Blar i forfatter "Asim, Muhammad"

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    • Evaluating Landsat-8 and Sentinel-2 Data Consistency for High Spatiotemporal Inland and Coastal Water Quality Monitoring 

      Hafeez, Sidrah; Wong, Man Sing; Abbas, Sawaid; Asim, Muhammad (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-30)
      The synergy of fine-to-moderate-resolutin (i.e., 10–60 m) satellite data of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2 Multispectral Instrument (MSI) provides a possibility to monitor the dynamics of sensitive aquatic systems. However, it is imperative to assess the spectral consistency of both sensors before developing new algorithms for their combined use. This study evaluates ...

    • Genome-Wide Identification and Expression Analysis of SnRK2 Gene Family in Dormant Vegetative Buds of Liriodendron chinense in Response to Abscisic Acid, Chilling, and Photoperiod 

      Hussain, Quaid; Zheng, Manjia; Chang, Wenwen; Ashraf, Muhammad Furqan; Khan, Rayyan; Asim, Muhammad; Riaz, Muhammad Waheed; Alwahihi, Mona S.; Elshikh, Mohamed S.; Zhang, Rui; Wu, Jiasheng (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-22)
      Protein kinases play an essential role in plants’ responses to environmental stress signals. SnRK2 (sucrose non-fermenting 1-related protein kinase 2) is a plant-specific protein kinase that plays a crucial role in abscisic acid and abiotic stress responses in some model plant species. In apple, corn, rice, pepper, grapevine, Arabidopsis thaliana, potato, and tomato, a genome-wide study of the ...

    • Improving Chlorophyll-a Estimation from Sentinel-2 (MSI) in the Barents Sea using Machine Learning 

      Asim, Muhammad; Brekke, Camilla; Mahmood, Arif; Eltoft, Torbjørn; Reigstad, Marit (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-22)
      This article addresses methodologies for remote sensing of ocean Chlorophyll-a (Chl-a), with emphasis on the Barents Sea. We aim at improving the monitoring capacity by integrating in situ Chl-a observations and optical remote sensing to locally train machine learning (ML) models. For this purpose, in situ measurements of Chl-a ranging from 0.014–10.81 mg/m <sup>3</sup> , collected for the years ...

    • A new spectral harmonization algorithm for Landsat-8 and Sentinel-2 remote sensing reflectance products using machine learning: a case study for the Barents Sea (European Arctic) 

      Asim, Muhammad; Matsuoka, Atsushi; Ellingsen, Pål Gunnar; Brekke, Camilla; Eltoft, Torbjørn; Blix, Katalin (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-12)
      The synergistic use of Landsat-8 operational land imager (OLI) and Sentinel-2 multispectral instrument (MSI) data products provides an excellent opportunity to monitor the dynamics of aquatic ecosystems. However, the merging of data products from multisensors is often adversely affected by the difference in their spectral characteristics. In addition, the errors in the atmospheric correction (AC) ...

    • Optical remote sensing of water quality parameters retrieval in the Barents Sea 

      Asim, Muhammad (Doctoral thesis; Doktorgradsavhandling, 2023-03-31)
      <p>This thesis addresses various aspects of monitoring water quality indicators (WQIs) using optical remote sensing technologies. The dynamic nature of aquatic systems necessitate frequent monitoring at high spatial resolution. Machine learning (ML)-based algorithms are becoming increasingly common for these applications. ML algorithms are required to be trained by a significant amount of training ...