Evaluation of landsat-8 thermal bands to monitor land surface temperature

Ponencia presentada en: IX Congreso de la Asociación Española de Climatología celebrado en Almería entre el 28 y el 30 de octubre de 2014.[ES]El nuevo Thermal Infrared Sensor (TIRS) a bordo del Landsat-8 (L8) dispone de dos bandas térmicas, 10 (11.60-11.19 μm) y 11 (11.50-12.51 μm), con una resolución espacial de 100m, con el fin de proporcionar temperaturas de la superficie terrestre (LST) de una manera más precisa que su predecesor Landsat-7 ETM+. El L8 fue lanzado en febrero de 2013, comenzando su adquisición operativa a mediados de abril. Los primeros estudios realizados por el equipo de calibración de L8 mostraron errores sistemáticos significativos para el TIRS, y en febrero de 2014 el archivo de imágenes L8 TIRS fue reprocesado para corregir dichos errores. En este estudio, con el fin de comprobar la calibración del L8 TIRS, realizamos medidas de campo en una zona llana y térmicamente homogénea dedicada al cultivo del arroz. A partir de estas medidas de LST simulamos las radiancias y temperaturas de brillo a nivel del satélite y las comparamos con los datos TIRS. Tal y como apuntaba el equipo de L8, nuestros resultados muestran una sobreestimación para la banda 11. Sin embargo, el recalibrado aplicado por dicho equipo para ambas bandas ha resultado no ser satisfactorio en nuestra zona experimental, ya que proponen sustraer errores sistemáticos mayores a los requeridos.[EN]The new Landsat-8 (L8) Thermal Infrared Sensor (TIRS) has two thermal bands, 10 (11.60- 11.19 μm) and 11 (11.50-12.51 μm) at 100-m spatial resolution, aimed to provide more accurate Land Surface Temperatures (LST) than Landsat-7 ETM+. L8 was launched on February 2013, and operational acquisitions started in middle April 2013. The first studies by the L8 Calibration Team showed significant TIRS temperature offsets, and in February 2014 the L8 TIRS archive was reprocessed to remove these offsets. In this study, ground LST measurements were performed in a flat and thermally homogeneous area of rice-crop fields for checking the calibration of the L8 TIRS bands. At-sensor radiances and brightness temperatures were simulated from ground-measured LSTs and compared with TIRS values. A significant overestimation was observed for band 11, in agreement with the L8 Calibration Team results. However, their recalibration was shown unsatisfactory in our test site for both bands, since they proposed subtracting higher offsets than required.This study was supported by the Spanish Ministerio de Economía y Competitividad (projects CGL2010-16364, CGL2010-17577/CLI, CGL2011-13579-E, CGL2011-30433 and GRACCIE Consolider-Ingenio 2010; and Dr. Niclòs "Ramón y Cajal" Research Contract) and Generalitat Valenciana (PROMETEO/2009/006 and PROMETEO/2009/086 projects)

Impact of Initial Soil Temperature Derived from Remote Sensing and Numerical Weather Prediction Datasets on the Simulation of Extreme Heat Events

Extreme heat weather events have received increasing attention and has become of special importance as they can remarkably affect sectors as diverse as public health, energy consumption, water resources, natural biodiversity and agricultural production. In this regard, summer temperatures have become a parameter of essential interest under a framework of a hypothetical increase in the number of intense-heat conditions. Thus, their forecast is a crucial aspect bearing in mind a mitigation of the effects and impacts that these intense-heat situations could produce. The current work tries to reach a better understanding of these sorts of situations that are really common over the Western Mediterranean coast. An extreme heat episode that took place in the Valencia Region in July 2009 is analysed, based on the simulations performed with the Regional Atmospheric Modeling System (RAMS). This event recorded maximum temperatures exceeding 40 °C amply extended over the region besides reaching minimum temperatures up to 25.92 °C. We examine the role of improved skin and soil temperature (ST) initial conditions in the forecast results by means of different modelling and satellite-derived products. The influence of incorporating the Land Surface Temperature (LST) into RAMS is not found to produce a meaningful impact on the simulation results, independently of the resolution of the dataset used in the initial conditions of the model. In contrast, the introduction of the ST in lower levels, not only the skin temperature, has a more marked decisive effect in the simulation. Additionally, we have evaluated the influence of increasing the number of soil levels to spread deeper underground. This sensitivity experiment has revealed that more soil levels do not produce any meaningful impact on the simulation compared to the original one. In any case, RAMS is able to properly capture the observed patterns in those cases where a Western advection is widely extended over the area of study. This region’s variability in orography and in distances to the sea promotes the development of sea-breeze circulations, thus producing a convergence of two opposite wind flows, a Western synoptic advection and a sea-breeze circulation. As a result, the RAMS skill in those cases where a sea breeze is well developed depends on the proper location of the boundary and convergence lines of these two flows.This work has been funded by the Spanish Ministerio de Economía y Competitividad and the European Regional Development Fund (FEDER) through the project CGL2015-64268-R (MINECO/FEDER, UE), by the Regional Government of Valencia through the project PROMETEOII/2014/086 and by the Spanish Ministerio de Economía y Competitividad through the project CGL2011-30433-C02-02 (MINECO)

Determining water use of sorghum from two-source energy balance and radiometric temperatures

Estimates of surface actual evapotranspiration (ET) can assist in predicting crop water requirements. An alternative to the traditional crop-coefficient methods are the energy balance models. The objective of this research was to show how surface temperature observations can be used, together with a two-source energy balance model, to determine crop water use throughout the different phenological stages of a crop grown. Radiometric temperatures were collected in a sorghum (<i>Sorghum bicolor</i>) field as part of an experimental campaign carried out in Barrax, Spain, during the 2010 summer growing season. Performance of the Simplified Two-Source Energy Balance (STSEB) model was evaluated by comparison of estimated ET with values measured on a weighing lysimeter. Errors of ±0.14 mm h<sup>−1</sup> and ±1.0 mm d<sup>−1</sup> were obtained at hourly and daily scales, respectively. Total accumulated crop water use during the campaign was underestimated by 5%. It is then shown that thermal radiometry can provide precise crop water necessities and is a promising tool for irrigation management

Estimación de la evaporación/transpiración en un cultivo de viña mediante radiometría térmica

La estimación precisa de la evapotranspiración de cultivo (ETc), así como su partición en las componentes evaporativa (E) y transpirativa (T), resultan fundamentales para mejorar la eficacia en la gestión del riego de cultivos en hilera en regiones áridas y semiáridas. El objetivo de este trabajo es contribuir a un mejor entendimiento de la partición E/T sobre viña llevando a cabo un balance de energía por separado para las componentes de suelo y de vegetación. En este trabajo se presentan los resultados de un experimento llevado a cabo en la finca de Las Tiesas, Albacete, de junio a octubre de 2013. Se instalaron un conjunto de radiómetros de infrarrojo térmico, apuntando directamente a las plantas y al suelo entre hileras. Se tomaron medidas de las cuatro componentes de la radiación neta, del flujo de calor en el suelo, además de variables meteorológicas y parámetros biofísicos. Todas las medidas se almacenaron en intervalos de 15 minutos, y se promediaron después a escala horaria y diaria. El valor medio observado de ETc fue de 3,1 mm día-1. La evaporación se estimó en torno al 30%. Los resultados presentados en este trabajo ofrecen una primera impresión de la partición E/T, y muestran el potencial de la caracterización térmica de la viña con este finAn accurate estimation of crop evapotranspiration (ETc), and its partition into both components, soil evaporation (E) and canopy transpiration (T), is known to be critical for a more effective irrigation scheduling of row-crops in arid and semi-arid environments. Vineyards are the best example in Mediterranean countries. The aim of this work is to improve our understanding of the E/T partition in vineyards by establishing a separate energy balance for soil and canopy components. An experiment was conducted in Las Tiesas experimental farm, Albacete (Spain), from June to October of 2013. A set of thermal-infrared radiometers were assembled pointing directly to the plants and the soil between rows. Measurements of the four components of the net radiation over the canopy and soil heat fluxes, as well as meteorological variables and biophysical parameters were all collected and stored every 15-min. Hourly and daily averages were then computed and analyzed. An average daily ETc value of 3.1 mm day-1 was observed in both sites. Interrow soil evaporation reached as much as 30% of the total ETc. These results provide a first insight into the partition E/T and show the potential of the vine thermal characterization with this aim.Ministerio de Economía y Competitividad CGL2013-46862-C2-1/2-PUnión Europea, AGL2014-54201-C4-4-RInstituto Nacional de Investigaciones Agrarias RTA 2011-00100-C05-04Instituto Nacional de Investigaciones Agrarias RTA 2014-00049-C05-03Generalitat Valenciana PROMETEOII/2014/08

Generative Models from the perspective of Continual Learning

Which generative model is the most suitablefor Continual Learning? This paper aims at evaluating andcomparing generative models on disjoint sequential imagegeneration tasks. We investigate how several models learn andforget, considering various strategies: rehearsal, regularization,generative replay and fine-tuning. We used two quantitativemetrics to estimate the generation quality and memory ability.We experiment with sequential tasks on three commonly usedbenchmarks for Continual Learning (MNIST, Fashion MNISTand CIFAR10). We found that among all models, the originalGAN performs best and among Continual Learning strategies,generative replay outperforms all other methods. Even ifwe found satisfactory combinations on MNIST and FashionMNIST, training generative models sequentially on CIFAR10is particularly instable, and remains a challenge. Our code isavailable online

Levelset and B-spline deformable model techniques for image segmentation: a pragmatic comparative study

International audienceDeformable contours are now widely used in image segmentation, using different models, criteria and numerical schemes. Some theoretical comparisons between some deformable model methods have already been published. Yet, very few experimental comparative studies on real data have been reported. In this paper,we compare a levelset with a B-spline based deformable model approach in order to understand the mechanisms involved in these widely used methods and to compare both evolution and results on various kinds of image segmentation problems. In general, both methods yield similar results. However, specific differences appear when considering particular problems

Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain

The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided by the original Noah LSM and the Noah LSM with multiple physics options (Noah-MP). Furthermore, we assess the WRF sensitivity to different Noah-MP physics schemes, namely the calculation of canopy stomatal resistance (OPT_CRS), the soil moisture factor for stomatal resistance (OPT_BTR), and the surface layer drag coefficient (OPT_SFC). It has been found that these physics options strongly affect the energy partitioning at the land surface in short-time scale simulations. Aside from in situ observations, we use the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor to assess the Land Surface Temperature (LST) field simulated by WRF. Regarding multiple options in Noah-MP, WRF has been configured using three distinct soil moisture factors to control stomatal resistance (β factor) available in Noah-MP (Noah, CLM, and SSiB-types), two canopy stomatal resistance (Ball–Berry and Jarvis), and two options for surface layer drag coefficients (Monin–Obukhov and Chen97 scheme). Considering the β factor schemes, CLM and SSiB-type β factors simulate very low values of the latent heat flux while increasing the sensible heat flux. This result has been obtained independently of the canopy stomatal resistance scheme used. Additionally, the surface skin temperature simulated by Noah-MP is colder than that obtained by the original Noah LSM. This result is also highlighted when the simulated surface skin temperature is compared to the MSG-SEVIRI LST product. The largest differences between the satellite data and the mesoscale simulations are produced using the Noah-MP configurations run with the Monin–Obukhov parameterization for surface layer drag coefficients. In contrast, the Chen97 scheme shows larger surface skin temperatures than Monin–Obukhov, but at the expense of a decrease in the simulated sensible heat fluxes. In this regard, the ground heat flux and the net radiation play a key role in the simulation results.This research was funded by the Assistance Programmes of the University of Alicante “Programa de Redes-I3CE de calidad, innovación e investigación en docencia universitaria. Convocatoria 2018–2019. Alicante: Instituto de Ciencias de la Educación (ICE) de la Universidad de Alicante. Ref: [4334].” and “Programa de Redes-I3CE de calidad, innovación e investigación en docencia universitaria. Convocatoria 2020-21. Alicante: Instituto de Ciencias de la Educación (ICE) de la Universidad de Alicante. Ref: [5150].” as well as by Research Group VIGROB-116 (University of Alicante) and by the Spanish Ministerio de Ciencia e Innovación through the project PID2020-118797RB-I00/AEI