Informativity of Earth remote sensing optical bands: practical algorithms

1Stankevich, SA
1State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine
Kosm. nauka tehnol. 2008, 14 ;(2):22-27
https://doi.org/10.15407/knit2008.02.022
Publication Language: Russian
Abstract: 
The algorithms for practical evaluation of informativity of Earth remote sensing optical bands using spectral responses of landscape standard objects and atmosphere are presented. We give quantitative estimations of informativity of optical spectral bands in solving unified thematic tasks. This can be useful for the elaboration of new satellite sensors and for configuring of existing ones.
Keywords: algorithms, informativity, remote sensing
References: 
1. Lyalko V. I., Popov M. O. (Eds) Multispectral remote sensing in nature management, 360 p. (Nauk.dumka, Kyiv, 2006) [in Ukrainian].
2. Kononov V. I. Basis of a technique for determining the resolution of aerospace systems with discrete photodetectors. Kosm. nauka tehnol., 8 (2-3), 91 — 102 (2002) [in Russian].
3. Kononov V. I., Stankevich S. A. Digital Aerospace Images with High and Low Resolution Informativity Comparative Evaluation. Scientific Notes of Taurida National V.I. Vernadsky University, 17 (2), 88—95 (2004) [in Russian].
4. Kriksunov L. Z. Handbook on the  Foundations of Infrared Equipment, 400 p. (Sov. Radio, Moscow, 1978) [in Russian].
5. Popov M. A., Stankevich S. A. Methods for optimizing the number of spectral channels in problems of processing and analysis of remote sensing data. In: Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, Is. 3, Vol. 1, 106—112 (IKI RAN, Moscow, 2006) [in Russian].
6. Sivyakov I. N. Calculating the resolution of optoelectronic systems. Opticheskij zhurn., 65 (2), 60—63 (1998) [in Russian].
7. Stankevych S. A. Static Aspects of the Vision of Functions Transferring Modulation of Aerocosmic and Systemic Systems with Discrete Photodetectors. In: Suchasni dosjagnennja geodezychnoi' nauky ta vyrobnyctva, Is. II, 142—147 (L'vivs'ka Politehnika, Lviv, 2005) [in Ukrainian].
8. Stankevich S. A. Probabilistic-frequency evaluation of equivalent spatial resolution for multispectral aerospace images. Kosm. nauka tehnol., 12 (2-3), 79—82 (2006) [in Ukrainian].
9. Stankevich S. A. The quantitative evaluation of the informativity of hyperspectral aerospace imagery on the solution of remote-sensing thematic tasks. Reports of the National Academy of Sciences of Ukraine, No. 10, 136—139 (2006) [in Ukrainian].
10. Stankevich S. A. Hyperspectral aerospace imagery spectral bands optimal selection in solving remote sensing thematic tasks. Kosm. nauka tehnol., 13 (2), 25—28 (2007) [in Russian].
https://doi.org/10.15407/knit2007.02.025
11. Stankevich S. A., Sholonik O. V. Adaptive multidimensional probabilistic transformation for multispectral digital aerospace images. Earth and Space Sciences for Society: Proc. of the 1st Scientific Conference. (CAKIZ, Kiev, 2007) [in Russian].
12. Fedorovsky O. D., Yakymchuk V.G. Simulation of the information acquisition process by space-based systems of Earth sensing. Geoinformatika, No. 1, 41—48 (2005) [in Ukrainian].
13. Fukunaga K. Introduction to statistical pattern recognition, Transl. from Eng., 368 p. (Nauka, Moscow, 1979) [in Russian].

14. Staenz K., Seeker J., Gao B.-C., et al. Radiative transfer codes applied to hyperspectral data for the retrieval of surface reflectance. ISPRS J. Photogrammetry and Remote Sensing, 57 (3), 194—203 (2002).