Object Based Image Analysis Technique for Distinguishing Tropical Native Forest from Plantations: A Landcover Classification Analysis of Patches Surrounding the Serra do Brigadeiro State Park, Minas Gerais, Brazil
dc.contributor.advisor | Swenson, Jennifer J | |
dc.contributor.author | Meehan, Kelly | |
dc.date.accessioned | 2016-04-29T20:17:19Z | |
dc.date.available | 2017-04-29T04:30:05Z | |
dc.date.issued | 2016-04-29 | |
dc.department | Nicholas School of the Environment and Earth Sciences | |
dc.description.abstract | The Brazilian Atlantic forest is regarded as one of the hottest biodiversity hotspots in the world. Nonetheless, this area has experienced massive deforestation and significant fragmentation as a result of encroaching pasture, coffee, and eucalyptus plantations. Satellite remote sensing is one of the primary methods of monitoring forest health and extent; yet, distinguishing native forest from plantations, such as eucalyptus, remains a significant challenge in most of the tropics. This study explores the use of moderately priced, high-resolution satellite imagery and identifies the algorithms and training parameters that successfully separate eucalyptus plantations from Atlantic forest patches for future conservation prioritization. | |
dc.identifier.uri | ||
dc.subject | object based image analysis | |
dc.subject | RapidEye | |
dc.subject | Brazilian Atlantic Forest | |
dc.title | Object Based Image Analysis Technique for Distinguishing Tropical Native Forest from Plantations: A Landcover Classification Analysis of Patches Surrounding the Serra do Brigadeiro State Park, Minas Gerais, Brazil | |
dc.type | Master's project | |
duke.embargo.months | 12 |