{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T18:52:38Z","timestamp":1776538358546,"version":"3.51.2"},"reference-count":42,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,3,30]],"date-time":"2017-03-30T00:00:00Z","timestamp":1490832000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>For most sub-Saharan African (SSA) cities, in order to control the historically unplanned urban growth and stimulate sustainable future urban development, there is a need for accurate identification of the past and present urban land use (ULU). However, studies addressing ULU classification in SSA cities are lacking. In this study, we developed an integrated approach of remote sensing and Geographical Information System (GIS) techniques to classify ULU in the developing SSA city of Lusaka. First, we defined six ULU classes (i.e., unplanned high density residential; unplanned low density residential; planned medium-high density residential; planned low density residential; commercial and industrial; public institutions and service areas). ULU parcels, created using road networks as homogenous units separating ULU classes, were used to classify ULU. We utilised the combined detail of cadastral and land use data plus high-resolution Google Earth imagery to infer ULU and classify the parcels. For residential ULU, we also created density thresholds for accurate separation of the classes. We then used the classified ULU parcels for post-classification sorting of built-up pixels extracted from three Landsat TM\/ETM+ imageries (1990, 2000, and 2010) into respective ULU classes. Three ULU maps were produced with overall accuracy values of 84.09% to 85.86%. The maps provide information that is relevant to urban planners and policy makers for sustainable future urban planning of Lusaka City. The study also provides an insight for ULU classification in SSA cities with complex urban landscapes similar to Lusaka.<\/jats:p>","DOI":"10.3390\/ijgi6040102","type":"journal-article","created":{"date-parts":[[2017,3,30]],"date-time":"2017-03-30T09:49:54Z","timestamp":1490867394000},"page":"102","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Integrating Geospatial Techniques for Urban Land Use Classification in the Developing Sub-Saharan African City of Lusaka, Zambia"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6363-7410","authenticated-orcid":false,"given":"Matamyo","family":"Simwanda","sequence":"first","affiliation":[{"name":"Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba City, Ibaraki 305-8572, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4397-6882","authenticated-orcid":false,"given":"Yuji","family":"Murayama","sequence":"additional","affiliation":[{"name":"Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba City, Ibaraki 305-8572, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,30]]},"reference":[{"key":"ref_1","unstructured":"Mather, P.M. (1993). Geographical Information Handling\u2014Research and Applications, John Wiley and Sons."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1068\/a3496","article-title":"The use of remote sensing and landscape metrics to describe structures and changes in urban land uses","volume":"34","author":"Herold","year":"2002","journal-title":"Environ. Plan. A"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"31","DOI":"10.2747\/1548-1603.49.1.31","article-title":"Assessing the utility of satellite imagery with differing spatial resolutions for deriving proxy measures of slum presence in Accra, Ghana","volume":"1","author":"Stoler","year":"2012","journal-title":"GISci. Remote Sens."},{"key":"ref_4","first-page":"949","article-title":"Inferring urban land use from satellite sensor images using kernel-based spatial reclassification","volume":"62","author":"Barnsley","year":"1996","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2015.12.026","article-title":"Locally optimized separability enhancement indices for urban land cover mapping: Exploring thermal environmental consequences of rapid urbanization in Addis Ababa, Ethiopia","volume":"175","author":"Feyisa","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1080\/01431160050505865","article-title":"Improvement of classification in urban areas by the use of textural features: The case study of Lucknow city, Uttar Pradesh","volume":"22","author":"Shaba","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/j.rse.2010.12.017","article-title":"Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery","volume":"115","author":"Myint","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1394","DOI":"10.1109\/JSTARS.2013.2273074","article-title":"Improving the accuracy of urban land cover classification using Radarsat-2 PolSAR data","volume":"7","author":"Salehi","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_9","first-page":"993","article-title":"The integration of geographic data with remotely sensed imagery to improve classification in an urban area","volume":"61","author":"Harris","year":"1995","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Hu, T., Yang, J., Li, X., and Gong, P. (2016). Mapping Urban Land Use by using Landsat Images and Open Social Data. Remote Sens., 8.","DOI":"10.3390\/rs8020151"},{"key":"ref_11","first-page":"431","article-title":"The use of census data in urban image classification","volume":"64","author":"Mesev","year":"1998","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.rse.2006.02.010","article-title":"Use of impervious surface in urban land-use classification","volume":"102","author":"Lu","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2831","DOI":"10.1080\/01431160500117865","article-title":"Analysis of land use\/cover changes and urban expansion of Nairobi city using remote sensing and GIS","volume":"26","author":"Mundia","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"322","DOI":"10.4236\/ars.2013.24035","article-title":"Monitoring urban spatial growth in Harare Metropolitan","volume":"2","author":"Kamusoko","year":"2013","journal-title":"Adv. Remote Sens."},{"key":"ref_15","first-page":"67","article-title":"The Use of Structural Information for Improving Land-Cover Classification Accuracies at the Rural-Urban Fringe","volume":"56","author":"Gong","year":"1990","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_16","first-page":"841","article-title":"Integration of Spectral and Spatial Classification Methods for Building a Land-Use Model of Austria","volume":"31","author":"Steinnocher","year":"1996","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.landurbplan.2011.03.017","article-title":"Mapping form and function in urban areas: An approach based on urban metrics and continuous impervious surface data","volume":"102","author":"Jacquet","year":"2011","journal-title":"Landsc. Urban Plan."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.14358\/PERS.70.9.1053","article-title":"Spectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery","volume":"70","author":"Lu","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_19","first-page":"611","article-title":"Remote sensing of urban suburban infrastructure and socio-economic attributes","volume":"65","author":"Jensen","year":"1999","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"185","DOI":"10.4314\/sajg.v3i2.5","article-title":"Monitoring urban growth around Rustenburg, South Africa, using SPOT 5","volume":"3","author":"Mudau","year":"2014","journal-title":"S. Afr. J. Geomat."},{"key":"ref_21","unstructured":"Central Statistical Office (CSO) (2017, January 20). 2010 Census of Population and Housing, Available online: http:\/\/www.zamstats.gov.zm\/report\/Census\/2010\/National\/2010%20Census%20of%20Population%20Summary%20Report.pdf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1016\/j.apgeog.2010.01.009","article-title":"Per-pixel and object-oriented classification methods for mapping urban features using Ikonos satellite data","volume":"30","author":"Bhaskaran","year":"2010","journal-title":"Appl. Geogr."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.apgeog.2011.10.010","article-title":"Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico","volume":"34","author":"Seijmonsbergen","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4655","DOI":"10.1080\/01431161.2013.780669","article-title":"A hybrid method combining pixel-based and object-oriented methods and its application in Hungary using Chinese HJ-1 satellite images","volume":"34","author":"Li","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","unstructured":"Trimble (2015, February 22). eCognition\u00ae Developer 9.0 User Guide, 2014. Available online: http:\/\/www.eCognition.com\/."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.apgeog.2010.10.012","article-title":"Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data","volume":"31","author":"Ismail","year":"2011","journal-title":"Appl. Geogr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classification of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0034-4257(01)00204-8","article-title":"Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to arid urban centers","volume":"77","author":"Stefanov","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_29","first-page":"1173","article-title":"A subpixel classifier for urban land-cover mapping based on a maximum-li kelihood approach and expert system rules","volume":"68","author":"Hung","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1007\/s10661-008-0707-6","article-title":"Land cover classification with an expert system approach using Landsat ETM imagery: A case study of Trabzon","volume":"160","author":"Kahya","year":"2010","journal-title":"Environ. Monit. Assess."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1177\/0265813515604767","article-title":"Automated identification and characterization of parcels with OpenStreetMap and points of interest","volume":"43","author":"Liu","year":"2016","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Anderson, J.R., Hardy, E.E., Roach, J.T., and Witmer, R.E. (1976). A Land Use and Land Cover Classification System for Use with Remote Sensor Data, USGS. Geological Survey Professional Paper.","DOI":"10.3133\/pp964"},{"key":"ref_33","first-page":"251","article-title":"Effect of Category Aggregation on Map Comparison","volume":"3234","author":"Pontius","year":"2004","journal-title":"Geogr. Inf. Sci."},{"key":"ref_34","unstructured":"Rocha, J., Sousa, P.M., Tened\u00f3rio, J.A., and Encarna\u00e7\u00e3o, S. (2005, January 6\u201311). Land use\/cover maps by RS and ancillary data integration in a GIS environment. Global developments in environmental earth orbservation from space. Proceedings of the 25th EARSeL Symposium, Porto, Portugal."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Chang, C., Ye, Z., Huang, Q., and Wang, C. (2015, January 3\u20136). An integrative method for mapping urban land use change using geo-sensor data. Proceedings of the 1st International ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics, Seattle, WA, USA.","DOI":"10.1145\/2835022.2835031"},{"key":"ref_36","first-page":"576","article-title":"Land use mapping using visual vs. digital image interpretation of TM and Google Earth derived imagery in Shrivan-Darasi watershed (Northwest of Iran)","volume":"3","author":"Ghorbani","year":"2013","journal-title":"Eur. J. Exp. Biol."},{"key":"ref_37","first-page":"763","article-title":"Comparison between land use\/land cover mapping through Landsat and Google Earth imagery","volume":"13","author":"Jaafari","year":"2013","journal-title":"Am. J. Agric. Environ. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1177\/194008291300600110","article-title":"Distribution and abundance of lions in northwest Tete Province, Mozambique","volume":"6","author":"Jacobson","year":"2013","journal-title":"Trop. Conserv. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.envsoft.2015.06.011","article-title":"A novel approach to mapping land conversion using Google Earth with an application to East Africa","volume":"72","author":"Jacobson","year":"2015","journal-title":"Environ. Model. Softw."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"991","DOI":"10.14358\/PERS.69.9.991","article-title":"Spatial Metrics and Image Texture for Mapping Urban Land Use","volume":"69","author":"Herold","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3525","DOI":"10.1080\/01431160110109606","article-title":"Land cover mapping principles: A return to interpretation fundamentals","volume":"23","author":"King","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","unstructured":"Puig, C.J., Hyman, G., and Bola\u00f1os, S. (2017, March 28). Digital Classification vs. Visual Interpretation: A case study in humid tropical forests of the Peruvian Amazon. Available online: https:\/\/www.researchgate.net\/publication\/237021820_Digital_Classification_vs_Visual_Interpretation_a_case_study_in_humid_tropical_forests_of_the_Peruvian_Amazon."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/4\/102\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:31:38Z","timestamp":1760207498000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/4\/102"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,3,30]]},"references-count":42,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2017,4]]}},"alternative-id":["ijgi6040102"],"URL":"https:\/\/doi.org\/10.3390\/ijgi6040102","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,3,30]]}}}