Geology topics

C. M. U. Neale

Publications and source records attributed to C. M. U. Neale.

3 recordsLinked to original sources

USGS2011

Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil evaporation. Copyright ?? 2011 John Wiley & Sons, Ltd.

Hydrological Processes↗

USGS2008

Integrating remotely acquired and field data to assess effects of setback levees on riparian and aquatic habitat in glacial-melt water rivers

Setback levees, in which levees are reconstructed at a greater distance from a river channel, are a promising restoration technique particularly for alluvial rivers with broad floodplains where river-floodplain connectivity is essential to ecological processes. Documenting the ecological outcomes of restoration activities is essential for assessing the comparative benefits of different restoration approaches and for justifying new restoration projects. Remote sensing of aquatic habitats offers one approach for comprehensive, objective documentation of river and floodplain habitats, but is difficult in glacial rivers because of high suspended-sediment concentrations, braiding and a lack of large, well-differentiated channel forms such as riffles and pools. Remote imagery and field surveys were used to assess the effects of recent and planned setback levees along the Puyallup River and, more generally, the application of multispectral imagery for classifying aquatic and riparian habitats in glacial-melt water rivers. Airborne images were acquired with a horizontal ground resolution of 0.5 m in three spectral bands (0.545-0.555, 0.665-0.675 and 0.790-0.810 ??m) spanning from green to near infrared (NIR) wavelengths. Field surveys identified river and floodplain habitat features and provided the basis for a comparative hydraulic analysis. Broad categories of aquatic habitat (smooth and rough water surface), exposed sediment (sand and boulder) and vegetated surfaces (herbaceous and deciduous shrub/forest) were classified accurately using the airborne images. Other categories [e.g. conifers, boulder, large woody debtis (LWD)] and subdivisions of broad categories (e.g. riffles and runs) were not successfully classified either because these features did not form large patches that could be identified on the imagery or their spectral reflectances were not distinct from those of other habitat types. Airborne imagery was critical for assessing fine-scale aquatic habitat heterogeneity including shallow, low-velocity regions that were not feasible or practical to map in the field in many cases due to their widespread distribution, small size and poorly defined boundaries with other habitat types. At the reach-scale, the setback levee affected the amount and distribution of riparian and aquatic habitats: (1) the area of all habitats was greater where levees had been set back and with relatively more vegetated floodplain habitat and relatively less exposed sediment and aquatic habitat, (2) where levees confine the river, less low-velocity aquatic habitat is present over a range of flows with a higher degree of bed instability during high flows. As river restoration proceeds in the Pacific Northwest and elsewhere, remotely acquired imagery will be important for documenting its effects on the amount and distribution of aquatic and floodplain habitats, complimenting field data as a quantitative basis for evaluating project efficacy.

River Research and Applications↗

USGS2000

Characteristic length scale of input data in distributed models: implications for modeling grain size

The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m 2 modeling grid size. A modeling grid size of about 10×10 m 2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.

Idaho↗