Lynn McKee

Canopy attributes of desert grassland and transition communities derived from multiangular airborne imagery

Abstract The surface bidirectional reflectance distribution function (BRDF) contains valuable information on canopy physiognomy for desert grassland and grass–shrub transition communities. This information may be accessed by inverting a BRDF model against sets of observations, which encompass important variations in viewing and illumination angles. This paper shows that structural canopy attributes can be derived through inversion of the Simple Geometric Model (SGM) of the BRDF developed in this paper. It is difficult to sample BRDF features from the ground because of the discontinuous nature of the canopies and long intrinsic length scales in remotely sensed spectral measures (>10 m). A multispectral digital camera was therefore used to derive spatial multiangular reflectance data sets from the air and the SGM was validated against and inverted with these. It was also validated using 3-D radiosity simulations driven with maps of field-measured plant dimensions. The interpretation of the retrieved parameter maps (shrub density, shrub width and canopy height) reveals variations in canopy structure within desert grassland and grassland–shrubland transition communities, which are clearly related to structural and optical features in high resolution panchromatic and vegetation index images. To our knowledge, this paper reports on the first attempts to acquire structural canopy attributes of desert landscapes using multiple view angle data at scales less than 1 km. The results point to further opportunities to exploit multiangular data from spaceborne sensors such as the Multiangle Imaging SpectroRadiometer (MISR) and the Compact High Resolution Imaging Spectrometer (CHRIS) on the NASA Terra and European Space Agencys PROBA satellites, respectively.

Comparison of field-scale herbicide runoff and volatilization losses: an eight-year field investigation.

An 8-yr study was conducted to better understand factors influencing year-to-year variability in field-scale herbicide volatilization and surface runoff losses. The 21-ha research site is located at the USDA-ARS Beltsville Agricultural Research Center in Beltsville, MD. Site location, herbicide formulations, and agricultural management practices remained unchanged throughout the duration of the study. Metolachlor [2-chloro--(2-ethyl-6-methylphenyl)--(2-methoxy-1-methylethyl) acetamide] and atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] were coapplied as a surface broadcast spray. Herbicide runoff was monitored from a month before application through harvest. A flux gradient technique was used to compute volatilization fluxes for the first 5 d after application using herbicide concentration profiles and turbulent fluxes of heat and water vapor as determined from eddy covariance measurements. Results demonstrated that volatilization losses for these two herbicides were significantly greater than runoff losses ( < 0.007), even though both have relatively low vapor pressures. The largest annual runoff loss for metolachlor never exceeded 2.5%, whereas atrazine runoff never exceeded 3% of that applied. On the other hand, herbicide cumulative volatilization losses after 5 d ranged from about 5 to 63% of that applied for metolachlor and about 2 to 12% of that applied for atrazine. Additionally, daytime herbicide volatilization losses were significantly greater than nighttime vapor losses ( < 0.05). This research confirmed that vapor losses for some commonly used herbicides frequently exceeds runoff losses and herbicide vapor losses on the same site and with the same management practices can vary significantly year to year depending on local environmental conditions.

Soil moisture and metolachlor volatilization observations over three years.

A 3-yr study was conducted to focus on the impact of surface soil water content on metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl) acetamide) volatilization from a field with different surface soil water regimes created by subsurface water flow paths. Metolachlor vapor fluxes were measured at two locations within the field where local meteorological and soil conditions were relatively constant, except for surface soil water content, which differed significantly. Surface soil water content at the two sites differed in response to the presence of subsurface flow pathways. Detailed soil moisture observations over the duration of the study showed that for the first 2 yr (2004 and 2005), surface soil water contents at the dry location (V1) were nearly half those at the wetter location (V2). Cumulative metolachlor vapor fluxes during 2004 and 2005 at V1 were also about half that at V2. In the third year (2006), early-season drought conditions rendered the soil water content at the two locations to be nearly identical, resulting in similar metolachlor volatilization losses. Analysis of infrared soil surface temperatures suggests a correlation between surface soil temperatures and metolachlor volatilization when soils are wet (2004 and 2005) but not when the soils are dry (2006). Field-averaged metolachlor volatilization losses were highly correlated with increasing surface soil water contents (r(2) = 0.995).

Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards

Wine grape quality and quantity are affected by vine growing conditions during critical phenological stages. Field observations of vine growth stages are too sparse to fully capture the spatial variability of vine conditions. In addition, traditional grape yield prediction methods are time consuming and require large amount grape samples. Remote sensing data provide detailed spatial and temporal information regarding vine development that is useful for vineyard management. In this study, Landsat surface reflectance products from 2013 and 2014 were used to map satellite-based Normalized Difference Vegetation Index (NDVI) and leaf area index (LAI) over two Vitis vinifera L. cv. Pinot Noir vineyards in California, USA. The spatial correlation between grape yield maps and the interpolated daily time series (LAI and NDVI) was quantified. NDVI and LAI were found to have similar performance as a predictor of spatial yield variability, providing peak correlations of 0.8 at specific times during the growing season, and the timing of this peak correlation differed for the two years of study. In addition, correlations with maximum and seasonal-cumulative vegetation indices were also evaluated, and showed slightly lower correlations with the observed yield maps. Finally, the within-season grape yield predictability was examined using a simple strategy in which the relationship between grape yield and vegetation indices were calibrated with limited ground measurements. This strategy has a strong potential to improve the accuracy and efficiency of yield estimation in comparison with traditional approaches used in the wine grape growing industry.

Investigating water use over the Choptank River Watershed using a multisatellite data fusion approach

The health of the Chesapeake Bay ecosystem has been declining for several decades due to high levels of nutrients and sediments largely tied to agricultural production systems. Therefore, monitoring of agricultural water use and hydrologic connections between crop lands and Bay tributaries has received increasing attention. Remote sensing retrievals of actual evapotranspiration (ET) can provide valuable information in support of these hydrologic modeling efforts, spatially and temporally describing consumptive water use by crops and natural vegetation and quantifying response to expansion of irrigated area occurring with Bay watershed. In this study, a multi-sensor satellite data fusion methodology, combined with a multi-scale ET retrieval algorithm, was applied over the Choptank River watershed located within the Lower Chesapeake Bay region on the Eastern Shore of Maryland, USA to produce daily 30-m resolution ET maps. ET estimates directly retrieved on Landsat satellite overpass dates have high accuracy with relative error (RE) of 9%, as evaluated using flux tower measurements. The fused daily ET time series have reasonable errors of 18% at the daily time step - an improvement from 27% errors using standard Landsat-only interpolation techniques. Annual water consumption by different land cover types was assessed, showing reasonable distributions of water use with cover class. Seasonal patterns in modeled crop transpiration and soil evaporation for dominant crop types were analyzed, and agree well with crop phenology at field scale. Additionally, effects of irrigation occurring during a period of rainfall shortage were captured by the fusion program. These results suggest that the ET fusion system will have utility for water management at field and regional scales over the Eastern Shore. Further efforts are underway to integrate these detailed water use datasets into watershed-scale hydrologic models to improve assessments of water quality and inform best management practices to reduce nutrient and sediment loads to the Chesapeake Bay.

The Grape Remote Sensing Atmospheric Profile and Evapotranspiration Experiment

AbstractParticularly in light of California’s recent multiyear drought, there is a critical need for accurate and timely evapotranspiration (ET) and crop stress information to ensure long-term sust...

Event-based estimation of water budget components using a network of multi-sensor capacitance probes

Abstract A new approach was developed for estimating vertical soil water fluxes using soil water content time series data. Instead of a traditional fixed time interval, this approach utilizes the time interval between two sequential minima of the soil water storage time series to identify groundwater recharge events and calculate components of the soil water budget. We calculated water budget components: surface-water excess (Sw), infiltration less evapotranspiration (I – ET) and groundwater recharge (R) from May 2001 to January 2003 at eight locations at the USDA Agricultural Research Center, Beltsville, Maryland, USA. High uncertainty was observed for all budget components. This uncertainty was attributed to spatial and temporal variation in Sw, I – ET and R, and was caused by nonuniform rainfall distributions during recharge events, variability in the profile water content, and spatial variability in soil hydraulic properties. The proposed event-based approach allows estimating water budget components when profile water content monitoring data are available. Citation Guber, A., Gish, T., Pachepsky, Y., McKee, L., Nicholson, T. & Cady, R. (2011) Event-based estimation of water budget components using a network of multi-sensor capacitance probes. Hydrol. Sci. J. 56(7), 1227–1241.

Evaluation of TSEB turbulent fluxes using different methods for the retrieval of soil and canopy component temperatures from UAV thermal and multispectral imagery

The thermal-based Two-Source Energy Balance (TSEB) model partitions the evapotranspiration (ET) and energy fluxes from vegetation and soil components providing the capability for estimating soil evaporation (E) and canopy transpiration (T). However, it is crucial for ET partitioning to retrieve reliable estimates of canopy and soil temperatures and net radiation, as the latter determines the available energy for water and heat exchange from soil and canopy sources. These two factors become especially relevant in row crops with wide spacing and strongly clumped vegetation such as vineyards and orchards. To better understand these effects, very high spatial resolution remote-sensing data from an unmanned aerial vehicle were collected over vineyards in California, as part of the Grape Remote sensing and Atmospheric Profile and Evapotranspiration eXperiment and used in four different TSEB approaches to estimate the component soil and canopy temperatures, and ET partitioning between soil and canopy. Two approaches rely on the use of composite

Daily mapping of Landsat-like LAI and correlation to grape yield

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