基于Landsat-8影像和GIS的蛇颈龟空间生境适宜性建模

Kurnia Latifiana, Hartono, P. Danoedoro, M. As-singkily, A. Cahyana
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引用次数: 2

摘要

利用陆地卫星影像建立空间生境适宜性模型,预测生境质量和评价潜在生境。然而,图像必须限制特定栖息地特征的信息,如海龟的栖息地。Chelodina mccordi是一种来自Roti岛的特有海龟,但之前的许多研究都是生物或非空间研究。本研究通过地理信息系统(GIS),以Landsat-8 OLI和TIRS作为实际数据,以Landsat-5 TM作为历史数据。本研究旨在建立麦科迪空间生境适宜性地图模型及其制图精度。建模方法是利用logistic回归叠加指示性参数图,得到生境适宜性指数。本研究采用归一化差水指数(NDWI)、地表温度(LST)、坡度、地形湿度指数(TWI)、距高冠密度距离、距聚落和农业距离、距淡水距离、距海或咸水距离、距街道距离等9个参数进行建模。结果表明,NDWI、LST和TWI对气候变化的贡献较大。基于Landsat-8 OLI/TIRS和GIS分析的mccordi空间生境适宜性模型的制图精度约为75%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Habitat Suitability Modeling of the Roti Snake-Necked Turtle (Chelodina Mccordi) Based on Landsat-8 Imagery and GIS
Landsat imagery can be used to establish spatial habitat suitability modeling for prediction habitat quality and evaluation potential habitat. However, the imagery has to limit information for specific habitat characteristics such as turtles' habitat. Chelodina mccordi is an endemic turtle from Roti Island but many previous studies have been done either biological or non-spatial studies. This study uses Landsat-8 OLI and TIRS as actual data and support with Landsat-5 TM as historical data, through a Geographic Information System (GIS). This study aims to create a spatial habitat suitability map model of C. mccordi and its mapping accuracy. The method that is used for modeling is overlaying indicative parameter maps use of logistic regression to presents the habitat suitability index (HSI). There are nine parameters used for modeling in this study, i.e. normalized difference water index (NDWI), land surface temperature (LST), slope, the topographic wetness index (TWI), distance from high canopy density, distance from settlement and agriculture, distance from freshwater, distance from the sea or salty, and distance from the street. We found three parameters that have strong contribution i.e. the NDWI, the LST, and the TWI. The result of spatial habitat suitability model of C. mccordi based on Landsat-8 OLI/TIRS and GIS analysis presents the value of mapping accuracy is about 75%.
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