A comparison of the economic benefits of urban green spaces estimated with NDVI and with high-resolution land cover data

2015 ◽  
Vol 133 ◽  
pp. 105-117 ◽  
Author(s):  
Wei Li ◽  
Jean-Daniel M. Saphores ◽  
Thomas W. Gillespie
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Economic Benefits ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Land Cover Data

scholarly journals Assessing Impacts of Urban Form on Landscape Structure of Urban Green Spaces in China Using Landsat Images Based on Google Earth Engine

2018 ◽  
Vol 10 (10) ◽  
pp. 1569 ◽  
Author(s):  
Conghong Huang ◽  
Jun Yang ◽  
Peng Jiang
Keyword(s):  
Land Cover ◽  
Landscape Structure ◽  
Urban Form ◽  
Google Earth ◽  
Green Spaces ◽  
Road Density ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Google Earth Engine ◽  
Land Cover Maps

The structure of urban green spaces (UGS) plays an important role in determining the ecosystem services that they support. Knowledge of factors shaping landscape structure of UGS is imperative for planning and management of UGS. In this study, we assessed the influence of urban form on the structure of UGS in 262 cities in China based on remote sensing data. We produced land cover maps for 262 cities in 2015 using 6673 scenes of Landsat ETM+/OLI images based on the Google Earth Engine platform. We analyzed the impact of urban form on landscape structure of UGS in these cities using boosted regression tree analysis with the landscape and urban form metrics derived from the land cover maps as response and prediction variables, respectively. The results showed that the three urban form metrics—perimeter area ratio, road density, and compound terrain complexity index—were all significantly correlated with selected landscape metrics of UGS. Cities with high road density had less UGS area and the UGS in those cities was more fragmented. Cities with complex built-up boundaries tended to have more fragmented UGS. Cities with high terrain complexity had more UGS but the UGS were more fragmented. Our results for the first time revealed the importance of urban form on shaping landscape structure of UGS in 262 cities at a national scale.

scholarly journals Local Community Perceptions of the Ecological and Socio-Economic Benefits of Spiders in Small-Scale Urban Green Spaces for Conservation Reinforcement

2021 ◽  
pp. 115-123
Author(s):  
Brian Tampos Sabanal ◽  
◽  
Marion John Michael Macapil Achondo ◽  
Lief Erikson Diocampo Gamalo ◽  
Pedro Alviola IV ◽  
...  
Keyword(s):  
Local Community ◽  
Economic Benefits ◽  
The Philippines ◽  
Green Spaces ◽  
Small Scale ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Ecological Roles ◽  
Survey Questionnaires

Spiders are among the most ubiquitous arthropods that can dwell on diverse habitats, which include small-scale urban green spaces (UGS). To promote urban diversity, we assessed the awareness of a local community situated within UGS in Davao, Philippines about the ecological roles of spiders. Data were obtained by administering survey questionnaires to 80 households using convenience sampling. The survey revealed that the local community is knowledgeable on the occurrence of spiders in their area (97.5%), in which they are mostly acquainted with spiders of Pisauridae (25%) and Araneidae (20.3%). Also, the community has recognized the important ecological roles of spiders, in which they mostly acknowledged the role of spiders as a significant source of food for other organisms (71.62%). However, a high proportion of respondents also recognized the socio-economic benefits of spiders through spider wrestling (60.81%). Henceforth, the ecological roles of spiders could be subjugated as spider wrestling is practiced in the local community, which could be a possible threat to the spider population. Thus, we highly suggest to involve concerned local communities in urban biodiversity management for the conservation of spiders in the Philippines, which is highly at risk due to its perceived socio-economic benefits.

scholarly journals The influence of urban landscape spatial patterns on single-family housing prices

2016 ◽  
Vol 45 (1) ◽  
pp. 26-43 ◽  
Author(s):  
Jun-Hyun Kim ◽  
Wei Li ◽  
Galen Newman ◽  
Sung-Ho Kil ◽  
Sun Young Park
Keyword(s):  
Spatial Patterns ◽  
Green Space ◽  
Urban Forest ◽  
Housing Prices ◽  
Economic Benefits ◽  
Green Spaces ◽  
Single Family ◽  
Urban Green ◽  
Urban Green Spaces

Many empirical studies assessing the economic benefits of urban green space have continually documented that green space tends to increase both value and sale price of nearby residential properties. Previous studies, however, have not fully captured the quality of neighborhood level landscape spatial patterns on housing prices. To fill this literature gap, this study examined the association between landscape spatial patterns of urban green spaces and single-family home sale transactions using a spatial regression model. The research was conducted through the analysis of 11,326 housing transaction records from 2010 to 2012 in Austin, TX, USA. Variables measuring the structural, locational and neighborhood characteristics of housing were coupled with Geographic Information Systems, remote sensing and FRAGSTATS to calculate several landscape indices measuring the quality of existing landscape spatial patterns. After controlling for any spatial autocorrelation effects, we found that that larger tree and urban forest areas surrounding single-family homes positively contributed to property values, while more fragmented, isolated and irregularly shaped landscape spatial patterns resulted in the inverse. The results of this research increase awareness of the role of urban green spaces while informing community design/planning practices about the linkages between landscape spatial structure and economic benefits.

scholarly journals Providing Access to Urban Green Spaces: A Participatory Benefit-Cost Analysis in Spain

2020 ◽  
Vol 17 (8) ◽  
pp. 2818 ◽  
Author(s):  
Silvestre García de Jalón ◽  
Aline Chiabai ◽  
Alyvia Mc Tague ◽  
Naiara Artaza ◽  
Amaia de Ayala ◽  
...  
Keyword(s):  
Cost Analysis ◽  
General Public ◽  
Green Space ◽  
Participatory Evaluation ◽  
Economic Benefits ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Benefit Cost Analysis ◽  
Benefit Cost

The opening up of green spaces could provide significant benefits to society. This study develops a framework to assess the economic benefits and costs of public interventions providing citizen access to urban green spaces. The Thinking Fadura project in Getxo (Spain) was used as a case study. A method for participatory benefit-cost analysis is developed, where a stakeholder-participatory evaluation is combined with a standard cost-benefit analysis. The participatory evaluation followed a bottom-up approach in a sequential evaluation including three main focal points: key stakeholders and experts, visitors and the general public. The assessment demonstrates that the Thinking Fadura project’s benefits outweigh the costs. The results suggest that projects designed with the purpose of improving green space accessibility to the general public can be beneficial from a societal perspective. The highest economic benefits were an increase in the amenity and recreational value and an increase in people’s physical activity. The participatory evaluation indicates that giving access to people of lower socio-economic status and vulnerable groups and improving recreational use were perceived as the most beneficial. An increase in noise, dirt, and risk of criminal activities as well as potential conflicts between green space users were perceived as the most negative impacts of opening a previously restricted area to the general public. The economic assessment of Thinking Fadura project could serve as a model in the decision-making process in locations where the use of greenspaces is restricted.

scholarly journals Indicators for the Planning and Management of Urban Green Spaces: A Focus on Public Areas in Padua, Italy

2019 ◽  
Vol 11 (24) ◽  
pp. 7071 ◽  
Author(s):  
Thomas Campagnaro ◽  
Tommaso Sitzia ◽  
Vito Emanuele Cambria ◽  
Paolo Semenzato
Keyword(s):  
Economic Benefits ◽  
Green Spaces ◽  
Tree Cover ◽  
City Center ◽  
Policy Makers ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Public Areas ◽  
Trends Over Time ◽  
The City

Green spaces and trees are fundamental for the sustainability of cities. The use of management and planning indicators for green spaces, including urban forests, have been proposed, but are rarely applied and their potential to provide ecological, social, and economic benefits is usually overlooked by policy makers and managers. Here, we apply a set of indicators describing green spaces and their variability in different urban units within the Basso Isonzo, an area of the city of Padua (northern Italy). Eleven indicators were selected based on their capacity to consider availability, accessibility and the preservation or increase of urban green spaces and tree cover. The value of indicators was standardized and enabled to have five classes indicating increasing performance. The study indicates green spaces’ heterogeneous conditions. Interestingly, the indicators commonly change moving from the city center to the outskirts. Monitoring through these indicators will enable understanding whether specific management and planning targets are met and, in the absence of these targets, identifying main trends over time. The proposed approach and indicators applied are simple to collect, analyze, and convey information. The indicators are related to relevant social, economic and ecological conditions pertaining to green spaces. The proposed indicators can therefore be used as a simple tool to guide decision-making with the aim of enhancing green spaces.

scholarly journals Quantification and monetary valuation of urban ecosystem services in Munich, Germany

2015 ◽  
Vol 59 (3) ◽  
Author(s):  
Tim Aevermann ◽  
Jürgen Schmude
Keyword(s):  
Ecosystem Services ◽  
Land Cover ◽  
Urban Areas ◽  
Green Space ◽  
Local Population ◽  
Urban Green Space ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Runoff Reduction

AbstractUrban green spaces provide ecosystem services that can be used by the local population. The valuation of these ecosystem services in urban areas gives information for stakeholders and decision-makers to improve urban planning processes. In addition, this information can be used to provide a better understanding of how urban green spaces should be managed. In this study, we quantify and monetize four ecosystem services (carbon sequestration and storage, air pollution removal, runoff reduction, groundwater recharge) provided by the urban green space of Schlosspark Nymphenburg in Munich, Germany. We classify four different land cover types (tree, grass/herbaceous, water, impervious) to calculate different amounts of ecosystem services according to the land cover type. In addition, we quantify the maintenance costs which this urban green space causes to the city of Munich. The interpretation, communication and risks of valuations studies are discussed.

scholarly journals Mapping Urban Green Spaces at the Metropolitan Level Using Very High Resolution Satellite Imagery and Deep Learning Techniques for Semantic Segmentation

2021 ◽  
Vol 13 (11) ◽  
pp. 2031
Author(s):  
Roberto E. Huerta ◽  
Fabiola D. Yépez ◽  
Diego F. Lozano-García ◽  
Víctor H. Guerra Cobián ◽  
Adrián L. Ferriño Fierro ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Satellite Imagery ◽  
Semantic Segmentation ◽  
Well Being ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Geometric Patterns ◽  
Very High

Urban green spaces (UGSs) provide essential environmental services for the well-being of ecosystems and society. Due to the constant environmental, social, and economic transformations of cities, UGSs pose new challenges for management, particularly in fast-growing metropolitan areas. With technological advancement and the evolution of deep learning, it is possible to optimize the acquisition of UGS inventories through the detection of geometric patterns present in satellite imagery. This research evaluates two deep learning model techniques for semantic segmentation of UGS polygons with the use of different convolutional neural network encoders on the U-Net architecture and very high resolution (VHR) imagery to obtain updated information on UGS polygons at the metropolitan area level. The best model yielded a Dice coefficient of 0.57, IoU of 0.75, recall of 0.80, and kappa coefficient of 0.94 with an overall accuracy of 0.97, which reflects a reliable performance of the network in detecting patterns that make up the varied geometry of UGSs. A complete database of UGS polygons was quantified and categorized by types with location and delimited by municipality, allowing for the standardization of the information at the metropolitan level, which will be useful for comparative analysis with a homogenized and updated database. This is of particular interest to urban planners and UGS decision-makers.

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