- Dietz T, Shwom RL, Whitley CT. Climate change and society. Annual Review of Sociology. 2020; 46: 135-158.
- Höök M, Tang X. Depletion of fossil fuels and anthropogenic climate change—A review. Energy Policy. 2013; 52:
797-809.
- Loarie SR, Duffy PB, Hamilton H, Asner GP, Field CB, Ackerly DD. The velocity of climate change. Nature. 2009;
462(7276): 1052-1055.
- Trenberth KE. Changes in precipitation with climate change. Climate research. 2011; 47(1-2): 123-138.
- Calzadilla A, Rehdanz K, Betts R, Falloon P ,Wiltshire A, Tol RS. Climate change impacts on global agriculture.
Climatic change. 2013; 120: 357-374.
- Taylor RG, Scanlon B, Döll P, Rodell M, Van Beek R, Wada Y, et al. Ground water and climate change. Nature
climate change. 2013; 3(4): 322-329.
- Wheeler T, Von Braun J. Climate change impacts on global food security. Science. 2013; 341(6145): 508-513.
- Chartzoulakis K, Bertaki M. Sustainable water management in agriculture under climate change. Agriculture and
Agricultural Science Procedia. 2015; 4: 88-98.
- Rao CS, Rejani R, Rao CR, Rao K, Osman M, Reddy KS, et al. Farm ponds for climate-resilient rainfed agriculture.
Current Science. 2017; 471-477.
- Siebrits R. Swimming pools and intra-city climates: influences on residential water consumption in Cape Town.
Water SA. 2012; 38(1): 133-144.
- Chi M, Plaza A, Benediktsson JA, Sun Z, Shen J, Zhu Y. Big data for remote sensing: Challenges and
opportunities. Proceedings of the IEEE. 2016; 104(11): 2207-2219.
- Huang C, Chen Y, Zhang S, Wu J. Detecting ,extracting, and monitoring surface water from space using optical
sensors: A review. Reviews of Geophysics. 2018; 56(2): 333-360.
- Isikdogan F, Bovik AC, Passalacqua P. Surface water mapping by deep learning. IEEE journal of selected topics in
applied earth observations and remote sensing. 2017; 10(11): 4909-4918.
- Cheng G, Xie X, Han J, Guo L, Xia G-S. Remote sensing image scene classification meets deep learning:
Challenges, methods, benchmarks, and opportunities. IEEE Journal of Selected Topics in Applied Earth
Observations and Remote Sensing. 2020; 13: 3735-3756.
- Cai W, Wei Z. Remote sensing image classification based on a cross-attention mechanism and graph convolution.
IEEE Geoscience and Remote Sensing Letters. 2020; 19:1-5.
- Liu X, Song L, Liu S, Zhang Y. A review of deep-learning-based medical image segmentation methods.
Sustainability. 2021; 13(3): 1224.
- Edpuganti A, Akshaya P, Gouthami J, Sajith Variyar V, Sowmya V, Sivanpillai R. Effect of data quality on water
body segmentation with deeplabv3+ algorithm. The International Archives of the Photogrammetry, Remote
Sensing and Spatial Information Sciences. 2023; 48: 81-85.
- Harika A, Sivanpillai R, Sajith Variyar V, Sowmya V. Extracting water bodies in rgb images using deeplabv3+
algorithm. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.
2022; 46: 97-101.
- Li Z, Wang R, Zhang W, Hu F, Meng L. Multiscale features supported DeepLabV3+ optimization scheme for
accurate water semantic segmentation. Ieee Access. 2019; 7: 155787-155804.
- Weng L, Xu Y, Xia M, Zhang Y, Liu J, Xu Y. Water areas segmentation from remote sensing images using a
separable residual segnet network. ISPRS international journal of geo-information. 2020; 9(4): 256.
- Ma Z ,Xia M, Weng L, Lin H. Local feature search network for building and water segmentation of remote sensing
image. Sustainability. 2023; 15(4): 3034.
- Wang Y. Remote sensing image semantic segmentation algorithm based on improved ENet network. Scientific
Programming. 2021; 1-10.
- Paszke A, Chaurasia A, Kim S, Culurciello E. Enet: A deep neural network architecture for real-time semantic
segmentation. arXiv preprint arXiv:160602147. 2016.
- Aburaed N, Al-Saad M, Alkhatib M, Zitouni M, Almansoori S ,Al-Ahmad H. Semantic Segmentation of Remote
Sensing Imagery Using AN Enhanced Encoder-Decoder Architecture. ISPRS Annals of the Photogrammetry,
Remote Sensing and Spatial Information Sciences. 2023; 10: 1015-1020.
- Li W, Dong Y, Wang Y, Xu T, Liu Z, Yu K, Xiao C, editors. SE-UNet: Channel Attention Based UNet for Water
Body Segmentation from SAR Image. International Conference on Image, Vision and Intelligent Systems 2023
Aug 16 (pp 100-107); 2024; Singapore: Springer Nature Singapore.
- Al-Saad M, Aburaed N, Alkhatib MQ, Zitouni MS, Al-Ahmad H, editors. An Enhanced UNet Model to Detect
Water Bodies From Remote Sensing Data. International Conference on Information Technology (ICIT) 2023 Aug
9 (pp 411-415) IEEE; 2023: IEEE.
- Duan L, Hu X. Multiscale refinement network for water-body segmentation in high-resolution satellite imagery.
IEEE Geoscience and Remote Sensing Letters. 2019; 17(4): 686-690.
- Chen J, Xia M, Wang D, Lin H. Double branch parallel network for segmentation of buildings and waters in
remote sensing images. Remote Sensing. 2023; 15(6): 1536.
- Pellis E, Masiero A, Cortesi I, Tucci G, Betti M, Grussenmeyer P, editors. Performance Comparison Between
Segnet and DEEPLABV3+ on the Semantic Segmentation of Heritage Buildings. 12th International Symposium on
Mobile Mapping Technology (MMT 2023), May 24-26, 2023, Padua, Italy 2023 May 25 (Vol 48, pp 379-386);
2023: TCopernicus GmbH
)