Satellite Image Analysis
Definition
Satellite image analysis transforms raw images into interpretable information using detection, classification, segmentation, and time series methods. The process starts with sensor calibration and orthorectification, then feature extraction such as indices, textures, and object measures. Analysts apply algorithms from classical remote sensing and modern deep learning to map land cover, detect change, estimate biophysical variables, and measure human activities like new construction. Good practice uses representative training data, cross validation, and clear documentation of limitations.
Application
Governments use analysis for land use regulation, agriculture subsidies, and forest monitoring. Humanitarian teams map displacement and damage after disasters. Insurers and investors assess risk exposure and compliance. Environmental scientists study glaciers, lakes, and biodiversity. Because images are frequent and consistent, they reveal trends that are hard to capture with field surveys alone.
FAQ
How do you choose between pixel based and object based approaches?
Pixel methods are fast and work well when classes differ spectrally at the sensor resolution. Object based analysis segments images into meaningful patches and uses shape, texture, and context, which helps in urban scenes and high resolution data. A hybrid often performs best, using objects for context and pixels for spectral detail.
What is the role of transfer learning in satellite analysis?
Pretrained convolutional networks bring general spatial features that reduce training data needs. Fine tuning on local labeled data adapts the model to regional materials and lighting. It is crucial to check for domain shift when applying models to new sensors or climates.
How can analysts avoid spurious change detection from seasonal cycles or view angle?
Normalize for sun angle, use surface reflectance, compare like seasons, and include angular metadata. Time series models that look for persistent shifts work better than simple two date differencing. Quality masks that remove cloud and shadow are fundamental.
What ethical concerns should guide satellite analysis of human activity?
Protect privacy by avoiding unnecessary detail on individuals, respect sensitive sites, and be transparent about uncertainty. Work with affected communities and use imagery to improve services and safety, not to target or discriminate. Follow licensing rules and credit data sources appropriately.