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10 votes
Accepted

Global shapefile of biomes/ecoregions?

The WWF ecoregions are the original Olsen et al., (2001) classification units. If this is what you are after I would recommend using The Nature Conservancy modification to Olsen that deals with some ...
Jeffrey Evans's user avatar
6 votes
Accepted

SCP V.4.9.6 - after creating ROI, Warning: The following signature will be excluded if using Maximum Likelihood

The ROI is too small (or too homogeneous) for the Maximum Likelihood algorithm because that ROI has a singular covariance matrix. You should create larger ROIs or don’t use the Maximum Likelihood ...
obrob's user avatar
  • 857
6 votes
Accepted

Converting output of crosstab() in R to raster; from classified raster images to show overall land cover change in different classes?

Suppose two LULC rasters with 6 classes each one: library(raster) library(rasterVis) r <- raster() set.seed(123) lc1 <- setValues(r, sample(1:6, 64800, replace = T)) lc2 <- setValues(r, ...
aldo_tapia's user avatar
  • 13.6k
6 votes
Accepted

Replace specific raster class by surrounding classes

You can convert your clouds and shadows to null / no data (e.g. by using r.null) and then interpolate those "null areas" based on the surrounding values using the Fill nodata tool, see the ...
GISHuman's user avatar
  • 3,681
5 votes

Global shapefile of biomes/ecoregions?

There was a new map of ecorregions, published as part of this BioScience paper from 2017. https://academic.oup.com/biosci/article-lookup/doi/10.1093/biosci/bix014 Here there is an app to visualiza it,...
Javier Fajardo's user avatar
5 votes

Accuracy assessment using Google Earth Engine?

Yes, you can. This page describes how to do it. // Make a Random Forest classifier and train it. var classifier = ee.Classifier.randomForest(10) .train({ features: training, ...
Nicholas Clinton's user avatar
5 votes
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What are the necessary correction/calibration on Landsat 8 imagery for land cover classification?

You can perform a land cover classification on a single Landsat scene without performing spectral and radiometric corrections. You will only need to do those corrections if you're trying to apply ...
Dan's user avatar
  • 1,100
5 votes

Converting output of crosstab() in R to raster; from classified raster images to show overall land cover change in different classes?

Using sample data from @aldo_tapia : library(raster) library(rasterVis) r <- raster() set.seed(123) lc1 <- setValues(r, sample(1:6, 64800, replace = T)) lc2 <- setValues(r, sample(1:6, ...
Spacedman's user avatar
  • 63.9k
5 votes

Reclassify values of the land use land cover class of Copernicus Global Land Cover Layers in Google Earth Engine

The variable lulc1 is an image collection with 5 elements (images between years 2015 and 2019). If you want to reclassify it, it is preferable to map entire collection with a function. Following code ...
xunilk's user avatar
  • 29.9k
5 votes
Accepted

LULC Classification of Sentinel-2 Using XGBoost in R

It does not look like shp@data$class exists. In "shp" I see Classvalue and Classname but not class. Also, since your vector data are polygons extract(ras,shp) results in a list object (all ...
Jeffrey Evans's user avatar
5 votes
Accepted

Eliminate isolated pixels in Google Earth Engine classified image

Just use a focal operator or reduceNeighborhood with a mode reducer. image.focalMode(3) or image.reduceNeighborhood(ee.Reducer.mode(), ee.Kernel.circle(1))
Noel Gorelick's user avatar
4 votes
Accepted

Low Recall for Radar Image Flood Classification

Welcome to the trenches of classification, probability and statistics ;) . Assuming you used sklearn, it has a detailed user guide on what metrics it provides to evaluate your classifications: I'll ...
Senshi's user avatar
  • 1,767
4 votes

Processing LANDSAT 8 data in R (using packages Raster, RSToolbox, etc.) in order to calculate NDVI and land cover classification?

If you download surface reflectance data from espa you can skip steps 1, 2, 3, 5 and 6, and you will benefit from a more advanced atmospheric correction. Mask the clouds using the QA layer maskFun &...
Loïc Dutrieux's user avatar
4 votes

Do I need to perform any corrections on Level-2 Landsat imagery?

You do not need to do any further atmospheric correction with Landsat OLI/TIRS Level-2 data products as they are already corrected to surface reflectance. These data will be sufficient for time-series ...
Aaron's user avatar
  • 51.7k
4 votes

Replace specific raster class by surrounding classes

You can also do it in one step without replacing values with NULL values. Use the SAGA provided Majority filter for that: http://www.saga-gis.org/saga_tool_doc/2.2.0/grid_filter_6.html http://wiki....
eurojam's user avatar
  • 10.8k
4 votes

Sentinel-2 images

It is always preferable to use bottom of atmosphere reflectance (BOA) products (e.g. L2A) instead of top of atmosphere (TOA) reflectance products (e.g. L1C). For example, the image below shows a L1C ...
Aaron's user avatar
  • 51.7k
3 votes
Accepted

Can you apply Maximum Likelihood classification to NDVI?

You can apply a Maxiumum Likelihood classification to a single band image. However, the results will not be very useful and could be achieved just as easily by simply reclassifying the single band ...
Mikkel Lydholm Rasmussen's user avatar
3 votes
Accepted

vegetation classification from only the panchromatic band

You could try an image segmentation approach but, I would not hold my breath on usable results. As far as application of a classification algorithm to panchromatic imagery, it is quite doubtful that ...
Jeffrey Evans's user avatar
3 votes
Accepted

Accuracy assessment in R - Calculation of User Accuracy

The User's Accuracy is the reliability of the classes in the classified image. It is calculated as the fraction of correctly classified pixels with respect to all pixels classified as this class in ...
dmci's user avatar
  • 4,882
3 votes

Maximum likelihood classification, Landsat: Why to exclude thermal band?

In my opinion, the coarser resolution of the thermal band is not necessarily the reason why it gets excluded in many applications, after all, you can always resample the thermal band to unify the ...
TonyC's user avatar
  • 659
3 votes

Simplifying land cover classification in QGIS?

In QGIS I tried a majority filter (Processing>toolbox>geoalgorithms>filters) and also a sieve analysis (Raster>analysis). I found the Sieve function much easier to interpret and therefore get the ...
Archie Fisher's user avatar
3 votes

Land Use classification and canopy cover using LT8 imagery and ground truth points in QGIS

First of all you cannot create a spectral signature from a point. You will need polygons (training areas). Since it seems that you very exactly know your study area, you could add a column to your ...
Jochen Schwarze's user avatar
3 votes
Accepted

Export Google Earth Placemarks to shapefile

As for converting KML to SHP you can use an open source library GDAL. For conversion in command line tool you can type: ogr2ogr -f 'ESRI Shapefile' output.shp input.kml Of course you can put this in ...
deevee's user avatar
  • 499
3 votes
Accepted

Classifying raster that takes neighbours into account?

Thank to all those who made comments on my question. Based on those comments, I was able to write code that took neighbours into account in my classification, which was successful. I am sharing my ...
user3386170's user avatar
  • 1,957
3 votes
Accepted

Simple land classification (urban, suburban, rural) using polygons in MapInfo?

Do you have polygons defining the rural, suburban and urban areas? If so this should be fairly straightforward with a few steps add three float fields to your existing coverage table to hold the ...
T_Bacon's user avatar
  • 2,203
3 votes
Accepted

Classification of buildings using USGS Landsat 8 images on Google Earth Engine

The issue is clouds. You're trying to select only less cloudy scenes, but you're not doing anything to remove the cloudy pixels within those scenes. You are going to need a way to remove cloudy pixels ...
svangordon's user avatar
3 votes

Array in python just full of zeros when opened using GDAL

Firstly, why do you think the dataset is being read as all 0's? If you're just looking at the output of print(lc) then you're not seeing the whole array just snippets from the edges (3 elements from ...
user2856's user avatar
  • 65.9k
3 votes

Splitting up a region into training data and validation data for Landsat7 classification

Use randomColumn(columnName, seed), which adds a column of random values between 0 and 1 to the featurecollection. Then filter on <0.2 and >0.2 to get 20% for validation, 80% for testing. // Make ...
Kuik's user avatar
  • 10k
2 votes

Performing Random Forest using EnMap Box?

With the imageRF, you can use as many variables or layers as you want, you just need to have them stacked up together in one (ENVI) file. Then, you parameterize your model using that layer stack. ...
rsGIS's user avatar
  • 21
2 votes
Accepted

relating land cover raster to vector data

You can extract raster values of land cover classes to the point shapefile of archaeological sites using Plugin: Point sampling tool which can be downloaded from plugin manager in QGIS. The tool ...
ahmadhanb's user avatar
  • 40.9k

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