利用全栅格数据改进海参适宜性模型

B. Sulistyo, D. Purnama, Maya Anggraini, Dede Hartono, M. D. Wilopo, Ully Wulandari, N. Listyaningrum
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引用次数: 1

摘要

使用矢量数据的地理信息系统(GIS)建模是一种常用的建模方法,提供简单的数据输入和分析。然而,矢量数据模型在主观应用分类和简化的基础上假设映射单元的同质性,这可能导致过度简化,从而减少获得的信息的多样性和结果的不确定性。本研究旨在利用完全基于栅格的数据,对印度尼西亚北Bengkulu Enggano地区Kahyapu村Kiowa湾水域的海参(Holothuria scabra)适用性建模进行改进。利用GIS对影响海参适宜性的所有参数进行栅格化处理,以提高兼容性。相关数据包括海水酸度、深度、流速、温度、盐度、亮度、溶解氧浓度、海底状况、区域海岸防护等9个参数。这些参数在51个站点进行实地调查,然后对每个参数进行数字化和插值(使用Kriging方法),以创建连续的栅格数据集。然后进行相关分析,检验参数的相关性。相关系数> 0.75的参数被排除在进一步分析之外,因为结果可以从剩余的参数集中得到。然后应用主成分分析(PCA)确定各成分的权重。此外,还采用筛选图来选择与适用性公式相关的主成分。然后将最终结果与基于向量的数据作为参考数据集分析得出的适宜性图进行比较。研究结果表明,该方法可用于确定适合海参养殖的区域。利用全栅格数据分析得到的海参适宜性图的不确定性小于基于矢量数据的适宜性图。
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Refining Suitability Modelling for Sea Cucumber (Holothuria scabra) Using Fully Raster-Based Data
Geographical Information System (GIS) modelling using vector data is a commonly used method of modelling offering simple data input and analysis. However, the vector-data model assumes homogeneity in mapping units based on subjectively applied classification and simplification, and this may lead to over-simplification and consequent reduction in the variety of information obtained and uncertainty in results. This research aimed at refining the suitability modelling for sea cucumber (Holothuria scabra) using fully raster-based data for the waters of Kiowa Bay, Kahyapu village in the district of Enggano, North Bengkulu, Indonesia. Using a GIS, all parameters affecting suitability for sea cucumber were rasterised to improve compatibility. The relevant data includes nine parameters of sea water namely acidity, depth, current velocity, temperature, salinity, brightness, dissolved oxygen concentration, condition of the sea floor, and coastal protection of the area. These parameters were surveyed in the field at 51 stations and each parameter was then digitized and interpolated (using Kriging method) to create a continuous raster-dataset. Correlation analysis was then conducted to check parameter correlation. Parameters with a correlation coefficient of > 0.75 were excluded from further analysis since results could be derived from the remaining parameter set. Principal component analysis (PCA) was then applied to ascertain the weight of each component. Furthermore, scree plotting was employed to choose which principal components were relevant for insertion into the formula of suitability. The final result was then compared to the map of suitability from the analysis of vector-based data as the reference data set. The research results showed that this method can be used to locate areas that are suitable for sea cucumber farming. The suitability map for sea cucumber generated from the analysis using fully raster-based data displayed less uncertainty than the suitability map generated using vector-based data.
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来源期刊
CiteScore
0.10
自引率
0.00%
发文量
11
审稿时长
15 weeks
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