Questions tagged [machine-learning]
Field of study that gives computers the ability to learn without being explicitly programmed
87
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I am trying to perform a machine learning analyis using the ArcGIS module in Jupyter notebooks but strange error
I was trying to import all modules for ArcGIS to perform a machine learning analysis. However, the code gives me an error at the line from arcgis.learn.
Code:
%matplotlib inline
import pandas as pd
...
2
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0
answers
25
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Using images from different Landsat missions and Sentinel-2 for machine learning
I am doing some image segmentation using random forests on satellite imagery. The events I am trying to detect are somewhat rare so my training sets are very limited if I want to use Sentinel-2 ...
3
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21
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Projection best practices for applying ML to large scale Earth Observation imagery [closed]
I come from a data science background, rather than GIS, but work in a domain where remote-sensed imagery is widely used; so I'm still learning some of the do's & don'ts when it comes to the 'right'...
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1
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94
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Adding a column to a Google Earth Engine feature collection
I am trying to generate a ground truth feature collection to do some machine learning. I have a shapefile that contains one class of my ground truth. and I am manually creating a second feature ...
1
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0
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22
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Reusing regression or machine learning model in subsequent years
I have collected high-resolution UAV imagery and leaf area index (LAI) plot data. I plan on creating a model which uses my ground-based LAI to establish a relationship or train my UAV imagery. I will ...
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ModelMap error insists that my rasters are in different datums and projections but in ArcGIS Pro they are the same
I am using randomforest in the modelmap package to create a map output. I create a model with no issues, but when I use the model.mapmake() function, I get the following error message
"predictor ...
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20
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Sentinel 2 TIFF image for model prediction of crop type
I am new to the GIS image data. I recently created a prediction model based on the pixel value given in csv file of Sentinel 2 bands (12), classification was given for the crop type. I am struggling ...
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128
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Detection of tomato areas from UAV images using ML
I have many UAV .tif images which they contain tomato plant in a farm, and between them there is separation with soil. So by searching on google I have found this paper https://www.mdpi.com/2072-4292/...
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20
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Meaning of Jeffreys-Matusita Separation values
I've computed the JM separation values for my training classes for Sentinel-2 image classification. I understand that the values range between 0-2. Most of the values are above 1.9, but some are down ...
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Deep machine learning to improve satellite spatial resolution
Are there currently technologies based on deep machine learning that can improve the spatial resolution of satellite images (e.g. Sentinel-2)?
An example of the use of such technology to reconstruct a ...
- 5,602
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240
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Using RandomForest for land use classification in Google Earth Engine: Training accuracy shows error
I am using RandomForest classification for my LULCC study. I have been successful in running the classification including getting the "validation accuracy" as 0.87. However, my "...
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1
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61
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View values of clusters after unsupervised classification by NDVI in Google Earth Engine
I am creating unsupervised classifications of an area to detect landscape/vegetation change over time.
For each year:
I have created an NDVI of the area based on a composite of Landsat images ...
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1
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1
answer
55
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NameError in Machine learning with Open Data Cube notebook code
I am trying to run the "Machine learning with the Open Data Cube" using my own .shp file but seem to keep getting the same error. The only cell that I altered in the following link is number ...
- 19
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4
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196
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Automated extraction of road network from points
I have a huge dataset containing about zillion of points representing tracking locations of cars on the roads.
I also have roads datasets to compare to (from 3 different sources), to use for training ...
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99
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What's the maximum number of data points allowed to train a classifier in Google Earth Engine?
What is the maximum number of data points allowed to train a classifier in Google Earth Engine (n columns * n rows)? I know there is some threshold that if you go above, you get a Computed value too ...
- 409
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25
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Semantic Segmentation on a bigger image
I trained a U-net with inputs of satellite images of 120 X 120.
I need to apply my model to a bigger image (size 10980 X 10980). What I tried to do was slice the bigger images into slices of 120 X120 ...
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2
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29
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Find Optimal Subset of Feature Layer Based on Spatial Criteria & Attributes
I'm using a Census tract shapefile with their corresponding attributes of interest within ArcMap 10.7.1.
My project goal is to identify the subset of tracts that share a line segment while:
...
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43
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Google satellite basemap license
Where (if anywhere) can we buy a license to use Google satellite basemap as input to machine learning algorithms?
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58
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Adding point features by machine learning in QGIS 3.16
I've got several georeferenced traditional maps and there are circles on it. (these are the studied points) So I want to add point features to the middle of the circles. I could do it manually, but I ...
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180
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Extract values from rasterstack TIFF for point data locations in Python
I am working on machine learning algorithms for predicting wildfire sites on state level. I have a CSV of wildfire instances, that has 37 columns including a geometry column, a lat column and a lon ...
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How to programmatically identify landmarks (cemeteries) in Google Maps satellite data?
I'm searching Google Maps satellite view for cemeteries that are not listed in common repositories of cemeteries. I've spent a lot of time cruising around satellite mode searching for small ...
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1
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77
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Extracting only part of supervised output model in Raster format
I have a svm predicted model which when applied on raster images classifies the LULC of land and writes the output to raster file. I want to use only the Land used part out of the output raster image. ...
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2
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72
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How were walkways found and added to Google Maps or OSM?
Does Google Maps or OSM use any deep learning or machine learning model to extract walkways from satellite images? Examples of walkways are the green lines in the picture here. I wonder how they were ...
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53
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Preparing training data for crop species classification from drone images
I have high resolution multispectral (R,G,B,NIR,RE bands) images of a field taken from MicaSense RedEdge mounted on a drone. There are various species of crops planted. I want to classify the crops or ...
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4
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949
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Performing supervised classification on Sentinel images
I'm looking for python code which predicts the LULC of my data(other raster files apart from refernce data band1, band2 and soon) using svm classifier with rbf kernel based on reference data (truth ...
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1
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179
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Google Earth Engine: get data ready for ML export
I need to export data from GEE to get processed in MATLAB. I want to export CSV files of a region, aggregating meteo data ( CAMS, ERA5, MODIS AOT) with sentinel-2 images. These images have already ...
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20
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Where to find open tabular hyperspectral data for machine learning research?
Where can i find open datasets regarding " Wheat/Maize Leaf Spectra with Associated water content, Potassium and Nitrogen Measurements" for machine learning research i.e. hyperspectral ...
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1
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74
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Same confusion matrix depiste hyperparameter tuning using TrainImageClassifier in OTB
I am trying to run a land use land cover classification using TrainImageClassifier in OTB. Here are the settings I used :
The problem is that no matter how much I tweak the hyperparameters of any of ...
- 361
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76
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Classified image using RF method in R displays less no. of classes than it was trained to
I am trying to classify crops using Sentinel-2 image including 10 classes, using randomForest classification in R. For that, I extracted 2000 random samples points from the training areas for 11 bands ...
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SMILE classifiers/regressors in Earth Engine
I am working on a project intended for publication that leans heavily on Earth Engine for much of the workflow: assembling, compositing, and mosaicking lots of images from multiple data sources, ...
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58
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Eliminating end points automatically
In QGIS 3.10 I have a point file and I decided a colors palettes for it.
Let's say this palette is composed by 11 colours steps, from blue to red and its intermediates.
So, I would like to ...
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21
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Are there Sentinel crop labeled datasets available?
I am starting a project where I am going to use Sentinel-2 imagery and machine learning for detecting sugarcane and coffee. In order to train the algorithm I would need labeled sentinel datasets. I've ...
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51
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Highly Imbalanced dataset
I have a dataset (vector data) that contains the polygons and their corresponding crop type. This data is highly imbalanced i.e, I have a lot of classes that contain one sample only, as shown in the ...
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54
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Spike and crater detection in DSM using machine learning / deep learning / computer vision techniques
I'd like to try machine learning / computer vision / deep learning approaches for detecting artifacts in Digital Surface Models, and am specifically interested in doing this for common artifacts like ...
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Ground Truth Data for India [closed]
I'm starting to get involved in a humanitarian project to understand crop-type and crop-yield in India to identify areas where they may be food shortages.
The current approach for this project is to ...
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How to relate flood events (points) with flood conditioning rasters for Machine Learning?
I have point shapefile of flood events which has either flood occur or not.
On the other hand, I have 13 flood conditioning rasters i.e. slope, elevation, rainfall etc. these are all at 30 meter ...
3
votes
1
answer
980
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Google Earth Engine: Evaluate classifier of output type regression
Background
According to the Google Earth Engine documentation for supervised classification, the accuracy assessment of classifiers such as ee.Classifier.smileRandomForest can be done using a ...
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1
answer
242
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Predicting the whole image through trained classifier and visualize it as classified landuse and landcover image(LULC)
I am working on LULC classification of Sentinel-2 image(4-bands) using Machine Learning algorithms. I split the whole image into 64*64 patches and assigned class label (builtup, barren land, water and ...
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KeyError: 'BANDS' and NameError: 'bands'
I am trying to follow this tutorial: land cover fastai
And while executing the workflow, I got this error:
eopatch 0 has been processed!
---------------------------------------------------------------...
- 361
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1
answer
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ValueError: too many values to unpack (expected 2)
I am trying to follow this tutorial: land cover fastai
And while executing the workflow, I got this error:
This is the code where the error occurs:
def png_gen(patch, inference=False):
"""Save ...
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2
votes
2
answers
1k
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Pre-trained transfer learning models for satellite image classification
I am currently working on a project that tackles crop type classification using machine learning and deep learning. Given the limited amount of satellite data that I have, transfer learning sounds ...
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1
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81
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Using 3rd party PASCAL_VOC in arcgis.learn prepare_data() method
Has anyone had luck using the prepare_data method with data not exported from the Export Training Data tool in ArcGIS Pro? The documentation suggests prepare_data will take PASCAL_VOC_rectangles from ...
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Visualizing specific class from unsupervised classification in Earth Engine
I have classified an image into 20 classes using unsupervised classification for a specific region in Google Earth Engine. I want to check a specific class (say class 9) and visualize only that ...
3
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0
answers
3k
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Encoding categorical variable for random forest with sklearn
I have a random forest model that works pretty well, taking a bunch of vanilla remote sensing raster data as input. I think it could be improved with addition of some information that I currently have ...
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0
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76
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Using computer vision for linear feature detection [closed]
I am considering to use CV methods to detect linear features in very high resolution imagery (i've added an example below). These linear features are made by animals which transverse this section of ...
9
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2
answers
8k
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Moving from Earth Engine image to array for use in sklearn
I've produced a very large multiband image in EE with the goal of classifying it using the classifiers implemented in sklearn (the native ones implemented in EE don't provide enough flexibility for my ...
- 464
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3
answers
3k
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Identify spatially contiguous clusters in raster data using kmeans
I would like to cluster the cells of a raster object into k contiguous regions using kmeans. The number of regions, k, is known. Each cell has various geographical attributes, such as temperature, ...
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0
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54
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Creating square grid polygons from shapefile using ArcGIS Desktop and machine learning to predict wildfires [closed]
I'm currently working on a data science project where I would like to predict the probability of a wildfire in Washington state for a given location using machine learning.
I have latitude/longitude ...
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2
votes
1
answer
117
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Applying machine learning methods in orfeo toolbox into DEM raster
I would like to apply machine learning methods in orfeo toolbox to classify some landscape features such as shrub and coarse woody debris in woodland. I created DEM raster image from very dense ground ...
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1
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199
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Practical limitations of image classification of large rasters?
Been attempting (with no success so far) to implement the random forest classification in ArcMap on a reasonably large image. If I throw a raster with say 20-30 bands in it, works fine, just takes ...
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