张新阳, 池源, 刘大海, 等, xxxx. 基于“景观-植被-土壤”框架的海岛生态系统遥感评价−以辽宁长海县为例[J]. 海洋科学进展, x(x): xx-xx. doi: 10.12362/j.issn.1671-6647.20231022001.
引用本文: 张新阳, 池源, 刘大海, 等, xxxx. 基于“景观-植被-土壤”框架的海岛生态系统遥感评价−以辽宁长海县为例[J]. 海洋科学进展, x(x): xx-xx. doi: 10.12362/j.issn.1671-6647.20231022001.
ZHANG X Y, CHI Y, LIU D H, et al, xxxx. Island ecological evaluation based on remote sensing under the "landscape-vegetation-soil" framework: an empirical study in changhai county of liaoning province, china[J]. Advances in Marine Science, x(x): xx-xx. DOI: 10.12362/j.issn.1671-6647.20231022001
Citation: ZHANG X Y, CHI Y, LIU D H, et al, xxxx. Island ecological evaluation based on remote sensing under the "landscape-vegetation-soil" framework: an empirical study in changhai county of liaoning province, china[J]. Advances in Marine Science, x(x): xx-xx. DOI: 10.12362/j.issn.1671-6647.20231022001

基于“景观-植被-土壤”框架的海岛生态系统遥感评价以辽宁长海县为例

Island Ecological Evaluation Based on Remote Sensing Under the "Landscape-Vegetation-Soil" Framework: an Empirical Study in Changhai County of Liaoning Province, China

  • 摘要: 随着人类开发利用的日趋剧烈,海岛生态系统正承受着多重压力。全面准确地评估海岛生态系统是开展海岛保护与管理工作的基础,但这同时也对本底数据提出了更高的要求。由于海岛自身明显的空间隔离性和复杂的地形条件,现场调查难度大、成本高,本底数据获取困难。遥感技术的快速发展为海岛生态评估提供了丰富的数据来源,如何基于遥感数据全面准确地评估海岛生态系统亟待探索。本研究以辽宁长海县18个有居民海岛为研究对象,精细刻画了包含10大类、27小类的海岛地表覆盖体系,充分挖掘遥感影像生态意义,并构建了一套涵盖海岛景观、植被与土壤三方面要素的海岛遥感生态指数(island remote sensing ecological index, IRSEI),以期通过遥感数据替代现场调查,实现海岛生态评估工作的成本降低和过程简化。在30 m×30 m网格尺度与海岛尺度计算三类遥感生态指数与IRSEI,并与海岛地理参数进行相关性分析。结果表明:网格尺度上,海拔、坡度、距岸线距离对IRSEI具有正相关性,其中海拔与坡度对结果的贡献度高;海岛尺度上,海岛离岸距离对IRSEI具有正相关性。本研究验证了IRSEI对于评估海岛生态系统的全面性、准确性及其在不同尺度上的空间显示性,可推广至不同区域、多时空尺度的海岛生态系统研究中。

     

    Abstract: Increasing human activities bring remarkable pressure to island ecosystems, which are ecologically vulnerable. Comprehensive and accurate island ecological evaluation is the basis of island protection and management, however, it puts forward high requirements for fieldwork data. The island field investigation is difficult and costly due to the obvious spatial isolation and complex terrain conditions. The rapid development of remote sensing technology has provided abundant data source for the island ecological evaluation, and it is urgent to explore whether the island ecosystem can be accurately and comprehensively evaluated based only on remote sensing data. In the present work, 18 inhabited islands in Changhai County, Liaoning Province of China were selected to demonstrate such an study on island ecological evaluation based only on remote sensing to reduce the cost and provide a feasible method. A total of 10 types and 27 sub-types of land covers were systematically depicted and the ecological information of remote sensing was utilized to establish the island remote sensing ecological index (island remote sensing ecological index, IRSEI), which contains three components, namely, landscape, vegetation, and soil. The indices were calculated at 30×30 m grid scale and island scale, and their correlations with the geographical parameters were analyzed at the grid and island scales. The results indicated that altitude, slope, and distance to coastline have positive correlations with IRSEI at the grid scale, and altitude and slope have higher contributions than distance to coastline; at the island scale, distance to mainland has a positive correlation with IRSEI. This study has validated the comprehensiveness and accuracy of IRSEI for assessing island ecosystem and its spatial exhibitions at different scales, and the index can be applied to similar studies on island ecosystems in different regions and at multiple spatial and temporal scales.

     

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