Vasantha Kumar S

Department of Environmental and Water Resources Engineering

School of Civil Engineering

Vellore Campus

S Vigneshwaran

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Comparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery

Geocarto International

Assessing the Accuracy of Remotely Sensed Data

International Journal of Remote Sensing

Urban green space classification and water consumption analysis with remote-sensing technology: a case study in Beijing, China

Urban Green Spaces (UGS) offer social and environmental benefits that enhance quality of life of the residents. However, due to the underlying social and economic disparities, different sections of urban population have disproportionate level of access to UGS. The environmental inequity owing to the varied UGS distribution poses a challenge to urban planners in efficient resource allocation. This study attempts to counter this challenge using a novel remote sensing-based approach. The variations in UGS distribution (in terms of quantity, quality and accessibility) across the neighbourhoods in Mumbai vis-à-vis the socio-economic status (SES) of neighbourhood residents are assessed using remote sensing-based indicators. Further, as these indicators are susceptible to the effect of changing scales, a multi-scale approach is adopted to study the potential variations in the relationship between SES and spatial metrics of UGS with spatial resolution. The neighbourhood SES was assessed using the newly developed Socio-Economic Status Index (SESI) and the neighbourhoods were classified into multiple SES categories. The UGS were extracted from remotely sensed data using Normalized Difference Vegetation Index (NDVI), and their spatial distribution aspects were characterized using indicators at neighbourhood level. The variations in indicators of UGS distribution in the neighbourhoods belonging to different SES categories were analysed using a logistic regression model. The results showed that, while quantity of UGS is not statistically associated with neighbourhoods SES, the quality and accessibility aspects of UGS share a statistically significant relation with SES. Also, this relation was found to vary significantly with spatial resolutions. Further, it was found that the neighbourhoods with higher SES in Mumbai have a better access to green spaces, indicating spatial inequities in UGS distribution in Mumbai. This study has important implications for planning equitable green spaces in cities that are currently in urbanization transition. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

GIScience and Remote Sensing

Linking remotely sensed Urban Green Space (UGS) distribution patterns and Socio-Economic Status (SES) - A multi-scale probabilistic analysis based in Mumbai, India

ISPRS Journal of Photogrammetry and Remote Sensing

Social functional mapping of urban green space using remote sensing and social sensing data

PLOS ONE

The provision of urban green space and its accessibility: Spatial data effects in Brussels

Journal	Geocarto International
Publisher	Informa UK Limited
ISSN	1010-6049
Open Access	0