Unveiling China's Urbanization and Vegetation Restoration using Earth Observation
Publikation: Bog/antologi/afhandling/rapport › Ph.d.-afhandling › Forskning
Urbanization is a global trend with more than two-thirds of the world’s population expected to reside in urban areas by 2050. Despite urban areas covering only 4% of global lands, the process of urbanization, which involves the growth and expansion of cities, has a significant impact on the surrounding environment. China has experienced unprecedented urbanization in recent decades, resulting in rural depopulation and a substantial increase in the total population. Urbanization has been widely recognized as a significant contributor to the direct negative impact on vegetation cover and growth. However, the process of rural depopulation is expected to promote vegetation restoration by alleviating the pressure on agricultural land and natural land in rural regions. In addition, recognizing the adverse effects of urbanization, China has implemented various measures to mitigate these effects, including urban greening policy and conservation efforts towards achieving carbon neutrality.
While the negative and positive processes associated with urbanization and vegetation restoration are well understood, there is still a need to comprehensively analyze the trade-offs involved. Earth observation (EO) has been widely applied to study urbanization and vegetation dynamics. Advancements in computer science and high-resolution satellite technology have opened new opportunities for studying urban vegetation dynamics. Recent studies have reported successful application of cloud platforms and machine learning techniques in this field. Building upon this context, this thesis centers around the three questions: 1) To which extent and how is a large and transient carbon sink induced by urbanization and rural depopulation? 2) To what extent, in which locations, and how can vegetation browning from urban expansion can be balanced by urban greening in urban core areas based on segmentation methods using satellite time series? 3) What is the change in urban tree cover as a consequence of urbanization and urban tree planting in China? This thesis focuses on three interconnected questions that shed light on the relationship between urbanization, vegetation dynamics, and carbon neutrality.
The first study investigated the relationship between urbanization and carbon neutrality in China, with a focus on whether sustainable urbanization could help reduce atmospheric CO2. To do this, the study used various datasets, including satellite time series, gridded population density, mobile-phone-based location, and national census data, to examine changes in aboveground biomass and rural-urban population migration. The results found that although urban expansion caused an initial aboveground carbon loss of -0.02 Pg C between 2002 and 2010, urban greening helped to compensate for these losses, resulting in an overall balance of +0.03 Pg C in urban areas between 2002 and 2019. Interestingly, the study found that sustainable rural-urban population migration could help to reduce pressure on natural resources, as the maximum increase in aboveground carbon stocks occurred at intermediate distances (2 - 4 km) from rural settlements. The study also observed that rural areas experiencing depopulation (-14 million people per year) coincided with an extensive aboveground carbon sink of 0.28 ± 0.05 Pg C yr−1 during 2002-2019. However, the study also noted that reducing CO2 emissions from fossil fuel burning would be necessary to achieve carbon neutrality, as the capacity of forests to remove carbon is limited by tree cover growth saturation.
To further study the patterns of urban greening in China, the second study monitored vegetation change types of urban areas across China, utilizing MODIS and Landsat satellite NDVI time series. A total of 974 major cities (urban area > 20 km2) were studied over the period of 20002020, and an urban vegetation change typology was developed which included five types of vegetation dynamics: greening, browning, stable, reversal and recovery. The study revealed a rapid urban expansion, associated with browning in urban areas before 2011, followed by a widespread re-greening of urban areas after 2011. The recovery in greenness was observed in 63.45% of all cities, while 14.68% exhibited continuous browning and 8.13% continuous greening. The high proportion of cities classified as showing recovery could be attributed to the Chinese government's implementation of urban greening strategies aiming at improving the urban environment. The study's findings provide insight into the extent, location, and timing of vegetation browning due to urban expansion, balanced by urban greening in urban core areas.
Finally, the third study investigated the spatial distribution of urban trees and quantify the areal change of urban tree canopy for 2010-2019 using high-spatial-resolution satellite measurements. To achieve this, a deep learning framework was utilized to map urban tree canopies at 3-meter resolution using PlanetScope satellite imagery for the year 2019, in total covering 242 major cities (urban areas>50 km2) in China. The resulting map revealed a the mean tree cover of 11.47% in urban areas, corresponding to 5951 km2. To further investigate temporal changes in tree cover, RapidEye satellite imagery from 2010 was used to study tree cover changes for 145 selected cities, revealing an increase (+4 %) in tree cover from 20102019, concurring with continuous expansion of impervious surfaces. This increase in urban tree cover contributed to the observed urban greening in China. The high-resolution tree canopy maps derived from low-cost nanosatellites over a 10-year period can serve as a high-quality database for tree monitoring at street level and support the monitoring, reporting and verification of urban green policies.
In summary, this thesis utilizes advanced earth observation methods and analyzes the interplay between urbanization, vegetation recovery, along with the implementation of strategies for sustainable development. Specifically, it focuses on China's efforts to balance urban expansion with vegetation restoration, emphasizing the significance of integrating green spaces and vegetation within urban landscapes. The three national-scale studies demonstrate the positive impacts of these initiatives on the society, economy, and the environment, highlighting the potential for sustainable development in developing regions characterized by urbanization.
While the negative and positive processes associated with urbanization and vegetation restoration are well understood, there is still a need to comprehensively analyze the trade-offs involved. Earth observation (EO) has been widely applied to study urbanization and vegetation dynamics. Advancements in computer science and high-resolution satellite technology have opened new opportunities for studying urban vegetation dynamics. Recent studies have reported successful application of cloud platforms and machine learning techniques in this field. Building upon this context, this thesis centers around the three questions: 1) To which extent and how is a large and transient carbon sink induced by urbanization and rural depopulation? 2) To what extent, in which locations, and how can vegetation browning from urban expansion can be balanced by urban greening in urban core areas based on segmentation methods using satellite time series? 3) What is the change in urban tree cover as a consequence of urbanization and urban tree planting in China? This thesis focuses on three interconnected questions that shed light on the relationship between urbanization, vegetation dynamics, and carbon neutrality.
The first study investigated the relationship between urbanization and carbon neutrality in China, with a focus on whether sustainable urbanization could help reduce atmospheric CO2. To do this, the study used various datasets, including satellite time series, gridded population density, mobile-phone-based location, and national census data, to examine changes in aboveground biomass and rural-urban population migration. The results found that although urban expansion caused an initial aboveground carbon loss of -0.02 Pg C between 2002 and 2010, urban greening helped to compensate for these losses, resulting in an overall balance of +0.03 Pg C in urban areas between 2002 and 2019. Interestingly, the study found that sustainable rural-urban population migration could help to reduce pressure on natural resources, as the maximum increase in aboveground carbon stocks occurred at intermediate distances (2 - 4 km) from rural settlements. The study also observed that rural areas experiencing depopulation (-14 million people per year) coincided with an extensive aboveground carbon sink of 0.28 ± 0.05 Pg C yr−1 during 2002-2019. However, the study also noted that reducing CO2 emissions from fossil fuel burning would be necessary to achieve carbon neutrality, as the capacity of forests to remove carbon is limited by tree cover growth saturation.
To further study the patterns of urban greening in China, the second study monitored vegetation change types of urban areas across China, utilizing MODIS and Landsat satellite NDVI time series. A total of 974 major cities (urban area > 20 km2) were studied over the period of 20002020, and an urban vegetation change typology was developed which included five types of vegetation dynamics: greening, browning, stable, reversal and recovery. The study revealed a rapid urban expansion, associated with browning in urban areas before 2011, followed by a widespread re-greening of urban areas after 2011. The recovery in greenness was observed in 63.45% of all cities, while 14.68% exhibited continuous browning and 8.13% continuous greening. The high proportion of cities classified as showing recovery could be attributed to the Chinese government's implementation of urban greening strategies aiming at improving the urban environment. The study's findings provide insight into the extent, location, and timing of vegetation browning due to urban expansion, balanced by urban greening in urban core areas.
Finally, the third study investigated the spatial distribution of urban trees and quantify the areal change of urban tree canopy for 2010-2019 using high-spatial-resolution satellite measurements. To achieve this, a deep learning framework was utilized to map urban tree canopies at 3-meter resolution using PlanetScope satellite imagery for the year 2019, in total covering 242 major cities (urban areas>50 km2) in China. The resulting map revealed a the mean tree cover of 11.47% in urban areas, corresponding to 5951 km2. To further investigate temporal changes in tree cover, RapidEye satellite imagery from 2010 was used to study tree cover changes for 145 selected cities, revealing an increase (+4 %) in tree cover from 20102019, concurring with continuous expansion of impervious surfaces. This increase in urban tree cover contributed to the observed urban greening in China. The high-resolution tree canopy maps derived from low-cost nanosatellites over a 10-year period can serve as a high-quality database for tree monitoring at street level and support the monitoring, reporting and verification of urban green policies.
In summary, this thesis utilizes advanced earth observation methods and analyzes the interplay between urbanization, vegetation recovery, along with the implementation of strategies for sustainable development. Specifically, it focuses on China's efforts to balance urban expansion with vegetation restoration, emphasizing the significance of integrating green spaces and vegetation within urban landscapes. The three national-scale studies demonstrate the positive impacts of these initiatives on the society, economy, and the environment, highlighting the potential for sustainable development in developing regions characterized by urbanization.
Originalsprog | Engelsk |
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Forlag | Department of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen |
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Antal sider | 115 |
Status | Udgivet - 2023 |
ID: 383007235