Geomaticape Tools
Plugin ID: 4755
Landsat C2 L1/L2, Sentinel-2, CBERS-04A, MODIS 09/11/12/13 scale factor per product independently, PCA, spectral indices, supervised + unsupervised classification, band extraction, vector geoprocessing, zonal statistics and multi-point sampling
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GeomaticaPE is a QGIS plugin developed by Geomatica Ambiental to automate
preprocessing and analysis of multispectral satellite imagery and to
support common geoprocessing tasks.
Tools organized into three groups:
[Conversion]
- RS Landsat C2 L1 (SR + LST + PAN, autodetects MSS/TM/ETM/OLI)
- Landsat C2 L2 scale factor
- Sentinel-2 L1A scale factor
- Sentinel-2 L2A scale factor
[Processing]
- CBERS-04A Pansharpening Brovey 2m
- Landsat Pansharpening 30m -> 15m (Weighted Brovey)
- Multispectral PCA
- Spectral indices (17 indices)
- Extract bands from multispectral images:
detects number of bands
- Clip raster by study area:
- Combine bands with names
- Supervised classification and validation (DT/RF/NB/MLP/KNN).
[Geoprocessing]
- Create polygons from table (CSV/TXT/XLS/XLSX)
- Raster zonal statistics (Excel/CSV)
- Extract point values from multiple rasters
COMPATIBILITY:
- Qt5 (PyQt5) and Qt6 (PyQt6) via qgis.PyQt compatibility layer
- QGIS 3.40 to 4.99
REQUIREMENTS - Python modules bundled with QGIS (no installation needed):
- numpy (all tools)
- GDAL / osgeo (all tools)
- matplotlib (QGIS LTR 3.22+; supervised_classification, pca_satellite)
REQUIREMENTS - External modules NOT bundled with QGIS (must install):
- scikit-learn REQUIRED by: Unsupervised Classification (KMeans,
MiniBatchKMeans, GaussianMixture, Birch, StandardScaler),
Supervised Classification (DecisionTree, RandomForest,
NaiveBayes, MLP, KNN, train_test_split, classification_report),
Multispectral PCA (PCA, StandardScaler, make_pipeline)
- pandas REQUIRED by: Multispectral PCA (variance table),
Create Polygons from Table (read CSV/TXT/XLS/XLSX)
- openpyxl REQUIRED by: Raster Zonal Statistics (export .xlsx),
Extract Point Values (export .xlsx),
Classification Report (export .xlsx with charts),
Create Polygons from Table (read .xlsx)
Install all external dependencies (run once):
python -m pip install --upgrade scikit-learn pandas openpyxl
Developed and maintained by:
Geomatica Ambiental - www.geomatica.pe
Acknowledgments:
- Point Sampling Tool by Borys Jurgiel (GPL v2+) - inspiration for the
multi-raster point sampling tool. https://github.com/borysiasty/pointsamplingtool
vector
raster
landsat
polygon
confusion matrix
remote sensing
csv
pca
bbox
dos1
supervised classification
sentinel
kappa
xlsx
knn
svm
random forest
gmm
ndvi
lst
mlp
cbers
birch
multiband
zonal statistics
cross validation
kmeans
point sampling
isodata
band stacking
decision tree
clipping
lda
qda
pansharpening
spectral indices
etm
tirs
c2 l1
mss
tm
c2 l2
oli
surface reflectance
balanced accuracy
band combination
logistic regression
naive bayes
cutline
study area
gradient boosting
extra trees
weighted brovey
vrt pansharpened
band extraction
clip raster
brovey
f1
