Prediction and monitoring of LULC shift using cellular automata-artificial neural network in Jumar watershed of Ranchi District, Jharkhand
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s10661-022-10623-6.pdf
Reference115 articles.
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2. Abijith, D., and Saravanan, S. (2021). Assessment of land use and land cover change detection and prediction using remote sensing and CA Markov in the northern coastal districts of Tamil Nadu, India. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-15782-6
3. Adedeji, O., Olusola, A., James, G., Shaba, H. A., Orimoloye, I. R., Singh, S. K., and Adelabu, S. (2020). Early warning systems development for agricultural drought assessment in Nigeria. Environmental Monitoring and Assessment, 192(12). https://doi.org/10.1007/s10661-020-08730-3
4. Afshar, M. H., Al-Yaari, A., & Yilmaz, M. T. (2021). Comparative evaluation of microwave l-band vod and optical ndvi for agriculture drought detection over central europe. Remote Sensing, 13(7). https://doi.org/10.3390/rs13071251
5. Ahamad, A., Madhav, S., Singh, P., & Pandey, J. (2018). Assessment of groundwater quality with special emphasis on nitrate contamination in parts of Varanasi City, Uttar Pradesh India. Applied Water Science, 8(4), 1–13. https://doi.org/10.1007/s13201-018-0759-x
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