Abstract
Administering an urban boundary (UB) is increasingly important for curbing disorderly urban land expansion. The traditionally manual digitalization is time-consuming, and it is difficult to connect UB in the urban fringe due to the fragmented urban pattern in daytime data. Nighttime light (NTL) data is a powerful tool used to map the urban extent, but both the blooming effect and the coarse spatial resolution make the urban product unable to meet the requirements of high-precision urban study. In this study, precise UB is extracted by a practical and effective method using NTL data and Landsat 8 data. Hangzhou, a megacity experiencing rapid urban sprawl, was selected to test the proposed method. Firstly, the rough UB was identified by the search mode of the concentric zones model (CZM) and the variance-based approach. Secondly, a buffer area was constructed to encompass the precise UB that is near the rough UB within a certain distance. Finally, the edge detection method was adopted to obtain the precise UB with a spatial resolution of 30 m. The experimental results show that a good performance was achieved and that it solved the largest disadvantage of the NTL data-blooming effect. The findings indicated that cities with a similar level of socio-economic status can be processed together when applied to larger-scale applications.
Highlights
In the background of global urbanization, urbanization impacts on the natural ecosystems and social systems are increasingly concerning [1,2,3]
The widths of the outside and inside buffer, which was established around the rough urban boundary (UB), were about 390 m and 780 m, respectively
We combined the advantages of nighttime and daytime data for delimiting the UB, which is a concept that is different from urban impervious surface extraction
Summary
In the background of global urbanization, urbanization impacts on the natural ecosystems and social systems are increasingly concerning [1,2,3]. UBs are lines that encompass the urban land cover in a limited extent, which include urban green space, urban impervious surfaces, urban waters, and so on. The coarse spatial resolution of NTL data itself will affect the accuracy of urban extent Owing to these limitations, most NTL urban studies have been limited to large scales, such as continental and global scales. Multiple research studies have attempted to improve the accuracy of extracting the spatial extent of urban areas. An effective and relatively high-accuracy method has great practicability and will expand the application scope of NTL data Among these technologies, the primary method to identify urban areas is the threshold method because of its simplicity. WWeeddeveveleoloppeeddaastsetpep-b-byy-s-tseteppfrfarammeewwoorrkktotoeexxtrtraaccttththeeUUBB(F(Figiguurree22) )ththaat timimpplelemmeenntstsaarraappidid, , bbroroaadd-s-sccaaleleaapppplliiccaattiioonn,,wwhhiillsstt pprroovviiddiinngg rreellaattiivveellyyaaccccuurraatteerreessuultlsts. .ThTehefirfisrtssttesptewp awsatso troemreomveovthee thdeisdtoisrttioorntioinn tihnethraedriaadnicaenicmeaigmeafgoellfoowlleodwbedy tbhyetdheeledteiolentioofnaobfnaobrmnoarlmpaolinptosinintsthine tNhTeLNdTaLtad. aTtha.e TVheAVNAUNI UinIdienxdewxaws assusbusbeqseuqeunetlnytlcyaclcaulcluatlaedte,dp, epremrmittiitntigngththeeloloccaatitoionnoofftthhee rroouugghh UUBB bbyytthheeCCZZMM seseaarcrhchininggmmodoedaenadnvdarviaarnicaen-cbea-sbeadseadpparpopacrhoa. cThh.eTnh, aenn,inasnidiensainddeoauntdsidoeubtsuidffeerbwuaffsedr ewvealsopdeedvealloopnegd baoltohnsgidbeostohf tshideersouogfhtUheB troouingchorUpoBrattoe ailnmcoorspt oarllatoef tahlembolsotomalilngofeftfheect banlodomthienugnedfefreecsttiamnadtiothne aurenad. eFriensatlilmy,atthioenrevariseead. eFdingaelldye,tetchteionremviestehdodedalgloewdeedtefcotrioanprmeceistheoadndaclloonwtienduofuosr UaB.precise and continuous UB
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