American Journal of Civil Engineering and Architecture
ISSN (Print): 2328-398X ISSN (Online): 2328-3998 Website: Editor-in-chief: Mohammad Arif Kamal
Open Access
Journal Browser
American Journal of Civil Engineering and Architecture. 2018, 6(1), 13-23
DOI: 10.12691/ajcea-6-1-2
Open AccessArticle

Quantifying the Impact of 20-Year Flood Frequency on Land Cover Change Type

Francois G. F. Smith1 and David J. Alexander2,

1Senior Imagery Scientist, Radiant Solutions

2Chief Geospatial Scientist | Flood APEX Lead, First Responders Group, US Department of Homeland Security

Pub. Date: January 05, 2018

Cite this paper:
Francois G. F. Smith and David J. Alexander. Quantifying the Impact of 20-Year Flood Frequency on Land Cover Change Type. American Journal of Civil Engineering and Architecture. 2018; 6(1):13-23. doi: 10.12691/ajcea-6-1-2


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.

remote sensing GIS land cover change flooding Landsat bivariate analysis floodplain management

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit


Figure of 9


[1]  Pimenta, Matheus M., Fernando A.C. Cardoza, Rafael R. Ribeiro, and Andre C. Zingano (2016). Modern Environmental Science and Engineering, Vol. 2, No. 12, pp. 809-814. Academic Star Publishing Co.
[2]  Skidmore, A.K., Bijker, W., Schmidt, K.S. and Kumar, L. (1997). Use of remote sensing and GIS for sustainable land management. In: ITC journal = bulletin de l'ITC, Vol. 3|4, pp. 302-315.
[3]  aw A. Twumasi & Edmund C. Merem (2007). “Management of Watersheds with Remote Sensing and GIS: A case study of River Niger delta Region in Nigeria”, International Journal of Environmental Research and Public Health, Vol.4, No. 2.
[4]  Masek, J.G., Vermote, E.F., Saleous, N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Kutler, J., and Lim, T.K. A Landsat Surface Reflectance Dataset for North America, 1990-2000. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 3, NO. 1, JANUARY 2006.
[5]  Homer, C.H., Fry, J.A., and Barnes C.A. (2012). The National Land Cover Database, U.S. Geological Survey Fact Sheet 2012-3020, 4 p.
[6]  Benke, Arthur and Colbert Cushing, editors. (2005). Rivers of North America. Elsevier Academic Press. pp. 1144.
[7]  McPhee, John (February 23, 1987). "The Control of Nature: Atchafalaya". The New Yorker. Retrieved May 12, 2011. Republished in McPhee, John (1989). The Control of Nature. Farrar, Straus and Giroux.
[8]  Brock, Eric J. (2008). Shreveport History. Greater Shreveport Chamber of Commerce. Archived from the original on Feb 19, 2008. Retrieved 06-10-2010.
[9]  Stehman, S., Wickham, J., Smith, J. Yang, L, Thematic accuracy of the 1992 National Land-Cover Data for the eastern United States: Statistical methodology and regional results. Remote Sensing of Environment 86 (2003) 500-516.
[10]  Homer, C.G., Dewitz, J.A., Yang, L., Jin, S., Danielson, P., Xian, G., Coulston, J., Herold, N.D., Wickham, J.D., and Megown, K., 2015, Completion of the 2011 National Land Cover Database for the conterminous United States-Representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, v. 81, no. 5, p. 345-354.
[11]  Xian, G, Homer, C, and Fry, J. 2009. Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods. Remote Sensing of Environment, Vol. 113, No. 6. pp. 1133-1147.
[12]  Wickham, J.D., Stehman, S.V., Gass, L., Dewitz, J., Fry, J.A., and Wade, T.G. Accuracy assessment of NLCD 2006 land cover and impervious surface. Remote Sensing of Environment, Volume 130, 15 March 2013, Pages 294-304.