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Results for “Computers and Electronics in Agriculture”

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7 recordsLinked to original sources
USGS2004

An automated approach to mapping corn from Landsat imagery

Most land cover maps generated from Landsat imagery involve classification of a wide variety of land cover types, whereas some studies may only need spatial information on a single cover type. For example, we required a map of corn in order to estimate exposure to agricultural chemicals for an environmental epidemiology study. Traditional classification techniques, which require the collection and processing of costly ground reference data, were not feasible for our application because of the large number of images to be analyzed. We present a new method that has the potential to automate the classification of corn from Landsat satellite imagery, resulting in a more timely product for applications covering large geographical regions. Our approach uses readily available agricultural areal estimates to enable automation of the classification process resulting in a map identifying land cover as ‘highly likely corn,’ ‘likely corn’ or ‘unlikely corn.’ To demonstrate the feasibility of this approach, we produced a map consisting of the three corn likelihood classes using a Landsat image in south central Nebraska. Overall classification accuracy of the map was 92.2% when compared to ground reference data.

Computers and Electronics in Agriculture↗
USGS2026

Fish body midline segmentation using binary search

Body and caudal fin locomotion is ubiquitous in aquatic vertebrates, and kinematic models describing it are used in robotics, biomechanics and fisheries research. This paper presents a new algorithm to translate continuous body midlines of fish into a series of interconnected segments by identifying favorable joint positions along the body. The algorithm employs binary search to generate parsimonious kinematic models, aiming at minimizing the number of segments yet keeping approximation error below a user-defined threshold. To achieve this, the algorithm maximizes the length of each segment by determining the most distal joint position through repetitive shrinking of the search space. Theoretical and empirical analysis using two different datasets show that the binary search algorithm is substantially faster when compared to segment growing algorithm, which employs linear search to generate its models. There is four-fold improvement in computation time when generating models with less than 10 segments, which are typically sufficient to describe fish and fish-inspired robot movements. Furthermore, the multi-segment models generated by the binary search algorithm matched the ground truth models obtained through dynamic programming in over 97% of cases, and on average, contained one fewer segment than those produced by the Ramer–Douglas–Peucker algorithm, which is widely used in curvature simplification tasks. Our findings suggest that the binary search algorithm provides a computationally efficient approach for generating compact kinematic models and may facilitate the analysis of large datasets with high temporal and spatial resolution.

Computers and Electronics in Agriculture↗
USGS2023

Per- and polyfluorinated alkyl substances (PFAS) in Pennsylvania surface waters: A statewide assessment, associated sources, and land-use relations

The objectives of this study are to identify per- and polyfluoroalkyl substances (PFAS) in Pennsylvania surface waters, corresponding associations with potential sources of PFAS contamination (PSOC) and other parameters, and compare raw surface water concentrations to human and ecological benchmarks. Surface water samples from 161 streams were collected in September 2019 and were analyzed for 33 target PFAS and water chemistry. Land use and physical attributes in upstream catchments and geospatial counts of PSOC in local catchments are summarized. The hydrologic yield of the sum of 33 PFAS (∑PFAS) for each stream was computed by normalizing each site's load by the drainage area of the upstream catchment. Utilizing conditional inference tree analysis, the percentage of development (>7.58 %) was identified as a primary driver of the ∑PFAS hydrologic yields. When percentage of development was removed from analysis, ∑PFAS yields were closely related to surface water chemistry associated with landscape alteration (e.g., development or agricultural cropland), such as concentrations of total nitrogen, chloride, and ammonia, but also to count of water pollution control facilities (agricultural, industrial, stormwater, and/or municipal waste pollution abatement facilities). In oil and gas development regions, ∑PFAS yields were associated with combined sewage outfalls. Sites surrounded by ≥2 electronic manufacturing facilities had elevated ∑PFAS yields (median = 241 ng/s/km 2 ). Study results are critical to guide future research, regulatory policy, best practices that will mitigate PFAS contamination, and the communication of human health and ecological risks associated with PFAS exposure from surface waters.

Pennsylvania↗
USGS2026

Multiple-well monitoring site adjacent to the Midway- Sunset and Buena Vista Oil Fields, Kern County, California

Groundwater quality in and around oil fields in the Southern San Joaquin Valley is of interest to many California residents that rely heavily on groundwater for domestic, commercial, and agricultural use. To help assess the effects of historical oil-field activities and natural geologic sources on groundwater near the southwest margins of the Kern County Groundwater Subbasin, a multiple-well monitoring site was installed near the administrative boundary between the Midway-Sunset and Buena Vista Oil Fields in Kern County, California. The installation of the Midway-Sunset Buena Vista multiple-well monitoring site (MSBV) supports regional analysis of the relations of oil and gas sources to groundwater quality by providing information about the geology, hydrology, geophysical properties, and water quality of the alluvial and upper Tulare aquifers in areas where groundwater data were limited. Data collected from the site included drill cuttings, whole core samples, sidewall core samples, mud-gas analysis, borehole geophysical logs, depth to water measurements, and water quality samples. Whole cores were scanned using dual energy computed tomography. Subsamples of selected cores were analyzed for density, porosity, specific retention, and bulk minerology. Thin sections of the subsamples were prepared, photographed, and examined. Two samples were analyzed using scanning electron microscope technology to examine the microporosity of diatomite laden sediment. Instrumentation installed in the wells collect hourly depth to water measurements. Analysis of the data show there is 355 feet of alluvium overlying the Tulare Formation at the well site. The contact between the two formations is an aquitard resulting in a perched aquifer in the alluvium and unconfined aquifer in the Tulare Formation. The alluvium is more heterogenous and finer grained than the Tulare Formation resulting in markedly higher porosity in the alluvium compared to the Tulare Formation. Higher specific retention observed in the alluvium is attributed to the finer grained sediment and greater abundance of reworked diatomite (as represented by opal-CT [cristobalite-tridymite]) compared to the Tulare Formation. Total dissolved solids (TDS) approached or exceeded 10,000 milligrams per liter (mg/L) in the alluvium from approximately 176 to 242 feet below land surface and at the top of the Amnicola clay at approximately 670 feet below land surface within the Tulare Formation. Elevated TDS, chloride, and boron concentrations in the alluvium and on top of the Amnicola clay likely reflect groundwater that is mixed with oil-field water. Water chemistry and modern-aged groundwater in the alluvial monitoring well (MSBV #3) are consistent with the oil-field water in the alluvium being derived from documented historical surface disposal of oil-field water upslope (northwest) of the site. Water chemistry and pre-modern groundwater age in the deeper Tulare monitoring well (MSBV #1) on top of the Amnicola clay are consistent with oil-field fluids derived from upslope natural geologic sources or old oil wells that leak in the subsurface. Shallow groundwater in the Tulare (MSBV #2) is not affected by mixing with oil-field sources.

EarthArXiv↗
USGS1997

STATSGO soil characteristics for the conterminous United States

This digital data release consists of an ARC/INFO grid and associated INFO tables. The grid is called MUID and has STATSGO (U.S. Department of Agriculture, 1994) soil mapping unit identifiers gridded on a 1-kilometer resolution for the conterminous United States. The INFO tables have soil characteristics data in them. The ITEMS in the tables are weighted average values for several soil characteristics in the STATSGO data base. The weighted average values were computed by aggregating the soil layers and components in the data base. The INFO tables are called MUID.LAYER, MUID.COMP, MUID.KFACT, MUID.TFACT, and MUID.WEG. The INFO tables can be related or joined to the MUID grid or to individual State coverages (grids or polygons) of MUIDs. Joining or relating the tables to the MUID grid creates 1-kilometer resolution grids of the soil characteristics for the conterminous United States. The soil characteristics in MUID.LAYER are permeability (PERML and PERMH in the STATSGO data base), available water capacity (AWCL and AWCH), bulk density (BDL and BDH), and organic matter (OML and OMH). The soil characteristics in MUID.COMP are slope (SLOPEL and SLOPEH), depth to seasonally high water table (WTDEPL and WTDEPH), and depth to bedrock (ROCKDEPL and ROCKDEPH). The soil characteristic in MUID.KFACT is the soil erodibility factor (KFACT), the soil characteristic in MUID.TFACT is the soil loss tolerance factor (TFACT), and the soil characteristic in MUID.WEG is the wind erosion group (WEG). The MUID grid and INFO tables were created with a set of arc macro language (aml) and Fortran programs. Send electronic mail to dwolock@usgs.gov to obtain copies of the computer code. (See Procedures_Used.)

Open-File Report↗
USGS1979

Evaluation of methods for estimating ground-water withdrawals in western Kansas

During 1978, methods of estimating ground-water withdrawals in western Kansas were examined and evaluated, using both existing data from the files of the U.S. Geological Survey and newly collected data. Values for annual ground-water withdrawals reported to the Division of Water Resources, Kansas State Board of Agriculture, by water users probably contain substantial errors because most individual users do not possess the means to measure or accurately estimate the discharge rates of their wells. Such reported values are estimated to average 10 to 15 percent higher than the actual discharge rate. Values obtained from discharge-totaling meters are reasonably accurate, but few wells are equipped with these meters, and the cost of equipping all wells with meters may be prohibitive. Measured rates of power consumption can give good estimates of total withdrawal from wells where the power consumption is measured. However, power-consumption values cannot be extrapolated reliably from one well to another. Three techniques are regarded as promising for estimating areal ground-water withdrawals from readily collected data: Examination of a small sample of withdrawal values from metered wells indicates that the statistical approach used by Luckey (1972) may be applied to western Kansas to estimate total withdrawal with acceptable accuracy in a large area from a statistical sample of measured values. Measured values of irrigation application at a small number of selected wells might be used to compute total withdrawal for irrigation by crop type and precipitation zone. Evaluation of reported values of irrigation-water application for selected crops in zones of generally similar precipitation showed that, although the reported values are judged to be erroneously high, the reported values were consistent with each other and with average precipitation. Power-consumption coefficients may be used to calculate an average coefficient for an area. The method described by Luckey (1972) was used to calculate the number of power-consumption coefficients that would have to be determined to estimate the mean power consumption of wells pumped by electric or natural-gas engines. The results indicate that as few as 100 values would produce results accurate to within 10 percent of the true average at the 95-percent confidence level. Thus, power coefficients for a particular type of irrigation system in any given area can be used even though values of power coefficients have little transfer value from well to well. Efforts by the Instrument Development Laboratofy of the U.S. Geological Survey to design improved instruments for measuring ground-water withdrawals have produced two promising results: An electronic running-time meter (Running-time Sentry) that was tested during 1978 in western Kansas and Florida appears to give accurate values of total pumping time. Large-scale testing of this prototype running-time meter is planned for 1979. A low-cost discharge-totaling meter (REELTOT), based on the concept of sensing the velocity head in a pipe with differential-pressure transducers permanently installed in the pipe, is nearly complete. Early prototypes of this instrument may be tested in western Kansas during 1979. For the remainder of this study, the three techniques for estimating areal ground-water withdrawals described above will be tested on a larger scale in Groundwater Management District No. 1, an area of about 1,800 square miles in west-central Kansas. About 150 randomly selected wells will be equipped with Running-time Sentry units and monitored for total withdrawal, instantaneous discharge, and power consumption. A few wells will be equipped with prototype discharge-totaling meters. The performance of the Sentry units and discharge-totaling meters will be evaluated. Areal estimates of withdrawal from measured withdrawal values, from average power-consumption coefficients, and from irrigation application by crop will be calculated and compared with each other and with reported values of withdrawal.

Kansas↗