Abstract

Accurate mapping of temporal changes in urban land use and land cover (LULC) is important for monitoring urban expansion and changes in LULC, urban planning, environmental management, and environmental modeling. In this study, we present a feature-based approach of the decision tree classification (FBA-DTC) method for mapping LULC based on spectral and topographic information. Landsat 5 TM and Land 8 OLI images were employed, and the technique was applied to the coastal city of Xiamen, China. The method integrates multi-spectral features such as SAVI (soil adjustment vegetation index), NDWI (normalized water index), MNDBaI (modified normalized difference barren index), BI (brightness index), and WI (wetness index), with topographic features including DEM and slope. In addition, the new approach distinguishes between fallow land and cropland, and separates high-rise buildings from beaches and water bodies. Several of the FBA-DTC parameters (or rules) from 1997 to 2015 remained constant (i.e., DEM and slope), whereas others changed slightly. WI was negatively related to percent area of beach land, and BI was negatively related to percent area of arable land. The FBA-DTC method had an average user’s accuracy (UA) of 91.36% for built-up land, an average overall accuracy (OA) of 92.13%, and a Kappa coefficient (KC) of 0.90 for the period from 2003 to 2015, representing respective increases of 15.87%, 10.17%, and 0.13, compared with values calculated using maximum likelihood classification (MLC). Over the past 12 years, built-up land increased from 23.67% to 43.17% owing to occupation of coastal reclamation, arable land, and forest land. The FBA-DTC method presented here is a valuable technique for evaluating urban growth and changes in LULC classification for coastal cities.

Highlights

  • Urbanization represents the territorial and socioeconomic progress of an area and is associated with the transformation of land use and land cover (LULC) types from undeveloped to developed [1]

  • Since the Landsat satellite was launched in the early 1970s, medium-resolution remote sensing imagery (15–30 m resolution) such as Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Landsat Operational Land Imager (OLI), Hyperion [6], and SPOT5 [7] images, and high spatial resolution imagery (

  • Though beaches and even water bodies in Xiamen have been urbanized, sea level has a huge impact on beach area

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Summary

Introduction

Urbanization represents the territorial and socioeconomic progress of an area and is associated with the transformation of land use and land cover (LULC) types from undeveloped to developed [1]. Coastal urban areas have experienced fast population explosion and dynamic economic growth. LULC types and their areal distribution is essential for coping with a variety of environmental and socioeconomic issues [3,4]. Remote sensing can provide timely and detailed views of land cover, and is a useful approach for monitoring the growth and spatial distribution of urban areas [5]. Since the Landsat satellite was launched in the early 1970s, medium-resolution remote sensing imagery (15–30 m resolution) such as Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Landsat Operational Land Imager (OLI), Hyperion [6], and SPOT5 [7] images, and high spatial resolution imagery (

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