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Yeni Nesil Uzaktan Algılama Platformu: GEE (Google Earth Engine) ve fiziki coğrafya çalışmalarında kullanımı

Authors: Karadoğan, Sabri; Kavak, M. Tahir; Satar, Nesretullah;

Yeni Nesil Uzaktan Algılama Platformu: GEE (Google Earth Engine) ve fiziki coğrafya çalışmalarında kullanımı

Abstract

Google Earth Engine (GEE), büyük coğrafi veri kümelerini depolamak ve işlemek için tasarlanmış bulut tabanlı bir platformdur. Landsat serisinin 2008 yılında ücretsiz olarak kullanıma sunulmasından bu yana Google, Landsat, Sentinel, MODIS uyduları ve diğerlerinden alınanlar da dahil olmak üzere çok büyük miktarda uydu verisini arşivledi. Bu platform, kullanıcıların uydu görüntülerini verimli bir şekilde görselleştirmesine ve analiz etmesine olanak tanır. GEE’nin kapsamlı veri kataloğu çeşitli türlerde uydu görüntüleri, vektör verileri ve diğer coğrafi veri kümelerini içerir. Bu veri kümeleri araştırmacıların geniş bir yelpazede coğrafi analizler gerçekleştirmesine olanak tanır. GEE, veri görselleştirme ve analizi için GEE Kod Düzenleyici ve GEE Explorer gibi kullanıcı dostu araçlar sunar. GEE’nin temel işlevleri arasında görüntü işleme, vektör işleme, geometrik analiz, spektral işleme, zamansal analiz ve makine öğrenme algoritmaları yer alır. Bu özellikler araştırmacılara büyük veri kümelerini etkili bir şekilde yönetme ve analiz etme esnekliği sağlar. GEE, hidroloji, bitki örtüsü, tarım, kentsel çalışmalar, atmosfer ve iklim analizi, toprak ve jeomorfoloji ve afet yönetimi dahil olmak üzere çeşitli alanlarda yaygın olarak kullanılmaktadır. 2010'dan bu yana GEE kullanılarak yapılan bilimsel yayın sayısı hızla artmıştır ve bu yayınlar, çeşitli disiplinlerde geniş bir uygulama yelpazesine sahiptir. Bu Çalışmada özellikle Fiziki coğrafya araştırmalarında kullanımına ilişkin örnekler verilmiştir.

Google Earth Engine (GEE) is a cloud-based platform designed for storing and processing large geospatial datasets. Since the Landsat series became freely available in 2008, Google has archived vast amounts of satellite data, including those from Landsat, Sentinel, MODIS satellites, and others. This platform allows users to visualize and analyze satellite imagery efficiently. GEE's extensive data catalog includes various types of satellite images, vector data, and other geospatial datasets. These datasets enable researchers to perform a wide range of geospatial analyses. GEE offers userfriendly tools like the GEE Code Editor and GEE Explorer for data visualization and analysis. Key functionalities of GEE include image processing, vector processing, geometric analysis, spectral processing, temporal analysis, and machine learning algorithms. These features provide researchers with the flexibility to manage and analyze large datasets effectively. GEE is widely used across various domains, including hydrology, vegetation, agriculture, urban studies, atmospheric and climate analysis, soil and geomorphology, and disaster management. The number of scientific publications using GEE has increased rapidly since 2010, and these publications have a wide range of applications in various disciplines. In this study, examples of its use in physical geography research are given.

Country
Turkey
Related Organizations
Keywords

Fiziki coğrafya, Physical geography, Google Earth Engine (GEE), Remote sensing, Uzaktan algılama

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green