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Earth operational hyperspectral monitoring

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Presentation on theme: "Earth operational hyperspectral monitoring"— Presentation transcript:

1 Earth operational hyperspectral monitoring
Multilevel system of Earth operational hyperspectral monitoring A.V. Raschupkin, A.S. Egorov

2 Project «multilevel system of Earth operational hyperspectral monitoring»
The project on multilevel system of Earth operational hyperspectral monitoring is oriented towards development of regional system of operational hyperspectral monitoring of physicochemical conditions of natural and anthropogenic objects based on data obtained with hyperspectral sensors used in space, aviation and ground facilities in the interest of regional state authority and local government as well as in the interests of enterprises having different form of property to solve a wide range of socioeconomic and scientific tasks.

3 Multilevel system of Earth operational hyperspectral monitoring
Function Space Global observation of Earth surface using three type of equipments Aviation Operative high-resolution hyperspectral imaging. Synchronous under spacecraft imaging for calibration and validation remote sensing data from Resurs-P spacecraft Ground Probe fence of soil and water, their analyzing, forming and updating database of etalons of relations «spectral coefficient of surface reflection – chemical composition» Detection of chemical composition Database of spectral signatures

4 Subproject of multilevel system of Earth operational hyperspectral monitoring
Development and examination plane-laboratory equipped hyperspectral sensor (0,4 – 2,5 µm) and high-precision navigation equipment, attestation and certification it. Development of hyperspectral data found. Development of system of stationary and mobile physical and chemical laboratories. Development of software of thematic processing Information, obtained from the hyperspectral monitoring system. Organization business structures for dissemination of remote sensing information.

5 Space facilities of Monitoring
Basic specifications of Resurs-P spacecraft equipment High-resolution equipment Swath, km (with altitude 475 km) Spectral ranges, m - panchromatic band ,58 – 0,8 - narrow spectral bands 0,45 – 0,52 0,52 – 0,6 0,62 – 0,69 0,72 – 0,9 0,59 – 0,64 0,7 – 0,73 0,7 – 0,8 Ground resolution in nadir, m (with altitude 475 km) - panchromatic band - narrow spectral bands – 4 Wide-swath equipment Swath, km /441 Spectral ranges, m - panchromatic band ,43 – 0,7 - narrow spectral bands ,43 – 0,51 0,51 – 0,58 0,60 – 0,70 0,70 – 0,90 0,80 – 0,90 Ground resolution in nadir, m - panchromatic band /60 - narrow spectral bands /120 Hyperspectral equipment Swath, km Spectral range, m ,4 – 0.96 Number of spectral bands Ground resolution in nadir, m

6 Aviation facilities of Monitoring
MAIN specification of «Rysachok» airplane Aviation hyper spectral imager Aisa Fenix Feature Value Payload (without taking pilot’s weight), kg 470 Range of cruising speed, km/h Operating altitude, m до 6000 Distance of flight, km 1990 Flight endurance, h 7,5 HSI specification VNIR SWIR Spectral range, nm Spectral resolutions, nm 3,5 10 Spatial resolutions, m 1,47 (Н=1000 м) Number of spectral bands 344 275 Swath, m 580 (H=1000 m)

7 ground facilities of monitoring
Database of spectral signatures Detection of chemical composition Mobile physical and chemical laboratories

8 Development of software of thematic processing information, obtained from the hyperspectral monitoring system Identification of objects on the specified spectral characteristics Hyperspectral image Segmentation of objects Spectral characteristics of selected objects Database of etalons of spectral characteristics COMPARIOSON OF SPECTRAL CHARACTERISTICS Step 1. Segmentation of objects in a hyperspectral image based on correlation spectral characteristics Step 2. Determination of spectral characteristics for the selected segments Step 3. Comparison of the spectral characteristics of the selected segments with etalon spectral characteristics of the database based on determination of the spectral angle Step 4. Classification of objects and the formation objects map vegetation road surface water surface rooftops

9 Monitoring of waste oil pits using hypespectral information
Classification content of waste oil pits Different content of the pits Space image RGB composite according to the HSI Identifying the boundaries of regions with different concentrations of pollutants

10 Determination of pond’s depth with using methods of bathymetry
Three-dimensional model of the pond, built with the help of echo sounder’s measurements Pond in area of Chubovka village (Samara region) Bathymetry map constructed by spectral characteristics of hyperspectral image

11 Monitoring of landfills and solid waste using hyperspectral data
RGB – composite Classification result Landfill Contaminated water Soil Sand Metal roof Dirt road Vegetation

12 Targets of hyperspectral monitoring
Hyperspectral information gives us opportunity to create thematic maps and geo-information systems aimed to solve problems below:  water quality monitoring in water basins and rivers, mechanic, chemical and biological contaminant evaluation;  soil salinity classification;  soil fertility and mineral composition evaluation;  vegetation cover, agricultural and forest landscapes monitoring;  narcotic plants identification;  technogenic and natural dangerous substances emission and leakage monitoring, their consequences development forecasting;  dumping sites detection, their content and size estimation.

13 Forecast the North American market of hyperspectral information (million Dollars) *
Remote sensing market in North America 2009 2011 2014 2017 2020 Hyperspectral data 195,5 204,9 214,4 221,9 229,4 Multispectral data 218,0 233,0 248,0 258,5 269,0 Total: 413,5 437,9 462,4 480,4 498,4 * Expert’s forecast of the American Society for Photogrammetry and Remote Sensing Charles Mondello and George Hepner.

14 The problem of mixing of the spectra ("mixed pixel").
The main problems in the sphere of hyperspectral information processing The lack of highly qualified specialists in the field of processing and analysis of hyperspectral data; The elimination of the influence of atmospheric conditions (atmospheric correction); The absence of domestic spectral libraries of natural and man-made objects; Identification of receptor portions of the spectrum and determination of the optimal spectral intervals for specific tasks; The problem of mixing of the spectra ("mixed pixel").

15 Thank you for your attention!

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