Irrigation and Drainage

Oral

393590 - Estimation of Vegetation Coverage based on Seasonal Variabilities in MODIS-based Vegetation Indices

Tuesday, June 5
4:00 PM - 5:30 PM
Location: Skyway Room

Determination of the Vegetation Coverage (VC) plays an important role in different aspects of watershed management. Remote sensing products can provide estimates of VC; however, the uncertainty of the data acquisition and processing has always challenged the usability of spaceborne imagery data. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) products used to model VC of three basins: Lower Fox (LF) in Wisconsin, Lower East Fork White (LEFW) in Indiana, and Lower San Joaquin River (LSJR) in California. MODIS MOD13Q1 product is used to obtain VC based on Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI). However, the commonly used threshold value of 0.4, used to differentiate vegetated from non-vegetated areas, does not necessarily yield to accurate estimates when compared to the National Land Cover Dataset (NLCD). A statistical criterion—determined based on probability distributions of VC—used to filter pixels with low Vegetation Index (VI) values during the time of peak-vegetation as non-vegetated. The same approach implemented to determine vegetated areas during the low-vegetation season. These pixels were left out of analysis—regardless of the VI value—and their VC condition was determined based on the group of filtered data they belong to. Then, VC was calculated for the remaining pixels and results were integrated with those of the filtered areas. Application of the suggested technique improved VC estimations. The errors of VC estimations based on NLCD-VI comparison were reduced by 0.03%, 3%, and 5% for EVI and 17%, 6%, and 7% for NDVI in LF, LEFW, and LSJR basins, respectively.

Bahram Khazaei, MS

PhD Student
University of Wisconsin-Milwaukee

Education
(Expected 2018) Ph.D., Civil & Environmental Engineering
University of Wisconsin-Milwaukee, WI, USA
2017 Graduate Certificate, Geographic Information Systems
University of Wisconsin-Milwaukee, WI, USA
2012 M.Sc., Civil Engineering
Ferdowsi University of Mashhad, Mashhad, Iran
2009 B.Sc., Civil Engineering
Ferdowsi University of Mashhad, Mashhad, Iran

Research Interests
• Water Balance and Watershed Modeling
• Application of GIS and Remote Sensing in Modeling Water Resources Systems
• Water Quality Modeling, Limnology, Environmental Flows, and Hydrodynamic Modeling
• Hydroclimatology

Presentation(s):

Send Email for Bahram Khazaei

Changshan Wu

Professor
University of Wisconsin-Milwaukee

Presentation(s):

Send Email for Changshan Wu


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