Wetland Mapping Using Multi-Spectral Satellite Imagery and Deep Convolutional Neural Networks: A Case Study in Newfoundland and Labrador, Canada
Sign Up to like & getrecommendations! Published in 2021 at "Canadian Journal of Remote Sensing"
DOI: 10.1080/07038992.2021.1901562
Abstract: Abstract Due to the advent of powerful parallel processing tools, including modern Graphics Processing Units (GPU), new deep learning algorithms, such as Convolutional Neural Networks (CNNs), have significantly altered the state-of-the-art algorithms in satellite classification… read more here.
Keywords: wetland; neural networks; deep convolutional; convolutional neural ... See more keywords
Combining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes
Sign Up to like & getrecommendations! Published in 2019 at "Geocarto International"
DOI: 10.1080/10106049.2018.1474275
Abstract: Abstract Remote sensing has been proven promising in wetland mapping. However, conventional methods in a complex and heterogeneous urban landscape usually use mono temporal Landsat TM/ETM + images, which have great uncertainty due to the… read more here.
Keywords: heterogeneous urban; object based; complex heterogeneous; wetland mapping ... See more keywords
Protocols for Riverine Wetland Mapping and Classification Using Remote Sensing and GIS
Sign Up to like & getrecommendations! Published in 2017 at "Current Science"
DOI: 10.18520/cs/v112/i07/1544-1552
Abstract: Wetlands are one of the most important ecological environments that also have high socio-economic importance. India hosts a large number of wetlands, among which most are in the Indo-Gangetic Plains formed by riverine processes. In… read more here.
Keywords: classification; protocols riverine; mapping classification; wetland mapping ... See more keywords