Uzaktan algılama amaçlı algılayıcılar tarafından
elde edilen yansıma değerleri atmosferik etkilerden dolayı hatalar
içermektedir. Dolayısıyla, özellikle hiperspektral uydu görüntülerinin
işlenmesinde ve analizinde doğru sonuçlar elde edilmesi için atmosferik
düzeltme önemli bir işlemdir. Bu kapsamda, EO-1 Hyperion hiperspektral uydu
görüntüsü kullanılarak atmosferik ışınımsal transfer modelleri (FLAASH, ATCOR) ve Doğrusal Ampirik (EL) yöntemi kullanılarak
performans sonuçları sunulmuştur. Elde edilen düzeltilmiş verilerin kalite
analizi ASD spektroradyometre aleti ile yapılan yer ölçmeleri kullanılarak
gerçekleştirilmiştir. Çalışmada elde edilen sonuçlara göre EL ve ATCOR
yöntemlerinin atmosferik etkinin giderilmesinde en iyi sonuçları verdiği, FLAASH
yönteminin ise düzeltilmiş reflektans eğrilerinde güçlü sapmalara neden olduğu
görülmüştür.
The reflectance
values recorded by Earth observing satellite sensors can be different from the
surface reflectance values measured on the ground due to interference of gases
and water vapor in the atmosphere. Therefore, atmospheric correction is a
significant procedure to derive the true surface reflectance value during the
processing of remotely sensed imagery especially with hyperspectral data. In
this context, this study attempts to analyze the quality of the surface
reflectance derived from EO-1 Hyperion hyperspectral imagery using the
atmospheric radiative transfer (RT) models (FLAASH and ATCOR) and empirical
line (EL) method. In the study, ground-based reflectance measurements derived
from ASD FieldSpec spectroradiometer are used as reference to evaluate the
quality of the retrieved surface reflectance. The results showed that EL and
ATCOR methods achieved the best results for reducing some of the atmospheric
effects, but FLAASH method resulted in strong anomalies in the corrected
reflectance.
Subjects | Engineering |
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Journal Section | Research Articles |
Authors | |
Publication Date | April 25, 2017 |
Submission Date | February 26, 2016 |
Acceptance Date | February 28, 2017 |
Published in Issue | Year 2017 Volume: 22 Issue: 1 |
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