Surface parameters from SEVIRI observations through a Kalman filter approach: application and evaluation of the scheme in Southern Italy

Grazia,

doi:10.3369/tethys.2016.13.01

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…The retrieval process is physical-based and can be applied for both land-and sea-surface temperatures with very good results compared with LST from non-geostationary satellite observations [34]. The same Kalman filter methodology can be found to produce a very good result in different land cover types, including arid, cultivated, and vegetated, as well as urban, areas and sea water [35].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Land Surface Temperature in an Agricultural Region of Bangladesh from Landsat 8: Intercomparison of Four Algorithms

Sajib

Tao

2020

Sensors

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The presence of two thermal bands in Landsat 8 brings the opportunity to use either one or both of these bands to retrieve Land Surface Temperature (LST). In order to compare the performances of existing algorithms, we used four methods to retrieve LST from Landsat 8 and made an intercomparison among them. Apart from the direct use of the Radiative Transfer Equation (RTE), Single-Channel Algorithm and two Split-Window Algorithms were used taking an agricultural region in Bangladesh as the study area. The LSTs retrieved in the four methods were validated in two ways: first, an indirect validation against reference LST, which was obtained in the Atmospheric and Topographic CORection (ATCOR) software module; second, cross-validation with Terra MODerate Resolution Imaging Spectroradiometer (MODIS) daily LSTs that were obtained from the Application for Extracting and Exploring Analysis Ready Samples (A ρ ρ EEARS) online tool. Due to the absence of LST-monitoring radiosounding instruments surrounding the study area, in situ LSTs were not available; hence, validation of satellite retrieved LSTs against in situ LSTs was not performed. The atmospheric parameters necessary for the RTE-based method, as well as for other methods, were calculated from the National Centers for Environmental Prediction (NCEP) database using an online atmospheric correction calculator with MODerate resolution atmospheric TRANsmission (MODTRAN) codes. Root-mean-squared-error (RMSE) against reference LST, as well as mean bias error against both reference and MODIS daily LSTs, was used to interpret the relative accuracy of LST results. All four methods were found to result in acceptable LST products, leaving atmospheric water vapor content (w) as the important determinant for the precision result. Considering a set of several Landsat 8 images of different dates, Jiménez-Muñoz et al.’s (2014) Split-Window algorithm was found to result in the lowest mean RMSE of 1.19 ° C . Du et al.’s (2015) Split-Window algorithm resulted in mean RMSE of 1.50 ° C . The RTE-based direct method and the Single-Channel algorithm provided the mean RMSE of 2.47 ° C and 4.11 ° C , respectively. For Du et al.’s algorithm, the w range of 0.0 to 6.3 g cm−2 was considered, whereas for the other three methods, w values as retrieved from the NCEP database were considered for corresponding images. Land surface emissivity was retrieved through the Normalized Difference Vegetation Index (NDVI)-threshold method. This intercomparison study provides an LST retrieval methodology for Landsat 8 that involves four algorithms. It proves that (i) better LST results can be obtained using both thermal bands of Landsat 8; (ii) the NCEP database can be used to determine atmospheric parameters using the online calculator; (iii) MODIS daily LSTs from A ρ ρ EEARS can be used efficiently in cross-validation and intercomparison of Landsat 8 LST algorithms; and (iv) when in situ LST data are not available, the ATCOR-derived LSTs can be used for indirect verification and intercomparison of Landsat 8 LST algorithms.

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Section: Introductionmentioning

confidence: 99%

Estimation of Land Surface Temperature in an Agricultural Region of Bangladesh from Landsat 8: Intercomparison of Four Algorithms

Sajib

Tao

2020

Sensors

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“…SEVIRI is onboard a geostationary platform and as such its observations can resolve the diurnal cycle with high temporal resolution. There is evidence that time-space constraints can significantly enhance our ability to extract information from geostationary data in comparison to 'single-pixel' algorithms which only use the spectral information [1][2][3]. Hence there is a need to explore SEVIRI's full observational space to improve the quality of operationally derived products.…”

Section: Introductionmentioning

confidence: 99%

“…In a series of recent papers [1][2][3], the authors have described and presented a general Kalman Filter methodology for the simultaneous retrieval of surface emissivity (ε) and temperature (T s ) from SEVIRI infrared radiances . The KF or Kalman filter (e.g., see [4,5]) provides a general framework to develop physically based retrieval algorithms, which can exploit the temporal continuity expected from geostationary instruments such as SEVIRI.…”

Section: Introductionmentioning

confidence: 99%

“…The KF or Kalman filter (e.g., see [4,5]) provides a general framework to develop physically based retrieval algorithms, which can exploit the temporal continuity expected from geostationary instruments such as SEVIRI. The KF approach was applied for the first time to the combined retrieval of ε, T s by [1] and further improved and validated by [2,3]. Physically based schemes for the same problem and instrument have been also considered and developed by [6,7], although in this case the retrieval is based on a static Optimal Estimation approach.…”

Section: Introductionmentioning

confidence: 99%

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SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

Masiello

Serio

Venafra

et al. 2019

Preprint

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Timely processing of observations from hyper-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances for the physical retrieval of surface temperature and emissivity. The new radiative transfer model improves computational time by a factor of ≈ 7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the simultaneous retrieval of surface temperature and emissivity in three infrared channels (8.7, 10.8, 12 μm). The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e. average differences are generally well below 0.01.

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Integrating urban development and ecological sustainability: a study on land surface temperature and urban heat island effect in a Karst River Basin

Wu,

et al. 2024

Front. Built Environ.

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The Chishui River Basin, a vital waterway in Southwest China, has experienced rapid urbanization, leading to significant ecological and environmental changes, among which the urban heat island (UHI) effect is particularly pronounced. The UHI effect not only affects the quality of life for residents but also influences urban energy consumption and climate change, underscoring the need for in-depth study of its spatial distribution and contributing factors. The unique karst topography of the region further complicates UHI research, necessitating an investigation that can inform urban planning and sustainable development strategies. This study leveraged Landsat 8 TIRS satellite remote sensing imagery to examine the land surface temperature (LST) and UHI effect in the Chishui River Basin during the summers of 2016 and 2021. Employing the Mono-window Algorithm (MWA), the research quantitatively inverted the LST and analyzed its spatial distribution and the spatiotemporal characteristics of the surface urban heat island (SUHI) effect. The findings indicated a notable increase in average summer temperatures between the 2 years, with a 1.67°C rise from 2016 to 2021. Despite this increase, there was an observed reduction in the extent of SUHI areas, suggesting potential mitigation efforts. Additionally, the study revealed that karst regions were more susceptible to forming “abnormal” heat islands due to their distinct geomorphological features. The implications of this research are critical for urban development planning and the pursuit of sustainable urbanization in the Chishui River Basin. By understanding the thermal dynamics and their relationship with urbanization and karst landscapes, policymakers and urban planners can devise strategies to minimize the adverse effects of SUHI while promoting ecological balance and environmental health. Future research should extend the temporal analysis, employ higher resolution data, compare findings with other regions, and provide a detailed examination of mitigation efforts to enhance the robustness and applicability of the conclusions, provide stronger scientific evidence for the ecological sustainability of the Chishui River Basin.

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Surface parameters from SEVIRI observations through a Kalman filter approach: application and evaluation of the scheme in Southern Italy

Cited by 4 publications

References 17 publications

Estimation of Land Surface Temperature in an Agricultural Region of Bangladesh from Landsat 8: Intercomparison of Four Algorithms

Estimation of Land Surface Temperature in an Agricultural Region of Bangladesh from Landsat 8: Intercomparison of Four Algorithms

SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

Integrating urban development and ecological sustainability: a study on land surface temperature and urban heat island effect in a Karst River Basin

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