Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

Autor: Ninni Saarinen, Mikko Vastaranta, Roope Näsi, Tomi Rosnell, Teemu Hakala, Eija Honkavaara, Michael A. Wulder, Ville Luoma, Antonio M. G. Tommaselli, Nilton N. Imai, Eduardo A. W. Ribeiro, Raul B. Guimarães, Markus Holopainen, Juha Hyyppä

Publikováno v: Remote Sensing, Vol 10, Iss 2, p 338 (2018)

Forests are the most diverse terrestrial ecosystems and their biological diversity includes trees, but also other plants, animals, and micro-organisms. One-third of the forested land is in boreal zone; therefore, changes in biological diversity in bo

Externí odkaz: https://doaj.org/article/a9fb72cbd0d847b3b81a883af5ba7a7c

Band registration of tuneable frame format hyperspectral UAV imagers in complex scenes

Autor: Raquel Alves de Oliveira, Antonio Maria Garcia Tommaselli, Tomi Rosnell, Eija Honkavaara

Publikováno v: Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP

Made available in DSpace on 2018-12-11T17:15:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-12-01 Tekes Academy of Finland A recent revolution in miniaturised sensor technology has provided markets with novel hyperspectral imagers operatin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40278eb52e7aa2b28f64dee6a6da0633
https://doi.org/10.1016/j.isprsjprs.2017.10.014

Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV)

Autor: Rami Mannila, Christer Holmlund, Harri Ojanen, Eija Honkavaara, Heikki Saari, Niko Viljanen, Merja Pulkkanen, Tomi Rosnell, Matti A. Eskelinen, Teemu Hakala, Paula Litkey, Ilkka Pölönen

Publikováno v: Honkavaara, E, Eskelinen, M A, Pölönen, I, Saari, H, Ojanen, H, Mannila, R, Holmlund, C, Hakala, T, Litkey, P, Rosnell, T, Viljanen, N & Pulkkanen, M 2016, ' Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small Unmanned Airborne Vehicle (UAV) ', IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 9, pp. 5440-5454 . https://doi.org/10.1109/TGRS.2016.2565471

Miniaturized hyperspectral imaging sensors are becoming available to small unmanned airborne vehicle (UAV) platforms. Imaging concepts based on frame format offer an attractive alternative to conventional hyperspectral pushbroom scanners because they

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db68835d58c696243b239db37fca7e69
https://doi.org/10.1109/tgrs.2016.2565471

HYPERSPECTRAL REFLECTANCE SIGNATURES AND POINT CLOUDS FOR PRECISION AGRICULTURE BY LIGHT WEIGHT UAV IMAGING SYSTEM

Autor: Heikki Saari, Lauri Marklelin, Jussi Mäkynen, Ismo Pellikka, Tomi Rosnell, Liisa Pesonen, Heikki Salo, Jere Kaivosoja, Eija Honkavaara, Teemu Hakala

Publikováno v: Honkavaara, E, Kaivosoja, J, Mäkynen, J, Pellikka, I, Pesonen, L, Saari, H, Salo, H, Hakala, T, Marklelin, L & Rosnell, T 2012, Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system . in M Shortis, W Wagner & J Hyyppä (eds), XXII ISPRS Congress 2012 : Technical Commission VII . International Society for Photogrammetry and Remote Sensing ISPRS, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 1-7, pp. 353-358, 2012 XXII ISPRS Congress, Melbourne, Australia, 25/08/12 . https://doi.org/10.5194/isprsannals-I-7-353-2012
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol I-7, Pp 353-358 (2012)

The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76c5035739c75e38f6c5abaed798e313
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-7/353/2012/

Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle

Autor: Juha Hyyppä, Roope Näsi, Lauri Markelin, Tomi Rosnell, Mikko Vastaranta, Eija Honkavaara, Mohammad Imangholiloo, Teemu Hakala, Ninni Saarinen, Markus Holopainen

Publikováno v: Forests, Vol 10, Iss 5, p 415 (2019)
Forests
Volume 10
Issue 5

Seedling stands are mainly inventoried through field measurements, which are typically laborious, expensive and time-consuming due to high tree density and small tree size. In addition, operationally used sparse density airborne laser scanning (ALS)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7bddab4de3f2fb1e6c24b9525a57678
https://doi.org/10.3390/f10050415