{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T02:20:40Z","timestamp":1776219640473,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,1,5]],"date-time":"2022-01-05T00:00:00Z","timestamp":1641340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban vegetation growth is vital for developing sustainable and liveable cities in the contemporary era since it directly helps people\u2019s health and well-being. Estimating vegetation cover and biomass is commonly done by calculating various vegetation indices for automated urban vegetation management and monitoring. However, most of these indices fail to capture robust estimation of vegetation cover due to their inherent focus on colour attributes with limited viewpoint and ignore seasonal changes. To solve this limitation, this article proposed a novel vegetation index called the Multiview Semantic Vegetation Index (MSVI), which is robust to color, viewpoint, and seasonal variations. Moreover, it can be applied directly to RGB images. This Multiview Semantic Vegetation Index (MSVI) is based on deep semantic segmentation and multiview field coverage and can be integrated into any vegetation management platform. This index has been tested on Google Street View (GSV) imagery of Wyndham City Council, Melbourne, Australia. The experiments and training achieved an overall pixel accuracy of 89.4% and 92.4% for FCN and U-Net, respectively. Thus, the MSVI can be a helpful instrument for analysing urban forestry and vegetation biomass since it provides an accurate and reliable objective method for assessing the plant cover at street level.<\/jats:p>","DOI":"10.3390\/rs14010228","type":"journal-article","created":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T23:06:15Z","timestamp":1641769575000},"page":"228","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Multiview Semantic Vegetation Index for Robust Estimation of Urban Vegetation Cover"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0543-3350","authenticated-orcid":false,"given":"Asim","family":"Khan","sequence":"first","affiliation":[{"name":"The Institute for Sustainable Industries and Liveable Cities (ISILC), College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0501-7907","authenticated-orcid":false,"given":"Warda","family":"Asim","sequence":"additional","affiliation":[{"name":"The Institute for Sustainable Industries and Liveable Cities (ISILC), College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5145-7276","authenticated-orcid":false,"given":"Anwaar","family":"Ulhaq","sequence":"additional","affiliation":[{"name":"The Institute for Sustainable Industries and Liveable Cities (ISILC), College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia"},{"name":"School of Computing, Mathematics and Engineering, Charles Sturt University, Port Macquarie, NSW 2444, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8425-0709","authenticated-orcid":false,"given":"Randall W.","family":"Robinson","sequence":"additional","affiliation":[{"name":"The Institute for Sustainable Industries and Liveable Cities (ISILC), College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia"},{"name":"Applied Ecology Research Group, The Institute for Sustainable Industries and Liveable Cities (ISILC), College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1038\/s41586-018-0411-9","article-title":"Global land change from 1982 to 2016","volume":"560","author":"Song","year":"2018","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1177\/0309133319831673","article-title":"The chronostratigraphic method is unsuitable for determining the start of the Anthropocene","volume":"43","author":"Edgeworth","year":"2019","journal-title":"Prog. Phys. Geogr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6594","DOI":"10.1029\/2019GL082327","article-title":"Extensive 21st-Century Woody Encroachment in South America\u2019s Savanna","volume":"46","author":"Rosan","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_4","first-page":"396","article-title":"Business district streetscapes, trees, and consumer response","volume":"103","author":"Wolf","year":"2005","journal-title":"J. For."},{"key":"ref_5","unstructured":"Appleyard, D. (1979, January 13\u201316). Urban trees, urban forests: What do they mean. Proceedings of the National Urban Forestry Conference, Washington, DC, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"220","DOI":"10.48044\/jauf.2007.026","article-title":"Oxygen production by urban trees in the United States","volume":"33","author":"Nowak","year":"2007","journal-title":"Arboric. Urban For."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.rse.2005.11.016","article-title":"Remote sensing image-based analysis of the relationship between urban heat island and land use\/cover changes","volume":"104","author":"Chen","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.ufug.2010.06.002","article-title":"Evaluating the potential for urban heat-island mitigation by greening parking lots","volume":"9","author":"Onishi","year":"2010","journal-title":"Urban For. Urban Green."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1007\/s11252-014-0343-6","article-title":"How do people perceive urban trees? Assessing likes and dislikes in relation to the trees of a city","volume":"17","author":"Schondube","year":"2014","journal-title":"Urban Ecosyst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/S0169-2046(04)00052-0","article-title":"Attitudes toward urban green spaces: Integrating questionnaire survey and collaborative GIS techniques to improve attitude measurements","volume":"71","author":"Balram","year":"2005","journal-title":"Landsc. Urban Plan."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.isprsjprs.2019.11.018","article-title":"Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review","volume":"159","author":"Gao","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.landurbplan.2008.12.004","article-title":"Can you see green? Assessing the visibility of urban forests in cities","volume":"91","author":"Yang","year":"2009","journal-title":"Landsc. Urban Plan."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1016\/j.ufug.2015.06.006","article-title":"Assessing street-level urban greenery using Google Street View and a modified green view index","volume":"14","author":"Li","year":"2015","journal-title":"Urban For. Urban Green."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.ufug.2016.06.002","article-title":"Environmental inequities in terms of different types of urban greenery in Hartford, Connecticut","volume":"18","author":"Li","year":"2016","journal-title":"Urban For. Urban Green."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Dong, R., Zhang, Y., and Zhao, J. (2018). How green are the streets within the sixth ring road of Beijing? An analysis based on tencent street view pictures and the green view index. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15071367"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhang, Y., and Dong, R. (2018). Impacts of street-visible greenery on housing prices: Evidence from a hedonic price model and a massive street view image dataset in Beijing. ISPRS Int. J. Geo Inf., 7.","DOI":"10.3390\/ijgi7030104"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Long, Y., and Liu, L. (2017). How green are the streets? An analysis for central areas of Chinese cities using Tencent Street View. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0171110"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Cheng, L., Chu, S., Zong, W., Li, S., Wu, J., and Li, M. (2017). Use of tencent street view imagery for visual perception of streets. ISPRS Int. J. Geo Inf., 6.","DOI":"10.3390\/ijgi6090265"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kendal, D., Hauser, C.E., Garrard, G.E., Jellinek, S., Giljohann, K.M., and Moore, J.L. (2013). Quantifying plant colour and colour difference as perceived by humans using digital images. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0072296"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1002\/rse2.109","article-title":"How canopy shadow affects invasive plant species classification in high spatial resolution remote sensing","volume":"5","author":"Lopatin","year":"2019","journal-title":"Remote Sens. Ecol. Conserv."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.isprsjprs.2020.10.015","article-title":"Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks","volume":"170","author":"Schiefer","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., and Darrell, T. (2015, January 7\u201312). Fully convolutional networks for semantic segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Dvornik, N., Shmelkov, K., Mairal, J., and Schmid, C. (2017, January 22\u201329). Blitznet: A real-time deep network for scene understanding. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.447"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Li, Y., Qi, H., Dai, J., Ji, X., and Wei, Y. (2017, January 21\u201326). Fully convolutional instance-aware semantic segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.472"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Chen, L.C., Yang, Y., Wang, J., Xu, W., and Yuille, A.L. (2016, January 27\u201330). Attention to scale: Scale-aware semantic image segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.396"},{"key":"ref_26","unstructured":"Council, W.C. (2021, August 15). Street Tree Planting | Wyndham City, Available online: https:\/\/www.wyndham.vic.gov.au\/treeplanting."},{"key":"ref_27","unstructured":"(2021, August 17). Street View Static API Overview | Google Developers. Available online: https:\/\/developers.google.com\/maps\/documentation\/streetview\/overview."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1049\/iet-ipr.2012.0323","article-title":"Three-dimensional positioning from Google street view panoramas","volume":"7","author":"Tsai","year":"2013","journal-title":"IET Image Process."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.neucom.2019.11.118","article-title":"A brief survey on semantic segmentation with deep learning","volume":"406","author":"Hao","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Uhrig, J., Cordts, M., Franke, U., and Brox, T. (2016). Pixel-level encoding and depth layering for instance-level semantic labeling. German Conference on Pattern Recognition, Springer.","DOI":"10.1007\/978-3-319-45886-1_2"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s13735-017-0141-z","article-title":"A review of semantic segmentation using deep neural networks","volume":"7","author":"Guo","year":"2018","journal-title":"Int. J. Multimed. Inf. Retr."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1007\/s10462-018-9641-3","article-title":"Recent progress in semantic image segmentation","volume":"52","author":"Liu","year":"2019","journal-title":"Artif. Intell. Rev."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., and Adam, H. (2018, January 8\u201314). Encoder-decoder with atrous separable convolution for semantic image segmentation. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., and Girshick, R. (2017, January 22\u201329). Mask r-cnn. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref_35","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","volume":"Volume 9351","author":"Ronneberger","year":"2015","journal-title":"Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2015"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Garcia-Garcia, A., Orts-Escolano, S., Oprea, S., Villena-Martinez, V., and Garcia-Rodriguez, J. (2017). A review on deep learning techniques applied to semantic segmentation. arXiv.","DOI":"10.1016\/j.asoc.2018.05.018"},{"key":"ref_37","first-page":"134","article-title":"Vegetation extraction from free google earth images of deserts using a robust BPNN approach in HSV Space","volume":"1","author":"Almeer","year":"2012","journal-title":"Int. J. Adv. Res. Comput. Commun. Eng."},{"key":"ref_38","first-page":"555","article-title":"Object-oriented image processing in an integrated GIS\/remote sensing environment and perspectives for environmental applications","volume":"2","author":"Blaschke","year":"2000","journal-title":"Environ. Inf. Plan. Politics Public"},{"key":"ref_39","unstructured":"(2021, August 15). APEER. Available online: https:\/\/www.apeer.com\/."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/0306-4573(89)90048-4","article-title":"Similarity measures in scientometric research: The Jaccard index versus Salton\u2019s cosine formula","volume":"25","author":"Hamers","year":"1989","journal-title":"Inf. Process. Manag."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Khan, A., Ulhaq, A., and Robinson, R.W. (2019). Multi-temporal registration of environmental imagery using affine invariant convolutional features. Pacific-Rim Symposium on Image and Video Technology, Springer.","DOI":"10.1007\/978-3-030-34879-3_21"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/228\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:36:23Z","timestamp":1760362583000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/228"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,5]]},"references-count":41,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14010228"],"URL":"https:\/\/doi.org\/10.3390\/rs14010228","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,5]]}}}