scholarly journals Global Changes in Urban Vegetation Cover

2019 ◽  
Vol 12 (1) ◽  
pp. 23 ◽  
Author(s):  
Daniel R. Richards ◽  
Richard N. Belcher
Keyword(s):  
Vegetation Cover ◽  
Urban Areas ◽  
Well Being ◽  
Google Earth ◽  
Eastern North America ◽  
Urban Vegetation ◽  
Global Changes ◽  
Suburban Sprawl ◽  
The World ◽  
Google Earth Engine

Urban vegetation provides many ecosystem services that make cities more liveable for people. As the world continues to urbanise, the vegetation cover in urban areas is changing rapidly. Here we use Google Earth Engine to map vegetation cover in all urban areas larger than 15 km2 in 2000 and 2015, which covered 390,000 km2 and 490,000 km2 respectively. In 2015, urban vegetation covered a substantial area, equivalent to the size of Belarus. Proportional vegetation cover was highly variable, and declined in most urban areas between 2000 and 2015. Declines in proportional vegetated cover were particularly common in the Global South. Conversely, proportional vegetation cover increased in some urban areas in eastern North America and parts of Europe. Most urban areas that increased in vegetation cover also increased in size, suggesting that the observed net increases were driven by the capture of rural ecosystems through low-density suburban sprawl. Far fewer urban areas achieved increases in vegetation cover while remaining similar in size, although this trend occurred in some regions with shrinking populations or economies. Maintaining and expanding urban vegetation cover alongside future urbanisation will be critical for the well-being of the five billion people expected to live in urban areas by 2030.

scholarly journals INVESTIGATING WATER STORAGE CHANGES IN IRAN USING GRACE AND CHIRPS DATA IN THE GOOGLE EARTH ENGINE SYSTEM

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 981-984
Author(s):  
S. Shami ◽  
Z. Ghorbani
Keyword(s):  
Satellite Data ◽  
Water Storage ◽  
Google Earth ◽  
Annual Precipitation ◽  
Resources Management ◽  
Total Annual Precipitation ◽  
The World ◽  
Grace Satellite ◽  
Google Earth Engine ◽  
Engine System

Abstract. Water storage in regions with the weather hot and arid or semi-arid such as Iran have many uses. Including these water storage, can be referred to groundwater. Groundwater is one of the sources of sweet waters in the world, and one of the factors is economical and social development. Hence, monitoring its changes in water resources management is of great importance. On the other hand, precipitation is one of the factors directly affecting the water storage level and groundwater level changes. In this study, water storage changes with GRACE satellite data and total annual precipitation with CHIRPS data in the Google Earth Engine system investigated for Iran during 2003–2017. The results obtained from the GRACE satellite data indicate over 10 cm reducing of the water storage levels in Iran during the period between 2008 to 2017. Also, the chart obtained from the CHIRPS data for the total annual precipitation shows that the amount of rainfall since 2008 has decreased in this region.

scholarly journals A Long-term Spatial and Temporal Analysis of NDVI Changes in Java Island Using Google Earth Engine

2021 ◽  
Vol 936 (1) ◽  
pp. 012038
Author(s):  
Benedict ◽  
Lalu Muhamad Jaelani
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Data ◽  
Temporal Analysis ◽  
Google Earth ◽  
Vegetation Density ◽  
Angle Sensor ◽  
Study Results ◽  
Google Earth Engine

Abstract Java is Indonesia’s and the world’s most populous island. The increase in population on the island of Java reduces the area of forest and other vegetation covers. Landslides, floods, and other natural disasters are caused by reduced vegetation cover. Furthermore, it has the potential to lead to the extinction of flora and fauna. The Normalized Difference Vegetation Index (NDVI) can be used to monitor the vegetation cover. This study analyzes the NDVI changes value from 2005 to 2020 using Terra and Aqua MODIS image data processed using Google Earth Engine. Processing was carried out in some stages: down-setting, performing NDVI processing, calculating monthly average NDVI, calculating annual average NDVI, and analyzing. From the study results, the NDVI value of Terra and Aqua MODIS data has a solid but imperfect correlation coefficient due to differences in orbital time which causes differences in solar zenith angle, sensor viewing angle, and azimuth angle. Then from this study, it was found that overall, changes in vegetation density cover on the island of Java decreased, which was indicated by the NDVI decline rate of -0.00047/year. The most significant decrease in NDVI value occurred in the period 2015–2016, covering an area of 13994.630 km2, and the most significant increase in NDVI occurred in the period 2010–2011, covering an area of 2256.101 km2.

scholarly journals An Assessment of Urban Vegetation Abundance in Accra Metropolitan Area, Ghana: A Geospatial Approach

2018 ◽  
Vol 11 (1-2) ◽  
pp. 37-44 ◽  
Author(s):  
Alex Barimah Owusu
Keyword(s):  
Metropolitan Area ◽  
Vegetation Cover ◽  
Urban Areas ◽  
Rate Of Change ◽  
Urban Vegetation ◽  
City Development ◽  
Key Informants ◽  
Development Agenda ◽  
Green Vegetation ◽  
The City

Abstract The essential role played by urban vegetation in making urban areas livable is often overlooked in many developing cities. This is the case of Ghana where its capital, Accra is developing at the expense of urban vegetation. This study was conducted at the metropolitan area of Accra to estimate how the extent of vegetation cover has changed in the period of 1986-2013, using remote sensing satellite data from Landsat TM and ETM+. Furthermore, views of key informants were assessed on changes in the livability of the city of Accra which may be attributed to loss of urban green vegetation in the city. It was found that between 1986 and 2013, 42.53 km2 of vegetation was lost representing 64.6% of total vegetation in 1986. The rate of change in vegetation cover between 1986 and 1991 measured around 2.14% of the total land area annually. This however, reduced in the subsequent years measuring 0.26% between 2002 and 2008. Key informants interviewed, also believe that the loss of vegetation in the city creates livability concerns relating to ecosystem functioning, temperature rise and air quality. It is therefore recommended for urban planners and decision makers to address three critical concerns of resilience, sustainability and livability, which are the missing links in the city development agenda.

scholarly journals Blue-Green Smart Mobility Technologies as Readiness for Facing Tomorrow’s Urban Shock toward the World as a Better Place for Living (Case Studies: Songdo and Copenhagen)

Technologies ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 39
Author(s):  
Hamid Doost Mohammadian ◽  
Fatemeh Rezaie
Keyword(s):  
Quality Of Life ◽  
Case Studies ◽  
Urban Areas ◽  
Wave Theory ◽  
Well Being ◽  
Sustainable Mobility ◽  
Sustainable Infrastructure ◽  
The World ◽  
Environment Sustainability

Nowadays, we are on the cusp of a future that will face many global challenges and crises, as well as unforeseeable shocks of tomorrow. The rapid growth and development of technology will bring forth exponential change that may challenge and threaten our human psychology. Solutions and policies are needed to deal with today’s challenges, tomorrow’s shocks, and global crises to preserve the world and mankind for the future. In this research, Blue-Green sustainable mobility technologies are introduced as a pathway to create modern sustainable and livable urban areas to tackle these challenges. Clean and inclusive mobility, based on Blue-Green and sustainable infrastructure, low emission greenhouse gases, ubiquitous computing, smartness and digitalization is realized as one of the keys that could make the world a better place for living. This research examines inclusive transportation technology, its indicators and its impacts on creating modern livable urban areas with high a quality of life as a pathway to navigate the cusp of tomorrow. Furthermore, the roles of technology such as Information Technology, Internet of Things, Internet of Business, Internet of Manufacturing, and Internet of Energy as technology tools to develop such mobility is investigated. Literature reviews, surveys, case studies—including Songdo as a ubiquitous city and Copenhagen as a digital and clean city—and revised versions of Kiwi and Kampenhood and BESQoL (built environment sustainability and quality of life) methodologies are the main methods in this study. New concepts of mobility technology and eventuating cultural synergies, as a readiness for facing tomorrow’s world crises with a higher quality of life and well-being by using the 5th wave theory, are discussed.

scholarly journals Understanding the Spatial Distribution of Urban Forests in China Using Sentinel-2 Images with Google Earth Engine

Forests ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 729 ◽  
Author(s):  
Qianwen Duan ◽  
Minghong Tan ◽  
Yuxuan Guo ◽  
Xue Wang ◽  
Liangjie Xin
Keyword(s):  
High Resolution ◽  
Forest Cover ◽  
Urban Forest ◽  
Urban Forests ◽  
Well Being ◽  
Google Earth ◽  
Machine Learning Algorithms ◽  
Sustainable Urban Development ◽  
Google Earth Engine ◽  
Sentinel 2

Urban forests are vitally important for sustainable urban development and the well-being of urban residents. However, there is, as yet, no country-level urban forest spatial dataset of sufficient quality for the scientific management of, and correlative studies on, urban forests in China. At present, China attaches great importance to the construction of urban forests, and it is necessary to map a high-resolution and high-accuracy dataset of urban forests in China. The open-access Sentinel images and the Google Earth Engine platform provide a significant opportunity for the realization of this work. This study used eight bands (B2–B8, B11) and three indices of Sentinel-2 in 2016 to map the urban forests of China using the Random Forest machine learning algorithms at the pixel scale with the support of Google Earth Engine (GEE). The 7317 sample points for training and testing were collected from field visits and very high resolution images from Google Earth. The overall accuracy, producer’s accuracy of urban forest, and user’s accuracy of urban forest assessed by independent validation samples in this study were 92.30%, 92.27%, and 92.18%, respectively. In 2016, the percentage of urban forest cover was 19.2%. Nearly half of the cities had an urban forest cover between 10% and 20%, and the average percentage of large cities whose urban populations were over 5 million was 24.8%. Cities with less than half of the average were mainly distributed in northern and western parts of China, which should be focused on in urban greening planning.

scholarly journals Estimating urban vegetation cover fraction using Google Earth® images

2012 ◽  
Vol 7 (3) ◽  
pp. 311-329 ◽  
Author(s):  
Tiffany R. Duhl ◽  
Alex Guenther ◽  
Detlev Helmig
Keyword(s):  
Vegetation Cover ◽  
Google Earth ◽  
Urban Vegetation

scholarly journals Sociological modeling of smart city with the implementation of UN sustainable development goals

2021 ◽  
Author(s):  
Olga Kolesnichenko ◽  
Lev Mazelis ◽  
Alexander Sotnik ◽  
Dariya Yakovleva ◽  
Sergey Amelkin ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Personal Space ◽  
Well Being ◽  
Data Governance ◽  
Individual Level ◽  
The World ◽  
The Individual

AbstractThe COVID-19 pandemic before mass vaccination can be restrained only by the limitation of contacts between people, which makes the digital economy a key condition for survival. More than half of the world’s population lives in urban areas, and many cities have already transformed into “smart” digital/virtual hubs. Digital services ensure city life safe without an economy lockout and unemployment. Urban society strives to be safe, sustainable, well-being, and healthy. We set the task to construct a hybrid sociological and technological concept of a smart city with matched solutions, complementary to each other. Our modeling with the elaborated digital architectures and with the bionic solution for ensuring sufficient data governance showed that a smart city in comparison with the traditional city is tightly interconnected inside like a social “organism”. Society has entered a decisive decade during which the world will change by moving closer towards SDGs targets 2030 as well as by the transformation of cities and their digital infrastructures. It is important to recognize the large vector of sociological transformation as smart cities are just a transition phase to human-centered personal space or smart home. The “atomization” of the world urban population raises the gap problem in achieving SDGs because of different approaches to constructing digital architectures for smart cities or smart homes in countries. The strategy of creating smart cities should bring each citizen closer to SDGs at the individual level, laying in the personal space the principles of sustainable development and wellness of personality.

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