{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T19:39:21Z","timestamp":1791401961528,"version":"4.3.3"},"reference-count":38,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2015,12,31]],"date-time":"2015-12-31T00:00:00Z","timestamp":1451520000000},"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>The identification of species within an ecosystem plays a key role in formulating an inventory for use in the development of conservation management plans. The classification of mangrove species typically involves intensive field surveys, whereas remote sensing techniques represent a cost-efficient means of mapping and monitoring mangrove forests at large scales. However, the coarse spectral resolution of remote sensing technology has up until recently restricted the ability to identify individual species. The more recent development of very high-resolution spatial optical remote sensing sensors and techniques has thus provided new opportunities for the accurate mapping of species within mangrove forests over large areas. When dealing with the complex problems associated with discriminating among species, classifier performance could be enhanced through the adoption of more intrinsic features; such as textural and differential spectral features. This study explored the effectiveness of textural and differential spectral features in mapping mangrove inter-species obtained from WorldView-3 high-spatial-resolution imagery for mangrove species in Hong Kong. Due to the different arrangement of leaves, the branch density, and the average height and size of plants, we found that the differential spectral features could aid in reducing inner-species variability and increasing intra-species separation. Using a combination of textural and differential spectral features thus represents a promising tool for discriminating among mangrove species. Experimental results suggest that combining these features can greatly improve mapping accuracy, thereby providing more reliable mapping results.<\/jats:p>","DOI":"10.3390\/rs8010024","type":"journal-article","created":{"date-parts":[[2016,1,5]],"date-time":"2016-01-05T02:29:07Z","timestamp":1451960947000},"page":"24","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":111,"title":["Textural\u2013Spectral Feature-Based Species Classification of Mangroves in Mai Po Nature Reserve from Worldview-3 Imagery"],"prefix":"10.3390","volume":"8","author":[{"given":"Ting","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong, China"},{"name":"Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongsheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong, China"},{"name":"Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Lin","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong, China"},{"name":"Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China"},{"name":"Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China"},{"name":"Department of Geography and Resource Management, The Chinese University of Hong Kong, New Territories, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaoyang","family":"Fang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,12,31]]},"reference":[{"key":"ref_1","unstructured":"Food and Agriculture Organization of the United Nations (2007). The World\u2019s Mangroves 1980\u20132005, Food and Agriculture Organization of the United Nations."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10661-015-4426-5","article-title":"Classifying spatially heterogeneous wetland communities using machine learning algorithms and spectral and textural features","volume":"187","author":"Szantoi","year":"2015","journal-title":"Environ. Monit. Assess."},{"key":"ref_3","unstructured":"Suratman, M.N. (2008). Managing Forest Ecosystems: The Challenge of Climate Change, Springer."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1111\/j.1466-8238.2010.00584.x","article-title":"Status and distribution of mangrove forests of the world using earth observation satellite data","volume":"20","author":"Giri","year":"2011","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_5","first-page":"204","article-title":"Analyzing fine-scale wetland composition using high resolution imagery and texture features","volume":"23","author":"Szantoi","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_6","first-page":"433","article-title":"The assessment of mangrove areas using high resolution multispectral airborne imagery","volume":"14","author":"Green","year":"1998","journal-title":"J. Coast. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3625","DOI":"10.1080\/014311698213858","article-title":"Remote sensing techniques adapted to high resolution mapping of tropical coastal marine ecosystems (coral reefs, seagrass beds and mangrove)","volume":"19","author":"Chauvaud","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","first-page":"226","article-title":"Mapping the distribution of mangrove species in the core zone of Mai Po Marshes nature reserve, Hong Kong, using hyperspectral data and high-resolution data","volume":"33","author":"Jia","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2688","DOI":"10.3390\/rs5062688","article-title":"Mineral mapping using simulated Worldview-3 short-wave-infrared imagery","volume":"5","author":"Kruse","year":"2013","journal-title":"Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1023\/A:1020908432489","article-title":"Satellite remote sensing of wetlands","volume":"10","author":"Ozesmi","year":"2002","journal-title":"Wetl. Ecol. Manag."},{"key":"ref_11","unstructured":"Green, E.P., Clark, C.D., and Edwards, A.J. (2000). Remote Sensing Handbook for Tropical Coastal Management, UNESCO."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/S0034-4257(02)00196-7","article-title":"Spectral discrimination of vegetation types in a coastal wetland","volume":"85","author":"Schmidt","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6064","DOI":"10.3390\/rs6076064","article-title":"Mangrove species identification: Comparing Worldview-2 with aerial photographs","volume":"6","author":"Heenkenda","year":"2014","journal-title":"Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"878","DOI":"10.3390\/rs3050878","article-title":"Remote sensing of mangrove ecosystems: A review","volume":"3","author":"Kuenzer","year":"2011","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.rse.2004.04.005","article-title":"Comparison of IKONOS and Quickbird images for mapping mangrove species on the Caribbean coast of Panama","volume":"91","author":"Wang","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1582","DOI":"10.2112\/07-0987.1","article-title":"Using high resolution satellite imagery to map black mangrove on the Texas Gulf Coast","volume":"6","author":"Everitt","year":"2008","journal-title":"J. Coast. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1177\/0309133310385371","article-title":"Satellite remote sensing of mangrove forests: Recent advances and future opportunities","volume":"35","author":"Heumann","year":"2011","journal-title":"Prog. Phys. Geogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4753","DOI":"10.3390\/rs70404753","article-title":"Object-based approach for multi-scale mangrove composition mapping using multi-resolution image datasets","volume":"7","author":"Kamal","year":"2015","journal-title":"Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s11273-009-9169-z","article-title":"Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: A review","volume":"18","author":"Adam","year":"2010","journal-title":"Wetl. Ecol. Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.ecss.2005.06.014","article-title":"Tropical mangrove species discrimination using hyperspectral data: A laboratory study","volume":"65","author":"Vaiphasa","year":"2005","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7828","DOI":"10.1080\/01431161.2014.978034","article-title":"Combining EO-1 hyperion and ENVISAT ASAR data for mangrove species classification in Mai Po Ramsar Site, Hong Kong","volume":"35","author":"Wong","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","unstructured":"Agriculture, Fisheries and Conservation Department (2011). Mai Po Inner Deep Bay Ramsar Site Management Plan Executive Summary, Agriculture, Fisheries and Conservation Department (AFCD)."},{"key":"ref_23","first-page":"4531","article-title":"Co-occurrence matrix and its statistical features as an approach for identification of phase transitions of mesogens","volume":"2","author":"Rao","year":"2013","journal-title":"Int. J. Innov. Res. Sci. Eng. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1109\/LGRS.2009.2014398","article-title":"Evaluation of morphological texture features for mangrove forest mapping and species discrimination using multispectral IKONOS imagery","volume":"6","author":"Huang","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/0034-4257(90)90055-Q","article-title":"High resolution derivative spectra in remote sensing","volume":"33","author":"Steven","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_26","unstructured":"Jensen, J.R. (2005). Introductory Digital Image Processing: A Remote Sensing Perspective, Pearson Education."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Talsky, G. (1994). Derivative Spectrophotometry: Low and Higher Order, Wiley-VCH.","DOI":"10.1002\/3527601570"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1039\/ap9821900022","article-title":"Derivative spectroscopy and its applications in analysis","volume":"19","author":"Fell","year":"1982","journal-title":"Anal. Proc."},{"key":"ref_29","unstructured":"Tam, N.F.Y., and Wong, Y.-S. (2000). Hong Kong Mangroves, City University of Hong Kong Press."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/S0025-326X(99)00056-9","article-title":"Concentration of 7 heavy metals in sediments and mangrove root samples from Mai Po, Hong Kong","volume":"39","author":"Che","year":"1999","journal-title":"Mar. Pollut. Bull."},{"key":"ref_31","unstructured":"AFCD Mangroves in Hong Kong, Available online: http:\/\/www.afcd.gov.hk\/english\/conservation\/con_wet\/con_wet_man\/con_wet_man_local\/con_wet_man_local_true.html."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/TGRS.1990.572937","article-title":"Evaluation of the grey-level co-occurrence matrix method for land-cover classification using SPOT imagery","volume":"28","author":"Marceau","year":"1990","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"8424","DOI":"10.3390\/rs6098424","article-title":"A multichannel gray level co-occurrence matrix for multi\/hyperspectral image texture representation","volume":"6","author":"Huang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"6","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3417","DOI":"10.1080\/01431160701601782","article-title":"Analysis of co-occurrence and discrete wavelet transform textures for differentiation of forest and non-forest vegetation in very-high-resolution optical-sensor imagery","volume":"29","author":"Ouma","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3663","DOI":"10.1080\/014311699211264","article-title":"Yellowness index: An application of spectral second derivatives to estimate chlorosis of leaves in stressed vegetation","volume":"20","author":"Adams","year":"1999","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3858","DOI":"10.1109\/TGRS.2007.898446","article-title":"Fusion of support vector machines for classification of multisensor data","volume":"45","author":"Waske","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"45","DOI":"10.5589\/m02-004","article-title":"An analysis of co-occurrence texture statistics as a function of grey level quantization","volume":"28","author":"Clausi","year":"2002","journal-title":"Can. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/1\/24\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:55:05Z","timestamp":1760216105000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/1\/24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,12,31]]},"references-count":38,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,1]]}},"alternative-id":["rs8010024"],"URL":"https:\/\/doi.org\/10.3390\/rs8010024","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,12,31]]}}}