FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection

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Tarih

2020-08-02

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Yayıncı

Taylor and Francis Ltd.

Erişim Hakkı

info:eu-repo/semantics/closedAccess

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Özet

A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.

Açıklama

Anahtar Kelimeler

3D, Co-registration, Deforestation, DSM generation, Image matching, Orientation, VHR satellite imagery, Volumetric change detection, Volume precision

Kaynak

International Journal of Digital Earth

WoS Q Değeri

Q1
Q1

Scopus Q Değeri

Q1

Cilt

13

Sayı

8

Künye

Stylianidis, E., Akça, M. D., Poli, D., Hofer, M., Gruen, A., Sanchez Martin, V., . . .& Garcia, A. (2019). FORSAT: A 3D forest monitoring system for cover mapping and volumetric 3D change detection. International Journal of Digital Earth, 13(8), 854-885. doi:10.1080/17538947.2019.1585975