scholarly journals Landsat 9 Thermal Infrared Sensor 2 pre-launch characterization: initial imaging and spectral performance results

2018 ◽  
Author(s):  
Aaron J. Pearlman ◽  
Joel McCorkel ◽  
Matthew Montanaro ◽  
Boryana Efremova ◽  
Brian Wenny ◽  
...  
Keyword(s):  
Thermal Infrared ◽  
Infrared Sensor ◽  
Spectral Performance ◽  
Initial Imaging ◽  
Performance Results

Copper-Filled Through-Hole Electrode of a ZnS Window Material for Sealing a Thermal Infrared Sensor

2010 ◽  
Vol 130 (9) ◽  
pp. 437-442
Author(s):  
Takafumi Fukumoto ◽  
Naoki Okamoto ◽  
Yoshimi Ohta ◽  
Yasuhiro Fukuyama ◽  
Masaki Hirota ◽  
...  
Keyword(s):  
Thermal Infrared ◽  
Infrared Sensor ◽  
Window Material ◽  
Through Hole

Sensitivity improved thermal infrared sensor cell applying the heat insulating phononic crystals

2021 ◽  
Author(s):  
Naoki Tambo ◽  
Kouhei Takahashi ◽  
Kunihiko Nakamura ◽  
Yasuyuki Naito ◽  
Elizabeth M. Ashley ◽  
...  
Keyword(s):  
Thermal Infrared ◽  
Phononic Crystals ◽  
Infrared Sensor ◽  
Sensor Cell

MOMS-02 spectral performance: results of the D2-mission on STS-55

1994 ◽  
Author(s):  
Hermann J. Kaufmann ◽  
Michael Berger ◽  
Dieter Meissner ◽  
Gerhard Suessenguth
Keyword(s):  
Spectral Performance ◽  
Performance Results

scholarly journals Balanço de radiação através do satélite Landsat-8 na bacia do Rio Pajeú

2017 ◽  
Vol 33 ◽  
pp. 117
Author(s):  
Laurizio Emanuel Ribeiro Alves ◽  
Heliofábio Barros Gomes ◽  
Maurílio Neemias dos Santos ◽  
Ismael Guidson Farias de Freitas
Keyword(s):  
Thermal Infrared ◽  
Landsat 8 ◽  
Infrared Sensor

O presente estudo tem como objetivo realizar a estimativa do saldo de radiação à superfície-Rn através do algoritmo SEBAL e imagens do satélite Landsat-8 para a Bacia do Rio Pajeú. Os dados de Rn estimados pelo SEBAL foram comparados com medições obtidas em duas estações automáticas localizadas nos municípios de Floresta e Serra Talhada. Foi utilizada uma imagem dos sensores OLI (Operational Land Image) e TIRS (Thermal Infrared Sensor) abordo do satélite Landsat-8, orbita 216 e ponto 66, para o dia 20 de novembro de 2016. A partir das imagens se obteve a radiância e reflectividade espectral, seguido do albedo de superfície, índices de vegetação, emissividade, temperatura superficial, radiação de onda curta incidente – Rs, radiação de onda longa incidente e emitida - Rol,atm e Rol,emi, respectivamente, e Rn. Nos resultados encontrados observa-se que os menores valores de albedo e temperatura foram observados em corpos d’água e vegetação, e maiores valores em áreas urbanas. Estas componentes estão ligadas diretamente com as componentes do saldo de radiação, onde se observou menores valores de Rol,atm e Rol,emi que estão diretamente ligadas a maior ou menor Rn. A validação dos dados do algoritmo SEBAL a partir das estações automáticas foi observado um erro relativo entre 9 e 11% para a imagem Landsat-8 para o dia 20/09/2016, verificando a acurácia das imagens para a estimativa do saldo de radiação à superfície – Rn, para a Bacia do Rio Pajeú.

scholarly journals Pemetaan Suhu Permukaan Anomali Panas Bumi Daerah Gunung Ciremai Menggunakan Data Inframerah Termal Landsat 8

2021 ◽  
Vol 2 (2) ◽  
pp. 92-99
Author(s):  
Syatiya Mirwanda ◽  
Fatiha Salsabila ◽  
Regita Pramesti ◽  
Annida Rifqoh Zakiyyah ◽  
Muhammad Rizki Tuelzar
Keyword(s):  
Thermal Infrared ◽  
Landsat 8 ◽  
Infrared Sensor

Prospek geotermal di daerah Timur Ciremai berada pada aktivitas vulkanik aktif namun pencarian prospek panas bumi di area ini mengabur akibat adanya kontras antara batuan vulkanik dengan batuan sedimen. Penelitian ini mencoba mengidentifikasi area potensial panas bumi berdasarkan suhu permukaan menggunakan metode pengindraan jauh. Data yang digunakan berupa citra satelit Landsat 8 yang sudah mempunyai sensor termal yang disebut Thermal Infrared Sensor (TIRS) pada pita sensor 10 dan 11 yang dikombinasikan dengan NDVI. Hasil analisis NDVI menunjukkan bahwa daerah penelitian memiliki vegetasi dan permukaan berupa air atau awan yang lebih banyak memantulkan gelombang cahaya tampak dibandingkan gelombang infrared dengan nilai NDVI -0,75 - 0,88. Hasil analisis LST dapat diketahui bahwa suhu permukaan pada daerah tersebut memiliki nilai dalam rentang 15 °C – 31 °C. Area yang memiliki tingkat LST tinggi di antara tingkat LST yang rendah dapat diperkirakan sebagai area yang memiliki anomali. Hal ini bersesuaian dengan kerapatan vegetasi pada area tersebut yang tinggi sehingga seharusnya besar suhu permukaannya rendah bukan sebaliknya. Berdasarkan integrasi dengan data manifestasi di lapangan, maka dapat di pastikan bahwasanya terdapat beberapa anomali panas bumi pada arah tenggara dari Gunung Ciremai.

scholarly journals Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera

2018 ◽  
Vol 7 (4.20) ◽  
pp. 608 ◽  
Author(s):  
Muhammad Mejbel Salih ◽  
Oday Zakariya Jasim ◽  
Khalid I. Hassoon ◽  
Aysar Jameel Abdalkadhum
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Infrared Thermometer ◽  
Ground Truth Data ◽  
Land Cover Types

This paper illustrates a proposed method for the retrieval of land surface temperature (LST) from the two thermal bands of the LANDSAT-8 data. LANDSAT-8, the latest satellite from Landsat series, launched on 11 February 2013, using LANDSAT-8 Operational Line Imager and Thermal Infrared Sensor (OLI & TIRS) satellite data. LANDSAT-8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12 bits. In this search a trial has been made to estimate LST over Al-Hashimiya district, south of Babylon province, middle of Iraq. Two dates images acquired on 2nd &18th of March 2018 to retrieve LST and compare them with ground truth data from infrared thermometer camera (all the measurements contacted with target by using type-k thermocouple) at the same time of images capture. The results showed that the rivers had a higher LST which is different to the other land cover types, of less than 3.47 C ◦, and the LST different for vegetation and residential area were less than 0.4 C ◦ with correlation coefficient of the two bands 10 and 11 Rbnad10= 0.70, Rband11 = 0.89 respectively, for the imaged acquired on the 2nd of march 2018 and Rband10= 0.70 and Rband11 = 0.72 on the 18th of march 2018. These results confirm that the proposed approach is effective for the retrieval of LST from the LANDSAT-8 Thermal bands, and the IR thermometer camera data which is an effective way to validate and improve the performance of LST retrieval. Generally the results show that the closer measurement taken from the scene center time, a better quality to classify the land cover. The purpose of this study is to assess the use of LANDSAT-8 data to specify temperature differences in land cover and compare the relationship between land surface temperature and land cover types.   

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