Inexpensive Method to Assess Mangroves Forest through the Use of Open Source Software and Data Available Freely in Public Domain

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ISSN Print: 2151-1950
ISSN Online: 2151-1969
www.scirp.org/journal/jgis
E-mail: jgis@scirp.org

"Inexpensive Method to Assess Mangroves Forest through the Use of Open Source Software and Data Available Freely in Public Domain"
written by Fatwa Ramdani, Sabaruddin Rahman, Putri Setiani,
published by Journal of Geographic Information System, Vol.7 No.1, 2015

has been cited by the following article(s):

[1]	MAPPING DISTURBANCE FROM SELECTIVE LOGGING IN TROPICAL FORESTS OF THE YUCATAN PENINSULA, MEXICO
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[2]	Kuriositas: Metode Ilmiah Penelitian Teknologi Informasi
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[3]	Mangroves in the Galapagos islands: Distribution and dynamics
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[4]	Assessing Google Earth Pro images for detailed conservation diagnostics of mangrove communities
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[5]	Adaptation of mangrove trees to different salinity areas in the Ayeyarwaddy Delta Coastal Zone, Myanmar
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[6]	Principal polar spectral indices for mapping mangroves forest in South East Asia: study case Indonesia
	International Journal of Digital Earth, 2018

[7]	Applications of landsat-8 data: A Survey
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[8]	Development of bio-rights incentive scheme for participatory restoration and conservation of mangrove resources
	2017

[9]	Mapping potential of mangrove forests based on site demands (Geomorphological factors and physico-chemical characteristics of soil and water)
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[10]	Madagascar's Mangroves: Quantifying Nation-Wide and Ecosystem Specific Dynamics, and Detailed Contemporary Mapping of Distinct Ecosystems
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[11]	Usabilidade Percebida e Características de Cursos na Avaliação do Programa de Educação em Software Livre com apoio da Análise Multivariada de Dados
	2016

[1]	Improving pixel‐based classification of GRASS GIS with support vector machine Transactions in GIS, 2023 DOI:10.1111/tgis.13102

[2]	Preliminary study for spatial distribution of mangrove vegetation assessment by supervised classification algorithms in the Cirebon coastal areas MACHINE LEARNING AND INFORMATION PROCESSING: PROCEEDINGS OF ICMLIP 2023, 2023 DOI:10.1063/5.0181946

[3]	Assessing Google Earth Pro Images for Detailed Conservation Diagnostics of Mangrove Communities Journal of Coastal Research, 2019 DOI:10.2112/SI92-005.1

[4]	Principal polar spectral indices for mapping mangroves forest in South East Asia: study case Indonesia International Journal of Digital Earth, 2018 DOI:10.1080/17538947.2018.1454516

[5]	Madagascar’s Mangroves: Quantifying Nation-Wide and Ecosystem Specific Dynamics, and Detailed Contemporary Mapping of Distinct Ecosystems Remote Sensing, 2016 DOI:10.3390/rs8020106

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