Abstract

An understanding of historical and present land use and land cover (LULC) information and its changes, such as urbanization and urban growth, is critical for city planners, land managers and resource managers in any rapidly changing landscape. To deal with this situation, the development of a new supervised classification method for multitemporal LULC mapping with long-term reliable information is necessary. The ultimate goal of this study was to develop a new classification method using harmonic analysis with a minimum spectral distance algorithm for multitemporal LULC mapping. Here, the Jiangning District of Nanjing City, Jiangsu Province, China was chosen as the study area. The research methodology consisted of two main components: (1) Landsat data selection and time-series spectral reflectance reconstruction and (2) multitemporal LULC classification using HA with a minimum spectral distance algorithm. The results revealed that the overall accuracy and Kappa hat coefficients of the four LULC maps in 2000, 2006, 2011, and 2017 were 97.03%, 90.25%, 91.19%, 86.32% and 95.35%, 84.48%, 86.74%, 80.24%, respectively. Further, the average producer accuracy and user accuracy of the urban and built-up land, agricultural land, forest land, and water bodies from the four LULC maps were 92.30%, 90.98%, 94.80%, 85.65% and 90.28%, 93.17%, 84.40%, 99.50%, respectively. Consequently, it can be concluded that the newly developed supervised classification method using harmonic analysis with a minimum spectral distance algorithm can efficiently classify multitemporal LULC maps.

Highlights

  • By definition, “land use refers to what people do on the land surface while land cover refers to the type of material present on the landscape” [1]

  • To produce highly accurate land use and land cover (LULC) maps for any given time similar to the Change Detection and Classification (CCDC) approach [45], we propose a new supervised multitemporal LULC classification workflow using harmonic analysis and a minimum spectral distance algorithm with time-series Landsat 5, 7, and 8 datasets between 2000 and 2017

  • According to reports of the Ministry of Housing and Urban-Rural Development (MOHURD) of the People’s Republic of China [62] and the Nanjing Municipal Bureau of Statistics [63], the population in Nanjing City increased from 3.1 million persons in 2000 to 5.9 million persons in 2016, and the urban and built-up area expanded from 201.40 km2 to 773.79 km2 in the same period

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Summary

Introduction

“land use refers to what people do on the land surface (e.g., agriculture, commerce, settlement) while land cover refers to the type of material present on the landscape (e.g., water, crops, forest, wetland, humanmade materials such as asphalt)” [1]. Several studies on LULC changes and their impacts have been conducted worldwide from multiple dimensions using satellite remote sensing and GIS technology [9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]. All of these studies require time-series datasets that are mostly derived from Earth observation satellites to classify multitemporal LULC maps

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