDVI to Assess Ecological Responses to Environmental Change.” Trends in Ecology & Evolution 20 (9): 503–510. doi:10.1016/j.tree.2005.05.011.
   PubMed Web of Science ®Google Scholar
• Ronneberger, Olaf, Philipp Fischer, and Thomas Brox. 2015. “U-Net: Convolutional Networks for Biomedical Image Segmentation.” In International Conference on Medical image computing and computer-assisted intervention, 9351: 234–241. Springer, Cham. doi:10.1007/978-3-319-24574-4_28.
   Google Scholar
• Schiefer, Felix, Teja Kattenborn, Annett Frick, Julian Frey, Peter Schall, Barbara Koch, and Sebastian Schmidtlein. 2020. “Mapping Forest Tree Species in High Resolution UAV-Based RGB-Imagery by Means of Convolutional Neural Networks.” ISPRS Journal of Photogrammetry and Remote Sensing 170 (July): 205–215. doi:10.1016/j.isprsjprs.2020.10.015.
   Google Scholar
• Shahtahmassebi, Amir Reza, Chenlu Li, Yifan Fan, Yani Wu, Yue lin, Muye Gan, Ke Wang, Arunima Malik, and George Alan Blackburn. 2021. “Remote Sensing of Urban Green Spaces: A Review.” Urban Forestry & Urban Greening 57 (August 2020): 126946. doi:10.1016/j.ufug.2020.126946.
   Google Scholar
• Shochat, Eyal, Susannah B. Lerman, John M. Anderies, Paige S. Warren, Stanley H. Faeth, and Charles H. Nilon. 2010. “Invasion, Competition, and Biodiversity Loss in Urban Ecosystems.” BioScience 60 (3): 199–208. doi:10.1525/bio.2010.60.3.6.
   Web of Science ®Google Scholar
• Sun, Ying, Xinchang Zhang, Qinchuan Xin, and Jianfeng Huang. 2018. “Developing a Multi-Filter Convolutional Neural Network for Semantic Segmentation Using High-Resolution Aerial Imagery and LiDAR Data.” ISPRS Journal of Photogrammetry and Remote Sensing 143 (June): 3–14. doi:10.1016/j.isprsjprs.2018.06.005.
   Google Scholar
• Susca, T., S. R. Gaffin, and G. R. Dell’Osso. 2011. “Positive Effects of Vegetation: Urban Heat Island and Green Roofs.” Environmental Pollution 159 (8–9): 2119–2126. doi:10.1016/j.envpol.2011.03.007.
   PubMed Web of Science ®Google Scholar
• Taylor, John R., and Sarah Taylor Lovell. 2012. “Mapping Public and Private Spaces of Urban Agriculture in Chicago Through the Analysis of High-Resolution Aerial Images in Google Earth.” Landscape and Urban Planning 108 (1): 57–70. doi:10.1016/j.landurbplan.2012.08.001.
   Web of Science ®Google Scholar
• Tucker, Compton J. 1979. “Red and Photographic Infrared Linear Combinations for Monitoring Vegetation.” Remote Sensing of Environment 8 (2): 127–150. doi:https://doi.org/10.1016/0034-4257(79)90013-0.
   Web of Science ®Google Scholar
• Yang, Lan, Wei Chen, Pengshuai Bi, Hongzhao Tang, Fengjiao Zhang, and Zhe Wang. 2022. “Improving Vegetation Segmentation with Shadow Effects Based on Double Input Networks Using Polarization Images.” Computers and Electronics in Agriculture 199 (11): 107123. doi:10.1016/j.compag.2022.107123.
   Google Scholar
• Zhang, Peng, Peijun Du, Shanchuan Guo, Wei Zhang, Pengfei Tang, and Jike Chen. 2022. “A Novel Index for Robust and Large-Scale Mapping of Plastic Greenhouse from Sentinel-2 Images.” Remote Sensing of Environment 276: 113042. doi:10.1016/j.rse.2022.113042.
   Web of Science ®Google Scholar
• Zhang, Peng, Peijun Du, Cong Lin, Xin Wang, Erzhu Li, Zhaohui Xue, and Xuyu Bai. 2020. “A Hybrid Attention-Aware Fusion Network (Hafnet) for Building Extraction from High-Resolution Imagery and Lidar Data.” Remote Sensing 12 (22): 3764–3720. doi:10.3390/rs12223764.
   Web of Science ®Google Scholar
• Zhang, Zhixin, Zhen Qian, Teng Zhong, Min Chen, Kai Zhang, Yue Yang, Rui Zhu, et al. 2022. “Human EEG Recordings for 1,854 Concepts Presented in Rapid Serial Visual Presentation Streams.” Scientific Data 9 (1): 3–5. doi:10.1038/s41597-021-01102-7.
   PubMed Web of Science ®Google Scholar