Halme , E , Ihalainen , O , Korpela , I & Mõttus , M 2022 , ' Assessing spatial variability and estimating mean crown diameter in boreal forests using variograms and amplitude spectra of very-high-resolution remote sensing data ' , International Journal of Remote Sensing , vol. 43 , no. 1 , pp. 349-369 . https://doi.org/10.1080/01431161.2021.2018148
Title: | Assessing spatial variability and estimating mean crown diameter in boreal forests using variograms and amplitude spectra of very-high-resolution remote sensing data |
Author: | Halme, Eelis; Ihalainen, Olli; Korpela, Ilkka; Mõttus, Matti |
Contributor organization: | Faculty of Science Department of Forest Sciences Ilkka Korpela / Principal Investigator Forest Ecology and Management Department of Geosciences and Geography |
Date: | 2022-01-02 |
Language: | eng |
Number of pages: | 21 |
Belongs to series: | International Journal of Remote Sensing |
ISSN: | 0143-1161 |
DOI: | https://doi.org/10.1080/01431161.2021.2018148 |
URI: | http://hdl.handle.net/10138/340789 |
Abstract: | The retrieval of forest variables from optical remote sensing data using physically-based models is an ill-posed problem and does not make full use of the high spatial resolution imagery that is becoming available globally. A possible solution to this is to use prior information about the retrieved variables, which constrains the possible solutions and reduces uncertainty in forest variable estimation. Therefore, we tried to quantify physically-based parameters that could be retrieved using the second-order statistics of measured and simulated very-high-resolution (pixel size less than 1 m) images of Finnish boreal forests. These forests have a well-defined structure and are usually not closed, i.e. the reflected signal has a considerable contribution from a green forest floor. We retrieved the second-order statistics using variograms and Fourier amplitude spectra. We found, in line with previous studies, that the range of variograms correlates well (r = 0.83) with the mean crown diameter for spatially homogeneous forest patches, and it can be used to estimate crown diameters with reasonable accuracy (RMSE = 0.42 m). We present a novel approach, which uses the Fourier amplitude spectrum to study the spatial structure of a forest. The approach provided encouraging results with the measured data: despite the lower accuracy (RMSE = 0.67 m) compared with variograms, we found that it could also be used to estimate mean crown diameters for heterogeneous forest areas. The Fourier amplitude spectrum approach did not work with the simulated images. Our results highlight the possibility to obtain further information from very-high-resolution images of forests to solve the ill-posed problem of forest variable estimation from optical remote sensing data using physically-based models. |
Description: | Funding Information: This work was supported by the Academy of Finland under Grant [317387]. We would like to acknowledge assistance from the University of Helsinki and Ilkka Korpela for providing us with the field measured tree data from Hyyti?l?. Publisher Copyright: © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. |
Subject: |
TREE SPECIES CLASSIFICATION
TEXTURAL ORDINATION BIOMASS EQUATIONS STAND IMAGERY SEMIVARIOGRAM PARAMETERS VEGETATION CLIMATE LIDAR 4112 Forestry |
Peer reviewed: | Yes |
Rights: | cc_by |
Usage restriction: | openAccess |
Self-archived version: | publishedVersion |
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