Geospatial intelligence

Abstract: An enterprise geospatial intelligence service oriented architecture (EGI-SOA) provides a consumer with one or more tailored products in response to either a dynamic request or a standing request by the consumer.

Abstract: This paper describes a distributed system for agricultural monitoring in Ukraine at two levels, namely, at ministerial level and at agricultural enterprise level. Crop monitoring is performed using data and products obtained by moderate and high-resolution remote sensing satellites. The system includes a geoportal with a Web interface and a desktop geographic information system (GIS) with additional functions of automatic data retrieval and business-logic analysis. The system is constructed using open-source software that conforms to OGC standards for geospatial information management.

Abstract: Spatial information plays a fundamental role in building high-level content models for supporting analysts' interpretations and automating geospatial intelligence. We describe a framework for modeling directional spatial relationships among objects and using this information for contextual classification and retrieval. The proposed model first identifies image areas that have a high degree of satisfaction of a spatial relation with respect to several reference objects. Then, this information is incorporated into the Bayesian decision rule as spatial priors for contextual classification. The model also supports dynamic queries by using directional relationships as spatial constraints to enable object detection based on the properties of individual objects as well as their spatial relationships to other objects. Comparative experiments using high-resolution satellite imagery illustrate the flexibility and effectiveness of the proposed framework in image mining with significant improvements in both classification and retrieval performance.

Abstract: For centuries, humans’ capacity to capture and depict physical space has played a central role in industrial and societal development. However, the digital revolution and the emergence of networked devices and services accelerate geospatial capture, coordination, and intelligence in unprecedented ways. Underlying the digital transformation of industry and society is the fusion of the physical and digital worlds – ‘perceptality’ – where geospatial perception and reality merge. This paper analyzes the myriad forces that are driving perceptality and the future of geospatial intelligence and presents real-world implications and examples of its industrial application. Applications of sensors, robotics, cameras, machine learning, encryption, cloud computing and other software, and hardware intelligence are converging, enabling new ways for organizations and their equipment to perceive and capture reality. Meanwhile, demands for performance, reliability, and security are pushing compute ‘to the edge’ whe...