Pixel-based vs. object-based anthropogenic impervious surface detection: driver for urban-rural thermal disparity in Faridabad, Haryana, India

Kumar, Sunil; Midya, Kousik; Ghosh, Swagata; Singh, Sultan

doi:10.1080/10106049.2021.2002429

Cited by 17 publications

(1 citation statement)

References 59 publications

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“…The elevated humidity in the air results into more concentrated aerosol particles which are bonded by light rain droplets. During the past several years, the population density of the current study region has increased, and anthropogenic activities as a consequence have also increased in the study area, which has increased the aerosol load also (Ghosh et al, 2021;Kumar et al, 2021;Kumar & Rao, 2012;Ranjan et al, 2022). The spatial variation can be due to emission sources, meteorological conditions, monsoon rains and seasonal variation of dispersion (David et al, 2018).…”

Section: Variations In Aod By Season and Regionmentioning

confidence: 98%

Analysis and Variation of the Maiac Aerosol Optical Depth in Underexplored Urbanized Area of National Capital Region, India

Sharma

Ghosh

Kumari

et al. 2022

Journal of Landscape Ecology

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Aerosol monitoring is the emerging application field of satellite remote sensing. As a satellite-based indicator of aerosol concentration, aerosol optical depth (AOD) can aid in assessing the crucial effects of aerosols on the global environment. Among various satellite-based aerosol product, Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6), Multiangle Implementation of Atmospheric Correction (MAIAC) aerosol product (1 km resolution) has still untapped potential in Indian regions. Considering the importance of regional validation of such high-resolution aerosol product, the present study attempts to fill this gap by validating MAIAC aerosol estimates (AODMAIAC) in highly polluted districts (Faridabad, Ghaziabad, Gautam Budh Nagar, Gurugram) of National Capital Region (NCR) with heavy aerosol loading using limited AErosol RObotic NETwork (AERONET) observations obtained from AERONET sites at Amity University (AU) and Gual Pahari (GP). Such evaluation of satellite-retrieved aerosol product with ground data confirms its practicality based on retrieval errors (Expected Error (EE) values (EE = 0.05 + 15 %*AOD) (EE: 78.85 % at AU, 73.58 % at GP), root mean square error (RMSE) values (RMSE: 0.15 at AU, 0.24 at GP), and correlation coefficient (R) values (R: 0.86 at AU, 0.73 at GP). The seasonal variation in AOD over the study area from 2010-2019 reveals increasing trend of AOD in the monsoon and post-monsoon season due to natural and anthropogenic factors. In addition to contributing to a holistic assessment of MAIAC aerosol estimates as a recent, high-resolution aerosol product, present results provide a basis for further research into NCR aerosols.

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Section: Variations In Aod By Season and Regionmentioning

confidence: 98%