i have so many columns in my shp,
i use data from my shp to show vector layer,
and i did it but sometimes take a long time even unresponsive script
can anyone help me how to show vector layers from shp in geoserver faster
this is my code that im using
var hitungJumlah = vectorSource.getFeatures();
for(var k=0;k<hitungJumlah.length;k++){
var id = vectorSource.getFeatures()[k].getId();
var feature = vectorSource.getFeatureById(id);
if(feature.get('klas')!=null){
var a = feature.get('klas');
}else{
a = "";
}
if(a=="Utama"){
//warna is my ol.layer.Vector
warna.getSource().addFeature(feature);
}
}
Related
Please, how do get positive values of NDVI for my study area?
Please see my Javascript code below. Unfortunately, after running the code, the NDVI chart generated are mostly negative. (See image attached). How do I correct this please?
Image of generated NDVI chart
See my Javascript code:
var startDate = '2001-01-01'
var endDate = '2020-12-31'
var images = landsat7.filter(ee.Filter.date(startDate, endDate));
print(images);
var ndvi = function(image){
var ndv = image.normalizedDifference(['B4', 'B3']);
// for Sentinel, use var scaled = image.normalizedDifference(['SR_B4', 'SR_B3']);
return ndv.copyProperties(image, ['system:index', 'system:time_start'])
}
var ndvi = images.map(ndvi)
print(ndvi);
var nd = ndvi.max().clip(finni);
Map.addLayer(nd, {min:0,max:1,palette:['white', 'Green']}, 'NDVI');
var chart = ui.Chart.image.seriesByRegion({
imageCollection:ndvi,
regions:finni,
reducer: ee.Reducer.mean(),
scale:30,
});
print(chart);
I want to combine all the Landsat sensors from 1985 up today in Google Earth Engine, remove the clouds and calculate the time-series of the NBR index. As a new GEE user I have the following:
// find all data and filter them by date
var lst5 = ee.ImageCollection('LANDSAT/LT5_SR').filterDate('1984-10-01', '2011-10-01');
var lst7 = ee.ImageCollection('LANDSAT/LE7_SR').filterDate('2011-10-01', '2013-04-07');
var lst8 = ee.ImageCollection('LANDSAT/LC8_SR').filterDate('2013-04-07', '2018-05-01');
var lst7_08 = ee.ImageCollection('LANDSAT/LE7_SR').filterDate('2007-12-01', '2008-02-01');
var lst7_92 = ee.ImageCollection('LANDSAT/LT4_SR').filterDate('1992-01-02', '1992-04-01');
// Combine all landsat data, 1985 through 2015
var everything = ee.ImageCollection(lst5.merge(lst7));
everything = everything.merge(lst8);
everything = everything.merge(lst7_08);
everything = everything.merge(lst7_92);
var alltogether = ee.ImageCollection(everything.filterDate('1984-01-01', '2018-05-01'));
From this point, I do not know how to remove the clouds and calculate the NBR index (NBR index here) for every image in my final collection.
Can anyone help me?
Thank you.
EDIT:
I think that I need to map a normalizedDifference function over my collection in order to get the NBR index but I am not sure how to do this for my collection with the different sensors.
You've got quite a lot going on here, but here's what I think you want. You should check this very carefully to ensure it's behaving as intended:
// Function to cloud mask Landsat 8.
var maskL8SR = function(image) {
// Bits 3 and 5 are cloud shadow and cloud, respectively.
var cloudShadowBitMask = ee.Number(2).pow(3).int();
var cloudsBitMask = ee.Number(2).pow(5).int();
// Get the QA band.
var qa = image.select('pixel_qa');
// Both flags should be set to zero, indicating clear conditions.
var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0).and(
qa.bitwiseAnd(cloudsBitMask).eq(0));
return image
// Scale the data to reflectance and temperature.
.select(['B5', 'B7'], ['NIR', 'SWIR']).multiply(0.0001)
.addBands(image.select(['B11'], ['Thermal']).multiply(0.1))
.updateMask(mask);
};
// Function to cloud mask Landsats 5-7
var maskL57SR = function(image) {
var qa = image.select('pixel_qa');
// Second bit must be zero, meaning none to low cloud confidence.
var mask1 = qa.bitwiseAnd(ee.Number(2).pow(7).int()).eq(0).and(
qa.bitwiseAnd(ee.Number(2).pow(3).int()).lte(0)); // cloud shadow
// This gets rid of irritating fixed-pattern noise at the edge of the images.
var mask2 = image.select('B.*').gt(0).reduce('min');
return image
.select(['B4', 'B7'], ['NIR', 'SWIR']).multiply(0.0001)
.addBands(image.select(['B6'], ['Thermal']).multiply(0.1))
.updateMask(mask1.and(mask2));
};
// find all data and filter them by date
var lst5 = ee.ImageCollection('LANDSAT/LT05/C01/T1_SR')
.filterDate('1984-10-01', '2011-10-01')
.map(maskL57SR)
var lst7 = ee.ImageCollection('LANDSAT/LE07/C01/T1_SR')
.filterDate('2011-10-01', '2013-04-07')
.map(maskL57SR)
var lst8 = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
.filterDate('2013-04-07', '2018-05-01')
.map(maskL8SR)
var lst7_08 = ee.ImageCollection('LANDSAT/LE07/C01/T1_SR')
.filterDate('2007-12-01', '2008-02-01')
.map(maskL57SR)
var lst7_92 = ee.ImageCollection('LANDSAT/LT04/C01/T1_SR')
.filterDate('1992-01-02', '1992-04-01')
.map(maskL57SR)
// Combine all landsat data, 1985 through 2015
var everything = ee.ImageCollection(lst5.merge(lst7));
everything = everything.merge(lst8);
everything = everything.merge(lst7_08);
everything = everything.merge(lst7_92);
// NBR:
var nbrFunction = function(image) {
image = ee.Image(image)
return image.addBands(image.expression(
'(nir - 0.0001 * swir * thermal) / ' +
'(nir + 0.0001 * swir * thermal)', {
nir: image.select(['NIR']),
swir: image.select(['SWIR']),
thermal: image.select(['Thermal'])
}).rename('NBR').clamp(-1, 1));
};
everything = everything.map(nbrFunction);
var check = ee.Image(everything.first());
Map.centerObject(check);
Map.addLayer(check);
The answer works great for SR imagery! Thanks! Sorry I can't just comment because I don't have 50 reputation yet, but I saw #Abhilash Singh Chauhan's question about why ee.Number(2).pow(3)... is used for the variables cloudshadow and clouds. I had the same question and I wanted to answer that it's because of the fact that the QA Pixel bands are Decimal integers that contain Binary information. So for example band 3 for surface reflectance LANDSAT products indicates the band for cloud shadow but the values are in binary. To get the values you need to convert the band to binary, hence 2^3 and similarly 2^5 for cloud values. I hope that clarifies the comment. you can check this here: https://www.usgs.gov/landsat-missions/landsat-4-7-surface-reflectance-quality-assessment
Im developing an iOS app which allows users to take a sequence of photos - afterwards the photos are put in an animation and exported as MP4 and GIF.
While the MP4 presents the source quality, the GIF color grades are visible.
Here the visual comparison:
GIF:
MP4
The code I use for exporting as GIF:
var dictFile = new NSMutableDictionary();
var gifDictionaryFile = new NSMutableDictionary();
gifDictionaryFile.Add(ImageIO.CGImageProperties.GIFLoopCount, NSNumber.FromFloat(0));
dictFile.Add(ImageIO.CGImageProperties.GIFDictionary, gifDictionaryFile);
var dictFrame = new NSMutableDictionary();
var gifDictionaryFrame = new NSMutableDictionary();
gifDictionaryFrame.Add(ImageIO.CGImageProperties.GIFDelayTime, NSNumber.FromFloat(0f));
dictFrame.Add(ImageIO.CGImageProperties.GIFDictionary, gifDictionaryFrame);
InvokeOnMainThread(() =>
{
var imageDestination = CGImageDestination.Create(fileURL, MobileCoreServices.UTType.GIF, _images.Length);
imageDestination.SetProperties(dictFile);
for (int i = 0; i < this._images.Length; i++)
{
imageDestination.AddImage(this._images[i].CGImage, dictFrame);
}
imageDestination.Close();
});
The code I use for exporting as MP4:
var videoSettings = new NSMutableDictionary();
videoSettings.Add(AVVideo.CodecKey, AVVideo.CodecH264);
videoSettings.Add(AVVideo.WidthKey, NSNumber.FromNFloat(images[0].Size.Width));
videoSettings.Add(AVVideo.HeightKey, NSNumber.FromNFloat(images[0].Size.Height));
var videoWriter = new AVAssetWriter(fileURL, AVFileType.Mpeg4, out nsError);
var writerInput = new AVAssetWriterInput(AVMediaType.Video, new AVVideoSettingsCompressed(videoSettings));
var sourcePixelBufferAttributes = new NSMutableDictionary();
sourcePixelBufferAttributes.Add(CVPixelBuffer.PixelFormatTypeKey, NSNumber.FromInt32((int)CVPixelFormatType.CV32ARGB));
var pixelBufferAdaptor = new AVAssetWriterInputPixelBufferAdaptor(writerInput, sourcePixelBufferAttributes);
videoWriter.AddInput(writerInput);
if (videoWriter.StartWriting())
{
videoWriter.StartSessionAtSourceTime(CMTime.Zero);
for (int i = 0; i < images.Length; i++)
{
while (true)
{
if (writerInput.ReadyForMoreMediaData)
{
var frameTime = new CMTime(1, 10);
var lastTime = new CMTime(1 * i, 10);
var presentTime = CMTime.Add(lastTime, frameTime);
var pixelBufferImage = PixelBufferFromCGImage(images[i].CGImage, pixelBufferAdaptor);
Console.WriteLine(pixelBufferAdaptor.AppendPixelBufferWithPresentationTime(pixelBufferImage, presentTime));
break;
}
}
}
writerInput.MarkAsFinished();
await videoWriter.FinishWritingAsync();
I would appreciate for your help!
Kind regards,
Andre
This is just summarization of mine comments...
I do not code on your platform so I only provide generic answer (and insights from mine own GIF encoder/decoder coding experience).
GIF image format supports up to 8bit per pixel leading to max 256 colors per pixel with naive encoding. Cheap encoders just truncates input image to 256 or less colors usually leading to ugly pixelated results. To increase coloring quality of GIF there are 3 approaches I know of:
Multiple frames covering screen with own palettes
Simply you divide image into overlays each with its own palette. This is slow (in therm of decoding as you need to process more frames per single image which can cause sync errors with some viewers and you need to process all frame related chunks multiple times per single image). The encoding itself is fast as you just either separate the frames based on colors or region/position to multiple frames. Here (region/position based) example:
The sample image is taken from here: Wiki
The GIF supports transparency so the sub frames can overlap ... This approach physically increase the colors per pixel possible to N*256 (or N*255 for transparent frames) where N is the number of frames or palettes used per single image.
Dithering
Dithering is technique that approximate color of area to match colors as closely as possible while using only specified colors (from palette) only. This is fast and easily implementable but the result is kind of noisy. For more info see some related answers of mine:
Converting BMP image to set of instructions for a plotter?
c# image dithering routine that accepts an amount of dithering?
Better color quantization method
Cheap encoders just truncate the colors to predefined palette. Much better results are obtained by clustering the used colors based on histogram. For example see:
Effective gif/image color quantization?
The result is usually much better then dithering but the encoding time is huge in comparison to dithering...
The #1 and #3 can be used together to enhance quality even more ...
If you do not have access to the encoding code or pipeline you still can transform image itself before encoding doing the quantization and palette computation instead and load the result directly to GIF encoder which should be possible (if the GIF encoder you are using is at least a bit sophisticated ...)
I have a map, that has both new and migrated areas. The new areas are being pushed to the map, but the migrated ones are not. They are somewhat loading, as the length of the collection is correct. map.entites.push('polygon') is not working.
here is the code I am using:
var checkExist = setInterval(function () {
var counter = 0;
for (var i = 0; i < viewData.zones.length; i++) {
var zone = viewData.zones[i];
var id = zone["ID"];
var geometricArea = zone["CoverageArea"];
var geography = geometricArea["Geography"];
//console.log("geography object :" + JSON.parse(geography));
//var zoneShape = zoneShapes[i];
// console.log(geography.WellKnownText);
var polygon = WKTModule.Read(geography.WellKnownText)
polygon.shapeType = ('Polygon').toLowerCase();
polygon.id = id;
map.entities.push(polygon);
zoneEntities.push(polygon);
});
});
Also- Even though the polygon isnt being pushed to the map, the coordinates are there and it has an id. I am not sure what is happening.
Thanks!
What is the zoneEntities variable? If it is a layer/entityCollection this would cause an issue as you already tried adding the shape to the map. Which map control are you using V7 or v8. V8 renders on an HTML5 canvas and has to redraw with every change to your shape. If you are changing the shapes in an interval like this and the interval is too small, the renderer will wait for the changes to stop for a period of time before drawing. Looking at your code you aren't specifying an interval time which means it is firing this even a ridiculous number of times.
i am new in cocos2d-js here, i just created this code:`
var that = this;
that._dice
// add player
// create sprite sheet
cc.spriteFrameCache.addSpriteFrames(res.dice_plist);
var spriteSheet = new cc.SpriteBatchNode(res.diceRed_png);
that.addChild(spriteSheet, 2);
// init runningAction
var animFrames = [];
for (var i = 1; i < 7; i++) {
var str = "dieRed" + i + ".png";
var frame = cc.spriteFrameCache.getSpriteFrame(str);
animFrames.push(frame);
}
var animation = new cc.Animation(animFrames, 0.1);
that.runningAction = new cc.Repeat.create(new cc.Animate(animation), Math.random()*10);
var diceSprite = new cc.Sprite("#dieRed1.png");
diceSprite.visible = true;
console.log(this.getContentSize(diceSprite));
diceSprite.runAction(this.runningAction);
that._dice.push(diceSprite);
var size = cc.winSize;
spriteSheet.setPosition(size.width/6.5, size.height/1.20);
spriteSheet.setAnchorPoint(0.5, 0.5);
spriteSheet.addChild(diceSprite, 2);
`
and i would like to use the getFrames() feature to return the array of ccanimation frames. i'm just thinking to get the information of which picture are being animated on the screen there, for example, if the #dieRed1.png is being animated or visible on the screen, it would show value or return value of 1. i have tried to googled around and cannot find any other clue there. if there is any better method, i would love to see that as well. sorry for the english anyway, a bit confused how to arrange the words. thank you :)
Ok, so refering to
the official docs
{Array} getFrames()
Returns the array of animation frames
Which means you can just do:
var frames = animation.getFrames();
To get the array. And then you'll receive an array of cc.AnimationFrame.
To get sprite link do:
var frame = frames[0];//cc.AnimationFrame
var spriteFrame = frame.getSpriteFrame(); //cc.SpriteFrame
var texture = spriteFrame.getTexture(); // cc.Texture
And the texture itself should have the name attribute which may do the job.