KnE Engineering

ISSN: 2518-6841

The latest conference proceedings on all fields of engineering.

Spatio-Temporal Visualization of Peatlands Changes

Published date: Dec 26 2019

Journal Title: KnE Engineering

Issue title: The 1st International Conference on Geodesy, Geomatics, and Land Administration 2019

Pages: 158–171

DOI: 10.18502/keg.v4i3.5843

Authors:

Lea Kristi Agustina - lea.kristi@itera.ac.id

Trias Aditya

Abstract:

Increased deforestation and draining of peatlands with the started of the drainage occurs quickly makes the availability of peatlands as carbon storage is even more alarming. The presence of peat land conversion greatly affect the hydrological balance of the ecosystem. The conversion of peatland have the massive effect with the increase of drainage constructions for land cultivation needs. This makes the neighborhood unity peat hydrology (KHG) which is wet into dry so prone to burning and experiencing land subsidence. Information of peatland degradation is presented in the spatio - temporal visualization using Space Time Cube (STC). The usability in order to determine the extent of the spatio - temporal visualization can be used by users to obtaining information peatland degradation in terms of effectiveness, efficiency and satisfaction for users. Drainage density built on KHG getting bigger every year with the index of medium density classification. Increasing the number of long-drainage occurs at 119.4934 km per year from 2000 to 2008 and 148.6954 km per year from 2008 to 2012. Based on observations in 12 years has increased the number of distribution Hotspot significantly in February. In May and September the spread of hotspots increased by the average number of hotspots at 15 points per month. The drainage development’s and distribution of hotspot has dominant occurs at the HTI in the KHG Peatland degradation is presented in Visualization spatio-temporal, which visualization is very effective, fairly efficient, and give satisfaction to the users in displaying information peatland degradation in time series.

References:

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