-Get Feature Boundary from: data.humdata.org/dataset/pakistan-union-council-boundaries-along-with-other-admin-boundaries-dataset -Functions code: //declared function to convert the images types and perform the functions // Function to convert from d function toNatural(img) { return ee.Image(10.0).pow(img.select(0).divide(10.0)); } //Function to convert to dB function toDB(img) { return ee.Image(img).log10().multiply(10.0); } //Apllying a Refined Lee Speckle filter as coded in the SNAP 3.0 S1TBX: //github.com/senbox-org/s1tbx/blob/master/s1tbx-op-sar-processing/src/main/java/org/esa/s1tbx/sar/gpf/filtering/SpeckleFilters/RefinedLee.java //Adapted by Guido Lemoine // by Guido Lemoine function RefinedLee(img) { // img must be in natural units, i.e. not in dB! // Set up 3x3 kernels var weights3 = ee.List.repeat(ee.List.repeat(1,3),3); var kernel3 = ee.Kernel.fixed(3,3, weights3, 1, 1, false); var mean3 = img.reduceNeighborhood(ee.Reducer.mean(), kernel3); var variance3 = img.reduceNeighborhood(ee.Reducer.variance(), kernel3); // Use a sample of the 3x3 windows inside a 7x7 windows to determine gradients and directions var sample_weights = ee.List([[0,0,0,0,0,0,0], [0,1,0,1,0,1,0],[0,0,0,0,0,0,0], [0,1,0,1,0,1,0], [0,0,0,0,0,0,0], [0,1,0,1,0,1,0],[0,0,0,0,0,0,0]]); var sample_kernel = ee.Kernel.fixed(7,7, sample_weights, 3,3, false); // Calculate mean and variance for the sampled windows and store as 9 bands var sample_mean = mean3.neighborhoodToBands(sample_kernel); var sample_var = variance3.neighborhoodToBands(sample_kernel); // Determine the 4 gradients for the sampled windows var gradients = sample_mean.select(1).subtract(sample_mean.select(7)).abs(); gradients = gradients.addBands(sample_mean.select(6).subtract(sample_mean.select(2)).abs()); gradients = gradients.addBands(sample_mean.select(3).subtract(sample_mean.select(5)).abs()); gradients = gradients.addBands(sample_mean.select(0).subtract(sample_mean.select(8)).abs()); // And find the maximum gradient amongst gradient bands var max_gradient = gradients.reduce(ee.Reducer.max()); // Create a mask for band pixels that are the maximum gradient var gradmask = gradients.eq(max_gradient); // duplicate gradmask bands: each gradient represents 2 directions gradmask = gradmask.addBands(gradmask); // Determine the 8 directions var directions = sample_mean.select(1).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(7))).multiply(1); directions = directions.addBands(sample_mean.select(6).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(2))).multiply(2)); directions = directions.addBands(sample_mean.select(3).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(5))).multiply(3)); directions = directions.addBands(sample_mean.select(0).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(8))).multiply(4)); // The next 4 are the not() of the previous 4 directions = directions.addBands(directions.select(0).not().multiply(5)); directions = directions.addBands(directions.select(1).not().multiply(6)); directions = directions.addBands(directions.select(2).not().multiply(7)); directions = directions.addBands(directions.select(3).not().multiply(8)); // Mask all values that are not 1-8 directions = directions.updateMask(gradmask); // "collapse" the stack into a singe band image (due to masking, each pixel has just one value (1-8) in it's directional band, and is otherwise masked) directions = directions.reduce(ee.Reducer.sum()); //var pal = ['ffffff','ff0000','ffff00', '00ff00', '00ffff', '0000ff', 'ff00ff', '000000']; //Map.addLayer(directions.reduce(ee.Reducer.sum()), {min:1, max:8, palette: pal}, 'Directions', false); var sample_stats = sample_var.divide(sample_mean.multiply(sample_mean)); // Calculate localNoiseVariance var sigmaV = sample_stats.toArray().arraySort().arraySlice(0,0,5).arrayReduce(ee.Reducer.mean(), [0]); // Set up the 7*7 kernels for directional statistics var rect_weights = ee.List.repeat(ee.List.repeat(0,7),3).cat(ee.List.repeat(ee.List.repeat(1,7),4)); var diag_weights = ee.List([[1,0,0,0,0,0,0], [1,1,0,0,0,0,0], [1,1,1,0,0,0,0], [1,1,1,1,0,0,0], [1,1,1,1,1,0,0], [1,1,1,1,1,1,0], [1,1,1,1,1,1,1]]); var rect_kernel = ee.Kernel.fixed(7,7, rect_weights, 3, 3, false); var diag_kernel = ee.Kernel.fixed(7,7, diag_weights, 3, 3, false); // Create stacks for mean and variance using the original kernels. Mask with relevant direction. var dir_mean = img.reduceNeighborhood(ee.Reducer.mean(), rect_kernel).updateMask(directions.eq(1)); var dir_var = img.reduceNeighborhood(ee.Reducer.variance(), rect_kernel).updateMask(directions.eq(1)); dir_mean = dir_mean.addBands(img.reduceNeighborhood(ee.Reducer.mean(), diag_kernel).updateMask(directions.eq(2))); dir_var = dir_var.addBands(img.reduceNeighborhood(ee.Reducer.variance(), diag_kernel).updateMask(directions.eq(2))); // and add the bands for rotated kernels for (var i=1; i
Wonderful Sir, this video helped me a lot for my class report on "Impact of Flood and their mitigation strategies in Sindh " thank you Sir for your guidelines..... i really appreciate it....
Thank you for sharing this code but I got an error about "RefinedLee is not defined" and couldn't able to figure out how you did define this function. Can you help me please or any guys who have solved this issue?
Can I ask a question here mate, am sure you'all have encountered an issue where you have to clip a DEM file for a small area it shows pixels, just pixels, can this be Improved like using GEE to have the exact scale for proper representation of the map?
-Get Feature Boundary from:
data.humdata.org/dataset/pakistan-union-council-boundaries-along-with-other-admin-boundaries-dataset
-Functions code:
//declared function to convert the images types and perform the functions
// Function to convert from d
function toNatural(img) {
return ee.Image(10.0).pow(img.select(0).divide(10.0));
}
//Function to convert to dB
function toDB(img) {
return ee.Image(img).log10().multiply(10.0);
}
//Apllying a Refined Lee Speckle filter as coded in the SNAP 3.0 S1TBX:
//github.com/senbox-org/s1tbx/blob/master/s1tbx-op-sar-processing/src/main/java/org/esa/s1tbx/sar/gpf/filtering/SpeckleFilters/RefinedLee.java
//Adapted by Guido Lemoine
// by Guido Lemoine
function RefinedLee(img) {
// img must be in natural units, i.e. not in dB!
// Set up 3x3 kernels
var weights3 = ee.List.repeat(ee.List.repeat(1,3),3);
var kernel3 = ee.Kernel.fixed(3,3, weights3, 1, 1, false);
var mean3 = img.reduceNeighborhood(ee.Reducer.mean(), kernel3);
var variance3 = img.reduceNeighborhood(ee.Reducer.variance(), kernel3);
// Use a sample of the 3x3 windows inside a 7x7 windows to determine gradients and directions
var sample_weights = ee.List([[0,0,0,0,0,0,0], [0,1,0,1,0,1,0],[0,0,0,0,0,0,0], [0,1,0,1,0,1,0], [0,0,0,0,0,0,0], [0,1,0,1,0,1,0],[0,0,0,0,0,0,0]]);
var sample_kernel = ee.Kernel.fixed(7,7, sample_weights, 3,3, false);
// Calculate mean and variance for the sampled windows and store as 9 bands
var sample_mean = mean3.neighborhoodToBands(sample_kernel);
var sample_var = variance3.neighborhoodToBands(sample_kernel);
// Determine the 4 gradients for the sampled windows
var gradients = sample_mean.select(1).subtract(sample_mean.select(7)).abs();
gradients = gradients.addBands(sample_mean.select(6).subtract(sample_mean.select(2)).abs());
gradients = gradients.addBands(sample_mean.select(3).subtract(sample_mean.select(5)).abs());
gradients = gradients.addBands(sample_mean.select(0).subtract(sample_mean.select(8)).abs());
// And find the maximum gradient amongst gradient bands
var max_gradient = gradients.reduce(ee.Reducer.max());
// Create a mask for band pixels that are the maximum gradient
var gradmask = gradients.eq(max_gradient);
// duplicate gradmask bands: each gradient represents 2 directions
gradmask = gradmask.addBands(gradmask);
// Determine the 8 directions
var directions = sample_mean.select(1).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(7))).multiply(1);
directions = directions.addBands(sample_mean.select(6).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(2))).multiply(2));
directions = directions.addBands(sample_mean.select(3).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(5))).multiply(3));
directions = directions.addBands(sample_mean.select(0).subtract(sample_mean.select(4)).gt(sample_mean.select(4).subtract(sample_mean.select(8))).multiply(4));
// The next 4 are the not() of the previous 4
directions = directions.addBands(directions.select(0).not().multiply(5));
directions = directions.addBands(directions.select(1).not().multiply(6));
directions = directions.addBands(directions.select(2).not().multiply(7));
directions = directions.addBands(directions.select(3).not().multiply(8));
// Mask all values that are not 1-8
directions = directions.updateMask(gradmask);
// "collapse" the stack into a singe band image (due to masking, each pixel has just one value (1-8) in it's directional band, and is otherwise masked)
directions = directions.reduce(ee.Reducer.sum());
//var pal = ['ffffff','ff0000','ffff00', '00ff00', '00ffff', '0000ff', 'ff00ff', '000000'];
//Map.addLayer(directions.reduce(ee.Reducer.sum()), {min:1, max:8, palette: pal}, 'Directions', false);
var sample_stats = sample_var.divide(sample_mean.multiply(sample_mean));
// Calculate localNoiseVariance
var sigmaV = sample_stats.toArray().arraySort().arraySlice(0,0,5).arrayReduce(ee.Reducer.mean(), [0]);
// Set up the 7*7 kernels for directional statistics
var rect_weights = ee.List.repeat(ee.List.repeat(0,7),3).cat(ee.List.repeat(ee.List.repeat(1,7),4));
var diag_weights = ee.List([[1,0,0,0,0,0,0], [1,1,0,0,0,0,0], [1,1,1,0,0,0,0],
[1,1,1,1,0,0,0], [1,1,1,1,1,0,0], [1,1,1,1,1,1,0], [1,1,1,1,1,1,1]]);
var rect_kernel = ee.Kernel.fixed(7,7, rect_weights, 3, 3, false);
var diag_kernel = ee.Kernel.fixed(7,7, diag_weights, 3, 3, false);
// Create stacks for mean and variance using the original kernels. Mask with relevant direction.
var dir_mean = img.reduceNeighborhood(ee.Reducer.mean(), rect_kernel).updateMask(directions.eq(1));
var dir_var = img.reduceNeighborhood(ee.Reducer.variance(), rect_kernel).updateMask(directions.eq(1));
dir_mean = dir_mean.addBands(img.reduceNeighborhood(ee.Reducer.mean(), diag_kernel).updateMask(directions.eq(2)));
dir_var = dir_var.addBands(img.reduceNeighborhood(ee.Reducer.variance(), diag_kernel).updateMask(directions.eq(2)));
// and add the bands for rotated kernels
for (var i=1; i
Wonderful Sir, this video helped me a lot for my class report on "Impact of Flood and their mitigation strategies in Sindh " thank you Sir for your guidelines..... i really appreciate it....
All the best
@@createbytesir i have to do research on the topic (pre and post flood water quality analysis in sindh ) so plz sir can u guide me
I have a issues which "toDB is not defined" . Please let me know what is this issue?
Thank you for sharing this code but I got an error about "RefinedLee is not defined" and couldn't able to figure out how you did define this function. Can you help me please or any guys who have solved this issue?
i think the barren lands are classified as water bodies..... Just a tweak. Good Work
Well presented. Thank you so much.
Thank you for the video and the code sir, I appreciate it
Can I ask a question here mate, am sure you'all have encountered an issue where you have to clip a DEM file for a small area it shows pixels, just pixels, can this be Improved like using GEE to have the exact scale for proper representation of the map?
toDB function is not working in my code editor
Hello sir, thanks for the video. I wanna ask you how to determine the min max value?
Sir, what the name of methodh that you use, change detection or something else?
mine showing zero size and boundary is not adding in the layer
what can i do
how can access to all codes?
Which code can we use to output the final map result. please can you reply below. Thank you
map.layer and then include the layer you want add
thanks for your kind sharing bro, How can get other countries feature boundaries?
Yes . Just search for your country boundary shape files
Good morning Sir thanks for this kind explanation. Please can you share script with us?
Will upload soon
Thank you so much. Would you please share the code?
Good say sir, please i stuck 😢.
My good state size is printing as zero, what do i do?
Please I would appreciate getting a response as soon as possible
Is your issue fixed ?
The code says toDB is not defined.
Check the comments section and description
I have pinned the toDB function there
You can simply copy paste that into your editor
code
Is it possible to calculate total flood area of Pakistan?
yes
i'm getting same value of in inspector of good and flood filter its all same as you
Asslamualikum Sir. Thanks for This video, Can you share the flood report ! i need it
pdma.gos.pk/flood-2022-in-sindh/
Download the pdf from here brother
But this code shows a lot of water bodies on the eastern side, which we all know is a huge desert. I think its mixing sand with water.
can i get coding?
could you send me code of this anaysis
Even if I share you the code
It wont run because you wont have the imported assets , which are non shareable at the moment by Earth engine
It is Nice
flood water should be more than simple water. but in this analysis simple water is more. why?
bang bagi codingnya bang
Non-satisfied your answer, we want to see ce script, otherwise no explanation is required
Will surely try to work on that in upcoming videos
T