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Anuj Goyal,
Deepak Kumar Tiwari,
- Assistant Professor, Civil Engineering Department, GLA University, Mathura, Uttar Pradesh, India
- Assistant Professor, Civil Engineering Department, GLA University, Mathura, Uttar Pradesh, India
Abstract document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_abs_126921’);});Edit Abstract & Keyword
Polymer-based mapping approaches are utilized in this study to improve the accuracy and consistency of LULC classification. Utilizing the special qualities of polymers like their elasticity, robustness, and adaptability, we create a strong framework for mapping LULC dynamics. Over the past few years, the district of Mathura in the state of Uttar Pradesh has experienced substantial expansion and development. This study assessed the change detection and estimated the shift in land-use/cover for the duration of 2013–2023. Five main classifications have been identified from the land-use/land cover data obtained from satellite image: (i) Built-up; (ii) Fallow; (iii) Agriculture; (iv) Water Bodies; and (v) Forest. The use of the Landsat sensors from 2013 and 2023 with a Geoinformatics methodology aided the investigation. Observations of land-use and spread revealed that changes in the land under different classes over a ten-year period were more notable in degree. The rise of built-up and barren land is the most striking change. Along with this decrease in the amount of land used for agriculture, water bodies, and forests. The findings show a significant shift in the areas covered by different land use classifications between 2013 and 2023. From 14.86 percent in 2013 to 23.04 percent in 2023, the built-up area grew. Between 2013 and 2023, the extent of fallow land rose from 296.96% to 42.96%. From roughly 50.09% of the total area in 2013 to 31.66% in 2023, there was less agricultural land. Between 2013 and 2023, the percentage of water bodies fell from 2.53% to 0.56%. Additionally, the forest area shrank from 2.84 percent in 2013 to 1.77 percent in 2023. The anthropogenic activities of urban expansion have resulted in significant problems for water bodies, forests, and agricultural land.
Keywords: Polymer coating, Environmental monitoring, Remote sensing, change detection, Landsat sensor, land use/cover and GIS
Anuj Goyal, Deepak Kumar Tiwari. Polymer Composite Mapping: Analyzing Land Use/Land Cover Changes in Mathura District, Uttar Pradesh, India. Journal of Polymer and Composites. 2024; ():-.
Anuj Goyal, Deepak Kumar Tiwari. Polymer Composite Mapping: Analyzing Land Use/Land Cover Changes in Mathura District, Uttar Pradesh, India. Journal of Polymer and Composites. 2024; ():-. Available from: https://journals.stmjournals.com/jopc/article=2024/view=0
References
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1. Alberti G, Zanoni C, Losi V, Magnaghi LR, Biesuz R. Current Trends in Polymer Based Sensors. Chemosens 2021, Vol 9, Page 108 [Internet]. 2021 May 13 [cited 2024 May 16];9(5):108. Available from: https://www.mdpi.com/2227-9040/9/5/108/htm 2. Alam MW, Bhat SI, Al Qahtani HS, Aamir M, Amin MN, Farhan M, et al. Recent Progress, Challenges, and Trends in Polymer-Based Sensors: A Review. Polymers (Basel) [Internet]. 2022 Jun 1 [cited 2024 May16];14(11). Available from: https://www.researchgate.net/publication/361232149_Recent_Progress_Challenges_and_Trends_in_Polymer- Based_Sensors_A_Review 3. Ouchra H, Belangour A, Erraissi A. Spatial Data Mining technology for GIS: a review. 2022 Int Conf Data Anal Bus Ind ICDABI 2022 [Internet]. 2022 [cited 2024 May 16];655–9. Available from: https://www.researchgate.net/publication/368518484_Spatial_Data_Mining_technology_for_GIS_a_review 4. Rutten MGTA, Vaandrager FW, Elemans JAAW, Nolte RJM. Encoding information into polymers. Nat Rev Chem [Internet]. 2018 Nov 1 [cited 2024 May 16];2(11):365–81. Available from: https://www.researchgate.net/publication/328616168_Encoding_information_into_polymers 5. Troha A. Changing settlement patterns in areas of autochtonous dispersed settlement. Igra ustvarjalnosti – Creat Game [Internet]. 2017 [cited 2024 May 16];2017(05):076–88. Available from: https://www.researchgate.net/publication/324508726_Changing_Settlement_Patterns_in_Areas_of_Autochtonous _Dispersed_Settlement
Journal of Polymer and Composites
| Volume | |
| Received | 23/04/2024 |
| Accepted | 06/11/2024 |
| Published | 09/12/2024 |