Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2015, Vol. 12, No. 4, pp. 143-150
Model of onboard cloudiness evaluation over the survey area during remote sensing from space
1 A.F. Mozhaiskiy Military-Space Academy, Saint-Petersburg, Russia
The article discusses the results of a research on the development of mathematical apparatus of cloud field estimation over a given area of satellite imagery. The subject of research is mathematical objects that simulate informative data on cloud field at different stages of processing. The purpose of work is to improve the efficiency of remote sensing through a rational use of resources. Analysis of modern methods for cloud determination showed the possibility to use spectral data recorded in the range of 0.4–2.5 microns. The author has developed a new model for evaluating clouds over a given area to be calculated in a special onboard optical-electronic complex with units of cloud field data recording and processing. Cloudiness is evaluated based on the estimate array of cloud presence in resolution elements of the onboard special complex. The estimate array is formed according to the data from informative spectral channels. Processing of the spectral data is performed on the thresholds and weightings determined during planning for specific survey conditions. Real data of space hyperspectral survey were used for semi-experimental calculation of cloud evaluation. The author formulates the prospects for further development of the model of onboard cloud evaluation.
Keywords: survey condition, clouds mask, on-board processing, quantized brightness, radiometric correction, planning of survey
Full textReferences:
- Budovyi V.D., Bukharov M.V., Sposob opredeleniya vremeni provedeniya sputnikovoi s"emki pri distantsionnom zondirovanii (The method of determining the time of satellite imagery for remote sensing), Russian Federation Patent 2231811, Bull. of Inventions, 2004, No. 18.
- Grigor'ev A.N., Metodika formirovaniya spektral'nykh kharakteristik ob"ektov na osnove mul'tivremennykh dannykh kosmicheskoi giperspektral'noi s"emki (The method of formation of objects spectral characteristics on the basis of multitemporal data of space hyperspectral remote sensing), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2014, Vol.11, No. 2, pp. 175–184.
- Mitnik L.M., Mitnik M.L., Zabolotskikh E.V., Sputnik Yaponii GCOM-W1: modelirovanie, kalibrovka i pervye rezul'taty vosstanovleniya parametrov okeana i atmosfery (Japanese satellite GCOM-W1: modeling, calibration and the first results of recovering the parameters of the ocean and atmosphere), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2013, Vol.10, No. 3, pp. 135–141.
- Loupian E.A., Balashev I.V., Burtsev M.A., Efremov V.Yu., Mazurov A.A., Mal'tsev D.V., Matveev A.A., Proshin A.A., Tolpin V.A., Khalikova O.A., Krasheninnikova Yu.S., Vozmozhnosti raboty s dolgovremennym arkhivom dannykh sputnikov LANDSAT po territorii Rossii i prigranichnykh stran (Opportunities to work with long-term archive data LANDSAT satellites in the territory of Russia and neighboring countries), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2012, Vol. 9, No. 3, pp. 3073–15.
- Chapurskii L.I., O vozmozhnosti raspoznavaniya oblakov na fone snega (On the possibility of recognition of clouds on a background of snow), Meteorologiya i gidrologiya, 1976, No. 11, pp. 32–39.
- Chapurskii L.I., Andreeva N.I., Teleindikatsiya oblachnosti v spektral'nykh diapazonakh 0,35-0,85 i 1,2-3 mkm (Determination of cloud in the spectral range 0,35–0,85 and 1,2–3 microns), Meteorologiya i gidrologiya, 1978, No. 8, pp. 41–47.
- Ackerman S., Frey R., Strabala K., Liu Y., Gumley L., Baum B., Menzel P., Discriminating clear-sky from cloud with MODIS algorithm theoretical basis document (MOD35) v. 6.1, MODIS Cloud Mask Team, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin – Madison, 2010, 121 p.
- Ballou K. and Miller J., On-board Cloud Contamination Detection with Atmospheric Correction, Papers of Earth Science Technology Conference, 2002, 3 p.
- El-Araby E., Taher M., El-Ghazawi T., Moigne J., An Efficient Implementation of Automatic Cloud Cover Assessment (ACCA) on a Reconfigurable Computer, Proceedings of the 2005 Earth-Sun System Technology Conference, 2005, 5 p.
- Griffin M.K., Hsu S.M., Burke H.K., Orloff S.M., Upham C.A., Examples of EO-1 Hyperion Data Analysis, Lincoln laboratory journal, 2005, Vol. 15, No. 2, pp. 271–298.