Individual tree crown delineation from high-resolution UAV images in broadleaf forest

Miraki, Mojdeh; Sohrabi, Hormoz; Fatehi, P; Kneubuehler, M.

doi:10.1016/j.ecoinf.2020.101207

Cited by 71 publications

(38 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The delineation of Fabas forest (mixed forest) was better than that of Bernadouze forest (beech forest) and La Massane forest (multi-species broadleaf dominant forest) using the MCG-Tree method. This result is in agreement with some studies that compared results for delineation of different tree types [18,64,65]. However, in addition, our method is able to adapt criteria based on crown characteristics related to the tree type, thereby reducing the disparity between different forest applications.…”

Section: Mcg-tree Adaptability To Multi-sitessupporting

confidence: 91%

Individual Tree Crown Delineation Method Based on Multi-Criteria Graph Using Geometric and Spectral Information: Application to Several Temperate Forest Sites

Deluzet¹,

Erudel²,

Briottet³

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

Individual tree crown (ITC) delineation in temperate forests is challenging owing to the presence of broadleaved species with overlapping crowns. Mixed coniferous/deciduous forests with characteristics that differ with the type of tree thus require a flexible method of delineation. The ITC delineation method based on the multi-criteria graph (MCG-Tree) addresses this problem in temperate monospecific or mixed forests by combining geometric and spectral information. The method was used to segment trees in three temperate forest sites with different characteristics (tree types, species distribution, planted or natural forest). Compared with a state-of-the-art watershed segmentation approach, our method increased delineation performance by up to 25%. Our results showed that the main geometric criterion to improve delineation quality is related to the crown radius (performance improvement around 8%). Coniferous/deciduous classification automatically adapts the MCG-Tree criteria to the type of tree. Promising results are then obtained to improve delineation performance for mixed forests.

show abstract

Section: Mcg-tree Adaptability To Multi-sitessupporting

confidence: 91%

Individual Tree Crown Delineation Method Based on Multi-Criteria Graph Using Geometric and Spectral Information: Application to Several Temperate Forest Sites

Deluzet¹,

Erudel²,

Briottet³

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Considering that spatial variation between areas dominated by one species group or admixtures of the two species is continuous, the main strength of the proposed approach is to reduce as much as possible the elements of subjectivity in the delineation of boundaries between the three examined forest types, the main limit of the photointerpretation method, taking full advantage of multi-resolution segmentation potential. It is worth noting that, in the currently growing scientific literature reporting advances in the use of VHR imagery for forest type delineation [53,54], this study has demonstrated that the use of a simple and cheap single date image, despite its limited spectral resolution, allowed accurate mapping of mixed stands on the MMU of 500 m 2 .…”

Section: Discussionmentioning

confidence: 82%

Object Oriented Classification for Mapping Mixed and Pure Forest Stands Using Very-High Resolution Imagery

et al. 2021

View full text Add to dashboard Cite

The importance of mixed forests is increasingly recognized on a scientific level, due to their greater productivity and efficiency in resource use, compared to pure stands. However, a reliable quantification of the actual spatial extent of mixed stands on a fine spatial scale is still lacking. Indeed, classification and mapping of mixed populations, especially with semi-automatic procedures, has been a challenging issue up to date. The main objective of this study is to evaluate the potential of Object-Based Image Analysis (OBIA) and Very-High-Resolution imagery (VHR) to detect and map mixed forests of broadleaves and coniferous trees with a Minimum Mapping Unit (MMU) of 500 m2. This study evaluates segmentation-based classification paired with non-parametric method K- nearest-neighbors (K-NN), trained with a dataset independent from the validation one. The forest area mapped as mixed forest canopies in the study area amounts to 11%, with an overall accuracy being equal to 85% and K of 0.78. Better levels of user and producer accuracies (85–93%) are reached in conifer and broadleaved dominated stands. The study findings demonstrate that the very high resolution images (0.20 m of spatial resolutions) can be reliably used to detect the fine-grained pattern of rare mixed forests, thus supporting the monitoring and management of forest resources also on fine spatial scales.

show abstract

“…Last year, the popularity of UAVs increased, and many applications are explored and described. Speci cally, UAVs equipped with various cameras was successfully used for counting trees and measuring their heights and crowns (Ferreira et al, 2020;Miraki et al, 2021;Mohan et al, 2017). This paper compares widespread ready-made solutions for counting the trees and measuring their crown diameter.…”

Section: Discussionmentioning

confidence: 99%

The Potential of Widespread Ready-Made UAVs in Quantifying Conifers and Delineating Their Crowns

Komárek

Klápště

Hrach

et al. 2021

Preprint

View full text Add to dashboard Cite

With the ever-improving Earth observation capabilities, variables such as tree health status, biomass storage, or stand structure are increasingly estimated through remote sensing. While many protocols of data acquisition and satellite data processing are in place, the still novel unmanned aerial vehicles (UAVs) face some challenges during data acquisition and processing. While tree height extraction seems to be a common practice, identifying individual trees and measuring their crowns is still quite tricky. We performed several flights with three different UAVs and four different popular sensors over two sites with coniferous forests of various ages at flight levels of 100–200 m above ground level (AGL) using custom settings preset by UAV solution suppliers. Considering the success rate of the individual tree identification, casual RGB cameras provided more consistent results at all flight levels (84 − 77% for Phantom 4), while the success of tree identification decreases with higher flight levels and smaller crowns in the case of multispectral cameras (77 − 54% for RedEdge-M). In general, RGB cameras yielded the best results at 150 m AGL while multispectral cameras at 100 m AGL. Regarding the accuracy of the measured crown diameters, most datasets tended to overestimate when using automatic crown delineation within the lidR package. Only RGB cameras yielded satisfactory results (Mean Absolute Error – MAE of 0.79–0.99 m and 0.88–1.16 m for Phantom 4 and Zenmuse X5S, respectively). Multispectral cameras overestimated more than RGB cameras, especially in the full-grown forest (MAE = 1.26–1.77 m); on the other hand, they offered, in addition to the structural, also spectral information. We conclude that widespread ready-made solutions mounted with low-cost RGB cameras yield very satisfactory results for describing the structural forest information at 150 m AGL. When (multi)spectral information is needed, we recommend reducing the flight level to 100 m AGL to acquire sufficient structural forest information.

show abstract

Individual tree crown delineation from high-resolution UAV images in broadleaf forest

Cited by 71 publications

References 43 publications

Individual Tree Crown Delineation Method Based on Multi-Criteria Graph Using Geometric and Spectral Information: Application to Several Temperate Forest Sites

Individual Tree Crown Delineation Method Based on Multi-Criteria Graph Using Geometric and Spectral Information: Application to Several Temperate Forest Sites

Object Oriented Classification for Mapping Mixed and Pure Forest Stands Using Very-High Resolution Imagery

The Potential of Widespread Ready-Made UAVs in Quantifying Conifers and Delineating Their Crowns

Contact Info

Product

Resources

About