DESIS Calibration: Status and Results after 4 Years of Operation

The DESIS Hyperspectral instrument is approaching four years in operation at the MUSES platform on the International Space Station. DESIS operates in the VNIR range (400-1000 nm) and has some unique properties among spaceborne hyperspectral instruments like a narrow spectral sampling distance (2.55 nm), the use of a pointing unit and a LED equipped calibration unit. During this time, the instrument has been calibrated using a combination of vicarious calibration and calibration unit data. The calibration unit is used for the spectral calibration of the sensor. The analysis of the LED data has shown two different operation modes depending on the temperature gradient inside the instrument. Moreover, the data shows that the spectral calibration is stable within 0.1 nm (RMS) for each temperature gradient mode, with a separation between them of around 0.5 nm. The vicarious calibration is used for the radiometric calibration and uses as input Earth images over homogeneous areas and reference data from RadCalNet stations. Data from the homogeneous areas are used to update individual pixel coefficients in order to provide a uniform spatial and spectral sensor response. Later, RadCalNet data are used for an adjustment of the absolute calibration scale. With this approach the DESIS instrument can be calibrated within 4% (RMS) and absolute mean bias within 2% at wavelengths above 500 nm. The long-term analysis of the DESIS calibration data also shows that the sensor experiences a mean degradation of around 3.4%/year above 500 nm. Below 500 nm the instrument shows a stronger degradation (up to 20%/year at the shortest wavelengths) between the start of operations and July 2021, being stable after this date. Finally, the orthorectification process achieves a RMSE of 20 m in North and East directions with the automatic extraction of ground control points and comparison with reference images

Influence of the Solar Spectra Models on PACO Atmospheric Correction

The solar irradiance is the source of energy used by passive optical remote sensing to measure the ground reflectance and, from there, derive the ground properties. Therefore, the precise knowledge of the incoming solar irradiance is fundamental for the atmospheric correction (AC) algorithms. These algorithms use the simulation results of a model of the interactions of the atmosphere with the incoming solar irradiance to determine the atmospheric contribution of the remote sensing observations. This study presents the differences in the atmospherically corrected ground reflectance of multi- and hyper-spectral sensors assuming three different solar models: Thuillier 2003, Fontenla 2011 and TSIS-1 HRS. The results show no difference when the solar irradiance model is preserved through the full processing chain. The differences appear when the solar irradiance model used in the atmospheric correction changes, and this difference is larger between some irrradiance models (e.g., TSIS and Thuillier 2003) than for others (e.g., Fontenla 2011 and TSIS)

Procedimientos legales, administrativos y contables, que orienten el funcionamiento de las entidades comunales, que prestan el servicio de agua potable, en el municipio de San Esteban Catarina, a desarrollarse en el año 2020

Al sector de las entidades comunales que administran sistemas de agua, históricamente se le ha prestado poca atención en los estudios del campo de las ciencias económicas, sin embargo el impacto de estas entidades, en el desarrollo humano, social y económico de la población salvadoreña, hacen de El Salvador uno de los países de América Latina más privilegiados en términos del acceso al agua potable, siendo las asociaciones comunales, comités y juntas de agua, las que abastecen del vital líquido a más 1.1 millones de habitantes en las zonas rurales de El Salvador. En su mayoría, los sistemas de agua rurales, han logrado proveer de agua a sus comunidades durante décadas, sin embargo, a menudo algunos muestran problemas financieros, que consecuentemente provocan una disminución en la calidad del servicio que prestan. La causa principal de este fenómeno, es la escasa cultura del control interno, planeación y análisis financiero, aunado al desconocimiento de la legislación vigente aplicable a la explotación del agua, que aparte del cumplimiento obligatorio de las disposiciones, otorga una serie de beneficios subsidiarios, fiscales y estatus preferente sobre otros grupos ante los órganos reguladores

The DESIS L2A processor and validation of L2A products using AERONET and RadCalNet data

The hyperspectral instrument "DLR Earth Sensing Imaging Spectrometer" (DESIS) is a VNIR sensor on-board of the International Space Station (ISS) and operational since October 2019. DESIS acquires images of Earth on user request with a swath of about 30 km width and 235 bands with a Full Width at Half Maximum (FWHM) of 3.5 nm in the spectral range 400 to 1000 nm. In this contribution we will present the basis of the atmospheric correction by PACO software, implemented inside the DESIS Ground Segment as L2A processor. The resulting L2A products will be validated against independent in-situ measurements. The aerosol optical thickness and water vapor will be compared with the Aerosol Robotic Network (AERONET) measurements and the surface reflectance will be validated with the Radiometric Calibration Network (RadCalNet) data

DLR HySU—A Benchmark Dataset for Spectral Unmixing

Spectral unmixing represents both an application per se and a pre-processing step for several applications involving data acquired by imaging spectrometers. However, there is still a lack of publicly available reference data sets suitable for the validation and comparison of different spectral unmixing methods. In this paper, we introduce the DLR HyperSpectral Unmixing (DLR HySU) benchmark dataset, acquired over German Aerospace Center (DLR) premises in Oberpfaffenhofen. The dataset includes airborne hyperspectral and RGB imagery of targets of different materials and sizes, complemented by simultaneous ground-based reflectance measurements. The DLR HySU benchmark allows a separate assessment of all spectral unmixing main steps: dimensionality estimation, endmember extraction (with and without pure pixel assumption), and abundance estimation. Results obtained with traditional algorithms for each of these steps are reported. To the best of our knowledge, this is the first time that real imaging spectrometer data with accurately measured targets are made available for hyperspectral unmixing experiments. The DLR HySU benchmark dataset is openly available online and the community is welcome to use it for spectral unmixing and other applications