Abstract

Ecological land is a type of land that has considerable ecological value. Understanding the evolution of urban ecological land in Zhuhai, China, holds great significance for revealing the evolution of ecological land in the Dawan District of southern China. We explored the temporal and spatial variation in urban ecological land in Zhuhai using the transformation matrix, equivalent ecological land, landscape index and ecological land center of gravity migration methods. Multivariate logistic regression was used to analyze the mechanism of ecological land change, and a transition probability map of the ecological land in the study area was drawn. The results showed the following. (1) From 1991 to 2018, the area of ecological land in Zhuhai city continuously decreased, with a reduction in area of 274.8 km2, or 32.3%. Sharp changes mainly occurred from 1991 to 2000. (2) The ecological land in the study area has gradually become fragmented, and the degree of landscape heterogeneity has increased. Affected by the expansion of the outer edge of the city to the southwest and the construction of ecological land within the city, the center of gravity of the ecological land has shifted to the northeast by 1346 m. (3) The elevation, slope, distance from built-up land and growth rate of built-up land are important factors influencing the transformation of ecological land. In the future, rivers and shallow coastal waters, tidal flats, and grasslands in the study area have the highest probability of transformation. The Jinwan District and Xiangzhou District will face severe ecological land protection pressure. The method of spatial–temporal analysis of urban ecological land developed in this paper can be applied in similar studies on other cities, and the results obtained for Zhuhai, China, have reference value for future urban planning and ecological protection work.

Highlights

  • Ecological land is a type of land that has considerable ecological value

  • The method of spatial–temporal analysis of urban ecological land developed in this paper can be applied in similar studies on other cities, and the results obtained for Zhuhai, China, have reference value for future urban planning and ecological protection work

  • According to the land use planning map of Zhuhai city, the characteristics of the city, the status of human activities and land use, and the types of natural ecosystems, we identified and categorized land use into 10 types: woodland, grassland, rainfed cropland, paddy fields, aquaculture areas, reservoirs and pit ponds, tidal flats, rivers and shallow water, built-up land and unutilized land (Supplemental Materials S1: Land use types and descriptions)

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Summary

Introduction

Ecological land is a type of land that has considerable ecological value. Understanding the evolution of urban ecological land in Zhuhai, China, holds great significance for revealing the evolution of ecological land in the Dawan District of southern China. The rapid development of remote sensing (RS) Earth observation technology provides abundant, freely available, long-term, medium- and high-resolution satellite imagery resources for urban ecological research These images can be used to draw long time series and high-precision urban land spatial distribution ­maps[19,20]. Aspects of the regional environment, such as the slope, elevation, soil suitability, accessibility by road and location of urban centers, and socioeconomic factors, such as population, industry, and gross domestic product (GDP), are considered the main d­ rivers[23] Model analysis methods, such as correlation analysis, stepwise regression analysis, principal component analysis, random forest analysis, and logistic regression analysis, are widely used to explain the driving mechanisms of land use/cover change and to identify the key drivers of such ­change[24,25,26]. To evaluate ecological processes at the landscape level and to detect and quantify temporal and spatial changes in landscape composition and configuration, researchers have developed a series of indicators, such as patch area, shape, aggregation and diversity, for quantitative ­analysis[32,33]

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