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The influence of water balance in mangrove forests growth to mangrove’s degradation and depletion, case study: Southeast Asia
Wilwatikta F.N.a, Sakti A.D.a, Syahid L.N.a, Wikantika K.a
a Center for Remote Sensing, Institut Teknologi Bandung, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 IOP Publishing Ltd. All rights reserved.As natural drivers of mangrove forests’ degradation and depletion, mangrove forests’ water balance, as the ability of them to absorb and release water, which is related to mangrove’s coefficient growth, also makes an impact to those circumstances. The intention of this research is to identify the mangrove growth coefficient that used to analyze mangrove’s water balance and to identify the influence of mangrove’s water balance from mangrove’s depletion and degradation. The research is situated at Southeast Asia in 2000 and 2012. As a proxy for mangrove coefficient growth, MOD13A1 V6 satellite imagery that provides vegetation index values were used and will be multiplied by using the linear regression model that establishes the relationship between vegetation index and mangrove coefficient growth. The procedure for quantifying the mangrove’s water balance is carried out by multiplying the mangrove coefficient growth with evapotranspiration data derived from MOD16A2 V5 and then deducting it by precipitation data from CHIRPS V2. The results presented will confirm how these parameters influence the mangrove’s water balance and influential or not against the mangrove’s lost.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Influence of water,Linear regression models,Mangrove forest,Precipitation data,Southeast Asia,Vegetation index,Vegetation index values,Water balance[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]Thank you for the financial support from Centre of Remote Sensing (CRS) and Remote Sensing and GIS group Bandung Institute of Technology (ITB) to attend and submit the paper to The Fifth International Conferences of Indonesian Society for Remote Sensing (ICOIRS).[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1755-1315/500/1/012013[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]