ICESat-2 ATL08 Verileri Kullanılarak Veri Toplama Zamanının Orman Kanopi Örtüsü Tahmini Üzerindeki Etkisinin Değerlendirilmesi

Yıl 2023, Cilt: 23 Sayı: 3, 220 - 229, 06.12.2023

Emre Aktürk

https://doi.org/10.17475/kastorman.1394895

Öz

Çalışmanın amacı: Bu çalışmada, 2020 ve 2022 yılları için Orman Kanopi Örtüsü Tahmin Modeli (CCEM) ile Orman Örtü Örtüsü (FCC) haritalarının üretilmesinde gündüz ve gece segmentlerinin kullanılmasının tahmin başarısı üzerine etkisi araştırılmaktadır.
Çalışma alanı: Çalışma alanı, geniş ormanlık alanlarıyla bilinen, Louisiana eyaletine bitişik, Texas eyaletinin güneydoğu bölgesinde yer alan ve güney sahil şeridine yakın olan 17 birbirine bağlı ilçeyi kapsamaktadır.
Materyal ve yöntem: Çalışma, ICESat-2/ATLAS verilerinden alınan hem gündüz hem de gece segmentlerini kapsayacak şekilde, orman kanopi örtüsü haritalarını CCEM kullanarak tahmin başarısı kapsamlı bir karşılaştırmasını gerçekleştirdi.
Temel sonuçlar: Çalışmanın bulguları, gece segmentlerinden elde edilen FCC haritalarının, sırasıyla 2020 ve 2022 yılları için 0.77 ve 0.83 daha yüksek kappa katsayıları göstererek, gündüz segmentlerinden elde edilenlere göre daha üstün olduğunu ortaya koymaktadır. Ek olarak, gündüz ve gece segmentlerinden türetilen haritalar için FCC tahmin sınıflarının başarıları arasında belirgin farklılıklar gözlemlenmiştir.
Araştırma vurguları: Bu çalışma, gece segmentlerinden türetilen FCC haritalarının, gündüz segmentlerinden türetilenlere göre daha doğru sonuçlar verdiğini ortaya çıkan önemli bir bulguyu ortaya çıkartmıştır. Çalışma ayrıca, özellikle Orta Seviyede Orman Kanopi Örtüsü (MFCC) sınıfından elde edilen daha düşük FCC sınıflandırma başarısını tespit etmiştir

Anahtar Kelimeler

Kanopi Örtüsü, ICESat-2, ATL08, Google Earth Engine, Veri Toplama Zaman

Assessing the Influence of Acquisition Time in Forest Canopy Cover Estimation Using ICESat-2 ATL08 Dataset

Öz

Aim of study: This study investigates the estimation success of using day and night segments in producing Forest Canopy Cover (FCC) maps with the Canopy Cover Estimation Model (CCEM) for the years 2020 and 2022.
Area of study: The study area covers 17 interconnected counties situated in the southeastern part of Texas state, adjacent to the state of Louisiana, and near the southern coastlines, known for their extensive forested areas.
Material and methods: This study incorporated both day and night acquisition segments from Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data for a comprehensive comparison of their effectiveness in mapping the forest canopy cover using the CCEM.
Main results: The study’s findings reveal that night segment-derived FCC maps outperform those derived from day segments, showing higher kappa coefficients of 0.77 and 0.83 for the years 2020 and 2022, respectively. In addition, notable differences were observed among classes of FCC estimations successes for day and night segment-derived maps.
Research highlights: This study introduces a significant finding that the FCC maps derived from night segments yield more accurate results than those derived from day segments. The study further discovers a notable difference in the forest canopy cover classification success, particularly with a lower accuracy observed in the Moderate Forest Canopy Cover (MFCC) category.

Anahtar Kelimeler

Canopy cover, ICESat-2, ATL08, Google Earth Engine, Acquisition Time

Kaynakça

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