Browsing by Author "Kumar, Pankaj"

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    Analyzing landscape changes and their relationship with land surface temperature and vegetation indices using remote sensing and AI techniques
    (2025) Kumar, Pankaj
    Land use patterns and consumption occur widely due to fast industrialization and development in the previous several decades, which might lead to problems such as over-exploitation of land resources, food shortages, and pol lution. Monitoring and subsequent modeling of land use land cover (LULC) changes has become critical. A study of the variations in the LULC pattern of the Baghpat District of Uttar Pradesh, India, was attempted. This study assessed spatial patterns and fluctuations in growth in the Baghpat District of Uttar Pradesh (India) from 1991 to 2021. The study also analyzed the land cover changes and their effects on land surface temperature (LST), normalized difference vegetation index (NDVI), and soil indices in the Baghpat district. Decadal land use and land cover (LULC) changes were analyzed using Multitemporal Landsat Imagery and applying the maximum likelihood classifier in ENVI (Image Processing Software). Post-classification spatial measures were used to examine changes in LULC and the spatial distribution of urban growth, as well as to identify changes using ArcMap (GIS Software) across the period. Various AI techniques were used to show the trend variation in NDVI, LST, and SAVI indices using IBM-SPSS, Microsoft Office, OriginLab, and MATLAB for the study area to comprehend the variation in the index within the given period. The f indings indicated significant improvements in agriculture between 1991 and 2021 (from 58.94 to 84.79%), but sig nificant declines in vegetation cover (from 29.53 to 1.14%). The yearly percentage growth of the parallel built-up area was 3.77%, 5.59%, 6.71%, and 6.90%, respectively. Approximately 43.85% of the increase in agricultural land between 1991 and 2021 came from the conversion of vegetation covers, which fell by 96.13%. The analysis of LST, NDVI, and SAVI data revealed a substantial negative association for all years, except a slight positive correlation. NDVI and SAVI values were highest in agricultural fields with the lowest LST values, whereas fallow land regions exhibited the reverse pattern. With the help of these findings, urban planners and designers may reduce various socio-eco nomic and environmental consequences. Keywords Spatio-temporal changes, Geospatial techniques, LST, NDVI, SAVI
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    Unraveling intricacies of monsoon attributesin homogenous monsoon regions of india
    (Frontiers in Earth Science, 2022) Saini, Atul; Sahu, Netrananda; Dhan, Weili; Kumar, Manish; Ramavtar; Mishra, Manoranjan; Kumar, Pankaj; Pandey, Rajiv; Behera, Swadhin
    India observes the summer monsoon in June–July–August–September (JJAS) season, and the livelihood security of a huge population depends on it. The impact of the monsoon onset timing, length of monsoon season, rainfall amount, and related extreme events is huge on the Indian economy. Therefore, understanding the inherent intricacies needed a detailed investigation. In five homogenous monsoon regions of India, the trend of monsoon onset and the length of monsoon season are examined. The association between 1) monsoon onset ~ rainfall amount, 2) length of monsoon season ~ rainfall amount, and 3) monsoon onset ~ length of monsoon season is investigated. Subsequently, the behavior of rainfall and extreme excess days in the ±1 standard deviation (SD) length of monsoon season is also examined in detail. The trend for monsoon onset shows late onset in all the homogenous monsoon regions except the northeast region. The length of monsoon season is found increasing significantly with high magnitude in west central and northwest regions. A significantly strong negative correlation (~−0.6) for monsoon onset timing ~ length of monsoon season is observed. Therefore, the change in rainfall anomaly, extreme excess days, and rainy days is done concerning the length of the monsoon season. In the cases of the −1 SD (+1 SD) length of monsoon season, rainfall anomaly and extreme excess days are low (high) in most parts of the homogenous monsoon regions. Extreme excess days showed a significant association with rainy days, which indicates a high possibility of rainy days converting into extreme excess days. However, the increase in extreme excess days in the +1 SD length of monsoon season is limited to a great extent in JJAS and June only. Morlet wavelet power spectrum shows the delay (advance) of power in −1SD (+1 SD) length of monsoon season.