Abstract

Most land cover mapping methods require the collection of ground reference data at the time when the remotely sensed data are acquired. Due to the high cost of repetitive collection of reference data, however, it limits the production of annual land cover maps to a short time span. In order to reduce the mapping cost and to improve the timeliness, an object-based sample transfer (OBST) method was presented in this study. The object-based analysis with strict constrains in area, shape and index values is expected to reduce the accident errors in selecting and transferring samples. The presented method was tested and compared with same-year mapping (SY), cross-year mapping (CY) and multi-index automatic classification (MI). For the study years of 2001–2016, both the overall accuracies (above 90%) and detailed accuracy indicators of the presented method were very close to the SY accuracy and higher than accuracies of CY and MI. With the presented method, the times-series land cover map of Guangzhou, China were derived and analyzed. The results reveal that the city has undergone rapid urban expansion and the pressure on natural resources and environment has increased. These results indicate the proposed method could save considerable cost and time for mapping the spatial-temporal changes of urban development. This suggests great potential for future applications as more satellite observations have become available all over the globe.

Highlights

  • More than 50% of the world’s population live in cities and this figure is projected to reach 67.2% in 2050 [1]

  • This study aims to improve the accuracy of mapping land cover variations without current sampTlhesis, bstausdedy aoinmasntoobimjecptr-boavseedthesaamccpuleratcryanosffemr a(OppBiSnTg) lmanedthcoodvewritvharsitartiicotncsownsittrhaoinust cinurarreenat, ssahmappelesa,nbdaseinddoenxanvaolbujee.ctT-bhaesreed, soabmjepclte-btraasnesdfersa(mOBpSliTn)gmaenthdodchwainthgestrdicetteccotniostnraianlgs oinritahremas, shwaepree adnedveinlodpeexdvianluteh.eThperorec,eossbjoecft-sbaamspedlesasemlepcltiinogn aannddchsaamngpeledetrtaenctsifoenr,arlgesoprietchtmiveslwy.erItesdreevseullotspewdeirne tchaerepfruolclyescsoomfpsaamrepdlwe sitehletchtoiosne farnodmsSaYm,pCleYtaranndsMferI,. rAetsplaesctt,icvhealyr.aIcttserriesstuiclstsawnderpeoctaernetfiualllaypcpolmicpatairoends wabitohutthtohseepfrroompoSseYd, CstYraatnegdyMwI.eAretdlaissct,ucshseadra.cteristics and potential applications about the proposed strategy were discussed

  • Among the five land cover classes in this study, The built-up is defined as built environment with impervious surfaces dominated by man-made structures such as buildings and transportation facilities; water includes areas of open water such as rivers and ponds; bare land includes exposed soil surfaces with little vegetation cover such as deforested land, abandoned farmland, quarries and naturally non-vegetated areas; forest represents the woodlands; and cropland mainly includes herbaceous areas that are covered with shrubs, grass, farmland and orchard

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Summary

Introduction

More than 50% of the world’s population live in cities and this figure is projected to reach 67.2% in 2050 [1]. Along with the rapid growth of population concentrations and economic activities being intensified, the demand for developed land increased dramatically, manifesting as urbanization [2]. Global urban areas have been rapidly expanding, especially in developing countries. The conversion of rural areas into urban areas through development is currently proceeding more quickly in developing countries than in the developed world, for example, in China, India, Vietnam and Bangladesh [1,2,3,4,5,6]. Urban land covers only less than 3% of the global terrestrial surface, their marked effects on environmental conditions becomes increasingly serious and is generating increasing attention globally [5,6,7]

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