Modelling PM2.5 for Data-Scarce Zone of Northwestern India using Multi Linear Regression and Random Forest Approaches-Reference-Cited by-同舟云学术

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Modelling PM2.5 for Data-Scarce Zone of Northwestern India using Multi Linear Regression and Random Forest Approaches

Published:2023-02-27 Issue:3 Volume:29 Page:415-427
ISSN:1947-5683
Container-title:Annals of GIS
language:en
Short-container-title:Annals of GIS

Author:

Sharma Vipasha¹,Ghosh Swagata¹²^ORCID,Dey Sagnik³,Singh Sultan⁴

Affiliation:

1. Amity Institute of Geoinformatics and Remote Sensing (AIGIRS), Amity University, Noida, U.P, India

2. Department of Geography, School of Earth Sciences, Central University of Karnataka Kadaganchi, Kalaburagi, Karnataka, India

3. Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India

4. Haryana Space Applications Centre Node, Gurugram, Haryana, India

Funder

Science and Engineering Research Board

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/19475683.2023.2183523

Reference41 articles.

1. AHP-based Spatial Air Quality Impact Assessment Model of vehicular traffic change due to highway broadening in Sikkim Himalaya

2. A New Approach for Estimation of Fine Particulate Concentrations Using Satellite Aerosol Optical Depth and Binning of Meteorological Variables

3. Estimating PM2.5 concentration from satellite derived aerosol optical depth and meteorological variables using a combination model

4. Satellite-based estimates of outdoor particulate pollution (PM10) for Agra City in northern India

5. Spatio-temporal variations in the estimation of PM10 from MODIS-derived aerosol optical depth for the urban areas in the Central Indo-Gangetic Plain

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1. Spatiotemporal characteristics of PM2.5 concentrations and responses to land-use change in Urumqi, China;Journal of Applied Remote Sensing;2024-08-06

2. Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine;Journal of Environmental Management;2024-05

3. Prediction of Particulate Matter (PM2.5) Concentrations over an Urban Region using Different Satellite;Indian Journal of Pure & Applied Physics;2024

4. A Review of Spatial Analysis Techniques Used for LULC Change Detection Over Delhi NCR in the Past Two Decades;Geotechnologies and the Environment;2024

5. Insights into the Multifaceted Application of Technology to Empower Disaster Resilience: A Geospatial Perspective;Geotechnologies and the Environment;2024

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