The specific aim of this study is to find the probability of land loss and the degree of land fragmentation in the Lower Mississippi River Basin (LMRB), which is located in southeastern Louisiana, USA, and extends from the parishes north of Lake Pontchartrain to the coast. In order to decrease the statistical deviation of the results, the data is collected randomly from study area. Use ICAMS (Image Characterization and Modeling System) to acquire the spatial analysis to show the relationship between land fragmentation and land loss. Then, depend on the analysis to make suggestions for local department to provide powerful policy in friable area (McCulloh et al 37).
The two groups of comparison images should be described in the background, seems more fragmentation more land loss.
It can be observed from the research that there are large portions which have been occupied by the water bodies. There have been around 150 random boxes in the coastal regions. According to Dr. Witt H Braud, it can be said that 101 * 101 pixels is the best size as it gives the best idea for looking into the coastal line which has 50 % of land to water ratio.
Because the high fragment structure of the land is easier to be destroyed, my hypothesis is that the degree of land fragmentation and land loss has positive correlation, which means the higher the fragmentation the more lands will be lost. However, it is also important to consider the rise in sea level, because the lands are still connected under water level (Haer & Toon 1327). The fragment regions demand to have more strengthened protection to prevent loss.
Moran’s I is used for the spatial auto-correction of the land related attributes.
It can be seen that when the value of factual dimension is found to be around 2.25, the amount of land loss is identified to be 0. Also, when the value of factual dimension is 2.3, there is a 3% of land loss. When the value of factual dimension is nearing to 2.4, the land loss is 10%. However it has been observed that while the factual value has reached 2.6, the land loss has increased beyond 20 %.The peak value of land loss has been observed at the fractal dimension of 2.6 which is nearing 50 %. After this, there has been a slight variation in the land loss and it has begun to decrease (Smith et al 442). When the factual dimension is between 2.6 and 2.7, it can be seen that the percentage of land loss has decreased below 40 %. The percentage of land loss has been found to decrease further by the increase in fractal dimension. Further, when it has been found that the value of fractal dimension is 2.7, the land loss has further decreased below 20 %. In the range between 2.7 t0 2.8 it has been further observed the decrease. At the peak value of fractal dimension i.e. 2.85, the value of land loss is less than 10 % (Khalil et al 1467). Thus, it can be observed that the value of percentage of land loss initially increases and reaches a peak value of nearly 50 % and then begin to decrease with the increase in fractal dimension.