Landcover Change in the Amazon Rainforest: A Look at Deforestation
Academic Level at Time of Presentation
Senior
Major
Archaeology
List all Project Mentors & Advisor(s)
Dr. Robin Q. Zhang
Presentation Format
Poster Presentation
Abstract/Description
The deforestation of the Amazon Rainforest has been an ongoing problem for the past several decades. The Brazilian State of Rondônia is just one area that has been drastically affected. Remote sensing techniques will be applied to take a close look at the amount of deforestation between 1988 and 2018 in a selected area of the State of Rondônia. Landsat 8 and Landsat 5 data collected from USGS Earth Explorer will be used to detect change in forest cover. ERDAS Imagine will be used to clip the area of interest from the Landsat images. The images will then be analyzed using unsupervised classification and change detection processes in ERDAS Imagine. Maps depicting classification and deforestation results will be created in ArcMap to provide an appropriate and informative display. The results should show a dramatic change in the amount of forested area between the two images. The various effects of this deforestation will be examined and discussed. Resources that will be explored to provide an understanding about why this is occurring include examples of government policies and business practices which have either led to deforestation or come about in response to the deforestation. This information will provide some insight beyond the remote sensing visualization of the problem.
Fall Scholars Week 2019 Event
Earth and Environmental Sciences Poster Session
Landcover Change in the Amazon Rainforest: A Look at Deforestation
The deforestation of the Amazon Rainforest has been an ongoing problem for the past several decades. The Brazilian State of Rondônia is just one area that has been drastically affected. Remote sensing techniques will be applied to take a close look at the amount of deforestation between 1988 and 2018 in a selected area of the State of Rondônia. Landsat 8 and Landsat 5 data collected from USGS Earth Explorer will be used to detect change in forest cover. ERDAS Imagine will be used to clip the area of interest from the Landsat images. The images will then be analyzed using unsupervised classification and change detection processes in ERDAS Imagine. Maps depicting classification and deforestation results will be created in ArcMap to provide an appropriate and informative display. The results should show a dramatic change in the amount of forested area between the two images. The various effects of this deforestation will be examined and discussed. Resources that will be explored to provide an understanding about why this is occurring include examples of government policies and business practices which have either led to deforestation or come about in response to the deforestation. This information will provide some insight beyond the remote sensing visualization of the problem.