Master of Science (MS)
Coastal Louisiana, the seventh largest delta on earth, is one of the most vulnerable coastal areas in the United States of America (USA) because of its land loss problem. Coastal land loss is usually caused by many complicated factors. With the rapid increase in human activities, more studies on land loss have focused on the anthropogenic elements, but less on the pattern of the landscape. It is expected that the type of spatial arrangement, such as high degree of fragmentation, would affect the degree of land erosion. A quantitative evaluation of coastal landscape fragmentation and its influences on land loss would help coastal protection. The purpose of this research is to study the effects of landscape fragmentation on land loss in the Lower Mississippi River Basin (LMRB) region. The main scientific question addressed in this study is: does the degree of fragmentation influence the degree of coastal land loss? This thesis applied fractal analysis and spatial autocorrelation statistics to calculate the degree of fragmentation, using Landsat-TM land cover data in 1996 and 2010 with a pixel size of 30m * 30m. First, 100 samples of a 50-percent land-water ratio for each of the three box sizes – 101*101, 51*51, and 31*31 pixels – were extracted from the study area. Linear regressions were conducted to compute the relationship between fragmentation and land loss. The hypothesis is that the higher the degree of spatial fragmentation, the greater the degree of land loss. The results show that boxes with a higher degree of fragmentation had more land loss for box sizes of 51*51 and 31*31 with p-values less than 0.001. The relationship is not significant for 101*101 with p-values greater than 0.05. Thus, land fragmentation is a worthy element to be considered as a land loss factor. These results should be useful to the development of better strategies to strengthen the protection of a highly fragmented coast.
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Cheng, Weijia, "Effects of Landscape Fragmentation on Land Loss" (2016). LSU Master's Theses. 131.
Lam, Nina Siu-Ngan