Project overview

Space and airborne Mined Area Reduction Tools
May 2001- October 2004


New: A summary of the evaluation of the project by blind tests is available here.

Contents
SMART is a three-year project co-funded by the European Commission (Contract No IST-2000-25044).

This presentation of the project consists of the following:

 
Context
Millions of mines are infesting over seventy countries on all continents. They still maim or kill decades after they were laid. They have enormous and long-term effects on a country: they maim the young generations; they reduce the farming capabilities; they disorganize the transportation system; they slow down the reconstruction of power lines and waterways; they prevent the use of some drinkable water points, causing the appearance or re-appearance of diseases and making the health care system overburdened; they force budget to be dedicated to demining programmes instead of public health, education or infrastructure restoration. The whole industrial, economical and social life of a country can be disrupted by a mine infection.

Demining is a very dangerous and time-consuming activity. At the present speed, clearing all the known mined areas would take decades, even if no additional mine is laid. To face the problem of mine infection, a Convention on the Prohibition of the Use, Production, Transfer and Stockpiling of Anti-Personnel Landmines and on Their Destruction has been signed at Ottawa (Canada) in December 1997. Moreover many organizations are helping regularly the victims of mine injuries all over the world. Finally, many researchers are trying to use new technologies in order to improve mine clearance.

Three levels of survey of a country are usually defined:

  • Level One: General survey
    • to collect information on the general locations of suspected or mined areas.  Information must be collected about the areas affected by mines or UXO and areas that are not affected.  Areas must be categorised and the reliability and credibility of data recorded.  A Level One: General Survey is a prerequisite for the planning of a Level Two: Technical Survey.  The content and level of detail will vary according to the level of survey undertaken.
  • Level Two: Technical Survey
    • to determine and delineate the perimeter of mined locations initially identified by a Level One: General Survey.  The marked perimeter forms the area for future mine clearance operations.  The Level Two survey requires trained and properly equipped mine clearance personnel with the necessary skills to undertake and accurately record the survey work.  Where possible, with time and resources permitting, these teams should also undertake area reduction work in order to accurately define the outer perimeters of the minefield.
  • Level Three: Completion Survey
    •  The Level Three: Completion Survey is conducted in conjunction with the mine clearance teams and accurately records the area cleared.  The benchmark is to be left in the ground to serve as a minimum marker of the initial minefield area.  It is also recommended that permanent markers be used to indicate turning and intermediate points of the perimeter of the mined area. 
The relevant definitions from IMAS are:
  • General Mine Action Assessment
    • the process by which a comprehensive inventory can be obtained of all reported and/or suspected locations of mine or UXO contamination, the quantities and types of explosive hazards, and information on local soil characteristics, vegetation and climate; and assessment of the scale and impact of the landmine problem on the individual, community and country.
  • Area Reduction
    • the process through which the initial area indicated as contaminated (during the general mine action assessment process) is reduced to a smaller area.
      Note: Area reduction may involve some limited clearance, such as the opening of access routes and the destruction of mines and UXO which represent an immediate and unacceptable risk, but it will mainly be as a consequence of collecting more reliable information on the extent of the hazardous area. Usually it will be appropriate to mark the remaining hazardous area(s) with permanent or temporary marking systems.
      Note: Likewise, area reduction is sometimes done as part of the clearance operation.
  • Technical Survey
    • the detailed topographical and technical investigation of known or suspected mined areas identified during the planning phase. Such areas may have been identified during the general mine action assessment or have been otherwise reported (previously referred to as a Level 2 survey).


In this context and keeping in mind the Stability Pact for South Eastern Europe, the goal of SMART is to provide the end-users with 

  • safe,
  • cost-effective,
  • efficient,
  • innovative,
  • validated, and
  • user-friendly tools
for the monitoring of the environment and for the assistance to people in countries afflicted by landmines in order to achieve a higher quality of the service, by efficiently improving level 1 minefield surveys in South Eastern Europe.

SMART in a nutshell

Area reduction: a key process

Area reduction has been recognized as a mine action activity where reduction in time and resources could help a lot. Long-term empirical data from CROMAC show that we can estimate that around 10% to 15% of the suspected area in Croatia is actually mined. The minefield records alone do not have enough information for the proper allocation of limited de-mining resources to really mined areas. Their completeness and reliability are not high enough. Decision makers need additional information. SMART is intended to provide some of this additional information that would help in two ways: it can reinforce the suspicion of some places and reduce the suspected area on others. The goal of the SMART project is to provide a GIS-based system - the SMART system - augmented with dedicated tools and methods designed to use multispectral and radar data in order to assist the human analyst in the interpretation of the mined scene. The use of SMART includes a short field survey to collect knowledge about the site, a flight campaign to record the data, and the use of the SMART system by an operator to detect indicators of presence or absence of minefields. The operator will prepare thematic maps that will synthesise all the knowledge gathered with these indicators. These maps of indicators can be transformed into 'danger maps' showing how dangerous an area may be according to the location of known indicators. These maps are designed to help the area reduction process as described in the following examples.

Suspicion reinforcement

The use of SMART can help to detect abandoned fields in suspected areas, reinforcing that way the suspicion about these fields. Before the contamination by landmines, agricultural fields and pastures were enclosed by hedges but rarely with trees. If some fields are abandoned and not used, their borders change; hedges become mixed with smaller trees; bushes grow inside the field borders; low bushes become small tress. The trees and bushes inside the field or in the borders are significant indicators that the field is abandoned. Detecting abandoned areas can be done by classification of multi-spectral data. SAR, by making it possible to make the difference between trees and bushes, provides also very valuable information to make this analysis. If a field is abandoned now, it may be because the soil is not suited for agriculture. Using satellite data from before the war can help determine if the field was cultivated then. If it was, then it reinforces the suspicion. Multi-spectral data can also be used to detect locations where creating a minefield would have made sense: river shores, forest borders, crossroads, bridges and any other places that are better located on images than on old, obsolete maps.

Reducing the suspected area with SMART

The use of SMART can also prevent technical surveys and clearing of non-risky or non-hazardous areas. Experience shows that, in parts of the country that are considered as suspected, there are areas actually in agricultural use. Some farmers cannot wait for the official reduction or clearing of their fields and take the responsibility to clear them themselves or have them cleared unofficially - leading sometimes to incomplete clearing or casualties. These behaviours lead to discrepancies between reality and CROMAC's records of suspected areas. By using multi-spectral and SAR data and processing them to provide a classification of the areas, an operator of SMART can quickly have an objective point of view of the real land cover and land use of a large, theoretically-suspected area. Once the use of SMART has updated the MAC's records and identified cultivated fields inside suspected areas, a short field survey - shorter than what would have been needed without SMART- can be organised to determined if these fields can be officially declared reduced. Change detection is useful here too. By using satellite data from before the war it can help determine if a field that is abandoned now was already abandoned before the war. If this is the case then the neglected state of the field cannot be attributed to mine infection - although it does not mean that the field is not mined. As a general rule all information gained from the use of SMART must be appraised by the operator.

Limitations

The general knowledge used in SMART is strongly context-dependent. It has been currently derived from the study of three different test sites in Croatia chosen to be representative of the country. In the case of another context a new field campaign is needed in order to derive and implement new general rules. Before using SMART the list of indicators must be re-evaluated and adapted. It must be checked if the indicators can be identified on the data and if the new list is enough to reduce the suspected areas.

SMART: a help to area reduction

Despite these expected limitations the ideas presented here make us confident that SMART has the technical potential to be a working solution for an airborne general survey applied to area reduction.

The work
There are four phases in the project:
  • the data collection,
    • Planning and performing fights over several suspect areas in Croatia with SAR, multispectral, and high-resolution optical sensors, together with a ground-truth mission
  • the data processing,
    • Interpretation of the data, development and implementation of tools to help the interpretation; the data processing and data fusion are used to provide land cover classification and detect anomalies; a first list of indicators and locations of interest can be found here.
  • the integration of the tools into a GIS,
    • Providing an integrated environment to make the work of analysts easier
  • the validation of the results
    • Level Two survey to be performed on the sites to determine the actual borders of the minefields

The partners

 
  • TRASYS

  • TRASYS is project co-ordinator. Their technical involvement concerns the integration of data used by different partners in a central GIS-based database. TRASYS will also develop tools within the GIS to support End-User decision support procedures. 
    Contact: Jacques Willekens
    Renaissance
    The Signal and Image Centre of the Royal Military School  of Belgium participates to the project through Renaissance and is one of the signal & information processing partners. Its large experience in this field justifies its role in the project to develop methods for the data fusion, land-cover classification and anomaly detection modules. Renaissance will also contribute in the pre-processing task. 
    Contact: Yann Yvinec
  • ULB (Université  Libre de Bruxelles)

  • The ULB is involved in the land-cover classification module and the ground truth data collection sessions through its institute IGEAT (Institut de Gestion de l'Environnement et d'Aménagement du Territoire). 
    Contact: Eléonore Wolff
  • DLR (Deutsches Zentrum für Luft- und Raumfahrt)

  • DLR and its Institute for Radio Frequency Techniques and Radar Systems will contribute with his Experimental Synthetic Aperture Radar, Daedalus scanner and RMK sensor. DLR will also be responsible for the SAR and Optical processing and the coherence map generation. 
    Contact: Martin Keller
  • ENST (Ecole Nationale Supérieure des Télécommunications)

  • ENST will participate in the data fusion module and the land-cover classification module through its Signal and Image Department ENST will also contribute to anomaly detection. 
    Contact: Isabelle Bloch
  • Zeppelin

  • The company ZEPPELIN will participate with its airship to a airborne data test. 
    Contact: Hanns Harder
  • CROMAC (CROatian Mine Action Centre)

  • CROMAC, the end-user of the SMART project, will be involved in the data collection module, the validation module and the protocol definition module. During the whole project, CROMAC will advise the partners about the usefulness of their ideas. 
    Contact: Milan Bajic
  • RST (Radar SystemTechnik)

  • RST is mainly interested in the follow-up of the project and set-up of the later exploitation, especially in designing a fully polarimetric SAR system to be installed on board of a zeppelin. 
    Contact: Gunnar Triltzsch
  • IXL

  • IXL is mainly interested in the follow-up of the project and set-up of the later exploitation, especially in ruggedizing the exploitation software. 
    Contact: Wolfgang Noack

    Descriptions of sensors 
    • Available airborne sensors
    Sensor name Spectral resolution Spatial resolution Swath width  Radiometric resolution Compatibility future satellite sensors
    Daedalus line-scanner  11 channels between 0.380 & 2.7 µm
    1 channel 3-5 µm
    1 channel 8-13 µm
    < 1 m  450 m 8  bits/channel  yes
    SAR P-band fully polarimetric (HH-VV-HV-VH) 4 m


    SAR L-band fully polarimetric (HH-VV-HV-VH) 2 m 3.5 km < 2 dB yes
    SAR C-band (VV) 1.5 m


    SAR  X-band (VV)  1.5 m  3.5 km < 2 dB yes
    RMK  0.5 to 1.2 µm  3 to 5 cm 360 m photo  no
    •   Possible space sensors
    Sensor name  Spectral resolution  Spatial resolution  Radiometric resolution
    XSAR/SRTM X-band  6 m  2 dB
    RADARSAT C-band (5.3 GHz)  7 m   
    IKONOS  PAN (0.49-0.90 µm)
    Multi-spectral:
    0.42-0.52, 0.52-0.60, 0.63-0.69, 0.76-0.90 µm
    < 1 m

    4 m 

    11 bits

    11 bits

    KVR Coloured film  2 m  photo

    Contact persons 
    Daniele G. Galardini  (project management) and Marc Acheroy  (technical management).

    First public documents 
    Tables of potential indicators and suspect locations
    Publications
    Report on DLR work in SMART (Measurement campaign and data acquisition, data processing, available satellite data, Zeppelin feasibility study, SAR tool development and integration...)
    SMART final report is available on request.