Analysis of Using Dense Image Matching Techniques to Study the Process of Secondary Succession in Non-Forest Natura 2000 Habitats

Katarzyna Osińska-Skotak,Dorota Michalska-Hejduk,Łukasz Jełowicki,Justyna Wylazłowska,Dominik Kopeć,Krzysztof Bakuła

doi:10.3390/rs11080893

Katarzyna Osińska-Skotak, Dorota Michalska-Hejduk + Show 4 more

Open Access

https://doi.org/10.3390/rs11080893

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Abstract

Secondary succession is considered a threat to non-forest Natura 2000 habitats. Currently available data and techniques such as airborne laser scanning (ALS) data processing can be used to study this process. Thanks to these techniques, information about the spatial extent and the height of research objects—trees and shrubs—can be obtained. However, only archival aerial photographs can be used to conduct analyses of the stage of succession process that took place in the 1960s or 1970s. On their basis, the extent of trees and shrubs can be determined using photointerpretation, but height information requires stereoscopic measurements. State-of-the-art dense image matching (DIM) algorithms provide the ability to automate this process and create digital surface models (DSMs) that are much more detailed than ones obtained using image matching techniques developed a dozen years ago. This research was part of the HabitARS project on the Ostoja Olsztyńsko-Mirowska Natura 2000 protected site (PLH240015). The source data included archival aerial photographs (analogue and digital) acquired from various phenological periods from 1971–2015, ALS data from 2016, and data from botanical campaigns. First, using the DIM algorithms, point clouds were generated and converted to DSMs. Heights interpolated from the DSMs were compared with stereoscopic measurements (1971–2012) and ALS data (2016). Then, the effectiveness of tree and shrub detection was analysed, considering the relationship between the date and the parameters of aerial images acquisition and DIM effects. The results showed that DIM can be used successfully in tree and shrub detection and monitoring, but the source images must meet certain conditions related to their quality. Based on the extensive material analysed, the detection of small trees and shrubs in aerial photographs must have a scale greater than 1:13,000 or a 25 cm GSD (Ground Sample Distance) at most, an image acquisition date from June–September (the period of full foliage in Poland), and good radiometric quality.

Highlights

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One of the most significant features of airborne laser scanning (ALS) is that the laser beam (LIDAR technology) can penetrate the canopy, enabling measurements under the treetops. This feature allows for simultaneously obtaining a digital surface model (DSM) and digital terrain model (DTM), allowing for a canopy height model (CHM) generation named, as a normalized digital surface model
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Summary

Introduction

KKeyeywwoordrds:s:hhaabbitiatat tththreraetast;s;sesceoconnddaaryrysusucccecsessisoionn; ;trtereeeddeteetcetcitoiaonn;2;d5decnemnsesGeimSimDaga(geGemromautanctdhchinSiangmg; ;apralcerhcDhiviivasltaalnce) at most, an aeareirailapl phhotootgorgarpaphhs;sD; DSMSM; L; LIDIDAARR (the period of full foliage in Poland), and good radiom. Cessation of mowing or grazing causes species with clonal growth to complete their full development and induce changes in the quantitative and spatial structure of plant communities [12] The results of this process are the disappearance of some species groups (e.g., heliophilous) and the formation of shrub and forest communities created by species more adapted to poor light conditions. It is of great importance since it allows for tree segmentation [21], vegetation succession assessment [22], and biomass estimation [23] It can be obtained in the field by forest management planners; these measurements are very time consuming and are performed mostly on inventory plots [24]. Historical monitoring of past forest states using LIDAR is practically impossible [27]

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