The Importance of CIR Aerial Imagery in Inventory, Monitoring and Predicting Forest Condition

Kolić, Jelena; Pernar, Renata; Seletković, Ante; Ančić, Mario

doi:10.15177/seefor.15-18

Cited by 2 publications

(4 citation statements)

References 3 publications

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“…A comparison of the results of WV2 satellite imagery and satellite images taken from Google Earth (from 2014 and 2016) denoted a change in the tree health status, which confirms that satellite imagery can serve to inventory and track the condition in an area over a number of years. Field investigations and the assessment of tree health status confirmed the results obtained by satellite imagery interpretation, but also indicated that the future condition of stands can be predicted on the basis of the images [16,20]. Images taken in different years are a good starting point for predicting the condition in the field for a certain period, which is a prerequisite for good planning.…”

Section: Resultssupporting

confidence: 55%

“…After delineation, a systematic sample of 25x25 m was laid over the stratum to help interpret the tree health status (Figure 2). At each point of a grid (2982 points), 2 nearest trees (crowns) were estimated and damage indicators (damage -O, mean damage -SO, damage index -IO, mean damage 1 -SO 1 ) [16] were calculated for individual tree species, and for all the interpreted species together.…”

Section: Methodsmentioning

confidence: 99%

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Monitoring the Health Status of Trees in Maksimir Forest Park Using Remote Sensing Methods

Zagoranski¹,

Pernar

Seletković

et al. 2018

SEEFOR

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Section: Resultssupporting

confidence: 55%

Section: Methodsmentioning

confidence: 99%

Monitoring the Health Status of Trees in Maksimir Forest Park Using Remote Sensing Methods

Zagoranski¹,

Pernar

Seletković

et al. 2018

SEEFOR

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“…Therefore, timely location of stands with poorer health is necessary so that appropriate measures can be applied to maintain their vitality and productivity at an optimal level. CIR aerial photographs allow an insight into the field condition over a short period [36].…”

Section: Discussionmentioning

confidence: 99%

“…Multispectral images have also been successfully used for mapping individual forest stands [29,30], for crown reconstruction and individual tree phenotyping [31,32], for identification of tree species [33,34] and for determining the health status [15,18,[35][36][37][38][39][40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Determining the Optimal Sample Size for Assessing Crown Damage on Color Infrared (CIR) Aerial Photographs

Kolić,

Pernar,

Seletković

et al. 2023

Sustainability

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One of the priorities in sustainable forest management is monitoring the health status of trees and stands. From the aspect of remote sensing (RS), the best way of doing this is by interpreting color infrared (CIR) aerial photographs; however, this raises the issue of sample size. For this reason, to apply this method in practice, it is indispensable to determine an appropriate sample size to ensure sufficient reliability of the health status assessment of trees in CIR aerial photographs. This research was conducted in lowland forests of pedunculate oak in Croatia. To determine damage in the photographs of the main tree species, a systematic sample with varying dot grid densities—100 × 100 m, 200 × 200 m, 300 × 300 m, 500 × 500 m, 1000 × 1000 m—was used with combinations of different numbers of interpreted trees per sample. Damage indicators were also calculated based on tree distributions obtained by interpreting four trees, two trees and one tree in different sample sizes. The results of the testing showed that there were no statistically significant differences between different sample densities and numbers of interpreted trees in relation to mean damage assessment. Regardless of the fact that there were no statistically significant differences during damage assessment, it was found that by lowering sample densities, starting with 200 × 200 m, the number of trees and the number of sample points per particular sub-compartment significantly decreased, and so did the desired accuracy. Consequently, the participation (distribution) of particular species and damage degrees in the sample were lost, which significantly affected the overall tree health assessment. In contrast, grid densities of 100 × 100 m with one interpreted tree at the raster point proved to be the optimal sample size. This confirms the fact found in earlier research, that is, that the selected sample should have several spatially well-distributed points with a smaller number of trees in the point, and samples with larger numbers of trees in a smaller number of points should be avoided.

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The Importance of CIR Aerial Imagery in Inventory, Monitoring and Predicting Forest Condition

Cited by 2 publications

References 3 publications

Monitoring the Health Status of Trees in Maksimir Forest Park Using Remote Sensing Methods

Monitoring the Health Status of Trees in Maksimir Forest Park Using Remote Sensing Methods

Determining the Optimal Sample Size for Assessing Crown Damage on Color Infrared (CIR) Aerial Photographs

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