Assessing object-oriented LiDAR metrics for characterizing bird habitat in a management perspective

Presentation cancelled by author

Assessing object-oriented LiDAR metrics for characterizing bird habitat in a management perspective

(Oral)

Anouk Glad
anouk.glad@irstea.fr

Univ. Grenoble Alpes, Irstea, UR LESSEM, 2 rue de la Papeterie-BP 76, F-38402 St-Martin-d'Hères, France
,
Björn Reineking
Univ. Grenoble Alpes, Irstea, UR LESSEM, 2 rue de la Papeterie-BP 76, F-38402 St-Martin-d'Hères, France, France
,
Jean-Matthieu Monnet
Université Grenoble Alpes, Irstea, UR LESSEM, Centre de Grenoble, 2 rue de la Papeterie-BP 76, F-38402 St-Martin-d'Hères, France, France

DOI: 10.17011/conference/eccb2018/108124

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Light Detection and Ranging (LiDAR) provides detailed information on the three dimensional structure of the environment, and is increasingly used in habitat modeling for a wide variety of species including birds. LiDAR has been shown to improve predictive performance of species distribution models. It is recommended that explanatory variables in habitat models should be meaningful from the species point of view in order to best explain species distribution within a landscape [2]. However, is good predictive performance of a habitat suitability model sufficient to impact local conservation actions? In order to take appropriate and more efficient management decisions, we hypothesize that the metrics explaining the species distribution need to be also meaningful for managers. Some LiDAR point clouds metrics such as the standard-deviation of penetration ratio between 0.5-10m [1] are not easy to interpret. However, metrics extracted using object-oriented methods may fill this gap by giving metrics based on existing landscape components. Instead of calculating metrics over a surface unit (the pixel), an object-based classification group together neighboring points because they belong to the same overall structure which define an object type (tree, road, building, gap).
The aim of this study is to improve forest management planning by using LiDAR predictors meaningful for both the species and managers. We are here focusing on the case of the Capercaillie (Tetrao urogallus), an avian species of conservation concern occurring in the French Jura Mountains. Capercaillies favor old mixed forest with a mosaic of structurally different habitats (gap openings, moderate canopy cover area, isolated resting trees, presence of shelters) and the species is threatened by habitat loss and degradation. Habitat restoration planning is thus a fundamental aspect of species conservation actions.
We extracted a range of object-oriented metrics from LiDAR datasets, defined with the support of conservation experts and forest managers. We then compare habitat suitability models based on inhomogeneous point process models, such as Maxent, fitted with either commonly used “points cloud” or new “object-oriented” LiDAR metrics.
Preliminary results indicate that both categories of metrics yield similarly accurate predictions of Capercaillie habitat suitability. Thus, we hope that the use of object-oriented metrics, with their likely improved interpretability, will allow for more practical recommendations supporting forest management planning in favor of Capercaillie conservation.

[1] Bae, Soyeon, Bjoern Reineking, Michael Ewald, and Joerg Mueller. 2014. “Comparison of Airborne Lidar, Aerial Photography, and Field Surveys to Model the Habitat Suitability of a Cryptic Forest Species–the Hazel Grouse.” International Journal of Remote Sensing 35 (17): 6469–89.
[2] Johnson, Chris J, and Michael P Gillingham. 2005.

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INTRO:
When conserving species that conflict directly with economic human interests it is important and beneficial to put a lot of effort to take both sides into consideration when planning actions. In this case the authors aimed to develop the usage of LiDAR data for both Capercaillie conservation purposes and forest management planning. The authors approach the question with habitat suitability modelling combined with object observation technique instead of using metrics over a surface unit.
MERITS:
The idea is good and important because different Earth observation datas are more and more available and the possibilities, weaknesses etc. should be studied more. The research is related to real life challenges such as land use conflict between humans and wild life species and it brings this decision making challenge for bigger audience to see. Research starts from the usable everyday life level and brings ideas and views to continue with.
CRITIQUE:
I demand that the authors should have explained more detailed the data and methods used. Since the aim of the study is to improve forest management planning in a conservation perspective it's is very difficult to assess the methodology used if reader doesn't have any idea what is for example the sampling density of the LiDAR data and the other comparable datas, how well did these datas and modelling work when compared to real data and last but not least: if the main way to conserve Capercaillie is to do habitat restoration how would it really help the species if you can predict good habitat suitability for the species and not to identify new restoration places. Of course the conservation needs to start from the places where the bird still exists but this abstract leaves reader with an open question is it really about new conservation areas, habitat restoration or something else. As an addition I didn't get the idea how did the message and the contradicting needs of people representing forest management were taken into consideration in the planning process.
DISCUSSION:
When doing research for practical purposes (both in forest management and effective species conservation) with datas such as LiDAR there are many possible ways to find a dead end. The study area might be too small or theoretical, habitat suitability models have their weaknesses, collection of data can be too expensive or time demanding for real life entities, or research questions do not meet the requirements of the original problem. I see all these as possible threats here, but if that's not the case I wish this could be explained more carefully in the abstract.