Vegetation in recognition of changes in earth remote sensing images

• Autorzy: Areshkina L.
• Języki publikacji: EN

Abstrakty

EN

The method has been developed for recognition of changes, caused by vegetation, using the Earth remote sensing data obtained at different points of time. The method includes automatic calculation of brightness groups in segments of changes for each range in the multizonal image. Also, the problem of the spatial multispectral decomposition is resolved with regard to the areas of changes caused by vegetation, with the automatic selection of the object's components homogeneous in terms of their reflection properties.

Słowa kluczowe

EN

vegetation; calculation; changes

PL

wegetacja; obliczenia; zmiany

• Wydawca: Sieć Badawcza Łukasiewicz - Poznański Instytut Technologiczny
• Czasopismo: Journal of Research and Applications in Agricultural Engineering
• Rocznik: 2011
• Tom: Vol. 56, nr 3
• Strony: 7--14
• Opis fizyczny: Bibliogr. 13 poz.

Twórcy

autor

Areshkina L.

• United Institute of Informatics Problems, NAS of Belarus, 6 Surganova str., Minsk, 220012, Belarus,

Bibliografia

• [1] Savin I.Yu., Lupyan E.A., Bartalev S.A.: Operating satellite monitoring of the agricultural crops condition in Russia. Geomatics, 2011, № 2, p. 69-76.
• [2] Devyatova N.V., Ershov D.V.: МODIS/ТЕRRA imagery in the monitoring of the insect pest outbreaks. Modern problems of the Earth remote sensing from the space. Vol. II. Moscow, 2005. p. 262-266.
• [3] Cherepanov A.S., Druzhinina E.G.: Vegetation spectral properties and vegetation indices. Geomatics №3, 2009, p. 28-32.
• [4] Lupyan E.A., Mazurov A.A., Nazirov R.R., Proshin A.A., Flitman E.V., Krasheninnikova Yu.S.: Technologies for the design of the information systems for the remote monitoring. Modern problems of the Earth remote sensing from the space, 2011, Vol. 8, №1, p.26-43.
• [5] Belozerskii L. A., Oreshkina L.V.: Estimation of the Informative Content of Histograms of Satellite Images in the Recognition of Changes in Local Objects. Pattern Recognition and image Analysis, 2010, Vol. 20, No. 1, p. 65-72.
• [6] Belozerskii L. A., Areshkina L.V.: Principles of the selective brightness-based segmentation of changes of appearance for the object of the monospectral satellite imagery. Artificial intelligence, 2009, №3, p. 395-408.
• [7] Singh, A.: Digital change detection techniques using remotely-sensed data. International Journal of Remote Sensing, 1989, 10(6), p.989-1003.
• [8] Lu D., Mausel P. et al.: Change detection techniques. Int. J. Rem. Sens., 2004, Vol. 25, №12, p. 2365-2407.
• [9] Belozerskyy L.A., Areshkina L.V.: Histograms of satellite images and status of objects / Belozerskyy L.A., Areshkina L.V.: International Conference on Neural Networks and Artificial Intelligence ICNNAI'2008. May 27-30, 2008, Minsk, Belarus, p. 193-197.
• [10] Richard J., Radke S.A., Omar, A.K., Badrinath, R.: Image Change Detection Algorithms: A Systematic Survey, IEEE Transactions on Image Processing, 2005, 14(3), p.294-307.
• [11] Areshkina L.V.: Using the different-time satellite imagery for detection of changes of appearance of the monitoring objects / Areshkina L.V.: Proc. of the International scientific and technical conference. Donetsk: Nauka i Osvita Institute: 2010. p. 331-335.
• [12] Vygotskaya N.N., Gorshkova I..I.: Theory and experiment in the remote vegetation researches. Gidrometeoizdat Publ., Leningrad, 1987, p. 249.
• [13] Legend for NDVI images [Electronic data]. Mode of access: http://kaluga.infospace.ru/kaluga/html/legend.html - Date of access: July 30, 2011.