Wetland Restoration Response Analysis using MODIS and Groundwater Data

Sensors

Assefa M. Melesse³  Vijay Nangia²  Xixi Wang¹ 

[1] Department of Mathematics, Physics & Engineering, Tarleton State University;Earth System Science Institute, University of North Dakota;Department of Environmental Studies, Florida International University

关键词: Kissimmee;    MODIS;    wetlands;    latent heat flux;    fractional vegetation cover;    remote sensing;    albedo;   

DOI  :  10.3390/s7091916

来源: mdpi

【 摘 要 】

Vegetation cover and groundwater level changes over the period of restoration are the two most important indicators of the level of success in wetland ecohydrological restoration. As a result of the regular presence of water and dense vegetation, the highest evapotranspiration (latent heat) rates usually occur within wetlands. Vegetation cover and evapotranspiration of large areas of restoration like that of Kissimmee River basin, South Florida will be best estimated using remote sensing technique than point measurements. Kissimmee River basin has been the area of ecological restoration for some years. The current ecohydrological restoration activities were evaluated through fractional vegetation cover (FVC) changes and latent heat flux using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Groundwater level data were also analyzed for selected eight groundwater monitoring wells in the basin. Results have shown that the average fractional vegetation cover and latent heat along 10 km buffer of Kissimmee River between Lake Kissimmee and Lake Okeechobee was higher in 2004 than in 2000. It is evident that over the 5-year period of time, vegetated and areas covered with wetlands have increased significantly especially along the restoration corridor. Analysis of groundwater level data (2000-2004) from eight monitoring wells showed that, the average monthly level of groundwater was increased by 20 cm and 34 cm between 2000 and 2004, and 2000 and 2003, respectively. This change was more evident for wells along the river.

【 授权许可】

Unknown   
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