Browsing by Subject "Remote sensing."
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Item Methods of determining stream setback corridors in urban watersheds from remotely sensed data in the Dallas metropolitan area, Texas.(2010-02-02T20:03:48Z) Schreiner, Matthew R.; Allen, Peter M., 1947-; Geology.; Baylor University. Dept. of Geology.Bank stability in urbanized streams is worsening in response to increased runoff, causing unprecedented stream erosion. Eroding banks pose a serious threat to existing structures prompting cities to create buffer zone ordinances to prevent the loss of future structures. Unfortunately, most ordinances probably misjudge buffer zone widths due to the lack of sufficient topographic accuracy for their delineation. However, this study utilizes observations based from remotely sensed data, such as Light Detection and Ranging (LiDAR) with higher accuracy, as well as geological parameters such as channel material. Stream setbacks are easily calculated using computer-aided mapping technology, through the use of remotely sensed data and setbacks can be determined and mapped as corridors with minimal field checking. This study evaluates the overall accuracy of this methodology as compared with values acquired in the field. The results show that the LiDAR data, while being a relatively good fit to the field data, can misrepresent stream setbacks in areas of high relief, most likely due to the smoothing algorithms used in the post-processing of the raw LiDAR data, and field checking is advocated.Item Remotely sensed hyperspectral image unmixing.(2010-10-08T16:34:43Z) Yang, Zhuocheng.; Farison, James Blair.; Engineering.; Baylor University. Dept. of Electrical and Computer Engineering.Estimating abundance fractions of materials in hyperspectral images is an important area of study in the field of remote sensing. The need for liner unmixing in remotely sensed imagery arises from the fact that the sampling distance is generally larger than the size of the targets of interest. We present two new unmixing methods, both of which are based on a linear mixture model. The first method requires two physical constraints imposed on abundance fractions: the abundance sum-to-one constraint and the abundance nonnegativity constraint. The second method relaxes the abundance sum-to-one constraint as this condition is rarely satisfied in reality and uses the relaxed sum-to-one constraint instead. Another contribution of this work is that the estimation is, unlike many other proposed methods, performed on noise reduced hyperspectral images instead of original images.Item Scale dependencies in modeled fire behavior and effects in a southern U.S. grassland ecosystem.(2010-02-02T20:14:06Z) Yao, Jian, 1984-; White, Joseph Daniel.; Biology.; Baylor University. Dept. of Biology.FARSITE models were originally developed for the western grass and forests ecosystems thus predictive accuracy as a function of the scale of input data in southern grasslands is relatively unknown. To test predictive accuracy of the model in southern U.S grasslands ecosystem, two prescribed burns were conducted on the grasslands at Camp Swift, near Bastrop, TX. The spatial scale of FARSITE predicted fire behaviors and effects were assessed based on comparison of field observations and FARSITE simulations utilizing three different spatial resolutions of fuel map data. The FARSITE simulations showed that, fine-scale fuel map derived simulation offered better area of burned prediction, better time of arrival simulation, and closer average temperature output. The time of arrival of fire simulation was less a scale dependence process than the temperature simulation. Prediction of fires in grasslands is limited by our detailed knowledge about mapping fine fuel loading, structure, contiguity, and interannual variability.Item Using remote sensing to assess potential impacts of hurricanes on mosquito habitat formation : investigating the mechanisms for interrelationship between climate and the incidence of vector-borne diseases.(2010-02-02T19:59:59Z) Naqvi, Zainab R.; White, Joseph Daniel.; Environmental Science.; Baylor University. Dept. of Environmental Science.The present study examined the relationship between climate and the incidence of vector-borne disease. The climatological phenomenon El Niño Southern Oscillation (ENSO) was found to be significant in predicting the frequency and intensity of hurricane seasons for the Atlantic Ocean and the Yucatan Peninsula between 1985 to 2007. Satellite analysis for hurricanes that impacted the Yucatan Peninsula, specifically the country of Belize, between 1995 and 2007 determined changes in the Normalized Difference Vegetation Index (NDVI), mid-infrared range (MIR), and thermal infrared range (TIR) immediately after and one month after the hurricanes. Regression analyses found that correlations between reported cases of malaria and dengue fever for Belize and changes in the NDVI, MIR, and TIR existed between immediate and persistent impacts and disease incidence.