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Earth Observation Data Processing

Definition

Earth Observation Data Processing involves the handling, analysis, and transformation of remotely sensed data collected by satellites, aircraft, or drones. This includes preprocessing steps like geometric correction, atmospheric correction, and radiometric calibration, as well as post-processing such as classification, change detection, and feature extraction.

Application

Analysts process Earth observation data to map land cover, monitor agriculture, track deforestation, or model climate effects. Tools like Google Earth Engine, SNAP, and ArcGIS Pro allow cloud-based and desktop processing. Processing pipelines convert raw satellite images into georeferenced, analysis-ready data for time series evaluation and spatial modeling.

FAQ

1. What types of data are processed?

Satellite imagery (e.g., Landsat, Sentinel), aerial photos, LiDAR, and multispectral or SAR datasets.

2. What types of data are processed?

To correct distortions, normalize brightness, and align imagery for reliable analysis.

3. What types of data are processed?

Google Earth Engine, ESA SNAP, ENVI, QGIS, ArcGIS Pro, and ERDAS IMAGINE.

4. What types of data are processed?

Remote sensing specialists, climate researchers, environmental NGOs, and urban analysts.