The Indian-French Trishna Mission: Earth Observation in the Thermal Infrared with High Spatio-Temporal Resolution

Lagouarde, Jean‐Pierre; Bhattacharya, B. K.; Crebassol, Philippe; Gamet, Philippe; Babu, S. Suresh; Boulet, Gilles; Briottet, Xavier; Buddhiraju, Krishna Mohan; Cherchali, S.; Dadou, Isabelle; Dedieu, Gérard; Gouhier, M.; Hagolle, Olivier; Irvine, Mark; Jacob, Frédéric; Kumar, Akhilesh; Kumar, Karanam Kishore; Laignel, Benoı̂t; Mallick, Kaniska; Murthy, C. S.; Olioso, Albert; Ottlé, Catherine; Pandya, Mehul R.; Raju, P. L. N.; Roujean, Jean‐Louis; Sekhar, M.; Shukla, Munn Vinayak; Singh, Sushil Kumar; Sobrino, José A.; Ramakrishnan, R.

doi:10.1109/igarss.2018.8518720

Cited by 50 publications

(47 citation statements)

References 17 publications

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“…For example, in July at 10:00, 29 observations were identified clear-sky at Tonzi Ranch, CA on average, but only 16 at Chestnut Ridge, TN. In comparison to the global statistics for cloud-free MODIS observations produced by Lagouarde et al [23] with a 5 km resolution, we found that ground-based estimates were usually slightly higher than MODIS-derived products. This may be due to differences in spatial scales, i.e., a partly cloudy sky can significantly affect a km-scale satellite pixel and be flagged by the cloud mask algorithm without affecting in situ observations.…”

Section: Scaling Et From Instantaneous Observations To Daytime Averagesmentioning

confidence: 49%

“…Two overpass times have been considered to represent the nominal times of a morning and afternoon satellite overpass: 10:00 and 13:00 The 10:00 overpass corresponds to instruments like the Thermal Infrared Sensor (TIRS) onboard Landsat-8, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), MODIS onboard Terra or the Sea and Land Surface Temperature Radiometer (SLSTR) onboard Sentinel 3, and the afternoon overpass to instruments like MODIS onboard Aqua or VIIRS onboard the Suomi National Polar-Orbiting Partnership (Suomi-NPP) and Joint Polar Satellite System (JPSS) spacecrafts, for example. The afternoon overpass is also the preferred overpass time for missions in preparation, such as TRISHNA or LSTM [22,23]. The impact of acquisition time on the ability to detect water stress and then derive daily ET estimates in accordance with the actual stress level and the stability of temperature measurements was discussed by [54,55].…”

Section: Generation Of Series Of Observations With Different Revisit mentioning

confidence: 99%

“…To support agriculture management services, LSTM will have a spatial resolution of 30-50 m and a temporal resolution lower than three days [22]. The French Space Agency (CNES) and the Indian Space Research Organization (ISRO) have also started the design of a new satellite mission called TRISHNA, combining a high spatial resolution (50 m) and high revisit capacities (between two and three days) in the thermal infrared domain [23]. The launch of TRISHNA is planned at the 2024 horizon.…”

Section: Introductionmentioning

confidence: 99%

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Impact of the Revisit of Thermal Infrared Remote Sensing Observations on Evapotranspiration Uncertainty—A Sensitivity Study Using AmeriFlux Data

et al. 2019

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Thermal infrared remote sensing observations have been widely used to provide useful information on surface energy and water stress for estimating evapotranspiration (ET). However, the revisit time of current high spatial resolution (<100 m) thermal infrared remote sensing systems, sixteen days for Landsat for example, can be insufficient to reliably derive ET information for water resources management. We used in situ ET measurements from multiple Ameriflux sites to (1) evaluate different scaling methods that are commonly used to derive daytime ET estimates from time-of-day observations; and (2) quantify the impact of different revisit times on ET estimates at monthly and seasonal time scales. The scaling method based on a constant evaporative ratio between ET and the top-of-atmosphere solar radiation provided slightly better results than methods using the available energy, the surface solar radiation or the potential ET as scaling reference fluxes. On average, revisit time periods of 2, 4, 8 and 16 days resulted in ET uncertainties of 0.37, 0.55, 0.73 and 0.90 mm per day in summer, which represented 13%, 19%, 23% and 31% of the monthly average ET calculated using the one-day revisit dataset. The capability of a system to capture rapid changes in ET was significantly reduced for return periods higher than eight days. The impact of the revisit on ET depended mainly on the land cover type and seasonal climate, and was higher over areas with high ET. We did not observe significant and systematic differences between the impacts of the revisit on monthly ET estimates that are based on morning or afternoon observations. We found that four-day revisit scenarios provided a significant improvement in temporal sampling to monitor surface ET reducing by around 40% the uncertainty of ET products derived from a 16-day revisit system, such as Landsat for instance.

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Section: Scaling Et From Instantaneous Observations To Daytime Averagesmentioning

confidence: 49%

Section: Generation Of Series Of Observations With Different Revisit mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of the Revisit of Thermal Infrared Remote Sensing Observations on Evapotranspiration Uncertainty—A Sensitivity Study Using AmeriFlux Data

et al. 2019

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“…Among the existing two-source models (SPARSE [33], ESVEP [41], ALEXI [43], TSEB [32]), the thermal-based two-source energy balance (TSEB) [32] was chosen for its simplicity and because it has been shown to accurately predict LE in different contexts, including sparse canopy in semi-arid areas [9,21,25,34,38]. Until the launch of a future high-resolution and high-repetitiveness mission in the thermal infrared domain [44], the possibilities in terms of LST products are limited to the Moderate Sensors Resolution Imaging Spectroradiometer (MODIS) (1 km and a daily revisit time) and Landsat (60 to 100 m resolution, 16 days). The question arises as to what is the required level of heterogeneity representation in terms of input surface variables to get accurate predictions of convective fluxes (H and LE) with the TSEB model based on the available remote sensing products?…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Evaluation of the TSEB Model over a Complex Agricultural Landscape in Morocco

et al. 2020

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An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm−2 and 0.79 and 82.0 Wm−2 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm−2), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm−2). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.

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“…Several projects are currently under study to develop thermal satellites with high enough spatial resolution and revisit capacities to characterize the microscale structure of SUHIs. These are the Indian (ISRO)-French (CNES) mission TRISHNA [13], the European (ESA) LSTM [14], and HyspIRI in NASA/JPL [15]. But such missions lack in their spatial resolution of about 50-60 m and are not able to discern the local LST on an urban object scale.…”

Section: Introductionmentioning

confidence: 99%

Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data

et al. 2019

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Urban Heat Islands (UHIs) at the surface and canopy levels are major issues in urban planification and development. For this reason, the comprehension and quantification of the influence that the different land-uses/land-covers have on UHIs is of particular importance. In order to perform a detailed thermal characterisation of the city, measures covering the whole scenario (city and surroundings) and with a recurrent revisit are needed. In addition, a resolution of tens of meters is needed to characterise the urban heterogeneities. Spaceborne remote sensing meets the first and the second requirements but the Land Surface Temperature (LST) resolutions remain too rough compared to the urban object scale. Thermal unmixing techniques have been developed in recent years, allowing LST images during day at the desired scales. However, while LST gives information of surface urban heat islands (SUHIs), canopy UHIs and SUHIs are more correlated during the night, hence the development of thermal unmixing methods for night LSTs is necessary. This article proposes to adapt four empirical unmixing methods of the literature, Disaggregation of radiometric surface Temperature (DisTrad), High-resolution Urban Thermal Sharpener (HUTS), Area-To-Point Regression Kriging (ATPRK), and Adaptive Area-To-Point Regression Kriging (AATPRK), to unmix night LSTs. These methods are based on given relationships between LST and reflective indices, and on invariance hypotheses of these relationships across resolutions. Then, a comparative study of the performances of the different techniques is carried out on TRISHNA synthesized images of Madrid. Since TRISHNA is a mission in preparation, the synthesis of the images has been done according to the planned specification of the satellite and from initial Aircraft Hyperspectral Scanner (AHS) data of the city obtained during the DESIREX 2008 capaign. Thus, the coarse initial resolution is 60 m and the finer post-unmixing one is 20 m. In this article, we show that: (1) AATPRK is the most performant unmixing technique when applied on night LST, with the other three techniques being undesirable for night applications at TRISHNA resolutions. This can be explained by the local application of AATPRK. (2) ATPRK and DisTrad do not improve significantly the LST image resolution. (3) HUTS, which depends on albedo measures, misestimates the LST, leading to the worst temperature unmixing. (4) The two main factors explaining the obtained performances are the local/global application of the method and the reflective indices used in the LST-index relationship.

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The Indian-French Trishna Mission: Earth Observation in the Thermal Infrared with High Spatio-Temporal Resolution

Cited by 50 publications

References 17 publications

Impact of the Revisit of Thermal Infrared Remote Sensing Observations on Evapotranspiration Uncertainty—A Sensitivity Study Using AmeriFlux Data

Impact of the Revisit of Thermal Infrared Remote Sensing Observations on Evapotranspiration Uncertainty—A Sensitivity Study Using AmeriFlux Data

Multi-Scale Evaluation of the TSEB Model over a Complex Agricultural Landscape in Morocco

Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data

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