R.M. Schoemaker

The inter-comparison of AATSR dual-view aerosol optical thickness retrievals with results from various algorithms and instruments

The Advanced Along-Track Scanning Radiometer (AATSR) dual-view (ATSR-DV) aerosol retrieval algorithm is evaluated for a single scene over Germany (49–53˚ N, 7–12˚ E) on 13 October 2005 by comparison of the aerosol optical thickness (AOT) at 550 nm with products from Multiangle Imaging SpectroRadiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Medium Resolution Imaging Spectrometer (MERIS), in addition to the Atmospheric Aerosol Retrieval using Dual-View Angle Reflectance Channels (AARDVARC) algorithm developed at Swansea University. The AOT was retrieved from the AATSR using the ATSR-DV algorithm, for the pixel size of 1 km × 1 km (at nadir). Then these values were meshed to be consistent with the sampling of the products from the other satellite instruments. The ATSR-DV results compare favourably with the products from orbiting optical instruments dedicated to aerosol retrieval, such as MODIS and MISR, which leads to the conclusion that AATSR is well suited for aerosol retrieval over land when the dual view is used with the ATSR-DV algorithm.

Segmentation and wake removal of seafaring vessels in optical satellite images

This paper aims at the segmentation of seafaring vessels in optical satellite images, which allows an accurate length estimation. In maritime situation awareness, vessel length is an important parameter to classify a vessel. The proposed segmentation system consists of robust foreground-background separation, wake detection and ship-wake separation, simultaneous position and profile clustering and a special module for small vessel segmentation. We compared our system with a baseline implementation on 53 vessels that were observed with GeoEye-1. The results show that the relative L1 error in the length estimation is reduced from 3.9 to 0.5, which is an improvement of 87%. We learned that the wake removal is an important element for the accurate segmentation and length estimation of ships.

Characterisation of small targets in a maritime environment by means of laser range profiling

Potential asymmetric threats at short range in complex environments need to be identified quickly during coastal operations. Laser range profiling is a technology that has the potential to shorten the OODA loop (Orient, Observe, Detect, Act) by performing automatic characterisation of targets at large distance. The advantages of non-cooperative target recognition with range profiles are: (a) a relatively short time on target is required, (b) the detection range is longer than in the case of passive observation technologies such as IRST, and (c) characterisation of range profiles is possible at any aspect angle. However, the shape of a range profile depends strongly on aspect angle. This means that a large data set is necessary of all expected targets with reference profiles on a very dense aspect angle grid. Analysis of laser range profiles can be done by comparing the measured profile with a database of laser range profiles obtained from 3D models of possible targets. An alternative is the use of a profile database from one or several measurement campaigns. A prerequisite for this is the availability of enough measured profiles of the appropriate targets, for many aspect angles. Comparison of measured laser range profiles with a reference database can be performed using, e.g., formal statistical correlation techniques or histogram dissimilarity techniques. In this work, a field trial has been conducted to validate the concept of identification by using a laser range profiling system with a high bandwidth receiver and short laser pulses. The field trial aimed at characterization of sea-surface targets in a coastal/harbour environment. The targets ranged from pleasure boats like sailing boats, jet skis, and speed boats to professional vessels like barges, cabin boats, and military vessels, all ranging from 3 to 30 meters in length. We focus on (a) the use of a reference database generated via 3D target models, and (b) the use of a reference database of measured laser range profiles. A variety of histogram dissimilarity measures was examined in order to enable fast and reliable classification algorithms.

Identification of air and sea-surface targets with a laser range profiler

Current coastal operations have to deal with threats at short range in complex environments with both neutral and hostile targets. There is a need for fast identification, which is possible with a laser range profiler. A number of field trials have been conducted to validate the concept of identification with a laser range profile. A laser range profiler with a high bandwidth, fast laser receiver was used to perform tests on the capability of a laser range profiler for ship identification. Typical rise and fall times are 2 ns corresponding to a range resolution of 0.6 meter. The experimental profiles of the ships and simulated range profiles based on 3D target models show very good correspondence. It is shown that laser range profiles match closely the geometric structure of the ship. Furthermore, the good match between experimental and simulated laser range profiles means that a database of laser range signatures can be constructed from 3D-models, thus simplifying the database creation. Based on the experiments a system model was made for the range profiling of air targets. The validated system model shows that air targets can be identified at ranges of several tens of kilometers. An identification algorithm was used to distinguish three aircraft from their simulated range profile with good results.

Evaluation Tools for the Effectiveness of Infrared Countermeasures and Signature Reduction for Ships

The protection of ships against infrared guided missiles is a concern for modern naval forces. The vulnerability of ships can be reduced by applying countermeasures such as infrared decoys and infrared signature reduction. This paper will present a set of simulation tools which can be used for assessing the effectiveness of these measures. The toolset consists of a chain of models which calculate the infrared signature of a ship (EOSM), generate an infrared image of the ship in a realistic sea and sky background (EOSTAR) and determine the behaviour of an infrared missile seeker against these images and simulate the complete missile fly-out including countermeasure deployment (EWM). All model components will be briefly discussed. Typical simulation runs will be shown.

Construction of Satellite Derived PM2.5 Maps using the Relationship between AOD and PM2.5 at the Cabauw Experimental Site for Atmospheric Research (CESAR) - The Netherlands

To acquire daily estimates of PM2.5 distributions based on satellite data one depends critically on a well established relation between AOD and ground level PM2.5. In this study we aimed to experimentally establish the AOD-PM2.5 relationship for the Netherlands. For that purpose an experiment was set-up at the AERONET site Cabauw. The average PM2.5 concentration during this ten month study was 18 mug/ m3, which confirms that the Netherlands are characterized by a high PM burden. A first inspection of the AERONET level 1.5 (L1.5) AOD and PM2.5 data at Cabauw showed a low correlation between the two properties. However, after screening for cloud contamination in the AERONET L1.5 data, the correlation improved substantially. When also constraining the dataset to data points acquired around noon, the correlation between AOD and PM2.5 amounted to R 2 =0.6 for situations with fair weather. This indicates that AOD data contain information about the temporal evolution of PM2.5. We used lidar observations to detect residual cloud contamination in the AERONET L1.5 data. Comparison of our cloud-screed L1.5 with AERONET L2 data that became available near the end of the study showed favorable agreement. The final relation found for Cabauw is PM2.5 = 124.5* AOD - 0.34 (with PM2.5 in mug/m3) and is valid for fair weather conditions. The relationship determined between MODIS AOD and ground level PM2.5 at Cabauw is very similar to that based on the much larger dataset from the sun photometer data, after correcting for a systematic overestimation of the MODIS data of 0.05. We applied the relationship to a MODIS composite map to assess the PM2.5 distribution over the Netherlands for the first time based on MODIS data only.

Combining ANAM with satellite data to determine the EOSTAR aerosol component

The detection of targets at low levels above the sea surface by electro-optical (EO) sensors is affected by the atmosphere. Models have been developed to describe the electro-optical propagation in the marine atmospheric surface layer as a function of meteorological parameters. EOSTAR is an end-to-end model suite for EO sensor performance in which the Advanced Navy Aerosol Model (ANAM) is embedded for computing the aerosol extinction. While ANAM provides favorable results in open ocean conditions where the aerosols predominantly consist of sea salt particles, the model lacks accuracy in coastal zones due to the presence of aerosols from a variety of other sources. In offshore wind conditions continental aerosols of anthropogenic and natural origin mix with marine aerosols produced in the surf zone and by wave breaking further offshore. In principle, ANAM can be extended with the various aerosol types that may occur in the coastal zone, but to correctly handle their effect on EO propagation, information is required on the actual aerosol mixture over the range of interest. In this contribution we explore the potential of satellite instruments to provide this information. Radiometers on satellites can be used to retrieve the spatial variation over an extended area determined by the swath width, with a resolution determined by the radiometer pixel size. Input into this retrieval is a model describing the aerosol mixture in varying ratio, e.g. a mixture of continental and marine aerosol. While the marine component can be constrained by ANAM using local meteorological input parameters, the continental component can be retrieved and used as input to determine the fine particle distribution in ANAM.

Land Border Permeability and Irregular Migration Using Geospatial Intelligence from Satellite Data

Prediction about how migrants move in the pre-border terrain is important for effective border control. In this paper we present a method to obtain permeability indicators for accessibility and concealment on the basis of geographical terrain features, derived from high resolution satellite data. The indicators are used to estimate the mobility of migrants. A modelto predict the density of migrants arriving at the border, and to assess the impact of security measures, is introduced and discussed. The model was implemented and tested. The results are used as value adding products in pre-operational services for border control. Validation has to be done using actual irregular border-crossing geo-oriented statistics. By the time this paper was written no such statistics were available.

Unattended Monitoring of Suspicious Behaviour for Route Surveillance

A priori information on suspicious behaviour is extremely valuable for countering threats involving improvised explosive devices (IEDs). Suspicious activities along routes during expeditionary operations can be monitored by unattended networks using simple sensing nodes that can gather data for continuous monitoring of daily vehicle activity. Dedicated software yields the necessary intelligence on these activities by filtering suspicious behaviour from anomalous behaviour (including false alarms). Research has started to equip a commercially available sensor network with data analysis software. It aims at demonstrating the detection of suspicious behaviour along roads, within a required time span. Three phases are distinguished. First phase is the analysis of traffic flux in a simple scenario with three networks lying at three junctions. The second phase investigates the ability to track and classify one object in this scenario, while the third phase aims to track and classify two or more objects. Findings are presented for phase one, flux measurements.A priori information on suspicious behaviour is extremely valuable for countering threats involving improvised explosive devices (IEDs). Suspicious activities along routes during expeditionary operations can be monitored by unattended networks using simple sensing nodes that can gather data for continuous monitoring of daily vehicle activity. Dedicated software yields the necessary intelligence on these activities by filtering suspicious behaviour from anomalous behaviour (including false alarms). Research has started to equip a commercially available sensor network with data analysis software. It aims at demonstrating the detection of suspicious behaviour along roads, within a required time span. Three phases are distinguished. First phase is the analysis of traffic flux in a simple scenario with three networks lying at three junctions. The second phase investigates the ability to track and classify one object in this scenario, while the third phase aims to track and classify two or more objects. Findings are presented for phase one, flux measurements.

Intelligent route surveillance

Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent ground sensor networks use simple sensing nodes, e.g. seismic, magnetic, radar, or acoustic, or combinations of these in one housing. The nodes deliver rudimentary data at any time to be processed with software that filters out the required information. At TNO (Netherlands Organisation for Applied Scientific Research) research has started on how to equip a sensor network with data analysis software to determine whether behaviour is suspicious or not. Furthermore, the nodes should be expendable, if necessary, and be small in size such that they are hard to detect by adversaries. The network should be self-configuring and self-sustaining and should be reliable, efficient, and effective during operational tasks - especially route surveillance - as well as robust in time and space. If data from these networks are combined with data from other remote sensing devices (e.g. UAVs (Unmanned Aerial Vehicles)/aerostats), an even more accurate assessment of the tactical situation is possible. This paper shall focus on the concepts of operation towards a working intelligent route surveillance (IRS) research demonstrator network for monitoring suspicious behaviour in IED sensitive domains.