INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This research project uses the U model to study time series data, from the 'Sentinel 2 – Munich' dataset with the goal of improving crop mapping accuracy. By tackling data imbalances our research enhances the precision of crop mapping, which's crucial for agricultural practices. Through data preprocessing and feature extraction techniques the U Net model shows an increase in accuracy by 90.0882%. This analysis offers insights into how crop are distributed over time and space leading to more dependable mapping results. Suggestions emphasize the need to address data imbalances for crop mapping applications providing approaches for precise and efficient crop monitoring. Ultimately this study has implications, for enhancing food security and optimizing resource allocation in agriculture.
Keywords:
U-Net, Convolutional Kernels, Normalization
Cite Article:
"Satellite Image Time Series Analysis For Crop Mapping Using U-Net, Sentinel Dataset", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.a63-a67, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404008.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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