遥感技术在揭示沙特阿拉伯麦加省西部植被对气候变化的时空响应方面的作用

Q2 Environmental Science Environmental Challenges Pub Date : 2024-04-01 DOI:10.1016/j.envc.2024.100926
Basma Salama Alharbi
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引用次数: 0

摘要

气候变化是一个严重影响自然资源的全球性问题,它导致温度、降水和湿度发生重大变化,从而影响植被覆盖。有鉴于此,本研究旨在利用大地遥感卫星-5 专题成像仪、大地遥感卫星-8 业务陆地成像仪、全球陆地数据同化系统模型、全球降水测量和饥荒预警系统网络陆地数据同化系统模型数据,确定遥感技术的潜力,以揭示麦加省西部植被对气候变化的时空响应。数据处理采用了优化土壤调整植被指数(OSAVI)、分类、叠加、变化检测和相关分析等方法。对数据的时间序列分析表明,与气候有关的变化在最近几年尤为强烈。具体而言,温度、降水和湿度因地貌和季节的不同而不同。旱季的气温高于雨季。总体降水量有所减少,雨季降水量不超过 81.39 毫米,旱季降水量约为 11.46 毫米。此外,2023 年的降水量有所增加,但 2018 年的降水量有所减少。此外,除 2023 年的雨季外,研究区域在其他年份都位于半干旱地区。对气候变化敏感的 OSAVI 分析显示,植被覆盖率既会受到气候变化的积极影响,也会受到气候变化的消极影响。2023 年,研究区域的植被覆盖率最高。研究地区的降水量和植被之间也存在密切的相关性,旱季的高绿化率较低,草类分布较广。这些发现对制定半干旱地区生物多样性保护战略具有重要意义。
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Role of remote-sensing techniques in unveiling the spatiotemporal response of vegetation to climate change in the western Makkah Province of Saudi Arabia

Climate change is a global problem that dramatically affects natural resources, resulting in significant changes in temperature, precipitation, and humidity, which affect vegetation cover. Under this light, this study aimed to identify the potential of remote-sensing techniques to reveal the spatiotemporal response of vegetation cover to climate change in the western Makkah Province using Landsat-5 Thematic Mapper, Landsat-8 operational land imager, Global Land Data Assimilation System model, Global Precipitation Measurement, and Famine Early Warning Systems Network Land Data Assimilation System model data from 2000 to 2023. Optimised Soil-Adjusted Vegetation Index (OSAVI), classification, overlay, change detection, and correlation analysis were utilized to process data. Time series analysis of data revealed climate-related changes which were particularly intense in recent years. Specifically, temperature, precipitation, and specific humidity were found to differ depending on the landforms and season. Temperature was higher during the dry season compared to the wet season. A decrease was observed in the overall precipitation rate, which did not exceed 81.39 mm during the wet season and approximately 11.46 mm during the dry season. Additionally, precipitation increased in 2023 but decreased in 2018. Moreover, the study area was located on semi-arid lands for all years except for the wet season of 2023. OSAVI analysis, which is sensitive to climate change, revealed that vegetation coverage can be both positively and negatively affected by climate change. The most profound vegetation coverage in the study region was observed in 2023. A strong correlation was also observed between precipitation and vegetation in the study area, which showed less high-greenness in the dry season and more widespread grasses. The implications of these findings for the development of strategies for biodiversity conservation in semi-arid regions are significant.

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来源期刊
Environmental Challenges
Environmental Challenges Environmental Science-Environmental Engineering
CiteScore
8.00
自引率
0.00%
发文量
249
审稿时长
8 weeks
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