With the characters of the high resolution satellite image, we will use the recognition of the type of water bodies as an example, begin with the extraction of the spectrum features of the ground objects from the satellite digital images, separate water bodies from background and recognize it ...
employed to detect a water-body and compute the changes in its area from the time-lapsed images captured over 32 years, that is, 1984 to 2016. The models are validated using water-bodies images taken by the Sentinel-2 Satel-lite and compared based on the average precision (AP), 99.95 an...
Water resources play an important role in environmental, transportation andregion planning, natural disaster, industrial and agricultural production and so on.Surveying of water-bodies and delineate its features properly is very first stepfor any planning, especially for places like India, where the ...
The input given to the model is the water bodies dataset. The dataset is sourced from the Kaggle with the name Satellite Images of WaterBodies. These images are obtained and captured by sentinel-2 Satellite. The dataset contains two directories. The first one is Images and the other one is...
A Deep Learning Method of Water Body Extraction From High Resolution Remote Sensing Images With Multisensors Water body extraction from remote sensing images is an important task. Deep learning has become a more popular method for extracting water bodies from remo... M Li,P Wu,B Wang,... -...
This project uses a CNN based on the U-Net architecture to segment bodies of water in satellite images. - GitHub - wct432/water_bodies_segmentation: This project uses a CNN based on the U-Net architecture to segment bodies of water in satellite images.
In this letter, a new segmentation network called restricted receptive field deconvolution network (RRF DeconvNet) is proposed, with which to extract water bodies from high-resolution remote sensing images. Compared with natural images, remote sensing images have a weaker pixel neighborhood relativity;...
The test study results indicated that the NDVI–NDWI index is superior to the single index of NDVI and NDWI to enhance the contrast between water bodies and the rest of the features. On the basis of the accurately mapped water bodies in the HJ-1A/B CCD images of the study area...
Automated mapping of water bodies using Landsat multispectral data: automated mapping of water bodies. Limnol. Oceanogr. Methods 10, 1037–1050 (2012). Article Google Scholar Danielson, J. J. & Gesch, D. B. Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010). Report No. OFR ...
Combining Multi-Sensor Satellite Imagery to Improve Long-Term Monitoring of Temporary Surface Water Bodies in the Senegal River FloodplainOgilvie, AndrewPoussin, JeanChristopheBader, JeanClaudeBayo, FindaBodian, AnsoumanaDacosta, Honor茅Dia, Djiby...