Google Earth Engine – Add CSV with GPS Points and Bathymetry Data

bathymetrycsvgoogle-earth-engineimporterrortable

I'm trying to construct a bathymetry point map on GEE, and I want to import a CSV that contains bathymetry data.
The CSV that I'm about to import to GEE has the following columns: Latitude, Longitude and Depth.

I uploaded my data:

And I set the advanced settings as the following:

However, whenever I try to import the data, the following message shows up:

The table may not have valid geometries

the lat and lon becomes a floating point value, and the depth becomes 256 in all the rows. In addition, there is an additional column added to the table.

I cannot use this data for my analysis, and I would like to ask if anyone could help!

The CSV can be accessed from the following link:
https://drive.google.com/file/d/1cY86-r84u2OPfoKkO5ODBXfbosRamrGV/view?usp=sharing

Best Answer

The first line of your file has some UTF junk in it:

<U+FEFF>Latitude,Longitude,Depth

Remove that first character and it should work fine.

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[GIS] Adding x,y coordinates from table in Google Earth Engine

Go to the Assets tab of the Code Editor, click the “New” button, and choose “CSV file.”
Select your CSV file.
In the “Advanced options” section, change the “X column” to be “x” instead of the default “longitude”, and the “Y column” to “y”.
Click Upload and wait for the task to finish.

I presume you found most of these steps but might not have seen the column name options. (You could also change the column headings in your CSV file to be “longitude” and “latitude” instead of “x” and “y”.)

Google Earth Engine – How to Calculate NDVI Landsat 5 Time Series for Multiple Polygons

Your code have several issues. Main of them was in NDVI definition from L5 data. B3 and B4 bands were inverted for NDVI determination producing senseless negative values. You can corroborate that in this link. So, I modified your code as follows and, after running it in GEE Code Editor, values (nome_imo, date_edit and mean) were exported to Google Drive as expected CSV. I commented .filterMetadata line for obtaining more NDVI values. CLOUD_COVER less_than 1 is a very drastic restriction and it only produces three values per feature in considered data range.

//Study area
//the area has three divisions according to the "nome_imo" column: fazenda_1, fazenda_2 and fazenda_3
//I want to calculate the NDVI mean of each of the divisions over time
//and generate a spreadsheet with 
//the image date, division name and ndvi mean value

var roi = ee.FeatureCollection('users/joseguerreroa/area_fazenda')
  .filter(ee.Filter.or(ee.Filter.eq('nome_imo', 'fazenda_1'),
                       ee.Filter.eq('nome_imo', 'fazenda_2'),
                       ee.Filter.eq('nome_imo', 'fazenda_3')));

//print(roi);

//image collection
var L5 = ee.ImageCollection('LANDSAT/LT05/C01/T1_TOA')
  //.filterMetadata('CLOUD_COVER', 'less_than', 1)
  .filterDate('2011-01-01','2011-12-31')
  .filterBounds(roi);

//Calculate NDVI
var addNDVI = function(image) {
  var ndvi = image.normalizedDifference(['B4', 'B3'])
                  .rename('ndvi');
  return image.addBands(ndvi);
};

//aplly ndvi for collection
var L5_ndvi = L5.map(addNDVI);

print("count", L5_ndvi.size());

var L5_ndvi_list = L5_ndvi.toList(L5_ndvi.size());

var L5_ndvi = L5_ndvi.select(['ndvi']);

//print("L5_ndvi", L5_ndvi);

var L5_ndviVis = {
  min: 0.15348,
  max: 0.76315,
};

Map.addLayer(L5_ndvi, L5_ndviVis, 'L5_ndvi');
Map.addLayer(roi);
Map.centerObject(roi, 12);

var feats_list = roi.toList(roi.size());

var ndvi_values = feats_list.map(function (feat) {
  
  var ndvi_val = L5_ndvi_list.map(function (image) {
  
  var stats = ee.Image(image).reduceRegion(
    {reducer: ee.Reducer.mean(),
     geometry: ee.Feature(feat).geometry()});
  
    return [ee.Feature(feat).get('nome_imo'), ee.Date(ee.Image(image).get('system:time_start')).format('yyyy-MM-dd'), stats.get('ndvi')];
  
  });
  
  return ndvi_val;
  
}).flatten();

//print("ndvi_values", ndvi_values);

var len = ndvi_values.size();

var list = ee.List.sequence(0, len.subtract(1), 3);

var new_ndvi_values = list.map(function(ele){

  var start = ee.Number(ele).int(); 
  var end = ee.Number(ele).add(3).int(); 

  var new_list = ee.List([]);
  var element = ee.List(ndvi_values.slice(start, end));

  new_list = new_list.add(element);

  return new_list.get(0);

});

//print (new_ndvi_values);

var myFeatures = ee.FeatureCollection(new_ndvi_values.map(function(el){
  el = ee.List(el); // cast every element of the list

  return ee.Feature(null, {
    'nome_imo': el.get(0),
    'date_edit': el.get(1),
    'mean': el.get(2)
  });
}));

//print(myFeatures);

// Export features, specifying corresponding names.
Export.table.toDrive(myFeatures,
"CSV_Export", //my task
"GEE_teste", //my export folder
"NDVI_mean",  //file name
"CSV");

After running above code, general NDVI raster image and roi area were loaded in Map Canvas of GEE; as it can be observed in following image.

Produced CSV file can be observed as follows opened in LibreOffice Calc. It can be edited for deleting not desired fields and for expressing a different order fields.

Best Answer

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[GIS] Adding x,y coordinates from table in Google Earth Engine

Google Earth Engine – How to Calculate NDVI Landsat 5 Time Series for Multiple Polygons

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