scholarly journals Thermal remote sensing from Airborne Hyperspectral Scanner data in the framework of the SPARC and SEN2FLEX projects: an overview

2009 ◽  
Vol 6 (3) ◽  
pp. 4107-4124
Author(s):  
J. A. Sobrino ◽  
J. C. Jiménez-Muñoz ◽  
P. J. Zarco-Tejada ◽  
G. Sepulcre-Cantó ◽  
E. de Miguel ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Near Infrared ◽  
Short Wave ◽  
Scanner Data ◽  
Data Errors ◽  
Spectral Bands ◽  
Field Campaigns ◽  
First Time

Abstract. The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Técnica Aerospacial (INTA), and it has been involved in several field campaigns since 2004. This paper presents an overview of the work performed with the AHS thermal imagery provided in the framework of the SPARC and SEN2FLEX campaigns, carried out respectively in 2004 and 2005 over an agricultural area in Spain. The data collected in both campaigns allowed for the first time the development and testing of algorithms for land surface temperature and emissivity retrieval as well as the estimation of evapotranspiration from AHS data. Errors were found to be around 1.5 K for land surface temperature and 1 mm/day for evapotranspiration.

scholarly journals Thermal remote sensing from Airborne Hyperspectral Scanner data in the framework of the SPARC and SEN2FLEX projects: an overview

2009 ◽  
Vol 13 (11) ◽  
pp. 2031-2037 ◽  
Author(s):  
J. A. Sobrino ◽  
J. C. Jiménez-Muñoz ◽  
P. J. Zarco-Tejada ◽  
G. Sepulcre-Cantó ◽  
E. de Miguel ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Near Infrared ◽  
Short Wave ◽  
Scanner Data ◽  
Data Errors ◽  
Spectral Bands ◽  
Field Campaigns ◽  
First Time

Abstract. The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Técnica Aerospacial (INTA), and it has been involved in several field campaigns since 2004. This paper presents an overview of the work performed with the AHS thermal imagery provided in the framework of the SPARC and SEN2FLEX campaigns, carried out respectively in 2004 and 2005 over an agricultural area in Spain. The data collected in both campaigns allowed for the first time the development and testing of algorithms for land surface temperature and emissivity retrieval as well as the estimation of evapotranspiration from AHS data. Errors were found to be around 1.5 K for land surface temperature and 1 mm/day for evapotranspiration.

scholarly journals Deteksi Perubahan Suhu Permukaan Menggunakan Data Satelit Landsat Multi-Waktu Studi Kasus Cekungan Bandung

2018 ◽  
Vol 19 (2) ◽  
pp. 145 ◽  
Author(s):  
Widya Ningrum ◽  
Ida Narulita
Keyword(s):  
Land Use ◽  
Temperature Distribution ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Surface Temperature Distribution

ABSTRACTThe rapid population growth and development of infrastructure in the Bandung basin has triggered an uncontrolled land use changes. The changes of land use will impact on land surface temperature distribution. Finally, these changes will give influence on climate. Land surface temperature is one of the important climatic elements in the energy balance. Changes in land surface temperature variations will potentially change other elements of the climate. The purpose of this paper is to obtain and to analyze the changes of surface temperature distribution in Bandung basin using multi temporal satellite data processing that is Landsat 5 and Landsat 8 in 2004, 2009 and 2014. Near Infrared Channel (Near Infrared/NIR) and visible wave channels (Visible band) have used to obtain the value Normalized Difference Vegetation Index/NDVI index and Albedo. Land and vegetation emissivity value and thermal band have used to determine land surface temperature. The results showed that the surface temperature distribution of Bandung basin has been changes characterized by the presence of two hotspot characters i.e. hot areas in urban and hot areas in non-urban area. The area is characterized by decreasing vegetation index values, increasing albedo values and increasing on surface temperature.  Land Surface Temperatures average value increased by 1.3°C. Land surface temperature tends to rise supposed as a result of changes in vegetated area into open area and the build area  Keywords: land surface temperature, normalized difference vegetation index, albedoABSTRAKPesatnya pertumbuhan penduduk dan perkembangan infrastruktur di cekungan Bandung telah memicu perubahan tutupan lahan yang tidak terkendali. Perubahan tutupan lahan akan mempengaruhi distribusi suhu permukaan. Hal tersebut pada akhirnya nanti akan mempengaruhi iklim. Suhu permukaan merupakan salah satu unsur iklim yang penting dalam neraca energi. Perubahan variasi suhu permukaan berpotensi mengubah unsur unsur iklim yang lainnya. Tujuan makalah ini adalah untuk mengetahui dan menganalisis perubahan distribusi suhu permukaan di cekungan Bandung melalui pengolahan data satelit multi waktu yaitu Landsat 5 dan Landsat 8 tahun 2004, 2009, 2014 dan 2016. Kanal Inframerah Dekat (Near Infrared/NIR) dan kanal gelombang tampak (Visible band) digunakan untuk memperoleh nilai Indeks Kehijauan Vegetasi (Normalized Difference Vegetation Index/NDVI) dan Albedo. Nilai emisivitas dari tanah dan vegetasi serta Band termal digunakan untuk menentukan nilai Suhu Permukaan Tanah.Hasil penelitian menunjukkan bahwa di cekungan Bandung telah terjadi perubahan distribusi suhu permukaan yang dicirikan oleh adanya dua karakter hotspot yaitu daerah panas di daerah urban dan daerah panas di daerah non-urban. Daerah tersebut dicirikan menurunnya nilai indeks vegetasi, menurunnya nilai albedo dan meningkatnya nilai suhu permukaan tanah. Nilai rataan Suhu Permukaan Tanah tahun 2005 - 2014 meningkat sebesar 1.3°C. Kecenderungan naik ini diduga sebagai akibat adanya perubahan tutupan lahan bervegetasi menjadi daerah yang lebih terbuka dan daerah terbangun.Kata kunci: suhu permukaan, indeks kehijauan vegetasi, albedo 

Comparative Analysis of Two Land Surface Temperature Retrieval Algorithms Based on Multi-Source Remote Sensing Data

2011 ◽  
Vol 130-134 ◽  
pp. 4130-4134
Author(s):  
Wen Wu Zheng ◽  
Yong Nian Zeng
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Near Infrared ◽  
Single Channel ◽  
Landsat Tm ◽  
Average Deviation ◽  
Modis Data ◽  
Retrieval Algorithms ◽  
Atmospheric Profile

The main disadvantage of Land surface temperature (LST) retrieval methods from Landsat TM thermal channel images is that atmospheric profile parameters are needed, and MODIS has several near infrared bands that can be used to estimate atmospheric profile parameters. Two methods that could be used to retrieve the LST from Landsat TM and MODIS data were compared in this paper, the first of them is the mono-window algorithm developed by Qin et al. and the second is the single-channel algorithm developed by Jimenez-Munoz and Sobrino. Atmospheric profile parameters such as atmospheric moisture content, atmospheric transmittance and average atmospheric temperature have been estimated from MODIS data, and the land surface emissivity values have been estimated from a methodology based on spectral mixture analysis. Finally, a comparison between the LST measured in situ and retrieved by the algorithms over urban area of Changsha city in China is present. Result indicates that the two LST retrieval algorithms can get high-precision results in support of atmospheric parameters from MODIS images, the average deviation of mono-window algorithm is 0.76K, and the deviation of generalized single-channel algorithm is 1.23k.

scholarly journals APPLICATION OF LAND SURFACE TEMPERATURE DERIVED FROM ASTER TIR TO IDENTIFY VOLCANIC GAS EMISSION AROUND BANDUNG BASIN

2020 ◽  
Vol 16 (2) ◽  
pp. 179 ◽  
Author(s):  
Zaki Hilman ◽  
Asep Saepuloh ◽  
Very Susanto
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Near Infrared ◽  
Thermal Emission ◽  
Volcanic Gases ◽  
Gas Emission ◽  
Volcanic Gas ◽  
Gas Concentration ◽  
So2 Gas

Gas emission in volcanic areas is one of the features that can be used for geothermal exploration and to monitor volcanic activity. Volcanic gases are usually emitted in permeable zones in geothermal fields. The use of thermal infrared radiometers (TIR) onboard of advanced spaceborne thermal emission and reflection radiometers (ASTER) aims to detect thermal anomalies at the ground surface related to gas emissions from permeable zones. The study area is located around Bandung Basin, West Java (Indonesia), particularly the Papandayan and Domas craters. This area was chosen because of the easily detected land surface temperature (LST) following emissivity and vegetation corrections (Tcveg). The ASTER TIR images used in this study were acquired by direct night and day observation, including observations made using visible to near-infrared radiometers (VNIR). Field measurements of volcanic gases composed of SO2 and CO2 were performed at three different zones for each of the craters. The measured SO2 concentration was found to be constant over time, but CO2 concentration showed some variation in the craters. We obtained results suggesting that SO2 gas measurements and Tcveg are highly correlated. At Papandayan crater, the SO2 gas concentration was 334.34 ppm and the Tcveg temperature was 35.67 °C,  results that are considered highly anomalous. The same correlation was also found at Domas crater, which showed an increased SO2 gas concentration of 35.39 ppm located at a high-anomaly Tcveg of 30.65 °C. Therefore, the ASTER TIR images have potential to identify volcanic gases as related to high Tcveg.

A Split Window Algorithm for Retrieving Land Surface Temperature from FY-3D MERSI-2 Data

2019 ◽  
Vol 11 (18) ◽  
pp. 2083 ◽  
Author(s):  
Han Wang ◽  
Kebiao Mao ◽  
Fengyun Mu ◽  
Jiancheng Shi ◽  
Jun Yang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Near Infrared ◽  
Calibration Model ◽  
Threshold Method ◽  
Spatiotemporal Resolution ◽  
Simulation Data ◽  
Cross Calibration ◽  
Spectral Imager

The thermal infrared (TIR) data from the Medium Resolution Spectral Imager II (MERSI-2) on the Chinese meteorological satellite FY-3D have high spatiotemporal resolution. Although the MERSI-2 land surface temperature (LST) products have good application prospects, there are some deviations in the TIR band radiance from MERSI-2. To accurately retrieve LSTs from MERSI-2, a method based on a cross-calibration model and split window (SW) algorithm is proposed. The method is divided into two parts: cross-calibration and LST retrieval. First, the MODTRAN program is used to simulate the radiation transfer process to obtain MERSI-2 and Moderate Resolution Imaging Spectroradiometer (MODIS) simulation data, establish a cross-calibration model, and then calculate the actual brightness temperature (BT) of the MERSI-2 image. Second, according to the characteristics of the near-infrared (NIR) bands, the atmospheric water vapor content (WVC) is retrieved, and the atmospheric transmittance is calculated. The land surface emissivity is estimated by the NDVI-based threshold method, which ensures that both parameters (transmittance and emissivity) can be acquired simultaneously. The validation shows the following: 1) The average accuracy of our algorithm is 0.42 K when using simulation data; 2) the relative error of our algorithm is 1.37 K when compared with the MODIS LST product (MYD11A1); 3) when compared with ground-measured data, the accuracy of our algorithm is 1.23 K. Sensitivity analysis shows that the SW algorithm is not sensitive to the two main parameters (WVC and emissivity), which also proves that the estimation of LST from MERSI-2 data is feasible. In general, our algorithm exhibits good accuracy and applicability, but it still requires further improvement.

scholarly journals ANALYSIS OF SPATIAL-TEMPORAL VARIATION OF LAND SURFACE TEMPERATURE, VEGETATION AND SNOW COVER IN LAR NATIONAL PARK OF IRAN

2016 ◽  
Vol XLII-2/W1 ◽  
pp. 37-43
Author(s):  
M. Arekhi
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
National Park ◽  
Vegetation Change ◽  
Near Infrared ◽  
Main Tool ◽  
Surface Reflectance ◽  
Vegetation Greenness

Changes in land surface reflectance measured by remote sensing data can be useful in climate change studies. This study attempts to analyze the spatial-temporal extent change of vegetation greenness, Land Surface Temperature (LST), and Normalized Difference Snow Index (NDSI) in late spring at the Lar National Park of Iran using Landsat data. Vegetation indices (VIs), LST, and NDSI maps were calculated for each date (1985, 1994, 2010, and 2015). All VIs have shown an increasing trend from 1985 to 2015 which depicted increase of vegetation. Spectral reflectance of all bands is declining from 1985 to 2015 except in near-infrared (NIR) bands. High reflectance in NIR bands is due to increased vegetation greenness. The reduction was seen in the visible bands that show increased vegetation photosynthetic activity. In the short-wave infrared bands (SWIR) were observed reduced trend from 1985 to 2015 which is indicate increased vegetation. Also, in the mid-wave infrared (MWIR) bands were observed a declining trend which is the result of decreasing soil fraction from 1985 to 2015. LST has increased from 23.27 °C in 1985 to 27.45 °C in 2015. Snow patches were decreased over the study period. In conclusion, VIs and surface reflectance bands are considered the main tool to display vegetation change. Also, high VIs values showed healthy and dense vegetation. The results of our study will provide valuable information in preliminary climate change studies.

scholarly journals Modeling the distribution of land surface temperature for Bystrytsia river basin using Landsat 8 data

2019 ◽  
Vol 27 (3) ◽  
pp. 453-465
Author(s):  
I. P. Kovalchuk ◽  
O. S. Mkrtchian ◽  
A. I. Kovalchuk
Keyword(s):  
Surface Temperature ◽  
River Basin ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Near Infrared ◽  
Vertical Gradient ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Practical Applications ◽  
Infrared Spectral

Development of accurate and practicable methods of land surface temperatures (LST) mapping has benefits for a range of scientific and practical applications. The paperconsiders mapping of LST for the Bystrytsia river basin located in Western Ukraine using Landsat 8 imagerywith two thermal infrared bands, which capture emissivity values closely related to land surface temperature (LST).Three multispectral images referring to different seasons (autumn, winter and summer) were used in the study. The method of LST estimation consists of several successive steps. After preprocessing (clipping, masking, and re-projecting), the images were converted from digital numbers to top of atmosphere spectral radiance,and then – to brightness temperature.However, the brightness temperature differs from LST due to emissivity of land surface being different from that of ideal blackbody.The emissivity can vary significantly with vegetation, surface moisture and surface roughness, and can be approximately estimated from land surface reflectivity at red and near-infrared spectral ranges. Estimated values of LST were compared with measurements of Ivano-Frankivsk state weather station, showing rather good compliance for all the three scenes.Obtained estimates of LST show some regularities of its spatial distribution, which also vary significantly from season to season.All the three scenes show conspicuous vertical gradient in LST; summer and autumn scenes are also characterized by significant local variability in LST due to different land cover types (e.g., urban development, forests, different agricultural lands), whereas in winter, differences in LST for mountainous slopes of different aspects appear to be more pronounced. Graphs of LST change with elevation have a parabolic form: sharper decrease of LST is typical for lower elevations, while the vertical LST gradient decreases above 700–1000 m a.s.l.

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