Dr. Suyadi . Profile

Dr. Suyadi .

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Publications (1)

Proceedings Article | 29 January 2024 Paper

Drivers and projections of mangrove forest degradation in Segara Anakan Lagoon by using spatial dynamic model

Bayu Prayudha, Yaya Ulumuddin, Vincentius Siregar, Atriyon Julzarika, Lilik Prasetyo, Syamsul Bahri Agus, Suyadi ., Suyarso ., Praditya Avianto

Proceedings Volume 12977, 129771S (2024) https://doi.org/10.1117/12.3009640

KEYWORDS: Data modeling, Coastal modeling, Landsat, Statistical modeling, Statistical analysis, Oceanography, Ecosystems

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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.

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