Thesis--Auburn University, 2010. / Abstract. Includes bibliographic references (p.92-104).

No description available.

Grasslands are the most important ecosystem to humanity, as they are responsible for feeding that majority of the human population. These are also very large ecosystems; they cover approximately 40% of the surface of the earth (Loveland et al., 1998), making ground-based surveys for monitoring grassland health and productivity extremely time consuming. Remote sensing has the advantage of providing reliable and repeatable observations over large swaths of land; however, optical sensors exploiting the visible and near infrared regions of electromagnetic (EM) spectrum will be unable to collect information from the ground if clouds are present (Wang et al., 2009). Imaging radar sensors, the most common being synthetic aperture radar (SAR), have the advantage of being able to image the ground even during cloudy conditions. The longer wavelengths of EM energy used by the SAR sensor are able to penetrate clouds while shorter wavelength used by optical sensors are scattered. A grassland monitoring tool based on SAR imagery would have many advantages over an optical imagery system, especially when SAR data becomes widely available. To demonstrate the feasibility of grassland monitoring using SAR, this study experimented with a set of dual-polarimetric SAR imagery to extract several grassland biophysical parameters such as soil moisture, canopy moisture, and green grass biomass over the mixed grassland in southwestern Saskatchewan. Soil moisture was derived from these images using the simple Delta Index (Thoma et al., 2006) first developed for a sparsely vegetated landscape. The Delta Index was found to explain 80% of the variation in soil moisture, in this vegetated landscape. Canopy moisture was modeled using the water cloud model (Attema and Ulaby, 1978). This model has a similar explanatory power of R2 = 0.80. This study found that only the photosynthesizing green grass biomass had a significant relationship with the canopy moisture model. However, only about 40% of the variation in green grass biomass can be explained by canopy moisture alone. The cross-polarized ratio developed from the dual polarimetric images was found to reflect the plant form diversity of the grassland. Biophysical parameters extracted from optical satellite imagery, Landsat-5 in the case of this study, were compared to those derived from the SAR images. This comparison revealed that the SAR images were superior in sensitivity to soil and canopy moisture. Optical imagery was found to be more sensitive to green canopy cover. An approach combining the results from both sensors showed an improvement in green grass biomass estimation (Adjusted R2 = 0.71).

主催：JST/CREST，Vrije University, ALTERRA, IBPC

Thesis (M.S.)--Oregon State University, 2004. / Typescript (photocopy). Includes bibliographical references. Also available on the World Wide Web.

Thesis (M.S.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains vi, 68 p. : ill. (some col.), col. maps. Vita. Includes abstract. Includes bibliographical references (p. 61-67).

Thesis (Ph. D.)--West Virginia University, 1999. / Title from document title page. Document formatted into pages; contains x, 173 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 163-169).

Thesis (Ph.D. (Zoology & Entomology)) - Rhodes University, 2007.

Master of Science / Department of Biological & Agricultural Engineering / Danny H. Rogers / Recent innovations in the irrigation industry indicate a transition to more water efficient and uniform systems. This transition is necessary to preserve limited aquifer resources used by irrigation systems in the U.S. Great Plains where center pivot irrigation has become the dominant irrigation method. New in-canopy sprinkler packages have allowed these center pivot systems to operate more efficiently and uniformly, however, these in-canopy sprinklers hang low in the canopy and have the potential to become entangled in crop biomass and detach from the center pivot. Detached in-canopy sprinklers can impact the uniformity of the irrigation system resulting in decreased crop yields by disrupting the designed flow and pressure requirements of the sprinkler package. Therefore, it is crucial that producers detect and replace missing in-canopy sprinklers immediately. The current method to detect missing in-canopy sprinklers is manual inspection along the center pivot which uses significant time and labor. A monitoring system to alert the user of any detachments can eliminate unnecessary exploration and direct the user to the specific location of the detached in-canopy sprinkler. A prototype in-canopy sprinkler monitoring system was designed to monitor in-canopy sprinklers on a center pivot irrigation system and alerts the user when and where an in-canopy sprinkler becomes detached from the center pivot span. The system utilizes three major components to accomplish this task: a master controller node, a series of sprinkler nodes, and a digital compass node. The master controller node requests the status of in-canopy sprinklers from each connected sprinkler node, which constantly monitors its connected in-canopy sprinkler, and if a sprinkler is found to be missing alerts the user via an SMS text message sent to their cell phone that the in-canopy sprinkler is missing and can be found at specific geographic coordinates. The master controller node calculates the geographic coordinates of the detached in-canopy sprinkler by requesting the current compass bearing angle of the center pivot span from the digital compass node. This angle, combined with the known coordinates of the pivot point of the center pivot system and radius of the detached in-canopy sprinkler from the pivot point can be used to calculate the coordinates of the detached in-canopy sprinkler. To test the performance of the designed system, it was connected to a demonstration center pivot and several trials were performed. The demonstration center pivot consisted of a rotatable span with eight detachable drop hoses and in-canopy sprinklers. Trials performed were designed to test the system’s ability to react to detached in-canopy sprinklers and drop hoses, detect and identify issues that might arise during normal operation, and respond to user’s SMS text messages with the proper system information as part of the user interface. The system successfully passed each set of trials ensuring that this prototype will accurately detect when and where an in-canopy sprinkler becomes detached and promptly alert the user.

Corn requires the most nitrogen (N) of cereal grain crops and N supply is correlated with grain yield.  Canopy reflectance has been used to assess crop N needs and to derive optimum application rates in mid-season corn.  Canopy reflectance has not been useful for N rate determination in early season corn because of low biomass and the sensing background can interfere, or overwhelm crop canopy reflectance measures.  Widespread adoption of canopy reflectance as a basis for generating in-season corn N rates would be more likely if N rate recommendations could be made early, i.e. by the V6 growth stage.  The objectives of this research were to: i) examine the influence of soil color, soil moisture, surface crop residues, and sensor orientation on normalized difference vegetation index (NDVI) readings from corn from planting through the V6 growth stage; and ii) evaluate the effect of sensor orientation and field of view at early corn growth stages on the relationship between NDVI and corn biomass, N uptake, and chlorophyll meter readings.  Soil color, soil moisture, crop residue type, and sensor orientation influenced reflectance and these factors were much more influential when sensing plants with low biomass.  Canopy reflectance was capable of differentiating between N rates in the field and altering sensor orientation did not minimize sensing background influence or improve the ability of the sensor to distinguish plant N status.  Even when canopy reflectance detected differences in crop N status, N rate prescription based on NDVI was consistently below the profitable estimated sidedress N rate. / Master of Science