"The service is currently unavailable" Google earth engine - google-earth-engine

I am trying to produce some Landsat images which are intersecting large rivers. The output of the code is ImageID. However, when I run the code, it takes about 5 mins and shows "The service is currently unavailable" or "User memory limit exceeded". I guess too many images are selected and sorted. Please help. Any suggestions would be truly appreciated.
https://code.earthengine.google.com/1167e0c6656b0e99a345d15643a671b7
var table2 = ee.FeatureCollection("users/bo_wang1/Yukon_River");
//1. Display the shapefile into the interactive map
//Display the view to the center of the screen and scale the view
Map.centerObject(table2,10);
//Define styling and determine the color of the shapefile
var styling = {color: 'red', fillColor: '00000000'};
Map.addLayer(table.style(styling));
//2. Loading L8 image collection (TOA reflectance)
var l8_collection= ee.ImageCollection('LANDSAT/LC08/C01/T1_SR');
//3. Filter by time window
var x1= l8_collection.filterBounds(table2)
.filterDate('2019-05-01', '2019-09-30')
.sort('CLOUD_COVER');
print ('L8 2019 image collection:',x1);
print('# images', x1.size());
// extract the different rows and paths
var distinctRows = x1.distinct(['WRS_ROW']).aggregate_array('WRS_ROW');
var distinctPaths = x1.distinct(['WRS_PATH']).aggregate_array('WRS_PATH');
print(distinctRows, distinctPaths)
//Extract least cloudy L8 scene in each tile
var imagePerPath = distinctPaths.map(function(path){
var imagePerRow = distinctRows.map(function(row){
var images = x1.filter(ee.Filter.and(ee.Filter.eq('WRS_ROW', row), ee.Filter.eq('WRS_PATH', path)));
return images.sort('CLOUD_COVER').first();
});
return imagePerRow;
});
var leastCloud = ee.ImageCollection.fromImages(imagePerPath.flatten());
// print and add the geometries of the images to the map
Map.addLayer(ee.FeatureCollection(leastCloud.map(function(image){return image.geometry()})))
print('leastCloud',leastCloud);
//Get the number of images
var count = leastCloud.size();
print('Count:', count);
//Get and print property and ImageID
print(leastCloud.first().propertyNames());
var imageID = leastCloud.aggregate_array('LANDSAT_ID');
print(imageID);
//Export Landsat_ID to CSV
Export.table.toDrive({
collection: leastCloud,
description: 'Get_ImageID',
folder: 'Shapefile from GEE',
fileFormat: 'CSV',
selectors: ['LANDSAT_ID'],
});

Related

image.filter is not a function in google earth engine

As a newbie to the google earth engine, I have been trying something (https://code.earthengine.google.com/6f45059a59b75757c88ce2d3869fc9fd) following a NASA tutorial (https://www.youtube.com/watch?v=JFvxudueT_k&ab_channel=NASAVideo). My last line (line 60) shows image.filter is not a function, while the one in the tutorial (line 34) is working. I am not sure what happened and how to sort this out?
//creating a new variable 'image' from the L8 collection data imported
var image = ee.Image (L8_tier1 //the details in the data will represent that the band resolution is 30m
//the details in the data will represent that the band resolution is 30m
//.filterDate ("2019-07-01","2021-10-03") //for a specific date range. maybe good to remove it for the function.
//the details in the data will represent that the band resolution is 30m
//the details in the data will represent that the band resolution is 30m
//.filterDate ("2019-07-01","2021-10-03") //for a specific date range. maybe good to remove it for the function.
.filterBounds (ROI) //for the region of interest we are interested in
//.sort ("COLUD_COVER") //for sorting the data between the range with a cloud cover, the metadata property we are interested in. Other way to do this is using the function below.
//.first() //this will make the image choose the first image with the least amount of cloud cover for the area. Other way to do this is using the function below.
);
//print ("Hague and Rotterdam", image); //printing the image in the console
//console on the right hand side will explain everything from the data
//id will show the image deatils and date of the image, for this case 29th July 2019
//under the properties tab cloud cover can be found, this is the least we can get for this area during this period
// //vizualisation of the data in the map with true color rendering
// var trueColour = {
// bands:["SR_B4","SR_B3","SR_B2"],
// min: 5000,
// max: 12000
// };
// Map.centerObject (ROI, 12); //for the centering the area in the center of the map with required zoom level
// Map.addLayer (image, trueColour, "Hague and Rotterdam"); //for adding the image with the variable of bands we made and naming the image
//Alternate way
//Function to cloud mask from the qa_pixel band of Landsat 8 SR data. In this case bits 3 and 4 are clouds and cloud shadow respectively. This can be different for different image sets.
function maskL8sr(image) {
var cloudsBitMask = 1 << 3; //remember to check this with the source
var cloudshadowBitMask = 1 << 4; //remember to check this with the source
var qa = image.select ('qa_pixel'); //creating the new variable from the band of the source image
var mask = qa.bitwiseAnd(cloudsBitMask).eq(0) //making the cloud equal to zero to mask them out
.and(qa.bitwiseAnd(cloudshadowBitMask).eq(0)); //making the cloud shadow equal to zero to mask them out
return image.updateMask(mask).divide(10000)
.select("SR_B[0-9]*")
.copyProperties(image, ["system:time_start"]);
}
// print ("Hague and Rotterdam", image);// look into the console now. How many images the code have downloaded!!!
//filtering imagery for 2015 to 2021 summer date ranges
//creating joint filter and applying to image collection
var sum21 = ee.Filter.date ('2021-06-01','2021-09-30');
var sum20 = ee.Filter.date ('2020-06-01','2020-09-30');
var sum19 = ee.Filter.date ('2019-06-01','2019-09-30');
var sum18 = ee.Filter.date ('2018-06-01','2018-09-30');
var sum17 = ee.Filter.date ('2017-06-01','2017-09-30');
var sum16 = ee.Filter.date ('2016-06-01','2016-09-30');
var sum15 = ee.Filter.date ('2015-06-01','2015-09-30');
var SumFilter = ee.Filter.or(sum21, sum20, sum19, sum18, sum17, sum16, sum15);
var allsum = image.filter(SumFilter);
Filtering is an operation you can do on ImageCollections, not individual Images, because all filtering does is choose a subset of the images. Then, in your script, you have (with the comments removed):
var image = ee.Image (L8_tier1
.filterBounds (ROI)
);
The result of l8_tier1.filterBounds(ROI) is indeed an ImageCollection. But in this case, you have told the Earth Engine client that it should be treated as an Image, and it believed you. So, then, the last line
var allsum = image.filter(SumFilter);
fails with the error you saw because there is no filter() on ee.Image.
The script will successfully run if you change ee.Image(...) to ee.ImageCollection(...), or even better, remove the cast because it's not necessary — that is,
var image = L8_tier1.filterBounds(ROI);
You should probably also change the name of var image too, since it is confusing to call an ImageCollection by the name image. Naming things accurately helps avoid mistakes, while you are working on the code and also when others try to read it or build on it.

recursive function on each pixel in google earth engine

I want to filter time series in the google earth engine which requires two for loops over time-series of a single pixel. I searched around and not found any example related to this. I know about .map function and I am using it for the generation of RVI on the earth engine. I found about .toArray function but not found any example related to my problem.
I will appreciate any help in this regard. Also, I am new to the earth engine so this may be a trivial question for others.
This is the code that I have. I took it from a blog and modified it according to my need. I am stuck after this.
var sentinel1 = ee.ImageCollection('COPERNICUS/S1_GRD_FLOAT');
// Filter VH, IW
var vh = sentinel1
// Filter to get images with VV and VH dual polarization.
//.filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VH'))
// Filter to get images collected in interferometric wide swath mode.
.filter(ee.Filter.eq('instrumentMode', 'IW'))
// reduce to VH polarization
//.select('VH')
// filter 10m resolution
.filter(ee.Filter.eq('resolution_meters', 10));
// Filter to orbitdirection Descending
var vhDescending = vh.filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING'));
// Filter time 2015
var vhDesc2015 = vhDescending.filterDate(ee.Date('2021-01-01'), ee.Date('2021-04-30'));
// Filter to MKD roi
var s1_mkd = vhDesc2015.filterBounds(roi);
print('All metadata:', s1_mkd);
var count = s1_mkd.size();
print('Count: ', count);
//var dates = s1_mkd.aggregate_array("system:time_start")
//print('dates: ', dates);
var dates = s1_mkd
.map(function(image) {
return ee.Feature(null, {'date': image.date().format('YYYY-MM-dd')})
})
.distinct('date')
.aggregate_array('date')
print('dates: ', dates);
var featureCollection = ee.FeatureCollection(dates
.map(function(element){
return ee.Feature(null,{prop:element})}))
//Export a .csv table of date, mean NDVI for watershed
Export.table.toDrive({
collection: featureCollection,
description: 'Timeseries',
folder: 'WC_raw',
fileFormat: 'CSV',
});
var rvi4s1 = function(img){
var vh = img.select('VH');
var vv = img.select('VV');
var col = vv.divide(vv.add(vh)).sqrt().rename('dop');
var dop = col.select('dop')
var value = dop.multiply(vh.multiply(4).divide(vv.add(vh))).rename('rvi4s1');
return value;
};
var rvi = s1_mkd.map(rvi4s1);
print(rvi);

Google Earth Engine video export error (a.element.map is not a function)

I'm trying to export a time-lapse here but got a weird error:
Error Creating or Submitting Task
a.element.map is not a function
I want to keep the visParams on my exported video by visualize() which I'm not sure is the right way to do so or not. do you have any suggestions for it?
var l8 = ee.ImageCollection("LANDSAT/LC08/C01/T1_TOA"),
region = ee.Geometry.Polygon(
[[[44.76385083079123, 38.28074335406828],
[44.76385083079123, 37.1334667575582],
[46.08221020579123, 37.1334667575582],
[46.08221020579123, 38.28074335406828]]], null, false),
params = {"opacity":1,"bands":["B4","B3","B2"],"min":0.07630298537191671,"max":0.3954072752450793,"gamma":1.356};
var collection = l8.filterBounds(region)
.filterMetadata('CLOUD_COVER', 'LESS_THAN', 30);
.filterDate('1999-01-01', '2020-01-01');
var l8med = collection.median();
Map.addLayer(collection, params, 'Layer');
print(collection.size());
var newimg = l8med.visualize(params);
Export.video.toDrive({
collection: newimg,
description: 'a1',
dimensions: 720,
framesPerSecond: 12,
folder: "GEE",
maxFrames: 100000,
region: region
});
You made a single image out of the collection using .median() and then tried to export that, so it can't work — there's no time series to make a video out of, after that.
You do need .visualize() but you need to do it for each image:
Export.video.toDrive({
collection: collection.map(function (image) { return image.visualize(params); }),
...

How to increase resolution of exported image in Google Earth Engine?

I have some code to export an LS8 image to Drive using GEE. Somehow, the resolution of the image seems to be lower (larger pixels) than what I am able to see on the browser. How can I increase the resolution? This is the code I´ve been using, with two different options.
I attempted to use .resample() as a solution but it produced a single band image that did not look good.
geometry2 = /* color: #57d64b */ee.Geometry.Polygon(
[[[-78.2812086867645, 2.3386717366200585],
[-77.56984394067075, 2.3729749945579948],
[-77.72227924340513, 2.776314152654142],
[-78.20842426293638, 2.725560942159387]]]);
function maskL8sr(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 pixel 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 the masked image, scaled to TOA reflectance, without the QA bands.
return image.updateMask(mask).divide(10000)
.select("B[0-9]*")
.copyProperties(image, ["system:time_start"]);
}
// Map the function over one year of data.
var collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
.filterDate('2016-04-01', '2018-7-31')
.map(maskL8sr)
var composite = collection.median();
var VIS = {bands: ['B5', 'B6', 'B4'], min: 0, max: 0.47};
// Display the results.
Map.addLayer(composite,VIS ,"compt2");
var params ={
crs: 'EPSG:4326',
maxPixels: 1e12,
region:geometry2
}
Export.image(composite,'Guapi',params);
Export.image.toDrive({
image: composite,
description: 'Guapi',
scale: 30,
region: geometry2,
maxPixels: 1000000000
});

OpenLayer Popups for markers imported from google spreadsheet

I'm looking for a way to use framecloud type popup with my current setup. Unfortunately all my attempts have either not worked or will only work on the most recently placed maker.
In the course of trying to get it to work I have converted my original script from using Markers to using Vectors to placing the marker points (as I've seen that it's easier to customize vectors than markers.)
Now which ever one I can get to work I'll use, but after working on this for a few days I'm at my wits end and need a helping hand in the right direction.
My points are pulled from a google spreadsheet using tabletop.js. The feature is working how I wish it to, with the markers being placed on their respective layer based on a field I called 'type'.
While I have a feeling that might have been the source of my problem with the Markers type layer, I'm not sure how to fix it.
You can view the coding through these pages
(Links removed due to location change.)
Thanks for all help in advance.
I finally got it to work. For anyone in a similar situation here's my final code for the layers. I did change the names of the layers from what they are originally and blacked out the spreadsheet I used, but the changes should be noticeable.
//
//// Set 'Markers'
//
var iconMarker = {externalGraphic: 'http://www.openlayers.org/dev/img/marker.png', graphicHeight: 21, graphicWidth: 16};
var iconGeo = {externalGraphic: './images/fortress.jpg', graphicHeight: 25, graphicWidth: 25};
var iconAero = {externalGraphic: './images/aeropolae.jpg', graphicHeight: 25, graphicWidth: 25}; // Image is the creation of DriveByArtist: http://drivebyartist.deviantart.com/
var vector1 = new OpenLayers.Layer.Vector("1");
var vector2 = new OpenLayers.Layer.Vector("2");
var vector3 = new OpenLayers.Layer.Vector("3");
// Pulls map info from Spreadsheet
//*
Tabletop.init({
key: 'http://xxxxxxxxxx', //Spreadsheet URL goes here
callback: function(data, tabletop) {
var i,
dataLength = data.length;
for (i=0; i<dataLength; i++) { //following are variables from the spreadsheet
locName = data[i].name;
locLon = data[i].long;
locLat = data[i].lat;
locInfo = data[i].info;
locType = data[i].type; // Contains the following string in the cell, which provides a pre-determined output based on provided information in the spreadsheet: =ARRAYFORMULA("<h2>"&B2:B&"</h2><b>"&G2:G&"</b><br /> "&C2:C&", "&D2:D&"<br />"&E2:E&if(ISTEXT(F2:F),"<br /><a target='_blank' href='"&F2:F&"'>Read More...</a>",""))
locLonLat= new OpenLayers.Geometry.Point(locLon, locLat);
switch(locType)
{
case "Geopolae":
feature = new OpenLayers.Feature.Vector(
locLonLat,
{description:locInfo},
iconGeo);
vector1.addFeatures(feature);
break;
case "POI":
feature = new OpenLayers.Feature.Vector(
locLonLat,
{description:locInfo},
iconMarker);
vector2.addFeatures(feature);
break;
case "Aeropolae":
feature = new OpenLayers.Feature.Vector(
locLonLat,
{description:locInfo},
iconAero);
vector3.addFeatures(feature);
break;
}
}
},
simpleSheet: true
});
map.addLayers([vector1, vector2, vector3]);
map.addControl(new OpenLayers.Control.LayerSwitcher());
//Add a selector control to the vectorLayer with popup functions
var controls = {
selector: new OpenLayers.Control.SelectFeature(Array(vector1, vector2, vector3), { onSelect: createPopup, onUnselect: destroyPopup })
};
function createPopup(feature) {
feature.popup = new OpenLayers.Popup.FramedCloud("pop",
feature.geometry.getBounds().getCenterLonLat(),
null,
'<div class="markerContent">'+feature.attributes.description+'</div>',
null,
true,
function() { controls['selector'].unselectAll(); }
);
feature.popup.autoSize = true;
feature.popup.minSize = new OpenLayers.Size(400,100);
feature.popup.maxSize = new OpenLayers.Size(400,800);
feature.popup.fixedRelativePosition = true;
feature.popup.overflow ="auto";
//feature.popup.closeOnMove = true;
map.addPopup(feature.popup);
}
function destroyPopup(feature) {
feature.popup.destroy();
feature.popup = null;
}
map.addControl(controls['selector']);
controls['selector'].activate();
}

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