时空植被覆盖分析以确定巴布亚新几内亚的气候变化

IF 0.9 Q4 ENVIRONMENTAL STUDIES
T. Sekac, Sujoy Kumar Jana, I. Pal
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引用次数: 1

摘要

目的世界各地都经历了气候变化及其相关影响。气候变化的触发因素和影响各不相同。这项研究的目的是弄清楚植被覆盖的变化对气候变化的影响。这项研究将为植被保护和重新种植提供思路。设计/方法/方法从1981年到2015年,对调查进行了34年的调查。在对植被数据序列中的序列自相关进行测试和检查后,进行了Mann–Kendal非参数统计评估,以调查植被覆盖趋势。Sen的方法被用于调查每年以自然差异植被指数(NDVI)为单位的植被覆盖变化幅度。此外,ArcGIS空间分析工具用于计算NDVI的平均分布,并用于对研究区域内每个特定位置的趋势进行空间调查。研究发现,研究期间的年平均NDVI呈下降趋势。NDVI的平均值在0.32到0.98之间,因此,这意味着从植被较少或较差的区域到植被较高或较健康的区域。NDVI的平均值向高地地区递减。NDVI降雨量相关性强于NDVI温度相关性。NDVI降雨的面积覆盖率呈正相关高于负相关。NDVI温度负相关的%面积覆盖率高于研究区域内的正相关。降雨被视为比研究区域内的温度更能影响植被生长的气候因素。独创性/价值该国的这项研究为巴布亚新几内亚人民,特别是农民和沿海地区居民的生存,提供了一种新的气候变化监测和规划方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatio-temporal vegetation cover analysis to determine climate change in Papua New Guinea
Purpose The climate change and related impacts are experienced around the world. There arise different triggering factors to climate change and impact. The purpose of this study is to figure out how changes in vegetation cover may or may not have an impact to climate change. The research will produce ideas for vegetation preservation and replant. Design/methodology/approach The investigation was probed for 34 years’ time period starting from the year 1981 to 2015. After testing and checking for serial autocorrelation in the vegetation data series, Mann–Kendal nonparametric statistical evaluation was carried out to investigate vegetation cover trends. Sen’s method was deployed to investigate the magnitude of vegetation cover change in natural differential vegetation index (NDVI) unit per year. Furthermore, the ArcGIS spatial analysis tools were used for the calculation of mean NDVI distribution and also for carrying out the spatial investigation of trends at each specific location within the study region. Findings The yearly mean NDVI during the study period was observed to have a decreasing trend. The mean NDVI value ranges between 0.32 and 0.98 NDVI unit, and hence, this means from less or poor vegetated zones to higher or healthier vegetated zones. The mean NDVI value was seen decreasing toward the highlands regions. The NDVI-rainfall correlation was observed to be stronger than the NDVI-temperature correlation. The % area coverage of NDVI-rainfall positive correlation was higher than the negative correlation. The % area coverage of NDVI-temperature negative correlation was higher than the positive correlation within the study region. Rainfall is seen as a highly influencing climatic factor for vegetation growth than the temperature within the study region. Originality/value This study in this country is a new approach for climate change monitoring and planning for the survival of the people of Papua New Guinea, especially for the farmer and those who is living in the coastal area.
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来源期刊
CiteScore
3.40
自引率
6.20%
发文量
49
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