SavedAdd your journal

Journals / Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi / 2019 / Cilt: 19 - Sayı: 3

Mapping of Land Surface Temperature Using Landsat-8 Satellite Data Based on the Radiative Transfer Equation

Işınım Transferi Denklemi Baz Alınarak Yer Yüzey Sıcaklığının Landsat-8 Uydu Verileri ile Haritalanması

Aliihsan ŞEKERTEKİN
Pages
769–777
Publication Date
2022-10-12
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

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

Important results will be obtained in regional climate change studies by generating LST maps expeditiously from RTE method and conducting their temporal and spatial analyses.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study is to retrieve Land Surface Temperature (LST) using Landsat-8 satellite data and Radiative Transfer Equation (RTE) method.
📊
Key Findings & Data:Within the scope of the study, Landsat-8 data acquired on 27 September 2018 was used as satellite imagery and Ceyhan district of Adana province was selected as the study area.
💡
Conclusion & Impact:Important results will be obtained in regional climate change studies by generating LST maps expeditiously from RTE method and conducting their temporal and spatial analyses.
🔬Design:Research Article
📍Scope:2018 Verileri
⚙️Variables:Domain Parameters

Abstract

The aim of this study is to retrieve Land Surface Temperature (LST) using Landsat-8 satellite data and Radiative Transfer Equation (RTE) method. Within the scope of the study, Landsat-8 data acquired on 27 September 2018 was used as satellite imagery and Ceyhan district of Adana province was selected as the study area. Atmospheric transmittance (τλ ), downwelling atmospheric radiance (Lλ ↓) and upwelling atmospheric radiance (Lλ ↑) are the required atmospheric parameters for LST retrieval based on RTE method. These parameters were calculated by the atmospheric correction parameter calculator, which is published online by the American National Aeronautics and Space Administration (NASA). Surface emissivity (ελ ), which is another important parameter in LST retrieval, was calculated using Normalized Difference Vegetation Index (NDVI). As a result of the application, LST map was created using ERDAS Imagine remote sensing software and the cross-validation process was performed with MODIS LST product obtained in the same day with Landsat-8 data. As a result of the cross-validation, correlation coefficient was determined as 0.91 and the Root Mean Square Error (RMSE) was obtained as 3.93 K. Important results will be obtained in regional climate change studies by generating LST maps expeditiously from RTE method and conducting their temporal and spatial analyses.

Özet

Bu çalışmanın amacı Landsat-8 uydu verileri ve Işınım Transferi Denklemi (RTE) kullanılarak Yer YüzeySıcaklığının (YYS) konumsal olarak elde edilmesidir. Çalışma kapsamında 27 Eylül 2018 tarihli Landsat-8verisi kullanılmış ve Adana ili Ceyhan ilçe sınırları çalışma alanı olarak seçilmiştir. RTE yöntemi ile YYSçıkarımında atmosferik geçirgenlik (τλ), aşağı yönlü atmosferik ışınım (Lλ↓) ve yukarı yönlü atmosferikışınım (Lλ↑) gerekli atmosferik parametrelerdir. Bu parametreler, Amerikan Uzay Ajansı (NASA)tarafından çevrimiçi yayınlanan atmosferik düzeltme parametresi hesaplayıcı tarafındanhesaplanmıştır. YYS çıkarımında bir diğer önemli parametre olan yüzey yayınırlığı (ελ) Normalize FarkBitki İndeksi (NDVI) kullanılarak hesaplanmıştır. Uygulama sonucunda YYS haritası ERDAS Imagineuzaktan algılama yazılımı yardımıyla oluşturulmuş ve yersel veri olmadığı için aynı gün alınan MODIS YYSverisi ile karşılaştırma işlemi gerçekleştirilmiştir. Karşılaştırma sonucunda korelasyon katsayısı 0.91 veKaresel Ortalama Hata (KOH) 3.93 K olarak belirlenmiştir. RTE yöntemi kullanılarak hızlı bir şekilde YYSharitalarının üretimi ile zamansal ve konumsal analizler yapılarak bölgesel iklim değişikliği çalışmalarındaönemli sonuçlar elde edilecektir.

🔖

Cite This Article

ŞEKERTEKİN, A. (2022). Mapping of Land Surface Temperature Using Landsat-8 Satellite Data Based on the Radiative Transfer Equation. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Cilt: 19 - Sayı: 3, 769–777. https://ajindex.com/articles/429840

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (8)

  1. Anderson, M. C., Norman, J. M., Kustas, W. P., Houborg, R., Starks, P. J., and Agam, N., 2008. A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales. Remote Sensing of Environment, 112(12), 4227–4241.
  2. Arnfield, A. J., 2003. Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island. International Journal of Climatology, 23(1), 1–26.
  3. Arslan, N., 2018. Identification of hotspots using different statistical methods in a region of manufacturing plants. Environmental Monitoring and Assessment, 190(9), 550. Balcik, F., 2014. Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices. Environmental Monitoring and Assessment, 186(2), 859–872.
  4. Becker, F., and Li, Z. L., 1990. Toward a local split window method over land surface. International Journal of Remote Sensing, 11:3, 369-393.
  5. Carlson, T. N., and Ripley, D. A., 1997. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241–252.
  6. Dash, P., Göttsche, F.-M., Olesen, F., and Fischer, H., 2001. Retrieval of land surface temperature and emissivity from satellite data: Physics, theoretical limitations and current methods. Journal of the Indian Society of Remote Sensing, 29(1-2), 23–30.
  7. Gillespie, A., Rokugawa, S., Matsunaga, T., Steven Cothern, J., Hook, S., and Kahle, A. B., 1998. A temperature and emissivity separation algorithm for advanced spaceborne thermal emission and reflection radiometer (ASTER) images. IEEE Transactions on Geoscience and Remote Sensing, 36(4), 1113–1126.
  8. Hain, C. R., Crow, W. T., Mecikalski, J. R., Anderson, M. C., and Holmes, T. (2011). An intercomparison of available soil moisture estimates from thermal infrared and passive microwave remote sensing and land surface modeling. Journal of Geophysical Research, 116, D15107. Jiang, Y., and Weng, Q., 2017. Estimation of hourly and daily evapotranspiration and soil moisture using downscaled LST over various urban surfaces. GIScience & Remote Sensing, 54(1), 95–117. Jiménez-Muñoz, J. C., and Sobrino, J. A., 2003. A generalized single-channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research, 109(April), 8112. Karakuş, C. B., 2019. The Impact of Land Use/Land Cover (LULC) Changes on Land Surface Temperature in Sivas City Center an