Flood mapping using Synthetic Aperture Radar data impose limitations in fully distinguishing flood under vegetation due to false double bounce returns from inundated tree trunks along with seasonal heterogeneities devised from changing land cover settings. SARfvcVer1 (SAR Flood Vegetation Classifier version-1) is a fully automatic supervised classification tool that uses hybrid Naïve Bayes classifier and is used to detect various flooded vegetation classes. The tool eliminates ROI creation step. It incorporates polarimetric information/LULC in labelling the image. It works best in identifying floods in agricultural lands and forests.
Verify that version 9.10 (R2021a) of the MATLAB Runtime is installed.
If not, you can run the MATLAB Runtime installer.
To find its location, enter >> mcrinstaller at the MATLAB prompt.
Note
You will need administrator rights to run the MATLAB Runtime installer.
Alternatively, download and install the Windows version of the MATLAB Runtime for R2021a from the link on the MathWorks website
- SARFvc_Ver1.exe
- MCRInstaller.exe
STEP 1: Downlaod the installer "SARFvc_Ver1.exe" from for_redistribution_files folder in this page. Make sure you have the following inputs. Example datasets are included in the folder
Inputs Data Name of example data Classified PolSAR image procedure Any season Scat_Mod_Class_georef_fin Single band SAR image during flood Image to be classified FloodHV LULC Optional LULC_georef Note: All the images must be georeferenced
STEP 2: Follow all the prerequisites
STEP 3: If you run the executable with exisitng MATLAB in your system, set the path to your data folder.
STEP 4: When you run the program it prompts for data as shown below. Select your folder and upload the data in order.
STEP 5: Select the number of classes from the list. This step ensures your image to be classified into number of classes that the user has chosen.
STEP 6: Let the program run. User will receive the status once the operation is complete.
STEP 7: The output is written into the folder with the name "classified".
Please write for any issues here
Cite as:
@article{SURAMPUDI2024101361,
title = {Hybrid Naïve Bayes Gaussian mixture models and SAR polarimetry based automatic flooded vegetation studies using PALSAR-2 data},
journal = {Remote Sensing Applications: Society and Environment},
volume = {36},
pages = {101361},
year = {2024},
issn = {2352-9385},
doi = {https://doi.org/10.1016/j.rsase.2024.101361},
url = {https://www.sciencedirect.com/science/article/pii/S2352938524002258},
author = {Samvedya Surampudi and Vijay Kumar},
}
Source: https://www.sciencedirect.com/science/article/abs/pii/S2352938524002258?via%3Dihub