446 research outputs found

    Utility of thermal sharpening over Texas high plains irrigated agricultural fields

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    Irrigated crop production in the Texas high plains (THP) is dependent on water extracted from the Ogallala Aquifer, an area suffering from sever water shortage. Water management in this area is therefore highly important. Thermal satellite imagery at high temporal (~daily) and high spatial (~100 m) resolutions could provide important surface boundary conditions for vegetation stress and water use monitoring, mainly through energy balance models such as DisALEXI. At present, however, no satellite platform collects such high spatiotemporal resolution data. The objective of this study is to examine the utility of an image sharpening technique (TsHARP) for retrieving land surface temperature at high spatial resolution (down to 60 m) from moderate spatial resolution (1 km) imagery, which is typically available at higher (~daily) temporal frequency. A simulated sharpening experiment was applied to Landsat 7 imagery collected over the THP in September 2002 to examine its utility over both agricultural and natural vegetation cover. The Landsat thermal image was aggregated to 960 m resolution and then sharpened to its native resolution of 60 m and to various intermediate resolutions. The algorithm did not provide any measurable improvement in estimating high-resolution temperature distributions over natural land cover. In contrast, TsHARP was shown to retrieve high-resolution temperature information with good accuracy over much of the agricultural area within the scene. However, in recently irrigated fields, TsHARP could not reproduce the temperature patterns. Therefore we conclude that TsHARP is not an adequate substitute for 100-m-scale observations afforded by the current Landsat platforms. Should the thermal imager be removed from follow-on Landsat platforms, we will lose valuable capacity to monitor water use at the field scale, particularly in many agricultural regions where the typical field size is ~100 X 100 m. In this scenario, sharpened thermal imagery from instruments like MODIS or VIIRS would be the suboptimal alternative

    Utility of thermal image sharpening for monitoring field-scale evapotranspiration over rainfed and irrigated agricultural regions

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    The utility of a thermal image sharpening algorithm (TsHARP) in providing fine resolution land surface temperature data to a Two-Source-Model for mapping evapotranspiration (ET) was examined over two agricultural regions in the U.S. One site is in a rainfed corn and soybean production region in central Iowa. The other lies within the Texas High Plains, an irrigated agricultural area. It is concluded that in the absence of fine (sub-field scale) resolution thermal data, TsHARP provides an important tool for monitoring ET over rainfed agricultural areas. In contrast, over irrigated regions, TsHARP applied to kilometer-resolution thermal imagery is unable to provide accurate fine resolution land surface temperature due to significant sub-pixel moisture variations that are not captured in the sharpening procedure. Consequently, reliable estimation of ET and crop stress requires thermal imagery acquired at high spatial resolution, resolving the dominant length-scales of moisture variability present within the landscape

    Utility of thermal sharpening over Texas high plains irrigated agricultural fields

    Get PDF
    Irrigated crop production in the Texas high plains (THP) is dependent on water extracted from the Ogallala Aquifer, an area suffering from sever water shortage. Water management in this area is therefore highly important. Thermal satellite imagery at high temporal (~daily) and high spatial (~100 m) resolutions could provide important surface boundary conditions for vegetation stress and water use monitoring, mainly through energy balance models such as DisALEXI. At present, however, no satellite platform collects such high spatiotemporal resolution data. The objective of this study is to examine the utility of an image sharpening technique (TsHARP) for retrieving land surface temperature at high spatial resolution (down to 60 m) from moderate spatial resolution (1 km) imagery, which is typically available at higher (~daily) temporal frequency. A simulated sharpening experiment was applied to Landsat 7 imagery collected over the THP in September 2002 to examine its utility over both agricultural and natural vegetation cover. The Landsat thermal image was aggregated to 960 m resolution and then sharpened to its native resolution of 60 m and to various intermediate resolutions. The algorithm did not provide any measurable improvement in estimating high-resolution temperature distributions over natural land cover. In contrast, TsHARP was shown to retrieve high-resolution temperature information with good accuracy over much of the agricultural area within the scene. However, in recently irrigated fields, TsHARP could not reproduce the temperature patterns. Therefore we conclude that TsHARP is not an adequate substitute for 100-m-scale observations afforded by the current Landsat platforms. Should the thermal imager be removed from follow-on Landsat platforms, we will lose valuable capacity to monitor water use at the field scale, particularly in many agricultural regions where the typical field size is ~100 X 100 m. In this scenario, sharpened thermal imagery from instruments like MODIS or VIIRS would be the suboptimal alternative

    Soil profile method for soil thermal diffusivity, conductivity and heat flux: Comparison to soil heat flux plates

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    Diffusive heat flux at the soil surface is commonly determined as a mean value over a time period using heat flux plates buried at some depth (e.g., 5–8 cm) below the surface with a correction to surface flux based on the change in heat storage during the corresponding time period in the soil layer above the plates. The change in heat storage is based on the soil temperature change in the layer over the time period and an estimate of the soil thermal heat capacity that is based on soil water content, bulk density and organic matter content. One- or multiple-layer corrections using some measure of mean soil temperature over the layer depth are common; and in some cases the soil water content has been determined, although rarely. Several problems with the heat flux plate method limit the accuracy of soil heat flux values. An alternative method is presented and this flux gradient method is compared with soil heat flux plate measurements. The method is based on periodic (e.g., half-hourly) water content and temperature sensing at multiple depths within the soil profile and a solution of the Fourier heat flux equation. A Fourier sine series is fit to the temperature at each depth and the temperature at the next depth below is simulated with a sine series solution of the differential heat flux equation using successive approximation of the best fit based on changing the thermal diffusivity value. The best fit thermal diffusivity value is converted to a thermal conductivity value using the soil heat capacity, which is based on the measured water content and bulk density. A statistical analysis of the many data resulting from repeated application of this method is applied to describe the thermal conductivity as a function of water content and bulk density. The soil heat flux between each pair of temperature measurement depths is computed using the thermal conductivity function and measured water contents. The thermal gradient method of heat flux calculation compared well to values determined using heat flux plates and calorimetric correction to the soil surface; and it provided better representation of the surface spatiotemporal variation of heat flux and more accurate heat flux values. The overall method resulted in additional important knowledge including the water content dynamics in the near-surface soil profile and a soil-specific function relating thermal conductivity to soil water content and bulk density

    Radiometer Footprint Model to Estimate Sunlit and Shaded Components for Row Crops

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    Th is article describes a geometric model for computing the relative proportion of sunlit vegetation, shaded vegetation, sunlit soil, and shaded soil appearing in a circular or elliptical radiometer footprint for row crops, where the crop rows were modeled as continuous ellipses. Th e model was validated using digital photographs of row crops, where each component was determined by supervised classification. Root mean squared errors (RMSE) between modeled and observed components were 35, 49, 29, and 44% of observed means for sunlit vegetation, shaded vegetation, sunlit soil, and shaded soil, respectively. Mean bias errors (MBE) were, respectively, –5.6, 16.6, –4.0, and –0.5% of observed means. Th e continuous ellipse model was compared to the commonly used clumping index model, where the latter estimates total vegetation and total soil, but does not resolve these into their sunlit or shaded components and does not account for radiometer footprint shape dimensions. Th e continuous ellipse model resulted in RMSE for vegetation and soil of 22 and 19%, respectively, whereas the clumping index model resulted in respective RMSE of 37 and 31%. Th e continuous ellipse model had MBE of 3.3 and –2.6% for vegetation and soil, respectively, which was slightly greater than the respective MBE of –1.5 and 1.4% for clumping index model. Given the model sensitivity and uncertainty of leaf area index (LAI), the RMSE and MBE resulting from the continuous ellipse model would not be expected to be less than 20% of the observed means, and model performance was therefore deemed reasonable in this study

    Application of the Priestley–Taylor Approach in a Two-Source Surface Energy Balance Model

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    The Priestley–Taylor (PT) approximation for computing evapotranspiration was initially developed for conditions of a horizontally uniform saturated surface sufficiently extended to obviate any significant advection of energy. Nevertheless, the PT approach has been effectively implemented within the framework of a thermal-based two-source model (TSM) of the surface energy balance, yielding reasonable latent heat flux estimates over a range in vegetative cover and climate conditions. In the TSM, however, the PT approach is applied only to the canopy component of the latent heat flux, which may behave more conservatively than the bulk (soil + canopy) system. The objective of this research is to investigate the response of the canopy and bulk PT parameters to varying leaf area index (LAI) and vapor pressure deficit (VPD) in both natural and agricultural vegetated systems, to better understand the utility and limitations of this approximation within the context of the TSM. Micrometeorological flux measurements collected at multiple sites under a wide range of atmospheric conditions were used to implement an optimization scheme, assessing the value of the PT parameter for best performance of the TSM. Overall, the findings suggest that within the context of the TSM, the optimal canopy PT coefficient for agricultural crops appears to have a fairly conservative value of ~1.2 except when under very high vapor pressure deficit (VPD) conditions, when its value increases. For natural vegetation (primarily grasslands), the optimal canopy PT coefficient assumed lower values on average (~0.9) and dropped even further at high values of VPD. This analysis provides some insight as to why the PT approach, initially developed for regional estimates of potential evapotranspiration, can be used successfully in the TSM scheme to yield reliable heat flux estimates over a variety of land cover types

    Combining the bulk transfer formulation and surface renewal analysis for estimating the sensible heat flux without involving the parameter KB-1

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    The single‐source bulk transfer formulation (based on the Monin‐Obukhov Similarity Theory, MOST) has been used to estimate the sensible heat flux, H, in the framework of remote sensing over homogeneous surfaces (HMOST). The latter involves the canopy parameter, , which is difficult to parameterize. Over short and dense grass at a site influenced by regional advection of sensible heat flux, HMOST with  = 2 (i.e., the value recommended) correlated strongly with the H measured using the Eddy Covariance, EC, method, HEC. However, it overestimated HEC by 50% under stable conditions for samples showing a local air temperature gradient larger than the measurement error, 0.4 km−1. Combining MOST and Surface Renewal analysis, three methods of estimating H that avoid dependency have been derived. These new expressions explain the variability of H versus , where is the friction velocity, is the radiometric surface temperature, and is the air temperature at height, z. At two measurement heights, the three methods performed excellently. One of the methods developed required the same readily/commonly available inputs as HMOST due to the fact that the ratio between and the ramp amplitude was found fairly constant under stable and unstable cases. Over homogeneous canopies, at a site influenced by regional advection of sensible heat flux, the methods proposed are an alternative to the traditional bulk transfer method because they are reliable, exempt of calibration against the EC method, and are comparable or identical in cost of application. It is suggested that the methodology may be useful over bare soil and sparse vegetation.This research was funded by CERESS project AGL2011–30498 (Ministerio de Economía y Competitividad of Spain, cofunded FEDER), CGL2012–37416‐C04‐01 (Ministerio de Ciencia y Innovación of Spain), and CEI Iberus, 2014 (Proyecto financiado por el Ministerio de Educación en el marco del Programa Campus de Excelencia Internacional of Spain)

    Families in Transition: The Lived Experience of Parenting a Transgender Child

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    This qualitative study explored parent’s experiences of their child undergoing gender transition. Data analysis yielded themes that begin to identify the complex nature and struggles parents face as they encounter the emotional and physical aspects of this transition. The focus is on the context of the family rather than the broader social context of school or community. The central question is: “What is the experience of parenting a transgender child?
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