Teferi D. Tsegaye

Relationship Between Hyperspectral Reflectance, Soil Nitrate-Nitrogen, Cotton Leaf Chlorophyll, and Cotton Yield: A Step Toward Precision Agriculture

ABSTRACT Modern agriculture uses large amounts of organic and inorganic nutrients to optimize productivity. Excessive nutrient applications sometime lead to adverse effects on the environment and human health. Precision agriculture is evolving with the objectives of minimizing these adverse effects by enabling farmers to manage nutrient applications more efficiently while sustaining precious environmental resources. To develop a method that uses nutrients more efficiently on cotton, a field experiment involving three sources and three rates of nitrogen with and without nitrification inhibitor was carried out in four replications at Belle Mina, AL during the 1994-97 crop seasons. In 1997, these plots were used to determine if there was a relationship between remotely sensed hyperspectral reflectance data and three field measurements that included cotton leaf chlorophyll (defined as measurements of five leaves using a Minolta Chlorophyll SPAD Meter to represent cotton canopy), soil nitrate-nitrogen, and cotton yield. Our results showed that hyperspectral reflectance in the 807.6 nm region had the highest significant correlation with cotton leaf chlorophyll. Cotton leaf chlorophyll correlated significantly with soil nitrate-nitrogen and cotton yield. Because leaf chlorophyll is an indicator of nitrogen deficiency, our results suggest that hyperspectral reflectance may be used as a tool to help farmers determine nitrogen deficiency, which may subsequently lead to increased crop productivity and reduced environmental pollution.

Ground-based passive microwave remote sensing observations of soil moisture at S-band and L-band with insight into measurement accuracy

A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, AL, from July 1-14, 1996. The goal of the experiment was to evaluate the overall performance of an empirically-based retrieval algorithm at S-band and L-band under a different set of conditions and to characterize the site-specific accuracy inherent within the technique. With high temporal frequency observations at S-band and L-band, the authors were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L-band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cm/sup 3//cm/sup 3/ with an indication that it is less at higher moisture values. The S-band emitting depth was not readily distinguishable from L-band. The uncertainty in remotely sensed soil moisture observations due to surface heterogeneity and temporal variability in variables and parameters was characterized by imposing random errors on the most sensitive variables and parameters and computing the confidence limits on the observations. Discrepancies between remotely sensed and gravimetric soil moisture estimates appear to be larger than those expected from errors in variable and parameter estimation. This would suggest that a vegetation correction procedure based on more dynamic modeling may be required to improve the accuracy of remotely sensed soil moisture.

Calibration and modification of impedance probe for near surface soil moisture measurements

A reliable and low cost sensor that can measure soil moisture at or near the soil surface is currently not available. The objectives of this study were: (i) to evaluate the possibility of modifying an impedance probe (IP) to measure soil moisture content at a very shallow depth (2–5 cm); and (ii) to compare the soil moisture values obtained using the IP to the values obtained using the traditional gravimetric method. The research was conducted at the Winfred A. Thomas Agricultural Research Station (WTARS) Hazel Green, Alabama. The standard IP that is capable of measuring soil moisture content at 6-cm soil depth was modified to measure soil moisture at 2-, 3-, and 5-cm depths. Using a site and depth-specific calibration technique it provided results that were comparable to the values that were obtained following the traditional gravimetric water content determination protocol. We found that the instrument was very sensitive to changes in soil moisture content and has great potential as a replacement for th...

Role of albedo in sensing soil moisture under vegetation with passive L-band algorithms

Relations between various definitions of albedo for a layer of random discrete scatterers are established. Albedo and attenuation values are obtained for soybeans and corn using a discrete model. Attenuation values are also obtained using an empirical approach. Brightness temperatures, computed by transport theory with these albedo and attenuation values, are compared with the measured brightness temperature values for soybeans and corn

The application of remote sensing, geographic information systems, and Global Positioning System technology to improve water quality in northern Alabama

Recently, the water quality status in northern Alabama has been declining due to urban and agricultural growth. Throughout the years, the application of remote sensing and geographic information system technology has undergone numerous modifications and revisions to enhance their ability to control, reduce, and estimate the origin of non-point source pollution. Yet, there is still a considerable amount of uncertainty surrounding the use of this technology as well as its modifications. This research demonstrates how the application of remote sensing, geographic information system, and global positioning system technologies can be used to assess water quality in the Wheeler Lake watershed. In an effort to construct a GIS based water quality database of the study area for future use, a land use cover of the study area will be derived from LANDSAT Thermatic Mapper (TM) imagery using ERDAS IMAGINE image processing software. A Digital Elevation Model of the Wheeler Lake watershed was also from an Environmental Protection Agency Basins database. Physical and chemical properties of water samples including pH, Total Suspended Solids (TSS), Total Fecal Coliform (TC), Total Nitrogen (TN), Total Phosphorus (TP), Biological Oxygen Demand (BOD), Dissolved Oxygen (DO), and selected metal concentrations were measured.

Evaluating modified rainfall erosivity factors in the universal soil loss equation

Throughout the years, the Universal Soil Loss Equation (USLE) has undergone numerous modifications and revisions to enhance its ability to estimate soil loss caused by erosion in agricultural lands. Yet, there is still a considerable amount of uncertainty surrounding the use of the USLE as well as some of its modifications. This research examines the prediction capabilities of two very similar modifications that were made to the USLEs rainfall erosivity (R) factor; they are termed the Modified Universal Soil Loss Equation (MUSLE) and the Onstad-Foster Equation. The efficiency of these two modifications will be evaluated by comparing the actual erosion data that was retrieved from the field site to the erosion data that was simulated using the Erosion Productivity Impact Calculator (EPIC) Model. This experiment, which is being conducted at the Winfred A. Thomas Agricultural Research Station in Hazel Green, Alabama aims to enhance our understanding, estimation, and prediction of the soil erosion process.

Spatial distribution of soil physical properties under various forested and agricultural land use management practices

Understanding the interrelationships that exist in a soil is the key to understanding processes like, soil erosion. Notably, the severity of soil erosion will vary, depending on a number of factors. Among the most influential are soil physical and hydraulic properties and their spatial distribution. In this particular study, soil physical and hydraulic properties were characterized spatially for both agricultural and forest vegetated areas. The study site, which was located at the Winfred A. Thomas Agricultural Research Station, in Hazel Green, Alabama consisted of two blocks and each block contained four differently conditioned plots. The land use practices implemented were corn, switchgrass, sweetgum trees, and sweetgum trees with tall fescue grass as a cover crop. To examine the spatial distribution of soil properties, analyses were conducted to determine properties like, soil pH, texture, bulk density, and hydraulic conductivity for each land use practice. Interestingly, pH, bulk density, and water retention were all highest in the corn plots and lowest in the sweetgum tree plots with fescue as a cover crop. Contrastingly, the sweetgum tree plot with fescue had the lowest bulk density and the highest hydraulic conductivity.

Land Use/Cover change detection of the city of Addis Ababa, Ethiopia using remote sensing and geographic information system technology

Information about changes in land use/cover provides valuable insights while devising future natural resource management strategies. Remotely sensed data, serve as an effective tool for deriving this kind of information. Landsat Thematic Mapper images of 1987 and 1999 were used to extract land use/cover change of the city of Addis Ababa and the surrounding area. Analysis of the multitemporal Landsat images has clearly revealed the loss of forest to urban and residential sprawl within the city limit and the surrounding area.

Variation of Soil Dielectric Constant, Moisture Holding Capacity, and Nitrate-Nitrogen as Influenced by Application of Fresh and Compost Poultry Litter on a Decatur Silt Loam Soil

ABSTRACT Currently, there are major concerns about potential environmental impacts of poultry litter application as a nutrient source for agricultural crops. Composting of poultry litter is reported to have less groundwater pollution effects as compared to fresh litter. A field study was conducted to evaluate the effect of poultry litter applications at three different rates on variations of soil dielectric constant, moisture holding capacity, and soil NO3 −-N distribution on a Decatur slit loam soil. The results were compared with effects of urea (inorganic fertilizer) and composted poultry litter applications. The addition of fresh and composted poultry litter increased the soil dielectric constant and water holding capacity due to the increase in soil organic matter. The study indicates that there is a potential of groundwater contamination by application of urea, fresh poultry litter or composted poultry litter at the rates investigated. Urea and fresh poultry litter applications have comparable effects on surface and groundwater contaminations, whereas composting of litter reduced the potential risk for groundwater contamination.

Effect of vegetation density and vegetation conditions on the spectral backscattering in the visible and the near infrared

The work presented in this paper investigates the sensitivity of the hyperspectral remotely sensed data to the vegetation density under different soil moisture conditions. The research testbed comprised four corn plots with 4 different densities, one grass plot, and one bare soil plot. For this purpose, the hyperspectral data were recorded simultaneously as the field measurements, which included soil moisture and temperature, soil characterization (gravimetric soil moisture, bulk density, surface roughness), and vegetation measurements (biomass; plant height; leaf orientations, length, thickness; dielectric constant of stalks and leaves; stalk diameter and height). The findings of this study showed that physical and physiological aspects, as well as the structure of the vegetation, have noticeable effects on its spectral response. The results showed distinct spectral response among the different vegetation densities, thus biomass. They also showed that hyperspectral data are effective in detecting soil moisture variability and discriminating among vegetation densities and conditions. The hyperspectral data were in agreement with the ground data and discriminated among small variations in soil moisture and vegetation densities and conditions. This study also showed that the variation in the spectral variability from different vegetation densities becomes negligible when the vegetation leaves cover completely the ground surface.