Synthetic aperture radar imagery of airports and surrounding areas: Study of clutter at grazing angles and their polarimetric properties

The statistical description of ground clutter at an airport and in the surrounding area is addressed. These data are being utilized in a program to detect microbursts. Synthetic aperture radar data were collected at the Denver Stapleton Airport. Mountain terrain data were examined to determine if they may potentially contribute to range ambiguity problems and degrade microburst detection. Results suggest that mountain clutter may not present a special problem source. The examination of clutter at small grazing angles was continued by examining data collected at especially low altitudes. Cultural objects such as buildings produce strong sources of backscatter at angles of about 85 deg, with responses of 30 dB to 60 dB above the background. Otherwise there are a few sources which produce significant scatter. The polarization properties of hydrospheres and clutter were examined with the intent of determining the optimum polarization. This polarization was determined to be dependent upon the ratio of VV and HH polarizations of both rain and ground clutter

ARKTOS: An intelligent system for SAR sea ice image classification

©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.We present an intelligent system for satellite sea ice image analysis named Advanced Reasoning using Knowledge for T ping Of Sea ice (ARKTOS). ARKTOS performs fully automated analysis of synthetic aperture radar (SAR) sea ice images by mimicking the reasoning process of sea ice experts. ARKTOS automatically segments a SAR image of sea ice, generates descriptors for the segments of the image, and then uses expert system rules to classify these sea ice features. ARKTOS also utilizes multisource data fusion to improve classification and performs belief handling using Dempster-Shafer. As a software package, ARKTOS comprises components in image processing, rule-based classification, multisource data fusion, and graphical user interface-based knowledge engineering and modification. As a research project over the past ten years, ARKTOS has undergone phases such as knowledge acquisition, prototyping, refinement, evaluation, deployment, and operationalization at the U.S. National Ice Center. In this paper, we focus on the methodology, evaluations, and classification results of ARKTOS

ARKTOS: An Intelligent System for SAR Sea Ice Image Classification

We present an intelligent system for satellite sea ice image analysis named Advanced Reasoning using Knowledge for Typing Of Sea ice (ARKTOS). ARKTOS performs fully automated analysis of synthetic aperture radar (SAR) sea ice images by mimicking the reasoning process of sea ice experts. ARKTOS automatically segments a SAR image of sea ice, generates descriptors for the segments of the image, and then uses expert system rules to classify these sea ice features. ARKTOS also utilizes multisource data fusion to improve classification and performs belief handling using Dempster–Shafer. As a software package, ARKTOS comprises components in image processing, rule-based classification, multisource data fusion, and graphical user interface-based knowledge engineering and modification. As a research project over the past ten years, ARKTOS has undergone phases such as knowledge acquisition, prototyping, refinement, evaluation, deployment, and operationalization at the U.S. National Ice Center. In this paper, we focus on the methodology, evaluations, and classification results of ARKTOS

Synthetic Aperture Radar Imagery of Airports and Surrounding Areas: Denver Stapleton International Airport

This is the third in a series of three reports which address the statistical description of ground clutter at an airport and in the surrounding area. These data are being utilized in a program to detect microbursts. Synthetic aperture radar (SAR) data were collected at the Denver Stapleton Airport using a set of parameters which closely match those which are anticipated to be utilized by an aircraft on approach to an airport. These data and the results of the clutter study are described. Scenes of 13 x 10 km were imaged at 9.38 GHz and HH-, VV-, and HV-polarizations, and contain airport grounds and facilities (up to 14 percent), cultural areas (more than 50 percent), and rural areas (up to 6 percent). Incidence angles range from 40 to 84 deg. At the largest depression angles the distributed targets, such as forest, fields, water, and residential, rarely had mean scattering coefficients greater than -10 dB. From 30 to 80 percent of an image had scattering coefficients less than -20 dB. About 1 to 10 percent of the scattering coefficients exceeded 0 dB, and from 0 to 1 percent above 10 dB. In examining the average backscatter coefficients at large angles, the clutter types cluster according to the following groups: (1) terminals (-3 dB), (2) city and industrial (-7 dB), (3) warehouse (-10 dB), (4) urban and residential (-14 dB), and (5) grass (-24 dB)

Transition from Research to Operations: ARKTOS - A Knowledge-Based Sea Ice Classification System

ARKTOS is a fully automated intelligent system that classifies sea ice and that is now being used by the U.S. National Ice Center (NIC) for daily operations related to the NIC’s task of mapping the ice covered oceans. In this paper we describe the process of taking a research project and transitioning it to an operational environment. We discuss the theoretical methodologies implemented in ARKTOS, and how ARKTOS was developed, tested, and finally moved to operations

Operational Evaluation of a Knowledge-Based Sea Ice Classification System

ARKTOS (Advanced Reasoning Using Knowledge for Typing of Sea Ice) is a fully automated intelligent sea ice classification system. ARKTOS is in use at the U.S. National Ice Center (NIC) for daily operations related to the NIC’S task of mapping the ice covered oceans. ARKTOS incorporates image processing, input from ancillary data, and artificial intelligence (AI) to analyze and classify RADARSAT Synthetic Aperture Radar (SAR) imagery. The NIC and Naval Research Laboratory (NRL/ERIM) have been testing and evaluating ARKTOS through the freeze-up, winter, melt-out and summer seasons of the Beaufort Sea. In this paper we outline the development and evolution of ARKTOS, evaluate current output, and discuss future implementation