Preliminary estimate of calibration of the moderate resolution imaging spectroradiometer thermal infrared data using Lake Titicaca

Wan, Zhengming; Zhang, Yulin; Li, Zhao-Liang; Wang, Ruibo; Salomonson, V. V.; Arnaud, Yves; Bosseno, Roland; Hanocq, Jean Francois

doi:10.1016/s0034-4257(01)00327-3

Cited by 40 publications

(34 citation statements)

References 27 publications

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“…Cases 2 -7 in Table 3 are the six comparisons made for the MODIS LST products with the in situ measurement data that we collected over the silt playa in Railroad Valley, NV. Following the same procedures used in Wan et al (2002), the emissivity effect on the LSTs measured by the IR radiometers is calculated based on the spectral emissivity averaged from our measurements of silt playa samples collected from the site, typical atmospheric temperature and water vapor profiles measured at the site, and the spectral response function of the IR radiometer. It is 2.3 K with an estimated uncertainty slightly less than 1 K due to the spatial variation in the surface emissivities.…”

Section: Validation Of the 1-km Level-2 Lst Product Using Vegetation mentioning

confidence: 99%

Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data

Wan¹,

Zhang²,

Zhang³

et al. 2002

Remote Sensing of Environment

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Section: Validation Of the 1-km Level-2 Lst Product Using Vegetation mentioning

confidence: 99%

Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data

Wan¹,

Zhang²,

Zhang³

et al. 2002

Remote Sensing of Environment

Self Cite

771

488

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“…Recent applications include vegetated areas (Coops et al, 2009), CO 2 exchange (Schubert et al, 2010), and permafrost at regional ) and local scales (Langer et al, 2010;Westermann et al, 2011). MODIS 1 km LST products have been cross-compared or validated against ground-based temperature measurements over homogeneous surfaces such as lakes (Wan et al, 2002a(Wan et al, , b, 2004Hook et al, 2007;Wan, 2008;Crosman and Horel, 2009), rice crops (Coll et al, 2005(Coll et al, , 2009Wan et al, 2004;Galve et al, 2007), silt-playas (Snyder et al, 1997), and densely vegetated areas (Wan, 2008). The 1 km products have also been validated with the alternative radiance-based (R-based) method over a lake, rice crops (Wan and Li., 2008;Coll et al, 2009) and dense forest (Coll et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Comparison of MODIS-derived land surface temperatures with ground surface and air temperature measurements in continuous permafrost terrain

2012

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Abstract. Obtaining high resolution records of surface temperature from satellite sensors is important in the Arctic because meteorological stations are scarce and widely scattered in those vast and remote regions. Surface temperature is the primary climatic factor that governs the existence, spatial distribution and thermal regime of permafrost which is a major component of the terrestrial cryosphere. Land Surface (skin) Temperatures (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to ground-based nearsurface air (T air ) and ground surface temperature (GST) measurements obtained from 2000 to 2008 at herbaceous and shrub tundra sites located in the continuous permafrost zone of Northern Québec, Nunavik, Canada, and of the North Slope of Alaska, USA. LSTs (temperatures at the surface materials-atmosphere interface) are found to be better correlated with T air (1-3 m above the ground) than with available GST (3-5 cm below the ground surface). As T air is most often used by the permafrost community, this study focused on this parameter. LSTs are in stronger agreement with T air during the snow cover season than in the snow free season. Combining Aqua and Terra LST-Day and LST-Nigh acquisitions into a mean daily value provides a large number of LST observations and a better overall agreement with T air . Comparison between mean daily LSTs and mean daily T air , for all sites and all seasons pooled together yields a very high correlation (R = 0.97; mean difference (MD) = 1.8 • C; and standard deviation of MD (SD) = 4.0 • C). The large SD can be explained by the influence of surface heterogeneity within the MODIS 1 km 2 grid cells, the presence of undetected clouds and the inherent difference between LST and T air . Retrieved over several years, MODIS LSTs offer a great potential for monitoring surface temperature changes in high-latitude tundra regions and are a promising source of input data for integration into spatially-distributed permafrost models.

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“…The Terra MODIS 8-day LST with 1 km resolution (MOD11A2, collection v005) was used. The MODIS land surface temperature is derived from two thermal infrared band channels, i.e., 31 (10.78-11.28 µm) and 32 (11.77-12.27 µm) using the split-window algorithm [53] which corrects atmospheric effects and emissivity using a look-up table based on global land surface emissivity in the thermal infrared band. An accuracy assessment across a wide set of test sites indicates an accuracy better than 1 km with a root mean square (RMS) less than 0.5 K in most cases [54].…”

Section: Land Surface Temperature (Lst)mentioning

confidence: 99%

Identification of Ecosystem Functional Types from Coarse Resolution Imagery Using a Self-Organizing Map Approach: A Case Study for Spain

et al. 2014

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Ecosystem state can be characterized by a set of attributes that are related to the ecosystem functionality, which is a relevant issue in understanding the quality and quantity of ecosystem services and goods, adaptive capacity and resilience to perturbations. This study proposes a major identification of Ecosystem Functional Types (EFTs) in Spain to characterize the patterns of ecosystem functional diversity and status, from several functional attributes as the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and Albedo. For this purpose, several metrics, related to the spatial variability in seasonal and annual patterns (e.g., relative range), have been derived from remote sensing time series of 1 km MODIS over the period 2000-2009. Moreover, precipitation maps from data provided by the AEMet (Agencia Estatal de Meteorología) and the corresponding aridity and humidity indices were also included in the analysis. To create the EFTs, the potential of the joint use of Kohonen's Self-Organizing Map (SOM) and the k-means clustering algorithm was tested. The EFTs were analyzed using different remote sensing (i.e., Gross Primary Production) and climatic variables. The relationship of the EFTs with existing land cover datasets and climatic data were analyzed through a correspondence analysis (CA

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Preliminary estimate of calibration of the moderate resolution imaging spectroradiometer thermal infrared data using Lake Titicaca

Cited by 40 publications

References 27 publications

Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data

Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data

Comparison of MODIS-derived land surface temperatures with ground surface and air temperature measurements in continuous permafrost terrain

Identification of Ecosystem Functional Types from Coarse Resolution Imagery Using a Self-Organizing Map Approach: A Case Study for Spain

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