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Journals / Anadolu Orman Araştırmaları Dergisi / 2021 / Cilt: 7 - Sayı: 1

Validation of the EUMETSAT H-SAF H10 Snow Detection Product for the 2018-2019 Snow Season in Turkey using in-Situ Data and Sentinel 2 Imagery

EUMETSAT H-SAF H10 Kar Algılama Ürününün Yer Verisi ve Sentinel 2 Görüntüleri Kullanılarak 2018-2019 Türkiye Kar Sezonu için Doğrulaması

Semih KUTER
Kenan BOLAT
Zuhal AKYÜREK
Pages
52–58
Publication Date
2021-06-15
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to both reference datasets, it is seen that the false detection ratio of the product is quite low (≤ 0.11).

📌 3 Key Takeaways

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Objective & Hypothesis:Information on the characteristics of the snow cover is critical for various scientific studies and operational applications, especially for hydrological purposes.
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Key Findings & Data:The main purpose of this study is to validate the EUMETSAT H-SAF H10 coarse resolution snow detection product for the 2018-2019 Turkey snow season using ground station data and higher resolution Sentinel 2 satellite imagery.
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Conclusion & Impact:According to both reference datasets, it is seen that the false detection ratio of the product is quite low (≤ 0.11).
🔬Design:Research Article
📍Scope:2018-2019 Verileri
⚙️Variables:Karın uzaktan algılanması · H10 · Sentinel 2

Abstract

Information on the characteristics of the snow cover is critical for various scientific studies and operational applications, especially for hydrological purposes. Remote sensing is a very convenient source for continuous monitoring of seasonal snow cover over large areas. The main purpose of this study is to validate the EUMETSAT H-SAF H10 coarse resolution snow detection product for the 2018-2019 Turkey snow season using ground station data and higher resolution Sentinel 2 satellite imagery. In the study, snow depth measurements obtained from 101 ground stations and binary snow maps produced from 106 Sentinel 2 images were used as reference dataset. Validation with in-situ data shows that the probability of detection of the H-SAF H10 snow product is 0.60, whereas the reference satellite images reveal that the probability of detection for the 2018-2019 snow season is 0.89. According to both reference datasets, it is seen that the false detection ratio of the product is quite low (≤ 0.11).

Özet

Kar örtüsünün özellikleriyle ilgili bilgiler, özellikle hidrolojik amaçlar için yürütülen çeşitli bilimsel çalışmalar ve operasyonel uygulamalar için kritik öneme sahiptir. Uzaktan algılama mevsimsel kar örtüsünün geniş alanlarda ve sürekli olarak izlenebilmesi için oldukça uygun bir kaynaktır. Bu çalışmanın temel amacı Avrupa Meteorolojik Uydulardan Yararlanma Teşkilatı'nın (EUMETSAT - European Organization for the Exploitation of Meteorological Satellites) Operasyonel Hidroloji ve Su Yönetimine Destek (H-SAF - Satellite Application Facility on Support to Operational Hydrology and Water Management) projesi kapsamında üretilmekte olan düşük çözünürlüklü günlük operasyonel H10 (SN-OBS-1) kar algılama ürününün yer istasyon verisi ve daha yüksek çözünürlüğe sahip Sentinel 2 uydu görüntüleri kullanılarak 2018-2019 Türkiye kar sezonu için doğrulamasının yapılmasıdır. Çalışmada 101 yer istasyon verisinden elde edilen kar derinliği ölçümleri ile 106 Sentinel 2 görüntüsünden üretilen ikili kar haritaları referans veri olarak kullanılmıştır. Yer verisiyle yapılan doğrulama sonuçlarına göre H-SAF H10 kar ürününün algılama olasılığı 0.60 olurken, referans uydu görüntüleri ürünün 2018-2019 kar sezonu için algılama olasılığının 0.89 olduğunu ortaya koymaktadır. Her iki referans veriye göre ürünün yanlış algılama oranının ise oldukça düşük olduğu görülmektedir (≤ 0,11).

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Cite This Article

KUTER, S., BOLAT, K., AKYÜREK, Z. (2021). Validation of the EUMETSAT H-SAF H10 Snow Detection Product for the 2018-2019 Snow Season in Turkey using in-Situ Data and Sentinel 2 Imagery. Anadolu Orman Araştırmaları Dergisi, Cilt: 7 - Sayı: 1, 52–58. https://ajindex.com/articles/459711

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