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Indian Journal of Pharmaceutical Education and ResearchNOW IN
Article

Development of Geospatial Model for Preparing Distribution of Rare Plant Resources Using UAV/Drone

Takashi Watanabe1,2, Aedla Raju1,3★, Yasuhide Hiraga1,4, Koji Sugimura1,2★ Corresponding author

  1. 1Department of Medicinal Plant, School of Pharmacy, Kumamoto University, 5-1 Oe-honmachi, Kumamoto 862-0973, Kumamoto, JAPAN.
  2. 2School of Pharmacy, Joint Research Laboratory of Agro-medicine for the Innovation of Agriculture, Kumamoto University, 5-1 Oe-honmachi, Kumamoto 862-0973, Kumamoto, JAPAN.
  3. 3Graduate School of Science and Technology (GSST), Kumamoto University, 2-39-1, Kurokami, Kumamoto, 860-8555, JAPAN.
  4. 4Hirata Corporation, 111 Hitotsugi, Ueki, Kita, Kumamoto, 861-0198, JAPAN.

CORRESPONDENCE

Aedla Raju

Department of Medicinal Plant, School of Pharmacy, Kumamoto University, 5-1 Oe-honmachi, Kumamoto 862-0973, Kumamoto, JAPAN.

rajuaedla.nitk@gmail.com

Received: 30-08-2017; Revised: 17-11-2017; Accepted: 23-11-2017.

Volume 52, Issue 4S · pp. s146–s150 · PUBLISHED 2018 · DOI: 10.5530/ijper.52.4s.91

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ABSTRACT

Background: The study of functioning of ecosystems is significant with understanding the composition and distribution of plant resources at spatial and temporal scales. For comprehensive plant survey, the traditional methods are not accurate and it’s not possible at inaccessible areas. The remote sensing techniques with GIS and GPS are more helpful in acquiring the information in less time with more frequency at multiple altitudes. Objective: This study was proposed a remote sensing, image processing and GIS based an integrated geospatial model for identifying the rare plant resources using DJI Inspire 2 drone images. Methods: The drone images were pre-processed with band alignment, ortho-rectification and mosaicking and then enhanced using histogram equalization technique. The enhanced image was classified and analysed to generate the final distribution map. Results: The perfect zones of rare plant resources were identified from the enhanced image and the supervised classification has resulted accurate grouping of the plant resources. The weighted overlay analysis with soil data provided efficiently categorized the plant resources zones. Conclusion: The developed geospatial model was more efficient method for identification of plant resources. With additional developed remote sensing and image processing techniques, this model can provide automatic detection of plant resources based on spectral reflectance of the plants at different bands. To achieve this, the high resolution multi-spectral drone images are more appropriate.

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    Watanabe, T., Raju, A., Hiraga, Y., & Sugimura, K. (2018). Development of Geospatial Model for Preparing Distribution of Rare Plant Resources Using UAV/Drone. Indian Journal of Pharmaceutical Education and Research, 52(4S), s146–s150. https://doi.org/10.5530/ijper.52.4s.91