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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 5, pp. 174-182

Individual tree logging detection by shadows in Geoton sensor imagery of the Resurs-P satellite

A.I. Alexanin 1 , V. Kim 1 , M.A. Morozov 1 , E.V. Fomin 1 
1 Institute of Automation and Control Processes FEB RAS, Vladivostok, Russia
Accepted: 05.08.2019
DOI: 10.21046/2070-7401-2019-16-5-174-182
The problem of automatic detection of individual tree logging in Geoton sensor imagery (spatial resolution 0.7 m) of the Resurs-P satellite is considered. The logging of individual trees in the forest with a dense forest canopy is accompanied by the appearance of a shaded area in the place of logging. The logged trees open access to the sun for other trees, which increases significantly their brightness on the images. Such a pattern of brightness changes in a continuous forest canopy is used to determine logging sites. Using the procedure of image registration with pixel accuracy, it is possible to analyze the anomalies of brightness in a sequence of images by comparing them with each other. Numerous anomalies are detected in a pair of images. A comparison with previous anomalies leaves only those newly appeared. There are relatively few newly appeared anomalies, and the patterns of high and low brightness anomalies make it possible to confidently detect logging sites. An algorithm for detection of individual tree logging is considered, and its work is examined by an example of detected illegal logging during forest area monitoring carried out at the request of the Administration of Primorsky Krai. The issues of the influence of sensor orientation variability and inaccuracies of image registration are discussed. Logging sizes that can confidently be identified are estimated.
Keywords: Resurs-P, Geoton, individual tree logging, analysis of tree shadows
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References:

  1. Aleksanin A. I., Krasnopeev S. M., Morozov M. A., Fomin E. V., Sovmeshchenie izobrazhenii s rossiiskikh sputnikov Resurs-P (Resurs-P satellites image registration), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 1, pp. 18–28.
  2. Aleksanin A. I., Morozov M. A., Fomin E. V., Problemy sovmeshcheniya izobrazhenii s piksel’noi tochnost’yu (Problems of image registration with subpixel accuracy), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 1, pp. 9–16.
  3. Bartalev S. A., Kuryatnikova T. S., Stibig H.-J., Metody ispol’zovaniya vremennykh serii sputnikovykh izobrazhenii vysokogo prostranstvennogo razresheniya dlya otsenki masshtabov i dinamiki vyrubok taezhnykh lesov (Methods for the analysis of time-series of high-resolution satellite images for the assessment of logging in the taiga), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2005, Vol. 2, No. 2, pp. 217–227.
  4. Bartalev S. A., Egorov V. A., Zharko V. O., Loupian E. A., Plotnikov D. E., Khvostikov S. A., Shabanov N. V., Sputnikovoe kartografirovanie rastitel’nogo pokrova Rossii (Satellite mapping of the vegetation cover over Russia), Moscow: IKI RAN, 2016, 208 p.
  5. Borzov S. M., Potaturkin O. I., Obnaruzhenie vyborochnykh rubok lesa po dannym distantsionnykh izmerenii vysokogo prostranstvennogo razresheniya (Detection of selective forest logging based on high-resolution remote sensing data), Issledovanie Zemli iz kosmosa, 2014, No. 4, pp. 87–93.
  6. Das S., Aery A., A review: shadow detection and shadow removal from images, Intern. J. Engineering and Technology, 2013, Vol. 4, No. 5, pp. 1764–1767.
  7. Miettinen J., Stibig H.-J., Achard F., Remote sensing of forest degradation in Southeast Asia-Aiminig for a regional view through 5–30 m satellite data, Global Ecology and Conservation, 2014, No. 2, pp. 24–36.
  8. Shahtahmassebi A., Ning Ya., Ke W., Moore N., Zhangquan S., Review of shadow detection and de-shadowing methods in remote sensing, Chinese Geographical Science, 2013, Vol. 23, No. 4, pp. 403–420.
  9. Wijaya A., Application of Multi-stage Classification to Detect Illegal Logging with the Use of Multi-source Data: A Case Study in Labanan Forest Management Unit, East Kalimantan, Indonesia, ITC, 2005, 64 p.