(- )

( THE FIRE INFRARED-HYPERSPECTRAL MONITORING (RussianGermany Proposals for an International Earth Observation Mission)
Preprint, Inst. Appl. Math., the Russian Academy of Science)

., ., .., .., .., .., .., -., ., .., C., .., .., .., ..
(K.Bries, P.Behr, L.A.Vedeshin, D.V.Vorontsov, V.V.Egorov, S.K.Kalashnikov, A.P.Kalinin, K.-H.Kolk, S.Montenegro, A.G.Orlov, S.Pletner, A.I.Rodionov, I.D.Rodionov, E.Yu.Fedunin, B.R.Shub)

. ..

, 2004

- - . , . () , BIRD, () , , . DLR . 2003. 2004-2015., . , , , . .

Abstract

Preprint contains the proposal for creating a constellation of small satellites for space observation of forest fires, volcano eruptions and other natural catastrophes. The proposal is based on infrared remote sensing technology (IR) implemented by German Side in the small satellite BIRD and on hyperspectral remote sensing technology (HT) developed by Russian Side as a part of the Astrogon Project and tested in airborne experiments. The Project also includes a high-performance, low-fault onboard computer developed jointly by both Sides and based on industrial electronic elements. The concept of the project is based on integration of IT, providing wide observation span, and HT, providing the local analysis capability for detected energy sources. The Proposal was prepared for DLR as an international remote Earth monitoring Project. It was also presented in September, 2003 in Rosaviakosmos, included in the Program Spaceborne study of global and regional environmental processes on Earth using the infrared and hyperspectral sensors, and approved for years 2004 2015 by the Space Research Council of Russian Academy of Sciences, Section Earth study from the space.The project is open for potential investors and users. Keywords: infrared technology, remote monitoring, hyperspectrometry, fires, natural catastrophes.

 

INTRODUCTION

Forest fires and other natural and anthropogenic catastrophes that involve high thermal emission, such as gas/oil pipeline failures, power plant accidents, and volcano eruptions, cause the yearly damage in the billion USD range to nature, industry, and human health.

Obviously, the timely detection and localization of such catastrophes could help control them or, at least, reduce the damage. For effective control, administration and emergency services, in the first place, should have adequate information on catastrophe precursors, catastrophe dynamics, and post-catastrophe developments. Depending on the type of emergency, this information may be required at very different spatial scales.

This problem can be solved only with up-to-date spaceborne remote sensing technologies. In particular, the satellite systems should include high-sensitivity infrared sensors, and visible and near infrared hyperspectrometers with high spatial and spectral definition. Hyperspectrometers provide essential added-value information for artifact discrimination, precursor detection, catastrophe after-effect assessment. Effective use of satellite information also requires appropriate ground facilities for information storage, preprocessing, and distribution. An important link in information flow is the decision-making support system based on state-of-the-art thematic processing algorithms.

The BIRD satellite can be considered a prototype and a seed of such a system. Information provided by the infrared sensor on board this satellite proved quite effective for monitoring the forest fires and volcano eruptions. However, to enhance its potential, it is desirable to add a new sensor the hyperspectrometer Astrogon- Light by R&G Reagent. This instrument is based on the Astrogon-Vulcan prototype [1] and was tested in airborne experiments. The instrument complex is planned to use a high-performance, low-fault onboard computer developed jointly by Russian and German industry and based on industrial electronic elements [2], [3].

The proposals targeted to solving these problems were prepared for DLR as an international remote Earth monitoring mission project based on satellite clusters. They were also presented in September, 2003 in Rosaviakosmos, included in the Program Spaceborne study of global and regional environmental processes on Earth using the infrared and hyperspectral sensors, and approved for years 2004 2015 by the Space Research Council of Russian Academy of Sciences, section Earth study from space.

This preprint presents the proposal for creating a joint Russian and German constellation of small satellites for monitoring the disastrous terrestrial events natural and technogenous with high energy emission, such as forest fires. The system is based on combining the infrared and hyperspectral monitoring technology.

Included are experimental results from the BIRD satellite and the airborne hyperspectrometer. They confirm the effectiveness of instrument combination proposed. The Appendix includes the Program Spaceborne study of global and regional environmental processes on Earth using the infrared and hyperspectral sensors approved for years 2004 2015 by the Space Research Council of Russian Academy of Sciences, section Earth study from space.

BIRD Mission Rationale

 

The areas engulfed in yearly forest fires are a considerable part of major ecological zones of the planet:

h109 ha - savannah area

h107 ha - tropical rain forest

h106 ha - mediterranean vegetation

h108 ha - boreal forests.

 

 

The fires produce a negative influence on:

hatmosphere (greenhouse effect, ozone, aerosol, relation CO/CO2),

hclimate (global warming),

hglobal carbon cycle (closedness).

 

Up to now, there exists no dedicated fire observation system in orbit (except BIRD).

 

BIRD Mission Objectives
(BIRD = Bi-spectral Infra-Red Detection)

 

The BIRD project was awarded by DLR to several German organizations: Fraunhofer FIRST, Jenaoptronik, TUB, Astro and others. Its goals included:

        Test of a new generation of infrared sensors dedicated for fire investigation from space;

        Remote sensing of fires and of the land surface;

        Space demonstration of new micro-satellite technologies.

 

 

 

BIRD = Demonstrator for FIRE MONITORING CONSTELLATION

 

Mission Idea

 

The idea of the mission is to use the spaceborne remote sensing to obtain the detailed information on forest fires and other natural and technogenous catastrophes that have a high impact on environment, security, and quality of life.

As implementation of this mission, the Operational Fire Monitoring Constellation (FMC) project is proposed. It is based on integrating the IR technologies with wide viewing angle and the hyperspectral analysis of local areas for detection and localization of high-energy sources. This type of complex monitoring open the way to real-time processing of user request (from scientists, customers, etc.) and within a very short response time obtain the detailed information on the current state of observed processes.

 

Fire Monitoring Constellation FMC

FMC Mission Objectives

Mission goals include:

        Detection, monitoring and investigation of high-temperature phenomena (hot spots), like forest fires, volcano activities, coal seam fires or other from space on commercial basis

        Monitoring of land, sea surface and atmosphere parameters and phenomena with a combination of infrared and hyper-spectral channels for scientific and operational purposes

        Fast delivery of high level data products to the end user as an operational service

 

FMC Mission Constraints

Development time

2 -3 years

Lifetime

4 years in orbit

Launch constraints

low-cost launch into LEO (as auxiliary payload)

Mission type

micro-satellite constellation mission with operational objectives

Cooperation

German and Russian institutes and companies

Ground base segment

Russian and DLR ground stations

Funding

DLR-German space agency and Russian Academy of Sciences, Rosaviacosmos, industrial enterprises, investors

 

The optimal infrared channel selection for forest fore monitoring is based on the comparison of forest fire flaming spectra and standard spectra of natural vegetation.

Signatures of Vegetation Fire and Background

 

This comparison leads to the following conclusions:

        spectra contain information on land surface, atmospheric gases and aerosols;

 

        the second atmospheric window (MIR) is the optimum for the hot spot detection.

 

The key elements of FMC Instruments

 

The 2-channel-infra-red

sensor system (15kg, 90W) A VIS/NIR

2x 512pixel CdHgTe detectors pushbroom

GSD: 185m Sensor

Hyperspectral Sensor instrument (20kg, 30W)

Key elements

Acusto Optical Micro Channel Plate Detector

tunable Filter Sensor

The FMC Instruments

Payload platform of BIRD-type with assembling tools

 

 

VIS/NIR

MWIR

TIR

Hyperspectrometer

Wavelength

600-670nm
840-900nm

3.4-4.2m

8.5-9.3m

0.4-0.8m

Focal length

21.65mm

46.39mm

46.39 mm

~700mm

Detector

CCD

CdHgTe

CdHgTe

MCP

Ground pixel size

185m

370m

370m

20m

Ground sampling distance

185m

185m

185m

20m

Swath width

533km

190km

190km

20x20km2

at 572km orbit altitude

 

Payload platform of BIRD with assembling tools (without the hyperspectrometer)

 

FMC Payload Mass and Power Budget

system

mass

Power budget

IR-System

15kg

90W

VIS/NIR-Sensor

4kg

10W

Hyperspectrometer

20kg

30W

Star sensors, Magnetometer

3kg

5W

Structure

2kg

 

Harness

1kg

 

Total:

45kg

135W

 

BIRD payload top view

 

 

Comparison FUEGO and FIRE MONITORING CONSTELLATION

 

Parameters

FFEW-FUEGO

BIRD-FMC

Orbit geometry

700 km/47.5

700 km

No. of satellites

12

3 or 4

MIR channel (res., swath)

144/72 m, 250 km

550 km

TIR channel (res., swath)

390 m, 250 km

550 km

VNIR channel (res., swath)

RGB-CCD channel (res., swath

100/25 m , 250 km

-

-

225 m , > 500km

Minimal resolvable 800 K

fire area at nadir

~5/20 m2

~5/20 m2

Revisit Time

30.4 minutes

12 Hours

Average fire detection

15.2 minutes

6 Hours

Data transmission

L-Band, direct to users

S-Band, direct to users

 

 

Comparison between hyperspectrometer parameters

 

 

Wavelength Range

Best spectral resolution

Measurement of Polarization

Ground pixel size

Size of a data take

Warfinghter-1

(OrbView3-4)

0.45-2.5m
2.5-5.0m

11.4nm

No

8m

5x20km2

Hyperion
(NASA, EO-1)

0.4-2.5m

10nm

No

30m

7.5x100km2

FTHSI
(MightySat II.1)

0.47-1.05m

1.7nm

No

25-250m,
25-51m

6-26km x
20-87km

Astrogon- Vulkan

0.25-2.5m

1nm

Yes

5m

3x3 km2

Astrogon Light Hyper-spectrometer

0.4-0.8m

1nm

Yes

10m

10x10km2

 

The requirements to the BIRD bus type satellite bus:

hsuitable for different piggy-back launch opportunities in any LEO;

h200W peak power for 20min;

htotal mass max. 95kg incl. payload;

h3-axes stabilized;

hon-board navigation system;

hS-band telemetry with max. 2Mbps;

hradiation tolerance up to 7krad (Si).

 

 

BIRD-type Spacecraft Modes

The spacecraft supports the functional flexibility: it can work in different modes.

 

AAM - Auto Acquisition Mode, DAM- Damping Mode, LAM- Large Angle Manoeuvre, SPF- Sun-pointing Fix, SPR- Sun-pointing Rotate, EPM Earth-pointing Mode, IPG- Inertial Pointing Mode, SPM - Suspend Mode.

Launch Strategy: as Auxiliary Payloads on 2 launchers


2 examples:

         Cosmos (right)

         Resurs (left)

 

Target Orbit: 550800km, circular, i = sun-synchronous

3 or 4 satellites in the same orbit plane but at different positions

 

 

 

FMC Mission Architecture and Ground Segment

Mission operations by DLR

 

Data reception, processing

storage by DLR

 

Coordination of the user

requirements by an

operational user interface

 

Commercial distribution

of fire data products

 

Technology demonstration

of hyper-spectrometer

Option: direct receiving of data

by low-cost ground stations

including processing software

 

 

 


 

BIRD-Highlight:
Hot-Spot-Detection Within the Sub-Pixel Range

(Dozier, 1981: Bi-spectral Technique for retrieving temperature and area of sub-pixel hot spots)

 

LMIR (TF, q) = q BMIR (TF) + (1-q) LMIR-bg

LTIR (TF, q) = q BTIR (TF) + (1-q) LTIR-bg

 

BMIR/TIR - integral Planck-Function within each channel LMIR/TIR-bg estimated radiance of background from the surroundings

 


Infrared+hyperspectral remote sensing technologies: demonstration of usage

 

First Fire Evaluation From Space -
BIRD gives temperature and area extent of Australian bush fires

 

 


 


Comparison of the fire images and fire data products between MODIS and BIRD (detail image from 5. Jan. 2001 of Australia)


MODIS: Fire map BIRD: Fire map

 

Typical characteristics of fire fronts (BIRD, Australia, January 5, 2002)

 


 

Etna eruption (BIRD, November 2, 2002)

 

 

BIRD Detects Coal Seam Fires in China (February 6, 2002)

 


Osterfeuer (BIRD - Aufnahme, Region Berlin-Süd, 17. April 2003, 22:35 MEZ)

 


Classification of images in VNIR and MWIR

 

 


 


To increase the robustness and accuracy of on-board image classification, hyperspectral data should be used, in addition to IR data. This could provide the additional detailed information on the chemical composition of combustion products and on the environmental impact of fires.

R&G Center Reagent has designed, developed, and tested the Astrogon airborne prototype on board the helicopter.


Images from two hyperspectral modules at different wavelengths as seen on board the helicopter.

 

Examples of hyperspectral information and processing results

a

B/w representation of total hyperspectral signal.

b -

Classification resulting from correlational processing of hyperspectral data.

c

Accompanying camera view (total camera viewing angle 600, hyperspectrometer viewing angle 120 shown as a horizontal line).

d

Upper half: data from two hyperspectrometer modules corresponding to the cross-point in a, b, and . Lower half: spectrum in the cross-point.

e

List of categories used in classification.

 

 

 

Benefits of Cooperation

The hyperspectrometer Astrogon-Light on an operational Fire Monitoring Constellation would give:

        New scientific results related to land, sea surface and atmosphere

        Demonstration of advanced technology in space

        New knowledge about environment and security

        Additional scientific results about fire and volcano impacts

        Different application products on user request

        Additional detailed information on the chemical composition of combustion products and terrestrial objects.

 
Conclusion

 

The joint Russian-German Project proposed is based on the combined use of an infrared camera and a hyperspectrometer carried by the BIRD-type satellite cluster. It opens a new vista in global and regional monitoring of critical processes and catastrophes, such as forest fires, volcano eruptions, technogenous disasters, etc. The new capabilities are due to the synergistic effect of infrared and hyperspectrometric data. The following features add to the perspective of the Project:

1.    Temperature and area extent of vegetation fires or other hot spots can be evaluated from space.

2.    The new infrared array sensor system is suitable for small satellite missions.

3.    New hyperspectrometer data offer new science and new service for monitoring of environment and security.

4.    Microsatellites are interesting tools for operational missions open because of the low mission costs and the flexibility.

5.    An operational Fire Monitoring Constellation is First to market

6.    An operational hyperspectrometer is first to science and first to market.

 

 

 

 


APPENDIX

 

 

 

APPROVED

Vice-President of Russian Academy of Sciences,

President of the Section Space investigations of the Earth and natural resources, RAS Scientific Council on Space Investigations, Academician

N. P. Laverov

15 December 2003

 

 

 

Experimental study of regional and global terrestrial environmental processes using spaceborne hyperspectral and infrared sensors

 

Scientific program

 

 

 

 

 

 

Moscow, 2003

 

 

Introduction

 

Fires and other natural and anthropogenic catastrophes, such as trunk pipeline failures, large power plant accidents, volcano eruptions etc. lead to emission of enormous quantities of heat and cause several hundred million dollar losses yearly to environment, industry, housing, and population health.

The timely detection of events that start these catastrophes would help their prevention or, at least, would help in reducing their extent. The first thing to do is to provide the local administration and the specialized services with an adequate informational support, in order to track the catastrophe development from precursors to outbreak, the peak of event and then to post-catastrophic processes. A widely varying spatial coverage is usually required for that.

The solution to this problem can be based only on spaceborne remote sensing, armed with sensitive infrared sensors and with visible and near-infrared hyperspectrometers with high simultaneous spatial and spectral resolution. Hyperspectrometers are a must for screening out artifacts, detecting weak precursor symptoms, assessing the slow post-catastrophic dynamics. However, sensors are not the only hardware necessary: receiving stations, preliminary processing complexes, storage and distribution network all that must be taken into account. The software thematic processing algorithms and decision support systems adapted to fast response requirements characteristic for catastrophes - is as important as hardware. Both hardware and software should function on a permanent basis, in order to support precursor monitoring and post-catastrophic management.

As a prototype of the space-based part of such a system, one could indicate the BIRD satellite (Germany) with an infrared sensor. It has been functioning from 1999 till 2003. Its information proved quite effective in forest fire and volcano monitoring. However, for this system to live up to challenges listed above, it should be complemented with a hyperspectrometer. In our opinion, an adequate sensor for this purpose is the Astrogon-Light hyperspectrometer developed by R&G Reagent (Russia).

This paper contains a proposal for development of a joint Russian and German small satellite-based Earth monitoring system targeted at natural and technogenic catastrophes with high energetic yield fires, etc. It should be based on fusion of German infrared data and Russian hyperspectrometric data.

This proposal is supported by Russian Academy of Sciences. It covers the project of the system, experimental results from German infrared sensor, and results of test flights with Russian hyperspectrometer. The appendix includes the scientific program Space-based experimental study of global and regional environmental processes using hyperspectral and infrared sensors by Russian Academy of Sciences.

 

General

 

Justification

 

Recent decades have seen a number of programs and experiments in spaceborne remote sensing domain, both in Russia and abroad (LACIE, Seasat, FIFE, BOREAS etc.). Nevertheless, no implementation of regional or global environmental study, either targeted to atmosphere or to oceans or land, can be considered adequate. The basic reason is the so-called inductive approach, so that the objects of study were confined to individual biospheric components or processes, and the global picture was supposed to emerge from later synthesis of results. This approach inherently suffers from possible omissions or duplications or wrong weighting of the objects, and, consequently, leads to dissipation of resources and loss of time.

There is an alternative: the deductive approach based on the search for optimization of a chosen criterion, e.g., sustainability of global environmental and socio-economical development, closure of natural cycles of matter and energy, quality of human life, etc. The list of necessary studies and methodologies would follow as an unfolding of the criterion functional. This approach is widely used, e.g., in controller synthesis, statistical decision theory and many other scientific and technological domains.

This approach, if adopted, would call for a new informational support strategy for research, and, in particular, the strategy of space-based remote sensing. Specifically, the set of so-called unfolding parameters, such as wavelength, spatial coordinate, observation angle, scale, etc., should be made as rich as possible. Also, all components and stages of remote monitoring, which use these parameters, should be integrated into a coherent system beginning with problem statement and ending with marketing issues.

The space-based experiment we propose is a first step towards implementation of this strategy, testing its basic principles and providing a starting point for methodology of further studies. The experiment is based on spaceborne hyperspectral (0.3 2.5 ) and infrared (4 12 ) instruments, and its methodology would be extensible to other wavelengths.

The approach proposed implies the implementation of fundamental science through applied research, so that there is a feedback between scientific and practical problems. In particular, the scientific program is dependent on the #1 marketing issue: the traditional data, such as panchromatic and multispectral images, are a standard product on the market. They have almost a status of utility, their turnover is skyrocketing and could reach $20 billion by the year 2010.

The situation is different for a more complex type of data the hyperspectral. Their strong point is the possibility of remote physical and chemical analysis of Earth surface. However, the data processing methodology is still to be developed and tested, and until then, the commercialization is delayed. An important part of the program proposed is to remove the scientific obstacles and open the way first towards the engineering applications, and then towards commercialization of hyperspectral data.

The infrared camera, which is a part of onboard instrumentation, will be provided by a consortium of German enterprises:

        OHB System AG, responsible for satellite bus and launch

        Jena-Optronik GmbH, responsible for the Payload Segment

        DLR, responsible for mission operation and IR-technology

        Technical University of Berlin, Mission Planning and project management

        Fraunhofer FIRST, payload interface unit and payload data processing.

 

At the Russian German meeting on September 17, 2003, Rosaviakosmos has presented its proposals on the integration of information flows from Russian and German satellites.

 

Purpose of the program.

 

This document presents a joint scientific program by a number of leading RAS institutes (Keldysh Institute of Applied Mathematics, Semenov Institute of Chemical Physics, Center of Forest Ecology and Productivity, Institute of Atmospheric Physics, Institute of Oceanology, Institute of Geology of Ore Deposits, Petrography, Mineralogy, and Geochemistry, Lebedev Physical Institute), Center of Science-Intensive Export Technologies, and R&G Reagent. It includes the following sections:

-         goals, objectives, and contents of the experiment;

-         basic requirements for the experiment and for the methodologies of data processing;

-         organizational requirements for the implementation of the experiment;

-         other organizational issues.

 

Goals and objectives of the experiment

Main goal

Using the spaceborne hyperspectral and infrared remote sensing for discovery and study of interaction mechanisms between various biosphere components (atmosphere, ocean, and land) and between them and anthropogenic systems, in order to develop the strategy of monitoring and controlling these systems state as an informational support for global sustainable development, economic activities, early natural and anthropogenic catastrophe warning, and assessment of their after-effects.

 

Scientific and practical objectives

 

This goal implies:

                                 Definition, based on the above-mentioned deductive approach, of most urgent and/or most perspective scientific and applied problems, in a setting optimized by informativity of hyperspectral and infrared observations with respect to objects and processes involved;

                                 Determination of data informativity within each problem group as a function of time, territory, observation schedule, data processing methods. Optimizing the monitoring strategy for each problem group with respect to these parameters;

                                 Definition of requirements to auxiliary databanks: GIS information, additional databases, knowledge bases, and, most importantly, in situ experimental data. Developing a preliminary version of integrated auxiliary databank.

                                 Development of requirements for information channels and information shipment conditions, based on the dependence between admissible shipment delay, information volume, and processing depth and quality;

                                 Assessment of market capacity as a function of problem group and the quality of information. Assessment of total development and exploitation cost and expected profitability of the information system based on hyperspectral and infrared remote sensing.

                                 Developing the list of standing customers and coordinating the requirements for information products with them. Securing the informational support with problem-related in situ information from customers.

                                 Forming an expert group for scientific and methodological supervision of the information system;

                                 Feasibility study for a new way of information shipment based on peer-to-peer Internet networks including both individuals and institutions. This is especially valuable for catastrophe monitoring and control, e.g. targeted to population health during intensive forest fires;

                                 Feasibility study for a continuous monitoring-control feedback cycle for customers who wish to participate in this study.

 

Scientific and applied problems and application domains for the results of experiment

 

The following list of scientific and applied problems and expected results is preliminary. It will be refined as the work listed in section 0 will progress.

Table 1 Application domains and expected results

##

Problem

Expected results

1.

Diagnostic of main gas and oil pipelines

Pipeline positioning, monitoring of intersections, detection of protection zone infringements, forecast of slumps and arches, detection of micro-fractures and fistulas, detection of corrosion, soil and ice-lens dynamics, illegal cut-ins.

2.

Monitoring of deposit infrastructure

Monitoring the state of collector networks, roads, production sites

3.

Monitoring of underground gas reservoirs

Leak zones, leak volumes

4.

Monitoring of oil reservoirs

Reservoir fillup, shell deformation, product leakage (including subsurface leakage)

5.

Environmental support of land-based and offshore drilling

Condition of settling pits and reservoirs, leakages of drilling fluid, of mineralized stratal water, oil or condensate. Detection of oil spills on sea surface.

6.

Environmental condition of deposits

Anthropogenic defects of landscape, soil, vegetation, subsurface flow

7.

Environmental condition of trunk pipelines

Biota suppression zones caused by micro-leakages

 

8.

Potential borehole positioning. Monitoring of deposit exhaustion

Periodically renewed 2-D and 3-D deposit maps. Monitoring of strategic oil and gas reserves

9.

Monitoring of construction and repair activity on tracks

Monitoring of work progress and of excavation and filling volumes

10

Selection of new trunk pipeline tracks

Size and value of lands put out of use, soil composition, shorelines, slope stability, river crossing stability

11

Exploration geology

Delimitation of complex ore-bearing formations, ore typology and chemistry, small deposit halo

12

Construction geology

Tectonic faults, karst, running sand

13

Engineering geology

Mine surveys, design of pipelines, dams, channels, and nuclear power stations

14

Highway and railway diagnostics

Permafrost, subsidence, and landslide-caused deformations, disturbances of road-bed and pavement, condition of railroad track and trolley-wires

15

Monitoring of bridges and beam crossings

Segments in stressed and deformed state

16

Airfield monitoring

Condition of landing strips and runways

17

Monitoring of power transmission lines

Track certification (digitizing the power transmission poles), damage to insulators and poles, disruption of passages

18

City infrastructure, surface and subsurface networks, power lines, heating systems, water supply and sanitation, gas supply, transport

 

GIS information: topology of networks and damages, air and soil pollution zones by industry and transport. Approaches by emergency services to potentially dangerous sites and extraordinary events. Zones of town-planning value, cultural heritage.

 

19

Exact cartography

Visual maps (CD-ROM) of cities, cross-country, surveying party or tourist routes

20

Cadastral mapping and capacity mapping in megalopolises, high farming regions, health resort zones, and natural reserves. Environmental condition of freshwater sources.

Updatable database of property rights and differential rent. Detection of continuous and extraordinary pollutant emissions and localization of sources

21

Marine fishery monitoring

Zones of upwelling and turbulence, currents, spatial distribution, concentration, and gradients of chlorophyll, phytoplankton, organic and inorganic suspended sediments, salinity, and temperature

22

Borderguard services

Position of commercial fishery ships in zones of economical interest

23

Agriculture and forestry, including farming and nurseries

Spatial heterogeneity of fertilizers and additives composition and dosage, sprout condition, vegetation stages, phytomass, diseases and pests, yield forecast, damage assessment for insurance purposes

24

Forest fire monitoring

Detailed damage localization within fire site, target designation to fire services

25

Monitoring of deep and near-Earth space

Earth Limb imaging, detection of space debris and other objects, measurement of ozone layer state. Tomography of upper atmosphere.

26

Monitoring of catastrophe precursors for floods, ice jams, high dams, quarries, sludge ponds, tailing pits, chemical plants, nuclear power stations.

Anomaly identification, forecast of dynamics

27.

Volcano monitoring

Dynamics of gas, ash, and magma emission. Zones of potential danger to population

 

 

 

 

Scientific and methodological basis

 

Relationship between system-defining factors

 

Scientific and methodological basis for this program is provided by the methodology for development of information-optimal remote monitoring systems. The methodology was developed in Space Research Institute, Russian Academy of Sciences. Nine major groups of system factors are taken into account and related to each other:

-       Monitoring problem statement (major objects, parameters and processes);

-       Imaging platform and schedule;

-       Parameters of sensors (here, of the hyperspectrometer and IR-camera);

-       Prior and in-situ information;

-       Algorithms of preliminary data processing and correction;

-       Algorithms of thematic data processing, including specific analytical and empirical models used;

-       Logistics of information shipment from sensors to processing center and from processing center to users;

-       Marketing factors and business process definition focused on overall profitability of the system;

-       Procedures used to adapt the system to changes in problem setting, technology, market situation etc.

There are two basic types of relationship between these factors. The first one includes fixed constraints, which limit options within a factor group (e.g., monitoring schedule) as a function of choice made within another factor group (e.g., problem statement choice). The second one includes soft relationships defined by coefficients of information transfer from a factor to another factor (e.g., from a model of object dynamics to probability of success in the object detection problem). When all relationships are taken into account, the methodology provides an algorithm for identifying the viable, mutually compatible and informationally optimal configurations of factors. Each distinct cluster of factor configurations defines a distinct feasible type of the monitoring system. The choice between these options is the crucial system design decision. To a large extent, it is determined by the choice and weights of application domains.

The target monitoring problems are detailed into factors:

o       Application domain definition (e.g., for the federal forest fire aviation service, this includes fire detection, fire monitoring, and fire extinguishing);

o       Definition of objects that have to be detected;

o       Definition of spatially extended systems that have to be mapped;

o       Definition of quantitative parameters that have to be estimated;

o       Definition of dynamic processes to be taken into account within some dynamic modeling framework;

o       Indicator characteristics of objects, processes, etc., that allow for remote monitoring.

 

Capacity and informativity of data channels

 

Remotely sensed data obtained for training areas with in-situ measurements and other background information are used to calculate the capacity of information channels that connect sensors to users. Other factors are taken into account, as well, as intermediate nodes of information flow: indicator characteristics specific to application domain, methods of preliminary and thematic processing, methods of information shipment etc. Then, marketing studies are used to calculate the expected feedback from quality of information shipped to users to demand for information in different application domains, and then, to expected sales. Iterations of this modeling cycle will converge to the financial equivalent of a unit of information. Then, the cost-effectiveness criterion can be used to optimize the system design. Note that informativity parameter includes only the information that goes intact through this cycle and, in particular, is assigned a financial equivalent.

 

From experimental to operational mode

The tests that follow this methodology solve two related problems. First, they provide basic data, and in particular, remote sensing data, necessary for model calculations described above. Second, the results of modeling are used to correct the imaging schedules, data processing methods, data shipment procedures, etc. Thus, testing is more than a study: it is a practical informational design optimization of the environmental monitoring system based on hyperspectral and thermal imaging. As a result, the transition from experimental to operational mode will, hopefully, become smoother. In operational mode, the same methodology still remains valid as a way of adapting the monitoring system to changes of market and of other factors.

 

 

 

Improving the technology of hyperspectral and infrared remote sensing

This line of activity includes:

o       obtaining the paired sets of remote and in situ synchronous or quasi-synchronous, spatially compatible data, setting up the corresponding archives, databases and knowledge bases;

o       development of data validation methodology for remote and in situ studies;

o       development of planning and survey methodologies for remote and in situ studies at test sites;

o       determining the invariant relations between observed spectral reflectance / brightness temperature and parameters characterizing the state of remotely sensed objects;

o       determining the relations between observed spectral reflectance / brightness temperature and parameters characterizing the composition of atmosphere above the remotely sensed objects;

o       development of methodology for remote identification of atmospheric pollution sources from estimated pollutant concentrations;

o       identifying the existing and developing the new dynamical models to be used in monitoring and control of specific objects;

o       improvement of thematic data processing algorithms for remote and in situ measurements;

o       development of external calibration technology for onboard imagers.

 

Requirements for test site selection

 

Test sites play a major role in implementation of this space-based experiment, especially within the new deductive framework. First, they provide the crucial background information; second, they are necessary for validation of thematic processing results.

Therefore, test sites should be selected so that they a) contain a maximum possible diversity of natural and anthropogenic objects; b) be well studied during many years field experiments; c) be related to economically important application domains; d) be well covered with past remote sensing data, with topographic and thematic maps.

 

 

Basic requirements for the experiment

 

Preliminary stage

This stage includes:

o       preparation of ranked lists of application domains and specific problems within each domain, linked to potential customers and virtual test sites;

o       solving the organizational issues of test site equipment for future experiment, onboard instrument calibration, data processing validation;

o       collection, systematization, analysis, and, if necessary, extension of existing background information for selected test sites, in order to support the synchronous spaceborne and in situ experiments and the processing of respective data;

o       solving the organizational and methodological issues of information buildup and shipment to users;

o       development of advanced thematic data processing algorithms.

 

Experimental stage

 

The experimental stage is expected to produce the following results:

o       the full set of planned remote and in situ measurements performed;

o       informativity of measurements with respect to the preliminary set of application domains should be estimated;

o       organizational and marketing measures defined, in order to promote the usage of data in global and regional environmental studies and in geographical information technologies used in various industries;

o       potential improvements of remote sensing instruments, increasing their scientific and commercial usability, should be defined.

 

Organizational issues

 

The experiment spans the period 2004 2015.

The leading executive offices are:

o       Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, in trajectory calculations, imaging schedule, preliminary atmospheric correction;

o       Semenov Institute of Chemical Physics, Russian Academy of Sciences, - in studies of chemical composition of remotely sensed objects, methodology and organization of thematical interpretation of remote and in situ data;

o       Lebedev Physical Institute, Russian Academy of Sciences, - in studies of tropospheric gases distribution by means of correlational infrared radiometry from spaceborne and mobile terrestrial platforms. Participation in validation of hyperspectral measurements using a multispectral infrared spectroradiometer;

o       R&D Center Reagent in providing the onboard hyperspectral and infrared sensors, organization of test site studies, thematical processing of data. Includes the validation of hyperspectral data in helicopter/aircraft flights to obtain test data for analysis;

o       Semenov Institute of Chemical Physics Centre of Export High-Tech in marketing and commercialization of results.

Other participants: Center of Forest Ecology and Productivity, Russian Academy of Sciences; Institute of Atmospheric Physics, Russian Academy of Sciences; Institute of Geology of Ore Deposits, Petrography, Mineralogy, and Geochemistry, Russian Academy of Sciences; Institute of Oceanology, Russian Academy of Sciences.

References

 

..Belov, D.V.Vorontsov, D.Yu.Dubrovitskii, .P.Kalinin, V.N.Lubimov, L.A.Makridenko, M.Yu.Ovchinnikov, .G.Orlov, A.F.Osipov, G.M.Polishuk, A.A.Ponomarev, I.D.Rodionov, .I.Rodionov, N.A.Senik, N.N.Chrenov, Astrogon-Vulkan small spacecraft for high resolution hyperspectrometer, Preprint of IPMech RAS, 726, 32p., 2003 (in Russian).

A.A.Belov, P.Behr, E.Yu.Fedounin, A.A.Ilyin, S.K.Kalashnikov, A.P.Kalinin, S.Montenegro, A.G.Orlov, A.N.Ostanniy, A.M.Ovchinnikov, M.Yu.Ovchinnikov, S.Pletner, I.V.Ritus, A.I.Rodionov, I.D.Rodionov, I.P.Rodionova, D.V.Vorontsov, B.V.Zubkov, Software for the Distributed On-board Computer System Prototype, Preprint of KIAM RAS, N 14, 22p., 2004.

..Belov, D.V.Vorontsov, B.V.Zubkov, .P.Kalinin, A.A.Ilyin, ..M.Ovchinnikov, .G.Orlov, I.D.Rodionov, .I.Rodionov, I.B.Shilov, E.Yu.Fedounin, .N.Ostanniy, S.Pletner, P.Behr, S.Montenegro, Distributed On-board Computer System Prototype, Preprint of IKI RAS, -2097, 25p., 2003 (in Russian).