Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data

Coll, César; Caselles, Vicente; Galve, Joan M.; Valor, E.; Niclòs, Raquel; Sánchez, Juan Manuel; Rivas, Raúl Eduardo

doi:10.1016/j.rse.2005.05.007

Cited by 272 publications

(192 citation statements)

References 23 publications

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“…The results of the radiance-based and temperature-based validation indicated that the accuracy of the global MODIS LST product is better than 1 • C in most cases, including lakes, homogeneous vegetation, and soils under clear-sky conditions (Wan et al, 2002(Wan et al, , 2004Coll et al, 2005;Wan and Li, 2008;. Langer et al (2010) and Westermann et al (2011) focused on weekly averages and demonstrated an agreement generally better than 2 • C for MODIS LST in the summer season, at permafrost sites in Siberia and Svalbard, Norway, respectively.…”

Section: Modis Lst Productsmentioning

confidence: 96%

A new map of permafrost distribution on the Tibetan Plateau

et al. 2017

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Abstract. The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid-and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06 × 10 6 km 2 (0.97-1.15 × 10 6 km 2 , 90 % confidence interval) (40 %), 1.46 × 10 6 (56 %), and 0.03 × 10 6 km 2 (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.

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Section: Modis Lst Productsmentioning

confidence: 96%

A new map of permafrost distribution on the Tibetan Plateau

et al. 2017

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“…Uncertainties involved in the retrieval of LST can be related to (i) geographic characteristics of the test-site; (ii) the emissivity of land surface types and (iii) the atmospheric corrections (see [3]). Other sources of uncertainty include view-angle effect [2].…”

Section: Issues In Lst Retrievalmentioning

confidence: 99%

“…The importance of the land surface temperature (LST) in surface-based bio-geophysical processes and land-atmosphere interactions is well documented in the literature [1][2][3][4][5][6][7][8]. In complex terrain, meteorological stations and ground surveys are usually sparsely and/or irregularly distributed [6], hence, remotely sensed LST can be a critical source of data for the study of land surface processes.…”

Section: Introductionmentioning

confidence: 99%

“…Some of these studies have related LC indirectly to T a looking at LST as the intermediate link [18]. Finally, the last group of the published research have used modelling and in situ measurements for validation of the MODIS LST [3,4,[19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…Despite numerous research conducted on the validation of remotely sensed LST from various sensors, such as MODIS (e.g., [19,21,27]), Landsat (e.g., [23]) or a combination of sensors [3,4] in different parts of the world, a study of LST variations over different LC types is missing in the literature. LST itself is used to derive other surface parameters, such as the near-surface soil moisture (SM).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of MODIS LST Compared with WRF Model and in situ Data over the Waimakariri River Basin, Canterbury, New Zealand

2012

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In this study we examine the relationship between remotely sensed, in situ and modelled land surface temperature (LST) over a heterogeneous land-cover (LC) enclosed in alpine terrain. This relationship can help to understand to what extent the remotely sensed data can be used to improve model simulations of land surface parameters such as LST in mountainous areas. LST from the MODerate resolution Imaging Spectro-radiometer (MODIS), the modelled surface skin temperature by the Weather Research and Forecasting (WRF) mesoscale numerical model and the in situ measurements of surface temperature are used in the analysis. The test-site is located in a mountain valley in the Southern Alps of New Zealand. Geospatial analysis in GIS is used to relate pixels, grid-cells and points from the MODIS LST, model simulations and the in situ data, respectively. Differences between LST from MODIS, the WRF model and the in situ data are presented with respect to surface LC at different times of day. Initial results from regression analysis of the three datasets showed a goodness of fit R

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Seasonal evolution of ecohydrological controls on land surface temperature over complex terrain

2014

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The spatiotemporal distribution of Land Surface Temperature (LST) is linked to the partitioning of the coupled surface water and energy budgets. In watersheds with a strong seasonality in precipitation and vegetation cover, the temporal evolution of LST patterns are a signature of the interactions between the land surface and atmosphere. Nevertheless, few studies have sought to understand the topographical and ecohydrological controls on LST in regions of complex terrain. Numerical watershed models, tested against spatially distributed field and remote sensing data, can aid in linking the seasonal evolution of LST to meteorology, terrain, soil, and vegetation. In this study, we use a distributed hydrologic model to explore LST patterns in a semiarid mountain basin during the transition from a dry spring to the wetter North American monsoon (NAM). By accounting for vegetation greening through remotely sensed parameters, the model reproduces LST and surface soil moisture observations derived from ground, aircraft, and satellite platforms with good accuracy at individual sites and as spatial basin patterns. Distributed simulations reveal how LST varies with elevation, slope, and aspect and the role played by the seasonal vegetation canopy in cooling the land surface and increasing the spatial variability in LST. As a result, LST is shown to track well with ecosystem-specific changes in vegetation cover, evapotranspiration, and soil moisture during the NAM. Furthermore, vegetation greening is shown to modulate the spatial heterogeneity of LST during the NAM that should be considered in subsequent atmospheric studies in regions of complex terrain.

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Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data

Cited by 272 publications

References 23 publications

A new map of permafrost distribution on the Tibetan Plateau

A new map of permafrost distribution on the Tibetan Plateau

Analysis of MODIS LST Compared with WRF Model and in situ Data over the Waimakariri River Basin, Canterbury, New Zealand

Seasonal evolution of ecohydrological controls on land surface temperature over complex terrain

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