Modeling and monitoring cotton production using remote sensing techniques and machine learning: a case study of Punjab, Pakistan
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10668-024-05331-9.pdf
Reference50 articles.
1. AARI (Ayub Agricultural Research Institute). (2024). Cotton. https://aari.punjab.gov.pk/crop_varieties_cotton. Accessed on February 02, 2024.
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3. Agatonovic-Kustrin, S., & Beresford, R. (2000). Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research. Journal of Pharmaceutical and Biomedical Analysis, 22(5), 717–727. https://doi.org/10.1016/s0731-7085(99)00272-1
4. Akbar, H., & Gheewala, S. H. (2020). Effect of climate change on cash crops yield in Pakistan. Arabian Journal of Geosciences. https://doi.org/10.1007/s12517-020-05333-7
5. Ali, S. M., Khalid, B., Akhter, A., Islam, A., & Adnan, S. (2020). Analyzing the occurrence of floods and droughts in connection with climate change in Punjab province, Pakistan. Natural Hazards, 103, 2533–2559.
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