Samera Samsuddin Sah
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Samera Samsuddin Sah
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Samera, Samsuddin Sah
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Sah, Samera Samsuddin
Sah, S. S.
Samsuddin Sah, Samera
Samera, S. S.
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Scopus Author ID
56353171100

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  • Publication
    Monitoring of three stages of paddy growth using multispectral vegetation index derived from UAV images
    (Elsevier, 2023)
    Samera Samsuddin Sah
    ;
    Khairul Nizam Abdul Maulud
    ;
    Suraya Sharil
    ;
    Othman A. Karim
    ;
    Biswajeet Pradhan
    Paddy cultivation in Malaysia plays a crucial role in food production, with a focus on improving crop quality and quantity. With current national self-sufficiency levels ranging between 67 and 70%, the Malaysian government intends to produce higher-quality crops and boost agricultural production. However, the prominent paddy-producing state of Kedah has witnessed a decline in yields over the years. To address this, the study explores the effectiveness of unmanned aerial vehicles (UAVs) equipped with vegetation indices (VIs) for monitoring paddy plant health at various growth stages. Researchers acquired aerial imagery during two seasons in 2019, capturing three distinct growth stages: tillering (40 days after sowing), flowering (60 days after sowing), and ripening (100 days after sowing). These stages represent critical points in the paddy plant's life cycle. Agisoft Metashape software processed the images to extract VIs data. The study found that the Normalized Difference Vegetation Index (NDVI) and Blue Normalized Difference Vegetation Index (BNDVI) exhibited over 90% similarity. In contrast, the Normalized Difference Red Edge Index (NDRE), utilizing near-infrared and red-edge light reflections, demonstrated a unique relationship. NDRE outperformed NDVI and BNDVI with an R-squared value of 0.842, showcasing its superior accuracy, especially for dense crops like paddy plants sensitive to subtle changes in vegetation. In conclusion, this research highlights the potential of UAV-based VIs for effectively monitoring paddy plant health during different growth stages. The NDRE index, in particular, proves valuable for assessing dense crops, offering insights for precision agriculture and crop management in Malaysia.
  • Publication
    Extensive assessment of climate change impacts on coastal zone paddy growth using multispectral analysis and hydrodynamic modeling
    (Elsevier, 2023)
    Samera Samsuddin Sah
    ;
    Khairul Nizam Abdul Maulud
    ;
    Othman A. Karim
    ;
    Suraya Sharil
    ;
    Zaher Mundher Yaseen
    Global warming has led to sea levels raise (SLRs) and Malaysia is no exception to this problem. Especially for low-lying coastal areas including the Kuala Kedah area which is active in agricultural and fisheries activities. Farmers have had to bear up to 75 % of yield losses due to seawater breaches since 2016. Therefore, this study is designed to assess the impact of seawater encroachment on water quality through spatial technology approaches and hydrodynamic modeling related to the growth of paddy trees. The study was conducted during two different paddy cultivation seasons namely Season 1–2019 and Season 2–2019 which take place in the southwest and northeast monsoon in Kuala Kedah, Malaysia. The study involved three phases, which are the assessment of salinity and pH concentration levels, the assessment of the health of paddy crops through multispectral image analysis involving three plant indices (VI), namely Normalized Difference Vegetation Index (NDVI), Blue Normalized Difference Vegetation Index (BNDVI) and Normalized Difference Red Edge (NDRE), and finally, the assessment of the impact of SLR through the numerical method in MIKE 21 for hydrodynamic modeling considering two conditions that are without mitigation factor (K1) and with existing mitigating factor (K2). According to the findings, the salinity concentration trend is decreasing across the growth stage during Season 1–2019, whereas it is the contrary during Season 2–2019. It was discovered that during the study period for both tidal events, 73 % of the 44 sampling points in Season 1–2019, as opposed to just 3 % in Season 2–2019, were categorized as Class 4 and Class 5. Even though there were fluctuations throughout the observation, the pH reading is still within the allowed range of 6.5 to 9.0 for the estuary area. Following that, the ANOVA analysis proved that salinity concentration a statistically significant difference with tidal variations and pH levels. Moreover, the multispectral image analysis findings revealed that the VI value was correlated with both the yield and the health of the rice crop, with R-square values of 0.842 compared to 0.706 and 0.575 for NDVI and BNDVI values, respectively. It confirmed that NDRE granted a more accurate and reliable measurements. Additionally, the hydrodynamic simulation results demonstrated that, if the mitigation factors were considered in the modeling, overflow seawater to the mainland could be reduced by up to 20 %, reducing the impact of coastal flooding on the local area as well as the nearby rice cultivation area. Ultimately, these three elements—water quality, vegetation index, and hydrodynamic modeling—can assist in identifying the underlying cause of the problem and develop short and long-term solutions.