Αποτελέσματα Αναζήτησης
The Classifier package handles supervised classification by traditional ML algorithms running in Earth Engine. These classifiers include CART, RandomForest, NaiveBayes and SVM. The general...
20 Ιουν 2024 · This guide has walked you through the process of land cover classification using Google Earth Engine and Python. By retrieving and preprocessing satellite imagery, applying cloud masking, calculating NDVI, preparing training data, and using k-means clustering, we’ve classified land cover types in both New York and San Francisco.
11 Ιουλ 2023 · This tutorial will guide you through the process of performing supervised land cover classification using Google Earth Engine (GEE) and JavaScript. We will use a k-means clustering...
Describe how spectral space or data space are used in multivariate classification. Apply and compare three commonly-used classification algorithms. Assess possible sources of error in the classification process arising from pre-processing, sensor choice, and training sample design.
7 Μαρ 2021 · Objectives: 1. To classify Landsat 8 data into major land use and land cover classes using Random Forest Classifier, 2. To classify the Sentinel — 1C data into major land use and...
27 Μαΐ 2022 · I'm trying to do a land cover classification using Landsat-8 OLI/TIRS. However, I want to involve indexes (SAVI, and EVI) in this classification process. I don't know how to solve this problem.
3 Αυγ 2022 · In this section we explore the overall approach of image classification using real life and real location examples: from the pre-classification steps of preparing the imagery to post-classification procedures to enhance your classification outputs.
