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<p><strong>Abstract.</strong> The Indian and French Space Agencies, ISRO and CNES, have conceptualized a space-borne Thermal Infrared Reflectance (TIR) mission, TRISHNA (Thermal infRared Imaging Satellite for High-resolution Natural Resource Assessment). The primary design drivers of TRISHNA are the monitoring of (i) terrestrial water stress and use, and of (ii) coastal and continental water. A suit of four TIR bands and six optical bands is planned. The TIR bands will be centred at 8.6&amp;thinsp;&amp;mu;m, 9.1&amp;thinsp;&amp;mu;m, 10.3&amp;thinsp;&amp;mu;m and 11.5&amp;thinsp;&amp;mu;m to provide noon-night global observations at 57m nadir resolution over land and coastal regions. The field of view (FOV) is &amp;plusmn;34&amp;deg; and the orbit of 761&amp;thinsp;km altitude was designed to allow 3 sub-cycle acquisitions during the 8-day cycle. The optical bands correspond to blue, green, red, and NIR plus two SWIR bands at 1.38&amp;thinsp;&amp;mu;m and 1.61&amp;thinsp;&amp;mu;m. The green, red, NIR and the 1.61&amp;thinsp;&amp;mu;m SWIR bands will have better radiometry quality than those of AWiFS. ISRO and CNES will develop optical and TIR payloads, respectively. Assessing evapotranspiration and furthermore Gross and Net Primary Productivity (GPP and NPP) will in turn assist in quantifying water use in rainfed and irrigated agriculture, water stress and water use efficiency, with expected applications to agricultural drought and early warning, crop yield prediction, water allocation, implementation of water rights, crop insurance business and agro-advisories to farmers. The other scientific objectives of TRISHNA are also briefly described. TRISHNA instrument will fly aboard a ISRO spacecraft scheduled to be launched from 2024 for a minimum period of 5 years’ mission lifetime.</p>

Spatially distributed air temperature data are required for climatological, hydrological and environmental studies. However, high spatial distribution patterns of air temperature are not available from meteorological stations due to its sparse network. The objective of this study was to estimate high spatial resolution minimum air temperature (T min) and maximum air temperature (T max) over the Indo-Gangetic Plain using Moderate Resolution Imaging Spectroradiometer (MODIS) data and India Meteorological Department (IMD) ground station data. T min was estimated by establishing an empirical relationship between IMD T min and night-time MODIS Land Surface Temperature (T s). While, T max was estimated using the Temperature-Vegetation Index (TVX) approach. The TVX approach is based on the linear relationship between T s and Normalized Difference Vegetation Index (NDVI) data where T max is estimated by extrapolating the NDVI-T s regression line to maximum value of NDVI max for effective full vegetation cover. The present study also proposed a methodology to estimate NDVI max using IMD measured T max for the Indo-Gangetic Plain. Comparison of MODIS estimated T min with IMD measured T min showed mean absolute error (MAE) of 1.73 • C and a root mean square error (RMSE) of 2.2 • C. Analysis in the study for T max estimation showed that calibrated NDVI max performed well, with the MAE of 1.79 • C and RMSE of 2.16 • C.

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This letter presents quantification and comparison of spectral characteristics of three similar sensors, namely Linear Imaging Self-Scanning Sensor (LISS)-III, LISS-IV and Advanced Wide Field Sensor (AWiFS) on board Indian Remote Sensing (IRS) satellites Resourcesat-1 (RS1) and Resourcesat-2 (RS2). Theoretical estimates of three critical spectral characteristics, effective bandwidth ( λ), central wavelength (λ c ) and bandpass solar exoatmospheric irradiance (E 0 ), have been computed based on the laboratory measurements of the relative spectral response (RSR) for each spectral band. A comparative analysis between two estimates computed through the moment method and the full width at half maximum (FWHM) method showed noticeable differences of the order of 4.4-14.1 nm in λ and λ c for the corresponding band of Resourcesat sensors. A coefficient of variation (CV) of the order of 0.1-1.3% was noticed in E 0 among various Resourcesat sensors, which could induce a difference of 0.26-3.27% in the estimation of top-of-atmosphere (TOA) reflectance. The variations in spectral characteristics among the Resourcesat sensors should be taken into account when comparisons are made between measurements from sensors on board RS1 and RS2 satellites, for example, for long-term monitoring of the Earth's environment.