Quantifying Urban Vegetation Dynamics from a Process Perspective Using Temporally Dense Landsat Imagery

Abstract

Urban vegetation can be highly dynamic due to the complexity of different anthropogenic drivers. Quantifying such dynamics is crucially important as it is a prerequisite to understanding its social and ecological consequences. Previous studies have mostly focused on the urban vegetation dynamics through monotonic trends analysis in certain intervals, but not considered the process which provides important insights for urban vegetation management. Here, we developed an approach that integrates trends with dynamic analysis to measure the vegetation dynamics from the process perspective based on the time-series Landsat imagery and applied it in Shenzhen, a coastal megacity in southern China, as an example. Our results indicated that Shenzhen was turning green from 2000–2020, even though a large-scale urban expansion occurred during this period. Approximately half of the city (49.5%) showed consistent trends in greening, most of which were located in the areas within the ecological protection baseline. We also found that 35.3% of the Shenzhen city experienced at least a one-time change in urban greenness that was mostly caused by changes in land cover types (e.g., vegetation to developed land). Interestingly, 61.5% of these lands showed trends in greening in the recent change period and most of them were distributed in build-up areas. Our approach that integrates trends analysis and dynamic process reveals information that cannot be discovered by monotonic trends analysis alone, and such information can provide insights for urban vegetation planning and management.

Vegetation Dynamics under Rapid Urbanization in the Guangdong–Hong Kong–Macao Greater Bay Area Urban Agglomeration during the Past Two Decades

“…Taking the most developed GZ and SZ as an example, vegetation of old urban districts in both cities generally showed a significant increasing trend although the NDVI values in these areas were relatively low, and the greening trend was predicted to continue in the future (Figure 4). These results agree with other studies that also observed urban greening in most built-up areas in GZ and SZ recently [53,54]. Nevertheless, not all cities experienced greening in the BP regions, and some cities even presented vegetation degradation in most of the BP region such as ZQ.…”

The evaluation of land use cover changes through the composite approach of Landsat 8 and the land use capability index for the Bedadung watershed

“…Land cover can provide information through modeling and events that occurred in the past and affect the present, especially related to climate and human activities (Gong et al, 2013;Jia et al, 2014). Land cover becomes information through remote sensing with Landsat satellite data analysis through spatial (Gumma et al, 2011;Gong et al, 2013;Vahid et al, 2021;Yu et al, 2021). Remote sensing data in the form of satellite photos is a record of each time and the latest (Joyce et al, 2009;Phiri and Morgenroth, 2017;Chasmer et al, 2020).…”