PIE (Pixel Information Expert)

flagship software

product of PIESAT for remote sensing image and data processing.


Remote sensing computing cloud service platform

PIE-Engine remote sensing computing cloud service platform is based on remote sensing technologies (cloud computing, IoT, bid data, AI, etc.) and cloud computing infrastructure, to carry out standardized integration and operation on multiple industrial applications. The platform covers the whole data processing process of “collection, storage, calculation, management and application” of spatial-temporal data, providing one-stop “cloud + local” services. It provides online multi-source remote sensing satellite image data production, processing, intelligent interpretation, analysis, as well as industry-oriented SaaS application services, so as to maximize the value of massive remote sensing data, and promotes the industrialization of remote sensing applications.

Features of PIE-Engine

  • Data service: PIE-Engine provides data management and data retrieval functions. Users can search for the collection of the public data system, private data uploaded during history, location information, etc.
  • Data processing: Through independent writing of script codes, users can use cloud computing resource to process distributed real-time calculations to realize the processing, analysis and application of remote sensing data.
  • Vector editing: Users can draw vector graphics on the map layer for coding, machine learning model training and results editing.
  • General functions: Provides user management, authorization authentication, security prevention and control, code confusion, network protection and other functions.
  • Data visualization: The user can determine the style of displaying by controlling the configuration information of the display layer.
  • Code management: Users can create private scripts independently, and can process functions such as modification, deletion, editing, and version management.

Calculation results of national vegetation index based on Landsat-8

Analysis results of vegetation growth variation in Jinzhou in 2017

Urbanization progress of Beijing from 1985 to 2017

Analysis results of water body change of Chaohu Lake from 2017 to 2019

Real-time land classification results based on AI algorithm