Abstract

Flooding is the most common and destructive natural disaster in the United States. Ninety percent of all disasters in the US involve flooding, with impacts that cascade across the entire landscape. The primary objective of this study is to understand the impact of flooding on the landscape. One way to determine this is to observe the number of times a unit area of land is flooded and intersect that information with quantified changes in the landscape. The information for this analysis is derived from a complex workflow with inputs from large amounts of Landsat satellite imagery (more than 300 images) and multiple dates of land cover data from the USGS NLCD. The acquired NLCD data were used to generate from-to bivariate land cover change classes. A bivariate dataset was created for 5 date pair epochs. These classes were then used as zonal boundaries within which statistical variables were generated based on the flood frequency layer. By analyzing this information, we characterized what classes changed to what other classes given different frequencies of flooding. The area of interest for this study consists of one path row or footprint of a Landsat image on the border of Louisiana, Texas, and Arkansas near the city of Shreveport, Louisiana. This study area is known to have frequent flooding and a diverse landscape. During our analysis, we discovered that land cover changes in this study area more often occurred within areas that had flooded, rather than areas that had not flooded. Barren land cover change is clearly associated with flooding. Agricultural land changing to barren suggested that frequent flooding may cause arable land to not be as productive. When Barren land changes to vegetated cover and when Water changes to Barren, there is a strong likelihood that the change was due to flooding. Interestingly Urban land cover changes intersected with flood frequency regardless of the ratio. Over 2600 ha of Urban were built within the areas that have previously flooded. Some of the from-to change identified in this analysis was due to classification error, however this was minimized due to USGS’s approach to land cover classification update, whereby only areas of change are classified. The results of this analysis are very useful for identifying where land cover change areas exist, their extent, and the likelihood they are associated with flood activity. This has implications and applications to flood plain management and community land use planning. The results of this study showed there is a relationship between some land cover change types and areas that frequently flood.

Highlights

  • Flooding is the most common and destructive natural disaster in the United States

  • When analyzing the summarized tables, we discovered that land cover changes more often occurred within areas that had flooded; rather than, areas that had not flooded

  • This time period showed that Barren land cover change is highly correlated to flooding in this study area

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Summary

Introduction

Flooding is the most common and destructive natural disaster in the United States. Ninety percent of all disasters in the US involve flooding with impacts that cascade across the entire landscape. While advances have been made in weather forecasting and watershed modeling to predict the future; it is still difficult to measure or characterize and assess the broad impact of flood inundation on the ground over a large area with historical context. There is a gap in our understanding of how land management is influenced by flooding over time. Flooding can be quantified over time and space if you have access to satellite imagery at regular intervals. The Landsat mission, having acquired data since 1972, and since 1982 at 30m resolution, affords researchers the ability to compile a backward looking dataset of change that can be combined with forward looking models to project future conditions

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