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KNIME-GEE--Image-Classification

1 Read Image

2 Read Labeled Points

Chapter 6 Image Manipulation-Classification/Clustering

Cloud-Based Remote Sensing with Google Earth Engine: Fundamentals and Applications 2024
https://link.springer.com/book/10.1007/978-3-031-26588-4

KNIME workflow by

Lingbo Liu, Harvard Center for Geographic Analysis

3 Bands Sampling for Labeled Points

5 Unsupervised Clustering

4 Supervised Classification

Local to Cloud
Local to Cloud

6 Visualization

Google Authenticator
Google Earth Engine Connector
POINT (9.453 45.424)
Table Creator (deprecated)
LANDSAT/LC08/C02/T1_L2
Image Collection Reader
Image Collection Spatial Filter
GeoTable to Feature Collection
Fig. 6.15 K-means classification
GEE Image View
Image Class Predictor
K-Means Clustering Learner
GEE CART Learner
Apply Clustering
Label Points
CSV Reader
Feature Collection Partitioner
Reference Feature Collection Sampler
Image Random Sampling
Image Collection Aggregator
2019-01-01 ~ 2020-01-01Sort ascending by CLOUD_COVER
Image Collection General Filter
Column Filter
Fig. 6.11 CART classification
GEE Image View
GeoTable to Feature Collection
GeoJSON to Geometry
Fig. 6.2 Landsat image
GEE Image View
Image Class Predictor
Fig. 6.13 Random forest classified image
GEE Image View
GEE Random Forest Learner

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: lil928
Created at: 2025-12-05
On NodePit since: 2026-03-04
Last update: 2026-03-04
Created with KNIME version: v5.12.0 nightly

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