Retrieval of Land Surface Emissivities Over Partially Vegetated Surfaces From Satellite Data Using Radiative Transfer Models

Pérez-Planells, Lluís; Niclòs, Raquel; Valor, E.; Goettsche, Frank

doi:10.1109/tgrs.2022.3224639

Cited by 10 publications

(2 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some existing monthly LSE databases also do not account for angular variations, which were discovered and demonstrated previously [34,35]. Some other previous studies also endeavored to develop a model to produce LST with angular LSE and LST corrections [36] or to investigate several IR LSE angular variation models for vegetation canopies [37]. While further efforts are still needed in this study to address angular variations of the existing LSE database, extensive LSE field measurements can be made to comprehensively understand how LSE changes with viewing angles over different desert surface types and in different weather conditions.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of CAMEL over the Taklimakan Desert Using Field Observations

Han

et al. 2023

Land

View full text Add to dashboard Cite

Infrared (IR) land surface emissivity (LSE) plays an important role in numerical weather prediction (NWP) models through the satellite radiance assimilation. However, due to the large uncertainties in LSE over the desert, many land-surface sensitive channels of satellite IR sensors are not assimilated. This calls for further assessments of the quality of satellite-retrieved LSE in these desert regions. A set of LSE observations were made from field experiments conducted on 16–18 October 2013 along a south/north desert road in the Taklimakan Desert (TD), China. The observed LSEs (EOBS) are thus used in this study as the reference values to evaluate the quality of Combined ASTER MODIS Emissivity over Land (CAMEL) data. Analysis of these data shows four main results. First, the CAMEL datasets appear to sufficiently capture the spatial variations in LSE from the oasis to the hinterland of the TD (this is especially the case in the quartz reststrahlen band). From site 1 at the southern edge of the Taklimakan Desert to site 10 at the northern edge, the measured LSE and the corresponding CAMEL observation in the quartz reststrahlen band first decrease and reach their minimum around sites 4–6 in the hinterland of the Taklimakan Desert. Then, the LSE increases gradually and finally reaches its maximum at site 10, which has a clay ground surface, showing that the LSE is higher at the edges of the desert and lower in the center. Second, the CAMEL values at 11.3 μm have a zonal distribution characterized by a northeast–southwest strike, though such an artifact might have been introduced by ASTER LSE data during the merging process that created the CAMEL dataset. Third, the unrealistic variation of the original EOBS can be filtered out with useful signals, as identified by the first six principal components of the PCA conducted on the laboratory-measured hyperspectral emissivity spectra (ELAB). Fourth, the CAMEL results correlate well with the measured LSE at the 10 observation sites, with the observed LSE being slightly smaller than the CAMEL values in general.

show abstract

Section: Discussionmentioning

confidence: 99%

Evaluation of CAMEL over the Taklimakan Desert Using Field Observations

Han

et al. 2023

Land

View full text Add to dashboard Cite

show abstract

“…(a) Temperature-based (T-based) validation, in which satellite data are compared with concurrent in-situ measurements at ground stations located in homogeneous sites [13][14][15]; (b) Satellite-satellite intercomparison, in which the satellite product being assessed is compared with a second well-characterized satellite product. Although this method cannot be considered as a validation source itself when validating a new satellite product, it provides useful information regarding spatial differences and consistency between the intercompared sensors [16,17]; (c) Radiance-based (R-based) validation, which validates the satellite derived LST at a well-characterized homogeneous site using reference LSTs estimated from satellite data corrected from atmospheric and emissivity effects with concurrent atmospheric profiles and known emissivities [18][19][20]; (d) Time-series intercomparisons, which are generally used to detect issues in the satellite sensor during its time life [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Retrieval Consistency between LST CCI Satellite Data Products over Europe and Africa

et al. 2023

View full text Add to dashboard Cite

The assessment of satellite-derived land surface temperature (LST) data is essential to ensure their high quality for climate applications and research. This study intercompared seven LST products (i.e., ATSR_3, MODISA, MODIST, SLSTRA, SLSTRB, SEVIR2 and SEVIR4) of the European Space Agency’s (ESA) LST Climate Change Initiative (LST_cci) project, which are retrieved for polar and geostationary orbit satellites, and three operational LST products: NASA’s MODIS MOD11/MYD11 LST and ESA’s AATSR LST. All data were re-gridded on to a common spatial grid of 0.05° and matched for concurrent overpasses within 5 min. The matched data were analysed over Europe and Africa for monthly and seasonally aggregated median differences and studied for their dependence on land cover class and satellite viewing geometry. For most of the data sets, the results showed an overall agreement within ±2 K for median differences and robust standard deviation (RSD). A seasonal variation of median differences between polar and geostationary orbit sensor data was observed over Europe, which showed higher differences in summer and lower in winter. Over all land cover classes, NASA’s operational MODIS LST products were about 2 K colder than the LST_cci data sets. No seasonal differences were observed for the different land covers, but larger median differences between data sets were seen over bare soil land cover classes. Regarding the viewing geometry, an asymmetric increase of differences with respect to nadir view was observed for day-time data, which is mainly caused by shadow effects. For night-time data, these differences were symmetric and considerably smaller. Overall, despite the differences in the LST retrieval algorithms of the intercompared data sets, a good consistency between the LST_cci data sets was determined.

show abstract

Retrieval of high spatial resolution mountainous land surface temperature considering topographic and adjacency effects

He,

Tang,

2024

Sci. China Earth Sci.

View full text Add to dashboard Cite

Retrieval of Land Surface Emissivities Over Partially Vegetated Surfaces From Satellite Data Using Radiative Transfer Models

Cited by 10 publications

References 67 publications

Evaluation of CAMEL over the Taklimakan Desert Using Field Observations

Evaluation of CAMEL over the Taklimakan Desert Using Field Observations

Retrieval Consistency between LST CCI Satellite Data Products over Europe and Africa

Retrieval of high spatial resolution mountainous land surface temperature considering topographic and adjacency effects

Contact Info

Product

Resources

About