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ICESat-2 for Canopy Cover Estimation at Large-Scale on a Cloud-Based Platform        
Yazarlar
Dr. Öğr. Üyesi Emre AKTÜRK
Kastamonu Üniversitesi, Türkiye
Sorın Popescu
Lonesome Malambo
Özet
Forest canopy cover is an essential biophysical parameter of ecological significance, especially for characterizing woodlands and forests. This research focused on using data from the ICESat-2/ATLAS spaceborne lidar sensor, a photon-counting altimetry system, to map the forest canopy cover over a large country extent. The study proposed a novel approach to compute categorized canopy cover using photon-counting data and available ancillary Landsat images to build the canopy cover model. In addition, this research tested a cloud-mapping platform, the Google Earth Engine (GEE), as an example of a large-scale study. The canopy cover map of the Republic of Türkiye produced from this study has an average accuracy of over 70%. Even though the results were promising, it has been determined that the issues caused by the auxiliary data negatively affect the overall success. Moreover, while GEE offered many benefits, such as user-friendliness and convenience, it had processing limits that posed challenges for large-scale studies. Using weak or strong beams’ segments separately did not show a significant difference in estimating canopy cover. Briefly, this study demonstrates the potential of using photon-counting data and GEE for mapping forest canopy cover at a large scale.
Anahtar Kelimeler
ATL08 | canopy cover estimation | Google Earth Engine | ICESat-2 | Landsat | photon counting lidar
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale
Dergi Adı SENSORS
Dergi ISSN 1424-8220
Dergi Tarandığı Indeksler SCI-Expanded
Dergi Grubu Q2
Makale Dili İngilizce
Basım Tarihi 04-2023
Cilt No 23
Sayı 7
Sayfalar 3394 / 3410
Doi Numarası 10.3390/s23073394
Makale Linki http://dx.doi.org/10.3390/s23073394