Understanding the Correlation between Landscape Pattern and Vertical Urban Volume by Time-Series Remote Sensing Data: A Case Study of Melbourne

Mengyu Ge,Guang Yang,Wenbing Gong,Yan Gong,Pengjie Tao,Shenghui Fang

doi:10.3390/ijgi10010014

Abstract

Urbanization is changing the world’s surface pattern more and more drastically, which brings many social and ecological problems. Quantifying the changes in the landscape pattern and 3D structure of the city is important to understand these issues. This research study used Melbourne, a compact city, as a case study, and focused on landscape patterns and vertical urban volume (volume mean (VM), volume standard deviation (VSD)) and investigate the correlation between them from the scope of different scales and functions by Remote Sensing (RS) and Geographic Information System (GIS) techniques. We found: (1) From 2000 to 2012, the landscape pattern had a trend of decreasing fragmentation and increasing patch aggregation. The growth of VM and VSD was more severe than that of landscape metrics, and presented a “high–low” situation from the city center to the surroundings, maintaining the structure of “large east and small west”. (2) Landscape pattern was found closely associated with the urban volume. In the entire study area, landscape pattern patches with low fragmentation and high aggregation were directly proportional to VM with high value, which represented high urbanization, and patches with high connectivity and fragmentation had a positive relationship with high VSD, which represented strong spatial recognition. (3) The urban volumes of different urban functional areas were affected by different landscape patterns, and the analysis based on the local development situation can explain the internal mechanism of the interaction between the landscape pattern and the urban volume.

Highlights

Urban expansion refers to a form of natural land conversion into buildings, impervious surfaces, and related foundation facility that occurs with population growth, product development, scientific progress, and industrial structure adjustment [1]
In addition to manmade coverage, 4.51 km2 of grassland was converted into woodland, and 1.44 km2 and 2.78 km2 of bare land were converted into woodland and grassland, respectively, which resulted in the overall area of woodland unchanged, 8.44 km2 of woodland was converted to artificial coverage
Our study demonstrated that the volume mean (VM) and Volume Standard Deviation (VSD) value increased overall, while Patch Density (PD) and Landscape Shape Index (LSI), which represented 2D fragmentation and complexity, were generally reduced

Summary

Introduction

Urban expansion refers to a form of natural land conversion into buildings, impervious surfaces, and related foundation facility that occurs with population growth, product development, scientific progress, and industrial structure adjustment [1]. Urban expansion resulted in the change of the original landscape pattern [11], which referred to the spatial structure characteristics of the landscapes that are geospatial units composed of different kinds of ecosystem mosaics [12,13]. Detecting changes in the landscape pattern index through remote sensing can reflect the characteristics of urban expansion [14,15,16]. Effat used Landsat data to calculate the landscape index Shannon’s Diversity

Results

Discussion

Conclusion