4.7 Article

Spatial and temporal patterns of land loss in the Lower Mississippi River Delta from 1983 to 2016

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 250, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2020.112046

Keywords

Land loss; Fragmentation; LISA; Fragstats; Google earth engine; Landsat

Funding

  1. National Science Foundation [1426997, 1812019]
  2. Directorate For Geosciences
  3. Division Of Earth Sciences [1426997] Funding Source: National Science Foundation
  4. Directorate For Geosciences
  5. Division Of Earth Sciences [1812019] Funding Source: National Science Foundation

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The Mississippi Delta in coastal Louisiana has some of the highest rates of land loss in the world. This land-loss crisis might become a global problem because most major deltas are expected to be vulnerable to land loss during the remainder of the 21st century and beyond. Despite this predicament, we do not understand how land loss in a deltaic environment proceeds in time and space. Here, we evaluate the spatial and temporal trends of land loss in the Lower Mississippi River Delta (LMRD) region using spatial statistics and landscape metrics. We used nearly 4800 Landsat images to construct a series of three-year cloud-free composites from 1983 to 2016. From these data, we created a stability index (SI), which is a dimensionless measure of the number of land-to -water transitions that a land pixel makes before being considered lost. Our results indicate that on the LMRD, 75% of land loss is a single transition from land to water, while about 25% of land pixels have two or more transitions before being considered lost. Using a local indicator of spatial association, we show that pixels with similar SI tend to cluster together. Single transition clusters (low SI) form elongated shapes, they are densely packed, and they are predominantly, but not always, found on marsh edges. On the other hand, multi-transition clusters (high SI) form square-like shapes, they are more fragmented, and they are usually found in marsh interiors. Our analysis further shows that the land-loss area within the spatial patches with both high and low stability is strongly related to the density of land patches and their shape (R2 of 0.717 and 0.545 respectively). Our analysis suggests that land-loss pixels on the marsh edges undergo different temporal patterns of land loss compared to those in the marsh interior. We hypothesize that this arises because wave edge-erosion drives land loss on marsh edges, whereas subsidence-related flooding drives land loss in marsh interiors. The stability index provides a useful way to characterize the processes causing land loss.

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