Urban Green Cover Research Articles

Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis

India is home to 11 % of the global urban population and is ranks as the second-largest urban system in the world. This study introduces a Heat Health Risk Index (HHRI) rankings for 37 major Indian cities with more than one million residents, using geospatial and socio-ecological data to identify potential heat health risk areas. In this study, the Otsu method was employed to determine the critical parameters in the heat health index, considering factors such as Land Surface Temperature (LST), solar radiation, population density, mean temperature, urban green cover, rainfall, specific humidity, and wind speed. All data values were standardized to a uniform scale (0–1) for comparability. The standardized values, integrated with the assigned weights, formed the HHRI. Results indicate that cities such as Chennai, Mumbai, Kolkata, and Ahmedabad, each with populations exceeding 10 million, are deemed less livable due to their high HHRI (>0.50). Both Chennai and Mumbai stand out with highest hazard index as 0.66, followed by Kolkata (0.62) and Ahmedabad (0.56). Cities that lack sufficient green spaces are often more vulnerable, display elevated risk levels, and have decreased adaptability. In contrast, cities such as Ludhiana, Theni, Amritsar, and Nabarangpur are perceived as the most livable, with a mean HHRI of 0.21, owing to their higher adaptive capacity and lower exposure. Overall, this study serves as a foundation for conceiving future perspective plans for existing urban and peri‑urban areas, compared to living standards within the realms of sustainability.

Biomass, carbon stock and carbon dioxide sequestration by trees outside forests: A case study from Puducherry, India

Trees outside forests (ToF) play a vital role in reducing carbon from industrial activities and vehicles by sequestering and storing atmospheric Co2 generated as biomass. However, there is a scarcity of studies quantifying the biomass and carbon stock in the ToFs. To bridge this gap, we conducted a study on the potential of biomass and carbon dioxide sequestration in trees planted in Puducherry. Our findings show that the total above-ground biomass of adult trees in the city was 1926.03 Megagram (Mg), while belowground biomass was 244.47 Mg. The total carbon stored in adult trees was 966.53 Mg, while the volume of sequestered CO2 was 3547.17 Mg in the study area. To increase carbon dioxide sequestration in Puducherry town, we recommend increasing urban green cover and planting more fast-growing native species.

Assessment of Urban Green Cover and its Types using Threshold-based Approach

Assessment of Urban Green Cover and its Types using Threshold-based Approach

Unriddle the complex associations among urban green cover, built-up index, and surface temperature using geospatial approach: a micro-level study of Kolkata Municipal Corporation for sustainable city

Unriddle the complex associations among urban green cover, built-up index, and surface temperature using geospatial approach: a micro-level study of Kolkata Municipal Corporation for sustainable city

Assessment of carbon sequestration rate and tree diversity in a model urban green cover study using a college campus in Mangalore city

The extant green cover in a 140-year-old St Aloysius College campus in Mangalore, Karnataka, India, was used as a model to study tree diversity and carbon-sequestering rate (CSR), using a non-destructive biostatistics-based method. The results of the study indicated that the campus constituted a highly diverse tree flora with a Shannon Diversity index of 4.07. A total of 169 different tree species were found on the campus with an average population size of 9.98 per species. The green cover of 4.67 ha of the total area of the campus had a tree density of 361.03 trees/ha. Five tree species, namely Polyanthia longifolia, Cocos nucifera, Tectona grandis, Terminalia catappa, and Areca catechu, dominated the area. Using allometric equations, the total green cover in the campus area with biomass of 4594.6 Kg, which sequestered 8431.1 Kg of carbon at a carbon sequestration rate of 84.31 Kg per year was deduced. Olea europaea and Phoenix dactylifera, with the highest CSR of 0.09 and 0.08, respectively, were the most effective in sequestering 12.54 Kg and 11.19 Kg of carbon. The highest amount of Carbon sequestered (CS) per tree was in Olea europaea (12.54 Kg) and Phoenix dactylifera (11.19 Kg), followed by Acacia auriculiformis (10.44 Kg), and Adenanthera pavonina (10.08 Kg). It was observed that the amount of carbon sequestered decreased with the decrease in tree girth.

Examining the spatio-temporal relationship between LST, NDVI, NDBI and LULC change of Pachhua dun, Dehradun, Uttarakhand (India)

Recent climate change has had a negative impact on a wide range of human and natural systems, and it is clear that humans influence the climate. Because, as anthropogenic influence increases, the heat output from the land surface increases, speeding up the rate of climate change. In this regard, the use of RS and GIS techniques has provided various opportunities for research to examine these changes. The current analysis is based on the Landsat 1989, and 2020. Over the study period of 31 years, the built-up regions increased in size from 44.23 km2 to 154.56 km2. Whereas, the area covered by scrubland, water bodies, and vegetation cover has significantly decreased. The LST study further supports the outcome, showing that the mean and standard deviation increased from 14.81°C±1.32(1989) to 18.82°C±1.57(2020). The study also made an effort to examine how LULC affected LST; while vegetation cover has consistently helped to lower mean LST, built-up areas and scrubland are the main drivers of mean LST rise. The LST and NDBI revealed a positive correlation, while the NDVI/SLOPE and LST showed a negative correlation. Subsequently, the multiple linear regression (MLR) models concluded that the BUAs has evolved into a serious threat to the increase in LST, but increase in vegetation cover and SLOPE would result in slight decrease in LST. the study recommended that the government create policies that restrict future land encroachment and conversion, notably of forested area and water bodies, and make an immediate effort to increase the quantity and quality of urban green cover in the study area. So that we may, respectively, minimize the potential hazard posed by future LST rise and LULC change.

Usage of Airborne LiDAR Data and High-Resolution Remote Sensing Images in Implementing the Smart City Concept

The cities of the future should not only be smart, but also smart green, for the well-being of their inhabitants, the biodiversity of their ecosystems and for greater resilience to climate change. In a smart green city, the location of urban green spaces should be based on an analysis of the ecosystem services they provide. Therefore, it is necessary to develop appropriate information technology tools that process data from different sources to support the decision-making process by analysing ecosystem services. This article presents the methodology used to develop an urban green space planning tool, including its main challenges and solutions. Based on the integration of data from ALS, CLMS, topographic data, and orthoimagery, an urban green cover model and a 3D tree model were generated to complement a smart-city model with comprehensive statistics. The applied computational algorithms allow for reports on canopy volume, CO2 reduction, air pollutants, the effect of greenery on average temperature, interception, precipitation absorption, and changes in biomass. Furthermore, the tool can be used to analyse potential opportunities to modify the location of urban green spaces and their impact on ecosystem services. It can also assist urban planners in their decision-making process.

High-speed railway ripples on the greenness: Insight from urban green vegetation cover

Less attention has been paid to the potential ecological pressures brought about by high-speed rail (HSR) while promoting urban prosperity. Based on Normalized Difference Vegetation Index and multiple socio-economic and ecological data, this study examines the local effect and spatial spillover effect of HSR operation on green vegetation coverage (GVC) in Chinese cities from 2003 to 2014, using a difference-in-differences design and spatial econometrics. Main findings are: 1) HSR operation has reduced GVC of local cities by about 6.0%. Because HSR-triggered economic agglomeration has intensified the land development and increased the pollution emissions (represented by SO2 and dust), leading to the degradation of local green vegetation. 2) The local effects of HSR on urban GVC are heterogeneous. HSR operation seriously cuts down the GVC for development-saturated cities, slightly undercuts the GVC for cities with conventional railways, but positively boosts the GVC for ecotourism cities. 3) HSR operation increases the GVC of adjacent cities (cities contiguous to HSR-located cities) by about 3.8%. Because the economic siphoning effect of HSR on adjacent cities reduces their land needs and pollution emissions, thus providing conditions for the vegetation expansion. Note that the HSR’s impact on adjacent cities’ GVC is influenced by the economic disparity between HSR cities and their neighbors. This study re-identifies the role of the transportation infrastructure in reshaping ecological patterns, providing insights into regional sustainable development.

Urban Green Space Analysis and its Effect on the Surface Urban Heat Island Phenomenon in Denpasar City, Bali

The Urbanization process in Indonesia’s big cities causes adverse environmental impacts such as climate change and land cover change. Urban climate change causes the warming of urban areas compared to rural areas; it is called Urban Heat Island phenomenon. Loss of vegetation due to urban development is one of several causes that contribute to urban heat islands. This study examines the availability of green spaces and their effects on the surface urban heat island in Denpasar city. This study used the spatial approach for Urban Green space mapping with digitizing methods. Landsat 8's thermal band is used for land surface temperature mapping and to conduct a spatial pattern analysis of the SUHI phenomena. The Global Moran’s Index and Local Indicator of Spatial Association (LISA) were used to determine the correlation between urban green space and SUHI. The study result shows that Denpasar City's urban green space area covers 28.22 km2. That's equal to 22.1% of the Denpasar City Administrative area. Denpasar Selatan district has the largest urban green space cover, with 14.19 km2 covered, or 50.27% of all the green space in Denpasar City. The majority of Denpasar is affected by UHI occurrences, except the northern region of North Denpasar and the southern region of South Denpasar. The maximum UHI level reaches 4-5°C, located on the east side of South Denpasar, especially in the Sanur coastal area. According to the spatial pattern study, the association between urban green space and SUHI only exists on the north side of Denpasar. The correlation between low-SUHI intensity clusters and high cover of green space is shown in the same area. However, the association between High-UHI intensity and low green space cover has not significantly happened. It indicated that other factors besides green space could affect the land surface temperature.

Characterization and Mapping of Public and Private Green Areas in the Municipality of Forlì (NE Italy) Using High-Resolution Images

Urban Green Spaces (UGS) contribute to the sustainable development of the urban ecosystem, positively impacting quality of life and providing ecosystem services and social benefits to inhabitants. For urban planning, mapping and quantification of UGS become crucial. So far, the contribution of private green spaces to ecosystem services in urban areas has yet to be studied. At the same time, in many Italian cities, they represent a considerable part of the urban green cover. This study utilises a methodological approach and provides insights into the contribution of urban public and private green spaces by the consideration of a case study area in Northeast Italy. To achieve this goal, the main steps were: (i) NDVI extraction from very high-resolution (20 cm) orthophotos, (ii) classification of property status and (iii) analysis of the degree of the greenness of land cover units. From our results, the total amount of the green spaces is 5.70 km2, of which 72.1% (4.11 km2) is private, and 28.9% (1.59 km2) is public. As for the land cover, three NDVI classes were identified, highlighting different degrees of homogeneity in NDVI reflectance response within each urban land cover unit. These results will support the planning of new green areas in the post-epidemic National Recovery and Resilience Plan.

Artificial developed habitats can sustain plant communities similar to remnant ecosystems in the Tokyo megacity

Artificially developed habitats in urban ecosystems, known as novel ecosystems, have recently been underscored in terms of increasing urban green cover. However, patterns of changes in species diversity and composition in novel ecosystems over time remain poorly understood, making it unclear whether all novel ecosystems contribute to urban biodiversity. Here, we assessed how plant species diversity and composition in developed habitats changed over the years since the development of habitats (years since development) using a space-for-time substitution approach in the megacity, Tokyo, Japan. We established multiple survey transects at each study site to investigate the plant species diversity and composition. Using the ordination regression-based approach, we found that the plant species composition in developed habitats changed over the years since development and became similar to that in remnant habitats after approximately 130 years. We also found that the diversity of native plant species did not change whereas that of exotic species decreased with the years since development. Our results demonstrate the importance of developing new habitats for conserving urban biodiversity, while highlighting that exotic species can easily establish in newly developed habitats. Given that remnant ecosystems in urban areas are degraded by urbanization, the time required for novel ecosystems to become similar to remnant ecosystems is essential for predicting and conserving future urban ecosystems.

Spatiotemporal changes of green cover pattern in urban areas of Batticaloa, Sri Lanka

Sri Lanka’s cities are subject to varying green cover patterns due to rapid population growth in urban areas. Over the last two decades, urbanization has driven the rampant development of built-up areas, predominantly residential development. As a developing city in Sri Lanka, Batticaloa involves rapid construction development after the civil war. This trend increases pressure on green cover, making the city population more susceptible to urban challenges. This study investigates the spatial and temporal dynamics of green cover changes in selected urban areas in Batticaloa, Sri Lanka, from 2000 to 2020. Three (3) nearby areas were selected for the study, namely Kallady, Arayamapthy, and Kattankudy. ArcGIS Normalized Difference Vegetation Index (NDVI) analysis was used to identify the green cover pattern and changes using Landsat Images. The changing patterns were detected between 2000 - 2010 and 2010 – 2020. The study reveals that the total loss of green cover was high in the first decade, approximately 44.15%, which has slightly increased about 12.58% in the second decade of the selected years. The Kattankudy zone shows a high built-up density, while the Arayampathy zone is low. This pattern has led to the further loss of green cover in the Kattankudy zone, while the other two (2) zones are significantly mixed with the green cover. A significant proportion of the green cover is occupied by the newly built-up areas, mainly residential areas throughout the period. Thus, the green cover conservation should prioritize the built-up expansion to protect the environment. The residential green cover is essential for humans’ daily lives, and one of the most vital mechanisms in the urban green cover system cannot be ignored. This finding can contribute to the land use planning application and make policies to conserve the green cover in the future.

Remote sensing identification of green plastic cover in urban built-up areas.

Urban renewal can transform areas that are not adapted to modern urban life, allowing them to redevelop and flourish; however, the renewal process generates many new construction sites, producing environmentally harmful construction dust. The widespread use of urban green plastic cover (GPC) at construction sites and the development of high-resolution satellites have made it possible to extract the spatial distribution of construction sites and provide a basis for environmental protection authorities to protect against dust sources. Existing GPC extraction methods based on remote sensing images are either difficult to obtain the exact boundary of GPC or cannot provide corresponding algorithms according to different application scenarios. In order to determine the distribution of green plastic cover in the built-up area, this paper selects a variety of typical machine learning algorithms to classify the land cover of the test area image and selects K-nearest neighbor as the best machine learning algorithm through accuracy evaluation. Then multiple deep learning methods were used and the top networks with high overall scores were selected by comparing various aspects. Then these networks were used to predict the GPC of the test area image, and the accuracy evaluation results showed that the segmentation accuracy of deep learning was much higher than that of machine learning methods, but it took more time to predict. Therefore, combining different application scenarios, this paper gives the corresponding suggested methods for GPC extraction.

An Assessment of Land Use/Cover Suitable for Peri-urban Green Space Development: an Example of an Integration of GIS with the Multi-Criteria Analysis (MCA) Approach

Land allocation priorities to urban green cover are usually neglected particularly in the countries of developing economies such as Turkey. Lack of urban green space can cause many social and physical problems among the residents. Therefore, urban planning and policy should incorporate suitable green land in the urban planning of cities to optimise the benefits obtained from urban green spaces. Land suitability analysis is a commonly used methodology which provides a framework for developing strategies in the planning of green land development. Two different approaches will be utilised for the assessment of suitability of land uses for urban agriculture, forest and natural vegetation in the Pendik district of Istanbul. Standardisation of values in criteria maps was done using the deterministic approach in the first case whereas fuzzy membership was utilised as an alternative in the second case. Analytical Hierarchical Process (AHP) was used for the weighting of sub-criteria and map layers were overlaid using the weighted linear combination using the GIS software. Geophysical factors, transport and services accessibility, land cover/use, blue and green amenities, soil properties, geology and erosion susceptibility are the main criteria selected for the assessment of urban green land suitability. The provision of suitable land for urban agriculture, forest and natural vegetation uses will provide a framework to the land use planning and decision support aimed at contributing to urban sustainable development.

Future impacts of Urban and Peri-urban agriculture on carbon stock and land surface temperatures in India

Over the last two decades, cities in India have seen significant urban growth accompanied by green cover loss. Recently however, there has been a growing interest in urban and peri-urban agriculture (UPA) in these urban areas. The extent to which UPA mitigates the effects of urbanization is unclear. The present study aims to quantify the impact of UPA in the cities of Chennai and Bengaluru in India. Past trends of urban growth and green cover depletion are used to predict how urbanized Chennai and Bengaluru will be in the future, using CA Markov techniques on GIS data. A survey was then carried out to understand the general perception and growth trends pertaining to UPA. This survey data was then combined with our land use model to predict the growth of UPA in Chennai and Bengaluru in the future. These ‘future maps’ were then used to quantify the impact of UPA on biomass and land surface temperatures. We find that UPA can play a small, but not insignificant role in augmenting carbon stock and bringing down land surface temperatures and propose that urban development policies consciously include the role of UPA.

Assessing The Spatiotemporal Urban Green Cover Changes and Their Impact on Land Surface Temperature and Urban Heat Island in Lahore (Pakistan)

Urban vegetation has a decisive role in sustaining homogeneous Land Surface Temperature (LST) in a built-up environment. However, urban areas are facing rapid changes in land use/land cover (LULC) over the last few decades as green cover is being replaced by built-up structures. Consequently, LST is increasing and urban heat island (UHI) effects are expanding. In this context, this study was organized to assess urban green cover changes in Lahore and their impact on LST and UHI effects. For this, climate data was collected from the Pakistan Meteorological Department and Landsat images were acquired from Earth Explorer. LULC and LST maps were generated for 1990, 2000, 2010, and 2020 in ArcGIS 10.8. Also, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) were computed to analyze the effects of vegetation and built-up areas on LST and UHI. The study found that over the last three decades, built-up area increased 113.85% by removing 392.78 km2 of green cover in the study area. Similarly, a rapid expansion of the high LST range and UHI effects was found towards the eastern and southern parts of the study area. Moreover, a negative correlation was found between LST and NDVI, whereas the correlation between LST and NDBI was found to be positive. Therefore, it was concluded that the continuation of green cover reduction is highly damaging because this might render the city more fragile ecologically. So, the study calls the attention of the responsible authorities for suitable measures against continuous green cover loss in the study area.

Strategies to Mitigate the Deteriorating Habitat Quality in Dong Trieu District, Vietnam

Dong Trieu district is a vital connection for territorial ecological security and human welfare between Hanoi (the capital of Vietnam) and Quang Ninh province. Therefore, habitat quality (HQ) is of extraordinary importance to the area’s sustainable development. The ArcGIS platform, Dyna-CLUE, and InVEST models were utilized in this study to assess the spatial and temporal transformations of land use and the changes of HQ in 2030 under various scenarios, with intentions to find strategies that may mitigate the HQ’s deteriorating trend in the district. Simulated results indicated that, assuming the development is maintained as usual, the average HQ of the District at 2030 could diminish by 0.044 from that of 2019 (a four-times decrease compared to the previous decade). Cases comprised of four basic scenarios, including development as usual, built-up expansion slowdown, forest protection emphasized, and agricultural land conversion, were used to identify potential strategies to mitigate the deteriorating trend. Simulated results revealed that keeping the built-up expansion rate lower than 100 ha y−1, the deforestation rate lower than 20 ha y−1, and preferring orchards over agricultural land conversion is required to limit the drop in HQ to within 0.01 in the next decade. Other than the existing population growth control policy, new guidelines such as (1) changing urban expansion type from outward to upward to control the built-up expansion rate, (2) substituting forest-harming industries to forest-preservation industries to reduce deforestation rate, (3) encouraging orchards preferred over agricultural land conversion to increase incomes while maintaining higher habitat quality, (4) practicing better farming technologies to improve crop production and to alleviate potential food security issues due to considerable reduction in cropland, and (5) promoting Green Infrastructure and the Belt and Road Initiative to increase urban green cover and raise residents’ income should be considered in designing the new mitigation strategies.

Urban green plastic cover extraction and spatial pattern changes in Jinan city based on DeepLabv3+ semantic segmentation model

Urban green plastic cover extraction and spatial pattern changes in Jinan city based on DeepLabv3+ semantic segmentation model

Human Intervention for Protecting Urban Green Cover: Case of Nagpur, India

The important roles played by green spaces are social, economic, cultural and environmental aspects of sustainable development. Indian urban areas are developing at a very fast pace; simultaneously there is a rapid growth in population too, which impacts the ratio of demand and supply of basic services resulting to sustainability issues. This influences the interfaces between urbanization, population and the environment, as the surroundings are at the receiving end, leading to overexploitation of natural resources especially breathing spaces as parks, gardens and small forests on the name of infrastructural development. The situation augments due to absence of citizen participation in urban governance especially Urban Local Bodies (ULB). Though the 74th Constitution Amendment Act in India has given this opportunity to strengthen the links between the citizens and local democratic governance by way of public participation, the ground realities are different reducing the transparency of accountability of ULB. Based on this, the paper presents the case study of city of Nagpur, 2nd capital of state of Maharashtra, India, how environmental NGOs and citizens fought an eleven month struggle, venture to save a green patch of Nagpur, the Bharat Van from the clutches of local government bodies saving the ill effects on environment. This study is an attempt to highlight the necessity of an integrated approach regarding that the planning, monitoring, designing and maintaining of urban green spaces is required for improving the environmental sustainability in cities in different countries.

Assessing urban ecosystem services to prioritise nature-based solutions in a high-density urban area

Nature-based solutions have emerged as a concept for integrating ecosystem-based approaches whilst addressing multiple sustainable development goals. However, implementing nature-based solutions is inherently complex and requires consideration of a range of environmental and socio-economic conditions that may impact on their effectiveness. This research assesses ecosystem services within the Valletta urban agglomeration, Malta, and evaluates the implications arising from existing distributional patterns. Proxy-based indicators and expert knowledge were used to map and assess a set of 14 ecosystem services. Proximity and correlation analyses were used to assess distributional inequalities arising from differentiated availability of ecosystem types with high ecosystem service capacities for groups with different socio-economic characteristics. Data relating to schooling, employment, sickness, disability, and old age, were combined to identify areas of relative advantage and disadvantage. The highest ecosystem service capacities were in the urban fringes and the lowest in dense urban cores. Private gardens and urban trees had the highest regulating ecosystem service capacities per unit area. Contrastingly, public gardens had low effectiveness for regulating ecosystem services but the highest cultural ecosystem service capacities. Availability of urban green infrastructure and tree cover differ according to socio-economic advantage, and disadvantaged communities generally had reduced proximity to ecosystems with high ecosystem service capacities. Considering these findings, we argue that urban ecosystem service assessments can support greening strategies by identifying the most effective nature-based solutions that can play a redistributive role by addressing existing inequalities in green infrastructure and ecosystem services capacities distribution in cities.