Christopher M. U. Neale

Utility of Remote Sensing-Based Two-Source Energy Balance Model under Low- and High-Vegetation Cover Conditions

Abstract Two resistance network formulations that are used in a two-source model for parameterizing soil and canopy energy exchanges are evaluated for a wide range of soybean and corn crop cover and soil moisture conditions during the Soil Moisture–Atmosphere Coupling Experiment (SMACEX). The parallel resistance formulation does not consider interaction between the soil and canopy fluxes, whereas the series resistance algorithms provide interaction via the computation of a within-air canopy temperature. Land surface temperatures were derived from high-resolution Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM) scenes and aircraft imagery. These data, along with tower-based meteorological data, provided inputs for the two-source energy balance model. Comparison of the local model output with tower-based flux observations indicated that both the parallel and series resistance formulations produced basically similar estimates with root-mean-square difference (RMSD) values ranging from approximatel...

Development of Reflectance-Based Crop Coefficients for Corn

ABSTRACT Concurrent measurements of reflected canopy radia-tion and the basal crop coefficient (K^b) for corn were conducted throughout a season in order to develop a reflectance-based crop coefficient model. Reflectance was measured in Landsat Thematic Mapper bands TM3 (0.63 - 0.69 um) and TM4 (0.76 - 0.90 um) and used in the calculation of a vegetation index called the normalized difference (ND). A linear transformation of the ND was used as the reflectance-based crop coefficient (Kcr). The transformation equates the ND for dry bare soil and the ND at effective cover, to the basal crop coefficient for dry soil evaporation and at effective cover, respectively. Basal crop coefficient values for com were obtained from daily evapotranspiration measurements of corn and alfalfa, using hydraulic weighing lysimeters. The Richards growth curve function was fitted to both sets of data. The K^b values were determined to be within -2.6% and 4.7% of the K^^ values. The date of effective cover obtained from the K^b data was within four days of the date on which the ND curve reached its maxima according to the Richards function. A comparison of the Kcr with basal crop curves from the literature for several years of data indicated good agreement. Reflectance-based crop coefficients are sensitive to periods of slow and fast growth induced by weather conditions, resulting in a real time coefficient, independent from the traditional time base parameters based on the day of planting and effective cover.

Land surface temperature derived from the SSM/I passive microwave brightness temperatures

Passive microwave brightness temperatures from the Defense Meteorological Space Program Special Sensor Microwave/Imager (SSM/I) were used to determine surface temperature over land areas in the central plains of the United States. A regression analysis comparing all of the SSM/I channels and minimum screen air temperatures (representing the surface temperature) showed good correlations, with root-mean-square errors of 2-3 degC. Pixels containing large amounts of water, snow, and falling rain, as classified with SSM/I brightness temperatures, were excluded from the analysis. The use of independent ground truth data such as soil moisture or land surface type was not required to obtain the correlations between brightness temperatures and surface temperatures. >

Crop Coefficients Derived from Reflected Canopy Radiation: A Concept

ABSTRACT SIMILARITIES between the crop coefficient curve and a vegetation index showed potential for modeling a vegetation index into a crop coefficient. Therefore, the possibility of directly estimating the crop coefficient from measured reflectance properties of a crop/soil scene was investigated. Reflected canopy radiation in the 0.63 to 0.69 jwm and 0.76 to 0.90 jjim band widths was measured normal to and two meters above corn (Zea mays L.), and the normalized difference (ND) vegetation index was computed. The seasonal ND curve was curvilinear and resembled the basal crop coefficient (K^b) curve for corn. Leaf area index and canopy shading were 3.2 and 77.6%, respectively, when the ND reached its maximum valvue. A linear transformation of the ND was developed by equating the ND at effective cover and for dry, bare soil at the experimental site to the K^b at effective cover and for dry soil evaporation, respectively. This transformation produced a seasonal curve very similar to the basal crop coefficient curve and was named the basal spectral crop coefficient (K^J. Crop coefficients derived from spectral measurements are independent of the usual time base parameters, planting date and effective cover date, associated with traditional crop coefficients. Thus, the basal spectral crop coefficient is a real-time crop coefficient that permits the crop to express its response to weather, management practices, and stresses.

Land-surface-type classification using microwave brightness temperatures from the Special Sensor Microwave/Imager

The use of empirical parameter retrieval algorithms over land requires the prior classification of surface types according to their microwave emission properties. A land-surface-type classification scheme was developed to be used with the Special Sensor Microwave/Imager (SSM/I) algorithm package. The classification rules were based on statistical analysis of SSM/I brightness temperature combinations from several surfaces, including dense vegetation, rangeland and agricultural soils, deserts, snow, precipitation, surface moisture, etc. A set of independent classification rules was derived which should result in increased confidence of parameter retrievals. >

Comparing Aircraft-Based Remotely Sensed Energy Balance Fluxes with Eddy Covariance Tower Data Using Heat Flux Source Area Functions

Abstract In an effort to better evaluate distributed airborne remotely sensed sensible and latent heat flux estimates, two heat flux source area (footprint) models were applied to the imagery, and their pixel weighting/integrating functionality was investigated through statistical analysis. Soil heat flux and sensible heat flux models were calibrated. The latent heat flux was determined as a residual from the energy balance equation. The resulting raster images were integrated using the 2D footprints and were compared to eddy covariance energy balance flux measurements. The results show latent heat flux estimates (adjusted for closure) with errors of (mean ± std dev) −9.2 ± 39.4 W m−2, sensible heat flux estimate errors of 9.4 ± 28.3 W m−2, net radiation error of −4.8 ± 20.7 W m−2, and soil heat flux error of −0.5 ± 24.5 W m−2. This good agreement with measured values indicates that the adopted methodology for estimating the energy balance components, using high-resolution airborne multispectral imagery, ...

Tower and Aircraft Eddy Covariance Measurements of Water Vapor, Energy, and Carbon Dioxide Fluxes during SMACEX

Abstract A network of eddy covariance (EC) and micrometeorological flux (METFLUX) stations over corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] canopies was established as part of the Soil Moisture–Atmosphere Coupling Experiment (SMACEX) in central Iowa during the summer of 2002 to measure fluxes of heat, water vapor, and carbon dioxide (CO2) during the growing season. Additionally, EC measurements of water vapor and CO2 fluxes from an aircraft platform complemented the tower-based measurements. Sensible heat, water vapor, and CO2 fluxes showed the greatest spatial and temporal variability during the early crop growth stage. Differences in all of the energy balance components were detectable between corn and soybean as well as within similar crops throughout the study period. Tower network–averaged fluxes of sensible heat, water vapor, and CO2 were observed to be in good agreement with area-averaged aircraft flux measurements.

An airborne multispectral video/radiometer remote sensing system: development and calibration

Abstract Airborne multispectral videography is becoming a popular research and monitoring tool with the advent of charge coupled device (CCD) video technologies. However, most existing systems are not calibrated, resulting in radiometrically inaccurate imagery caused by nonuniform irradiance sensitivity of the CCD imaging arrays and lens vignetting. The latter effect results in a higher concentration of radiation in the center of the images. This article describes the Airborne Multispectral Video/Radiometer Remote Sensing System developed at Utah State University as well as the laboratory procedure developed to calibrate the spectral video imagery for radiance variations across the image plane.

Combining multifrequency microwave and optical data for crop management

Abstract The potential for the combined use of microwave and optical data for crop management is explored with the use of images acquired in the visible, near-infrared, and thermal spectrum and the synthetic aperture radar (SAR) wavelengths in the Ku (14.85 GHz) and C (5.3 GHz) bands. The images were obtained during June 1994 and covered an agricultural site composed of large fields of partial-cover cotton, near-full-cover alfalfa, and bare soil fields of varying roughness. Results showed that the SAR Ku backscatter coefficient (Ku-band σ†) was sensitive to soil roughness and insensitive to soil moisture conditions when vegetation was present. When soil roughness conditions were relatively similar (e.g., for cotton fields of similar row direction and for all alfalfa fields), Ku-band σ† was sensitive to the fraction of the surface covered by vegetation. Under these conditions, the Ku-band σ° and the optical normalized difference vegetation index (NDVI) were generally correlated. The SAR C backscatter coefficient (C-z.sbnd;band σ°) was found to be sensitive to soil moisture conditions for cotton fields with green leaf area index (GLAI) less than 1.0 and alfalfa fields with GLAI nearly 2.0. For both low-GLAI cotton and alfalfa, Cband σ° was correlated with measurements of surface temperature (T s ). A theoretical basis for the relations between Kuband σ° and NDVI and between C-band gs0 and T s was presented and supported with on-site measurements. On the basis of these findings, some combined optical and radar approaches are suggested for crop management applications

COMPARISON OF ELEVEN VEGETATION INDICES FOR ESTIMATING PLANT HEIGHT OF ALFALFA AND GRASS

A great variety of vegetation indices, derived from remote sensing measurements, are commonly used to characterize the growth pattern of cropped surfaces. In this study, multispectral canopy reflectance data were obtained from grass (Festuca arundinacea) and alfalfa (Medicago sativa L.) at Kimberly, Idaho, with the purpose of comparing the performance of 11 vegetation indices for estimating plant height of these two structurally different crop canopies. An additional purpose was to develop quantitative relationships between plant height and the different vegetation indices, which could be used to estimate plant height from remote sensing inputs. For alfalfa, good logistic growth relationships between plant height and all the different vegetation indices were found. The relationship resulted in r2 > 0.90 for all the vegetation indices, and r2 > 0.97 for most of them. While all the vegetation indices were very sensitive to changes in plant height at the beginning of the growing cycle, the Normalized Difference Vegetation Index (NDVI), the Infrared Percentage Vegetation Index (IPVI), and the Transformed Vegetation Index (TVI) became insensitive to additional plant growth when alfalfa reached heights of 0.45, 0.40, and 0.45 m, respectively. All the other vegetation indices performed reasonably well for the entire range of alfalfa plant heights considered in this study ( 2 ~ 0.76).