Spatial Analysis of Ecological Risk in a Coastal Dune Landscape Using High Resolution Aerial Photography

Noviyanti Listyaningrum; Djati Mardiatno; Evita Hanie Pangaribowo; Muhammad Anggri Setiawan; Junun Sartohadi; Bambang Sulistyo

doi:10.14746/quageo-2024-0001

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Spatial Analysis of Ecological Risk in a Coastal Dune Landscape Using High Resolution Aerial Photography

Quaestiones Geographicae

Volume 43 (2024): Issue 1 (March 2024)

By: Noviyanti Listyaningrum , Djati Mardiatno , Evita Hanie Pangaribowo , Muhammad Anggri Setiawan , Junun Sartohadi and Bambang Sulistyo

Open Access

|Mar 2024

Figures & Tables

Location of Parangtritis coastal dune (source: National Geospatial Agency 2020, processed).

Illustration of the Parangtritis coastal dune formation.

Table 1.

Formulas to calculate the landscape disturbance.

Index	Equation	Assessment Unit
Landscape disturbance (Xie et al. 2013; X. Zhang et al. 2013; Liu et al. 2020)	S_i = aCi + bN_i + cDi a + b + c = 1 a = 0,5; b = 0,3; c = 0,2	landscape class or sub-class
Landscape fragmentation (X. Zhang et al. 2013; Liu et al. 2020)	$C_{i} = \frac{n_{i}}{A_{i}}$	landscape class or sub-class
Landscape isolation, segmentation, or splitting (Xie et al. 2013; X. Zhang et al. 2013; Liu et al. 2020)	$C_{i} = \frac{A}{2 A_{i}} \sqrt{\frac{n_{i}}{A}}$	landscape class or sub-class
Landscape dominance (Jin et al. 2019)	$D_{i} = \frac{(Q_{i} + M_{i} + L_{i})}{3}$	landscape class or sub-class

1 Note: n_i = the number of patches of landscape i; A_i = the total area of landscape i; A = the total area of all landscape types; Q_i = the number of sampling units (including grid) of patch i divided by the total number of sampling units for all landscape types; M_i = the number of patches of landscape i divided by the total number of patches of all landscape types; L_i = the area of landscape i divided by the total area of all landscape types.

Table 2.

Landscape fragility index (Fi) of various landscape classes based on their genesis (natural processes or human interventions).

Landscape class	Natural	Agrogenic	Tree agrogenic	Industrogenic	Info-telecommunication	Tourismsports	Traffic	Urbanogenic	Water management
Index	1.000	0.686	0.145	0.472	0.068	0.319	0.098	0.048	0.215

Division of the Parangtritis coastal dune (risk calculation area) into grids of equal size and the centroid or sampling centre.

Table 3.

Landscape ecological risk index calculation.

Index	Equation	Assessment Unit
Ecological risk	$E R I_{i} = \sum_{i = 1}^{N} \frac{A_{k i}}{A_{k}} \times R_{i}$	grid (if one grid contains > 1 classes or sub-classes, their indices are summed, adjusting the area proportion)
Landscape loss degree	R_i = F_i × S_i	landscape class or sub-class

1 Note: A_ki = the area of landscape I within grid k; A_k = the area of grid k; F_i = the fragility index of landscape i; S_i = the disturbance index of landscape i.

Table 4.

Calculation of global and local spatial autocorrelation.

Global spatial autocorrelation

Local spatial autocorrelation

I = \frac{\sum_{i}^{n} \sum_{j \neq 1}^{n} W_{i j} {(x_{i} - x)}^{2}}{S^{2} \sum_{1}^{n} \sum_{j \neq 1}^{n} W_{i j}}

$S^{2} = \frac{1}{n} \sum_{1}^{n} {(x_{i} - \bar{x})}^{2}$

$\bar{x} = \frac{1}{n} \sum_{i (j)}^{n} x_{i j}$

$Z_{s c o r e} = \frac{I - E (I)}{\sqrt{V a r (I)}}$

I_{i} = z_{i} \sum_{j = 1}^{n} w_{i j} z_{j} (i \neq j)

1 Note: I = Moran’s I; x_i = the observed value of certain attribute in spatial unit i; x_j = the observed value of certain attribute in spatial unit j; x = the mean value of regional variables; S² = mean squared deviation; w_ij = spatial weight value (expressed by n dimensional matrix, W [n × n]); Var(I) = the variance of Moran’s I; E(I) = the expected value of Moran’s I; z_i = standardisation of the observation value in research unit i; z_j = standardisation of the observation value in research unit j; z_score = the significance level of Moran’s I.

Interpretation of clusters derived from using LISA: high-high = the increasing value in a region will be followed by increasing values in adjacent regions; high-low = the increasing value in a region will be followed by decreasing values in adjacent regions; low-high = the decreasing value in a region will be followed by increasing values in adjacent regions; low-low = the decreasing value in a region will be followed by decreasing values in adjacent regions.

Spatial distribution of land use and land cover types in 2011 (A) and 2020 (B).

Spatial distribution of human interventions in 2011 (A) and 2020 (B).

Spatial distribution of the landscape ecological risk (LER) levels for every landscape ecological unit (LEU) generated with four scenarios: 2011 sub-class (A), 2020 sub-class (B), 2011 class (C) and 2020 class (D).

Area of the five landscape ecological risk (LER) levels for each scenario.

Table 5.

Global spatial autocorrelation of landscape ecological risk (LER) in the Parangtritis coastal dune.

Scenario	Moran’s I	Z_score
Sub-class 2011	0.4112	18.0872
Sub-class 2020	0.6342	27.0196
Class 2011	0.5775	24.6668
Class 2020	0.6177	26.3570

Local indicator of spatial association (LISA) cluster map showing the local spatial autocorrelation of landscape ecological risk (LER) in the Parangtritis coastal dune.

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DOI: https://doi.org/10.14746/quageo-2024-0001 | Journal eISSN: 2081-6383 | Journal ISSN: 2082-2103 (formerly 0137-477X)

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Language: English

Page range: 5 - 19

Submitted on: Nov 25, 2022

Published on: Mar 30, 2024

Published by: Adam Mickiewicz University

In partnership with: Paradigm Publishing Services

Keywords:

landscape ecological unit,

landscape sub-class,

landscape class,

landscape pattern,

landscape ecological risk,

Parangtritis coastal dune

Related subjects:

Geosciences,

Geography

© 2024 Noviyanti Listyaningrum, Djati Mardiatno, Evita Hanie Pangaribowo, Muhammad Anggri Setiawan, Junun Sartohadi, Bambang Sulistyo, published by Adam Mickiewicz University
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 43 (2024): Issue 1 (March 2024)

Spatial Analysis of Ecological Risk in a Coastal Dune Landscape Using High Resolution Aerial Photography

Figures & Tables

Fig 1.

Fig 2.

Table 1.

Table 2.

Fig 3.

Table 3.

Table 4.

Fig 4.

Fig 5.

Fig 6.

Fig 7.

Table 5.

Fig 8.

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