Determination of Net Radiation Balance using Satellite Imagery in Odeda Local Government Area, Ogun State, Nigeria

The energy received on the earth surface is responsible for driving activities on the earth and not all energy emitted by the sun reaches the earth surface; some are absorbed, reflected or scattered. There is need to determine the amount of energy that reaches the earth surface since not all the energy emitted from the sun reaches the earth. This energy is also responsible for making our general climate warm which ultimately brings us to the determination of Net radiation. This study applied remote sensing method to determine net radiation over Odeda Local Government Area. A Sentinel image from 2013 covering the study area was downloaded and computations were done using bands 5 and 7. These bands were used to compute the surface albedo, incoming short wave radiation, incoming long wave radiation and outgoing long wave radiation. The spectral signatures for each component from sentinel data were analysed, using the ArcGIS 10.6. The results showed the net radiation to be of moderate intensity with values ranging between 630.83 wm-2 and 684.68 wm-2 . The mean value over majority of the area was 651.20 wm-2 and the albedo of the area was low, with values ranging from 0.0028 to a value of 0.29 which is an indication of low reflectivity. This implied that more radiation was absorbed in the study area which impacted the soil temperature thereby influencing reduced soil moisture and a higher rate of evapotranspiration from plants within the study area.Keywords: thermal energy, atmospheric transmissivity, spatial analysis, surface albed

Radiación solar a partir de datos satelitales

La radiación solar es la principal fuente de energía renovable necesaria para que se cumplan diversos procesos en los cultivos. La adquisición y registro de la radiación no es sencilla por lo cual las imágenes satelitales resultan una solución por su cobertura espaciotemporal. El objetivo de estudio fue evaluar la radiación solar reportada por CERES con los registros de distintas estaciones meteorológicas y proponer un modelo de regresión lineal de ajuste; su aplicación se realizó a estaciones ubicadas en distintas comunidades autónomas de España. Los resultados mostraron una buena correlación y adecuación de la evolución espacio-temporal, con estadísticos de ajuste de R2=0,98 y valores de RECM entre 5,9 y 19,9 Wm-2, cuando se aplicó el modelo de regresión para ajustar los datos de CERES. Se puede concluir que la radiación obtenida del satélite es confiable para utilizar a nivel localidad/región cuando no se dispone de información meteorológica.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Radiación solar a partir de datos satelitales

La radiación solar es la principal fuente de energía renovable necesaria para que se cumplan diversos procesos en los cultivos. La adquisición y registro de la radiación no es sencilla por lo cual las imágenes satelitales resultan una solución por su cobertura espaciotemporal. El objetivo de estudio fue evaluar la radiación solar reportada por CERES con los registros de distintas estaciones meteorológicas y proponer un modelo de regresión lineal de ajuste; su aplicación se realizó a estaciones ubicadas en distintas comunidades autónomas de España. Los resultados mostraron una buena correlación y adecuación de la evolución espacio-temporal, con estadísticos de ajuste de R2=0,98 y valores de RECM entre 5,9 y 19,9 Wm-2, cuando se aplicó el modelo de regresión para ajustar los datos de CERES. Se puede concluir que la radiación obtenida del satélite es confiable para utilizar a nivel localidad/región cuando no se dispone de información meteorológica.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Radiación solar a partir de datos satelitales

La radiación solar es la principal fuente de energía renovable necesaria para que se cumplan diversos procesos en los cultivos. La adquisición y registro de la radiación no es sencilla por lo cual las imágenes satelitales resultan una solución por su cobertura espaciotemporal. El objetivo de estudio fue evaluar la radiación solar reportada por CERES con los registros de distintas estaciones meteorológicas y proponer un modelo de regresión lineal de ajuste; su aplicación se realizó a estaciones ubicadas en distintas comunidades autónomas de España. Los resultados mostraron una buena correlación y adecuación de la evolución espacio-temporal, con estadísticos de ajuste de R2=0,98 y valores de RECM entre 5,9 y 19,9 Wm-2, cuando se aplicó el modelo de regresión para ajustar los datos de CERES. Se puede concluir que la radiación obtenida del satélite es confiable para utilizar a nivel localidad/región cuando no se dispone de información meteorológica.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Net Radiation in the Semiarid Region of the States of Paraíba and Rio Grande do Norte Using the MODIS Sensor

This study aimed to estimate the surface net radiation (Rn) for the States of Paraíba and Rio Grande do Norte and validate the results with data measured in validate the results with measurements in experimental recovering (CRec), degraded (CDeg), and preserved (CPres) areas of Caatinga. Seventeen images of the MODIS sensor on board the Terra satellite were selected for CRec and CDeg in the State of Paraíba and twenty-eight images for CPres in the state of Rio Grande do Norte, corresponding to the period of January to December 2014. The MODIS-Terra MOD09A1 and MOD11A2 products were used. Parametric (Shapiro-Wilk) and non-parametric (Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney) tests were applied to understand the patterns. Statistical error indices were applied to verify the accuracy of the estimates in relation to the observed values. Only the measured albedo (α_meas) met the assumption of normality. According to mean absolute percentage error statistics, the model used to estimate the albedo was classified as inappropriate for CPres and CRec ( 25%), while it was satisfactory for CDeg (15-25%). Significant differences between observed and estimated values were absent only for the variable Rn in the three observation sites. The good performance of Rn estimates confirms the efficiency of the application of the method in semiarid regions

Assessment of a Remote Sensing Energy Balance Methodology (SEBAL) Using Different Interpolation Methods to Determine Evapotranspiration in a Citrus Orchard

"(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."A surface energy balance algorithm for land (SEBAL) for estimating evapotranspiration (ET) has been parameterized and tested in a 400-ha drip irrigated citrus orchard. Simultaneously, during three growing seasons, energy fluxes were measured using Eddy Covariance. Instantaneous fluxes obtained with SEBAL using 10 images from Landsat-5 were compared with the measured fluxes. The Perrier function was the best method for properly estimating the roughness momentum length for discontinuous canopies, as in citrus orchards. Crop height was estimated using LIDAR data. In general, SEBAL performed well for net radiation estimation but failed in soil heat flux estimation. Latent heat estimations from the SEBAL model had a relative root mean square error (rRMSE) of 0.06 when compared with measurements obtained by Eddy Covariance. Three procedures were tested for up-scaling the instantaneous ET estimates from SEBAL to daily ET values: 1) assuming the fraction between the actual ET and the reference ET is constant throughout the day; 2) using actual local crop coefficient curves; and 3) using an up-scaling factor where the fraction of hourly ET to daily ET equals the ratio of hourly to daily global solar radiation. This last method gave acceptable results for daily ET estimations (rRMSE = 0.09) and for 15day ET (rRMSE = 0.19), and its main advantage is that no local data are required. It is concluded that the SEBAL methodology can be successfully applied for determining actual ET, even in discontinuous citrus canopies. However, additional parameterizations of momentum roughness length were needed in order to obtain reliable ET determinations.This work was supported in part by MINECO project Rideco-Consolider CSD2006-0067 and in part by Interreg IV Sudoe project "Telerieg."Jiménez Bello, MÁ.; Castel, JR.; Testi, L.; Intrigliolo Molina, DS. (2015). Assessment of a Remote Sensing Energy Balance Methodology (SEBAL) Using Different Interpolation Methods to Determine Evapotranspiration in a Citrus Orchard. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8(4):1465-1477. https://doi.org/10.1109/JSTARS.2015.2418817S146514778

Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress

Precision irrigation management requires operational monitoring of crop water status. However, there is still some controversy on how to account for crop water stress. To address this question, several physiological, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomatal conductance, or sap flow. On the other hand, thermal remote sensing has been shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Water Stress Index (CWSI), one of the most common indices used for assessing plant stress. CWSI relates the actual crop evapotranspiration ET (related to the canopy radiometric temperature) to the potential ET (or minimum crop temperature). However, remotely sensed surface temperature from satellite sensors includes a mixture of plant canopy and soil/substrate temperatures, while what is required for accurate crop stress detection is more related to canopy metrics, such as transpiration, as the latter one avoids the influence of soil/substrate in determining crop water status or stress. The Two-Source Energy Balance (TSEB) model is one of the most widely used and robust evapotranspiration model for remote sensing. It has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomatal conductance, to track crop water stress in a vineyard in California, part of the GRAPEX experiment. Four eddy covariance towers were deployed in a Variable Rate Irrigation system in a Merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomatal conductance and leaf/stem water potential were collected as proxy for in situ crop water stress. Results showed that the most robust variable for tracking water stress was the TSEB derived leaf stomatal conductance, with the strongest correlation with both the measured root-zone soil moisture and stomatal conductance gas exchange measurements. In addition, these metrics showed a better ability in tracking stress when the observations are taken early after noon.Funding and logistical support for the GRAPEX project were provided by E. & J. Gallo Winery and from the NASA Applied Sciences-Water Resources Program (Grant no. NNH17AE39I). This research was also supported in part by the U.S. Department of Agriculture, Agricultural Research Service. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Peer reviewe

Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products

This study assesses the accuracy of estimating daily grass reference evapotranspiration (PM-ETo) using daily shortwave radiation (Rs) and reference evapotranspiration (ETREF) products provided by the Meteosat Second Generation (MSG) geostationary satellite delivered by the Satellite Applications Facility on Land Surface Analysis (LSA-SAF) framework. The accuracy of using reanalysis ERA5 shortwave radiation data (Rs ERA5) provided by the European Center for Medium-Range Weather Forecasts (ECMWF) is also evaluated. The assessments were performed using observed weather variables at 37 weather stations distributed across continental Portugal, where climate conditions range from semi-arid to humid, and 12 weather stations located in Azores islands, characterized by humid, windy and often cloudy conditions. This study’s use of data from a variety of climate conditions contributed to a unique and innovative assessment of the usability of LSA-SAF and ERA5 products for ETo estimation. The first assessment focused on comparing LSA-SAF estimates of Rs (Rs LSA-SAF) against ground stations (Rs ground). The results showed a good matching between the two Rs data sets for continental Portugal but a tendency for Rs LSA-SAF to under-estimate Rs ground in the cloudy islands of Azores. ETo values computed using Rs LSA-SAF data and observed temperature, humidity and wind speed (ETo LSA-SAF) were then compared with PMETo estimates with ground-based data, which were used as benchmark; input data of temperature and humidity needed for PM-ETo were quality checked for surface aridity effects. It was observed that ETo LSA-SAF is strongly correlated with PM-ETo (R2 > 0.97) for most locations in continental Portugal, with regression coefficient of a linear regression forced to the origin ranging between 0.95 and 1.05, mean root mean square error (RMSE) of 0.13 mm d 1, and Nash and Sutcliff efficiency of modeling (EF) above 0.95. For most Azores locations, ETo LSA-SAF over-estimated PM-ETo. This is likely a consequence of the high spatio-temporal heterogeneity of weather conditions that occur in these oceanic islands together with the different footprints of satellite (averaged over the pixel) and station observations. Reanalysis ERA5 shortwave radiation data presented similar behavior to the LSA-SAF products, however with slightly lower accuracy. The daily LSA-SAF ETREF product (ETREF LSA-SAF) was assessed and results have shown a good accuracy of this product, with acceptable RMSE and high EF values, for continental Portugal but a low accuracy for the Azores islands. A simplified bias correction approach was shown to improve both ETo derived from the LSA-SAF products, namely for Azores stations, which seem to be representative of smaller areas. The use of the FAO-PM temperature approach (PMT) was also assessed using the Rs LSA-SAF and Rs ERA5 data, which showed a superiority of the LSA-SAF product for ETo estimations (ETo PMT LSA-SAF). No significant differences (p < 0.05) were observed in terms of the median value of the RMSE when adopting ETo PMT and ETREF LSA-SAF. Differently, results showed that using the Rs LSA-SAF in the PMT approach (ETo PMT LSA-SAF) produces significantly better RMSE results than ETo PMT and ETREF LSA-SAF. Overall, the performed assessment allows concluding that the use of Rs LSA-SAF, and to a lesser extent the use of the Rs ERA5, highly improves the accuracy of computation of ETo when Rs observations are not available, including when only temperature data are accessible. The use of the ETREF LSA-SAF product is a good alternative when observed weather data are not availableinfo:eu-repo/semantics/publishedVersio

CONTRIBUTIONS OF OPTICAL REMOTE SENSING TO PERMAFROST MAPPING IN DONNELLY TRAINING AREA, ALASKA

AN ABSTRACT OF THE THESIS OFKiran Thapa, for the Master of Science degree in Geography and Environmental Resources, presented on April 8, 2020, at Southern Illinois University Carbondale.TITLE: CONTRIBUTIONS OF OPTICAL REMOTE SENSING TO PERMAFROST MAPPING IN DONNELLY TRAINING AREA, ALASKA MAJOR PROFESSOR: Dr. Guangxing Wang Permafrost occupies about a quarter of the northern hemisphere land with 25.5 million ha. Global warming and anthropogenic activities affect the dynamics of permafrost. Snow and permafrost, in turn, serve as an indicator of climate change and human activity disturbance. The dynamics of permafrost are often estimated using interferometric Synthetic Aperture Radar (InSAR) methods. However, acquiring and processing InSAR images is costly and computation intensive. Due to various spectral variables and indices available from optical images, Landsat satellite images that are free-downloadable provide the potential for studying and monitoring changes of permafrost. The overall objective of this study was to explore the use of optical images as a cost-effective method to map permafrost in Donnelly Training Area (DTA) - an installation located in Alaska. First, Landsat 8 OLI/TIRS images from January 2014 to December 2018 were used to calculate various remote sensing variables. The variables included Land Surface Temperature (LST), albedo, Soil Moisture index (SMI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Snow Index (NDSI), Normalized Difference Built-up Index (NDBI), Normalized Difference Water index (NDWI), Simple Ratio (SR), Soil Adjusted Vegetation Index (SAVI), Normalized Burn Ratio (NBR), Triangular Vegetation Index(TVI), Visible Atmospherically Resistant Index (VARI), and Active Layer Thickness (ALT). Moreover, elevation, slope, and aspect were obtained from a digital elevation model (DEM). The variables were used to estimate the probabilities of permafrost presence (POP) for DTA. The logistic and linear models were respectively selected and optimized based on logistic and linear stepwise regression for the estimation of and ALT. A total of 414 field observations that were collected from 1994 to 2012 were utilized for validation of models.The results showed that the POP in DTA was significantly affected by all the factors except aspect and EVI. The factor that was most correlated with ln((1-POP)/POP) was elevation, then NDVI, albedo, ALT, LST, NDWI, NDSI, slope, TVI, RSR, SMI, NDBI, SR, SAVI, NBR and VARI. A total of six prediction models were obtained. The elevation, NDVI, LST, TVI, ALT, SLOPE, RSR, SMI, NBR, and NDSI were finally chosen in the best model 5.6 with the smallest relative root mean square error (RMSE) and Akaike information criterion (AIC). The albedo used in previous studies was excluded in the final model, implying that the albedo was not critical to the prediction of POP. In addition to the previously used elevation, NDVI and SMI, other predictors including LST, TVI, ALT, SLOPE, RSR, NBR, and NDSI could not be ignored in the prediction of POP. The model generated reasonable spatial distribution of POP in which POP had greater values in the east, northeast, north, and northwest parts and smaller in the south and southwest parts. Except for NDVI, NDWI, NDSI, aspect, and RSR, moreover, all other predictors showed significant contributions to the prediction of ALT. The SMI, ELEVATION, SAVI, NDBI, SLOPE, LST, SR, EVI, VARI, and TVI were finally selected in the best model 5.14 with the smallest relative RMSE and AIC. The ALT highly varied over the study area with the spatial patterns inversely consistent with those of POP.The results are essential for the governments, policymakers, and other concerned stakeholders to estimate the degradation of permafrost in DTA and minimize the risk of policy decision-making for land use management and planning. This study will help to understand the global climate change, changing ecosystems, increasing concentration in the atmosphere, and human activity-induced disturbance