Paper
29 January 2024 Drivers and projections of mangrove forest degradation in Segara Anakan Lagoon by using spatial dynamic model
Author Affiliations +
Proceedings Volume 12977, Eighth Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet; 129771S (2024) https://doi.org/10.1117/12.3009640
Event: 8th Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet, 2023, Yogyakarta, Indonesia
Abstract
The Segara Anakan Lagoon (SAL) is a prominent estuarine mangrove ecosystem located in Java, which is recognised as the most densely populated island in Indonesia. SAL is a degraded mangrove forest due to the encroachment of mangrove edge ecotone species such as Nypa frutican (NF), as well as the proliferation of understory communities including Derris trifoliata and Acanthus spp. within the interior of the forest. Nevertheless, there has been a scarcity of research conducted on this particular phenomenon. The present study employed a land-use/cover change model to examine the following inquiries pertaining to the expansion of these communities: 1) What factors contributed to the expansion of the community?, and 2) What are the projected patterns of future community expansion? Various statistical models were employed to conduct a causal analysis in order to assess the factors influencing driving factors. The multitemporal mangrove maps from the previous study were used as input data for the model. Explanatory variables used in the model included environmental data, such as multi-temporal maps depicting the coastline of the lagoon, distances to the shoreline and river mouth, as well as the lagoon outlet. Additionally, multi-temporal maps representing ground elevation were also incorporated. The Conversion of Land Use and its Effects at Small Regional Extent (CLUE-S) dynamic model was employed to forecast the extent of land spreading. The dynamic model was executed utilising the provided statistical model as the input. The land-use/cover change (LULCC) methodology was employed to execute all procedures in R. The results of the study indicated that alterations in ground elevation and shoreline played a significant role in influencing the spread of NF) and understory, as well as the displacement of mangrove tree, particularly in the western region of the study area. According to the prediction model, it was forecasted that the invasion would persist unless the influencing factors were effectively controlled.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Bayu Prayudha, Yaya I. Ulumuddin, Vincentius Siregar, Atriyon Julzarika, Lilik B. Prasetyo, Syamsul Bahri Agus, Suyadi ., Suyarso ., and Praditya Avianto "Drivers and projections of mangrove forest degradation in Segara Anakan Lagoon by using spatial dynamic model", Proc. SPIE 12977, Eighth Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet, 129771S (29 January 2024); https://doi.org/10.1117/12.3009640
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KEYWORDS
Data modeling

Coastal modeling

Landsat

Statistical analysis

Statistical modeling

Oceanography

Ecosystems

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