Mangrove area detection by using high resolution satellite imagery

Samad, Abd Manan; Iliyas, Nor Shafikah; Sahriman, Noorita; Ruslan, Fazlina Ahmat; Zainal, Mohd Zainee; Ghazali, Normah Mohd.; Zaki, Nurul Ain Mohd; Zainuddin, Khairulazhar

doi:10.1109/cspa.2017.8064968

Cited by 5 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the last few decades, the image sensors attached to satellites have evolved in a way that nowadays allows the capture of high-resolution multi-spectral satellite images, [1,2,3,4]. As a result, land cover classification became a widely-studied field providing also solutions on the detection and classification of buildings and other struc- [5,6] a) sociology, for the monitoring the dynamic processes that occur in a complex urban environment, b) citizen welfare, for city planning, c) city protection, for the analysis and assessment of the impact of fire, flood and natural disasters in an urban environment, d) illegal construction for detecting illegal building activity and e) navigation, for the development and constant update of accurate urban maps that can be employed for navigation purposes.…”

Section: Introductionmentioning

confidence: 99%

A modular CNN-based building detector for remote sensing images

et al. 2020

View full text Add to dashboard Cite

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

show abstract

Section: Introductionmentioning

confidence: 99%

A modular CNN-based building detector for remote sensing images

et al. 2020

View full text Add to dashboard Cite

show abstract

Temporal Changes of Mangrove Distribution In Mukim Kuala Selangor Using GIS Approach

Hashim

Zaharin

Hashim

et al. 2019

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Mangrove forests are commonly found along coastal line where they grow in saline soil and brackish water. With the advantage of new technology, mangrove distribution information can be studied by using Geographic Information System (GIS) technique. This study is to analyse the mangrove distribution changes using GIS over Mukim Kuala Selangor, Malaysia of years 2014, 2016 and 2018. Through this study, area selection technique from Landsat-8 OLI/TIRS data was used in image processing. Supervised and unsupervised classification were applied in image processing along with the maximum likelihood classification. The findings of this study show that there were changes occured essentially on mangrove area at the study area. Therefore, it is hoped that this study can help stakeholders for the management of mangrove distribution as well as the other land cover which is vital to provide ecological balance and essential services for the community.

show abstract