Mapping secondary succession species in agricultural landscape with the use of hyperspectral and airborne laser scanning data
Aleksandra Radecka , Dorota Michalska-Hejduk , Katarzyna Osińska-Skotak , Adam Kania , Konrad Górski , Wojciech Ostrowski
AbstractSecondary succession is a process that is often observed taking place in former agricultural ecosystems. Its characteristics are especially important in protected areas, for the purposes of monitoring and protective measures. Effective mapping of succession is facilitated by the development of automated methodologies based on remote sensing data, which are capable of complementing traditional field research. The objective of this work is to determine whether the classification of high-resolution hyperspectral and light detection and ranging (LiDAR) data with the use of the random forest algorithm enables us to produce an accurate succession species map. First, feature extraction techniques are applied to 1-m hyperspectral images and a ∼7 point∕m2 dense point cloud. Minimum noise fraction layers and vegetation indices are calculated from the hyperspectral data and geometry related indices from the LiDAR data. Finally, the recursive feature elimination algorithm is applied to the combined dataset and the reference polygons to select the optimal set of features for subsequent classification. The results indicate that the proposed methodology has the potential to be used operationally. The final classification product is characterized by a relatively high Cohen’s kappa value of 0.68, with single species classified with various accuracies, expressed by F1 scores ranging from 0.45 to 0.87.
|Journal series||Journal of Applied Remote Sensing, ISSN 1931-3195, (N/A 40 pkt)|
|Publication size in sheets||1.05|
|Keywords in English||ecological process; Natura 2000 monitoring; hyperspectral imaging; light detection and ranging data; data fusion; random forest|
|Score||= 40.0, 07-01-2020, ArticleFromJournal|
|Publication indicators||= 0; = 0; : 2018 = 0.701; : 2018 = 1.344 (2) - 2018=1.391 (5)|
|Citation count*||1 (2019-12-26)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.