CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City

Supriatna; Mutia Kamalia Mukhtar; Kartika Kusuma Wardani; Fathia Hashilah; Masita Dwi Mandini Manessa

doi:10.22146/IJG.71721

CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City

Supriatna
, Mutia Kamalia Mukhtar^*
, Kartika Kusuma Wardani
, Fathia Hashilah
, Masita Dwi Mandini Manessa

^*Corresponding author for this work

University of Indonesia
Terbuka University

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Changes in land cover are widespread in Indonesia. This tendency frequently causes annual deforestation rates to increase, which might lead to numerous natural calamities. This study will examine land cover changes, develop land cover prediction models, and examine the link between land cover changes and the Banjarmasin City and surrounding area flood disaster. Annual variations in land cover are determined using images from the GlobeLand30 satellite and a remote sensing method. Using the Cellular Automata - Markov Chain approach, satellite imagery is analyzed to estimate land cover. The results indicate that built-up land and forests will have the most remarkable change in land cover from 2000 to 2020, whereas forests are expected to face deforestation of 356 km2 from 2020 to 2030. In 2021, deforestation produced catastrophic floods, with 111 flood locations in the plantation zone. The water has reached areas with low predicted flood risk.

Original language	English
Pages (from-to)	365-372
Number of pages	8
Journal	Indonesian Journal of Geography
Volume	54
Issue number	3
DOIs	https://doi.org/10.22146/IJG.71721
Publication status	Published - Oct 2022
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities
SDG 15 Life on Land

Keywords

Cellular automata
deforestation
land cover change
land cover prediction
markov chain

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10.22146/IJG.71721

Cite this

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title = "CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City",

abstract = "Changes in land cover are widespread in Indonesia. This tendency frequently causes annual deforestation rates to increase, which might lead to numerous natural calamities. This study will examine land cover changes, develop land cover prediction models, and examine the link between land cover changes and the Banjarmasin City and surrounding area flood disaster. Annual variations in land cover are determined using images from the GlobeLand30 satellite and a remote sensing method. Using the Cellular Automata - Markov Chain approach, satellite imagery is analyzed to estimate land cover. The results indicate that built-up land and forests will have the most remarkable change in land cover from 2000 to 2020, whereas forests are expected to face deforestation of 356 km2 from 2020 to 2030. In 2021, deforestation produced catastrophic floods, with 111 flood locations in the plantation zone. The water has reached areas with low predicted flood risk.",

keywords = "Cellular automata, deforestation, land cover change, land cover prediction, markov chain",

author = "Supriatna and Mukhtar, \{Mutia Kamalia\} and Wardani, \{Kartika Kusuma\} and Fathia Hashilah and Manessa, \{Masita Dwi Mandini\}",

note = "Publisher Copyright: {\textcopyright} 2022 Faculty of Geography UGM and The Indonesian Geographers Association {\textcopyright} 2022 by the authors. Licensee Indonesian Journal of Geography, Indonesia.",

year = "2022",

month = oct,

doi = "10.22146/IJG.71721",

language = "English",

volume = "54",

pages = "365--372",

journal = "Indonesian Journal of Geography",

issn = "0024-9521",

publisher = "Gadjah Mada University",

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TY - JOUR

T1 - CA-Markov Chain Model-based Predictions of Land Cover

T2 - A Case Study of Banjarmasin City

AU - Supriatna,

AU - Mukhtar, Mutia Kamalia

AU - Wardani, Kartika Kusuma

AU - Hashilah, Fathia

AU - Manessa, Masita Dwi Mandini

PY - 2022/10

Y1 - 2022/10

N2 - Changes in land cover are widespread in Indonesia. This tendency frequently causes annual deforestation rates to increase, which might lead to numerous natural calamities. This study will examine land cover changes, develop land cover prediction models, and examine the link between land cover changes and the Banjarmasin City and surrounding area flood disaster. Annual variations in land cover are determined using images from the GlobeLand30 satellite and a remote sensing method. Using the Cellular Automata - Markov Chain approach, satellite imagery is analyzed to estimate land cover. The results indicate that built-up land and forests will have the most remarkable change in land cover from 2000 to 2020, whereas forests are expected to face deforestation of 356 km2 from 2020 to 2030. In 2021, deforestation produced catastrophic floods, with 111 flood locations in the plantation zone. The water has reached areas with low predicted flood risk.

AB - Changes in land cover are widespread in Indonesia. This tendency frequently causes annual deforestation rates to increase, which might lead to numerous natural calamities. This study will examine land cover changes, develop land cover prediction models, and examine the link between land cover changes and the Banjarmasin City and surrounding area flood disaster. Annual variations in land cover are determined using images from the GlobeLand30 satellite and a remote sensing method. Using the Cellular Automata - Markov Chain approach, satellite imagery is analyzed to estimate land cover. The results indicate that built-up land and forests will have the most remarkable change in land cover from 2000 to 2020, whereas forests are expected to face deforestation of 356 km2 from 2020 to 2030. In 2021, deforestation produced catastrophic floods, with 111 flood locations in the plantation zone. The water has reached areas with low predicted flood risk.

KW - Cellular automata

KW - deforestation

KW - land cover change

KW - land cover prediction

KW - markov chain

UR - https://www.scopus.com/pages/publications/85148365298

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DO - 10.22146/IJG.71721

M3 - Article

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SN - 0024-9521

VL - 54

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JO - Indonesian Journal of Geography

JF - Indonesian Journal of Geography

IS - 3

ER -

CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City

Abstract

UN SDGs

Keywords

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