EventsThe 6th International Electronic Conference on Remote Sensing
Published
This submission belongs to the session S6. Remote Sensing of the Environment of the event The 6th International Electronic Conference on Remote Sensing
Published date
14 Oct, 2026
Academic Editor
author-avatarMagaly Koch
Contribution&Funding
Conceptualization,
[Muhammad Umair]
Methodology,
[Muhammad Umair]
Software,
[Muhammad Umair]
Validation,
[Muhammad Umair]
Investigation,
[Muhammad Umair]
Resources,
[Muhammad Umair]
Data curation,
[Muhammad Umair]
Writing - original draft,
[Muhammad Umair]
Writing - review,
[editing] ; [Muhammad Umair]
Visualization,
[Muhammad Umair]
Project administration,
[Muhammad Umair]
Funding: This research received no external funding.
Citation
Muhammad Umair, Spatiotemporal Assessment of Snow Cover Dynamics, Black Carbon Radiative Forcing, and Albedo Decline in Northern Pakistan (2001–2024) Using MODIS Cloud-Gap-Filled Time Series and Google Earth Engine, in Proceedings of The 6th International Electronic Conference on Remote Sensing, 19 October–21 October 2026, MDPI: Basel, Switzerland
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Spatiotemporal Assessment of Snow Cover Dynamics, Black Carbon Radiative Forcing, and Albedo Decline in Northern Pakistan (2001–2024) Using MODIS Cloud-Gap-Filled Time Series and Google Earth Engine

Muhammad Umair 1
1. Institute of Space Science, University of the Punjab Lahore Pakistan, Lahore, 54000, Pakistan
Abstract

Snow cover across the Hindu Kush–Karakoram–Himalaya (HKH) ranges in Northern Pakistan forms a vital water tower sustaining over 220 million downstream residents in the Indus Basin. The primary goal of this study is to quantify multi-decadal cryospheric dynamics and assess how atmospheric aerosols and climatic warming co-modulate snow retreat. We investigate the hypothesis that while macro-scale snow cover area (SCA) may exhibit apparent stability, localized hypsometric upward shifts in snowline elevation occur concurrently with aerosol-driven snow albedo degradation. Addressing key gaps in multi-parameter cryospheric monitoring, this study couples 24 years (2001–2024) of cloud-gap-filled MODIS (MOD10A1/MYD10A1) daily time series processed via the Terra–Aqua Combination (TAC) algorithm in Google Earth Engine (cloud coverage reduced from 38% to 11%) with Black Carbon (BC) aerosol deposition and radiative forcing models across district, tehsil, and 500 m elevation zones. Snow mapping validation against Sentinel-2 (10 m) imagery demonstrated high accuracy (Overall Accuracy: 90.61%, Kappa: 0.81). Trend analyses using Mann–Kendall and Sen’s slope estimators reveal that regional annual SCA remained relatively stable (+0.01% yr⁻¹; p > 0.05), yet snowline elevation underwent a statistically significant upward migration of +12 m yr⁻¹ (p < 0.05). Mean BC concentration was 4.30 × 10⁻⁴ kg m⁻², contributing to localized radiative forcing between +5 and +56 W m⁻². BC exhibited significant negative correlations with snow albedo (r = -0.24) and SCA (r = -0.29), while temperature was inversely associated with SCA (r = -0.73, p < 0.001). The novel contribution of this work lies in integrating fine-scale administrative and hypsometric cryospheric monitoring with continuous aerosol radiative impact metrics, providing critical empirical evidence for downstream water security and hazard mitigation.

Keywords
Snow Cover Area
MODIS
Google Earth Engine
Black Carbon
Snow Albedo
Hindukush-Karakoram-Himalaya
Mann-Kendall Trend
Radiative Forcing
Northern Pakistan
Advance Gross Primary Product (GPP) Estimation by Integrating Remote Sensing-Based Evapotranspiration into Light Use Efficiency Modeling
Satellite-Based Monitoring of Total Dissolved Solids in a Semi-Arid Reservoir Using Sentinel-2 Imagery and Symbolic Regression