基于反照率-MSAVI 特征空间的东地中海地区荒漠化严重程度多尺度评估

IF 2.9 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Ahmad Alghababsheh
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引用次数: 0

摘要

对同一幅卫星图像重新取样以进行多尺度荒漠化评估可能会导致地面物体和光谱信息失真,从而导致生成的信息不确定。为解决这一问题,本研究利用同一时间同一场景的多传感器数据,对东地中海(约旦)干旱和半干旱气候地区的荒漠化严重程度进行了评估。为此,采集了 10 米和 60 米的哨兵-2 号、30 米的 Landsat-8 号以及 250 米和 500 米的 MODIS 号数据,以提取反照率和改良土壤调整植被指数(MSAVI),随后构建反照率-MSAVI 特征空间。利用反照率和 MSAVI 之间的负相关性,生成荒漠化程度指数(DDI)。生成的多尺度荒漠化程度指数图在空间分布、模式和比例方面都比较相似。荒漠化程度指数图显示,极严重和严重荒漠化的范围很广,占研究区域的 50%,主要分布在东部地区。然而,较精细的 DDI 地图(10 米、30 米和 60 米)由于能够捕捉局部空间变化,对于检测小尺度荒漠化特征至关重要,而较粗糙的 DDI 地图(250 米和 500 米)则更适合捕捉由气候因素驱动的大尺度荒漠化模式,其中 MODIS 数据与季节平均降水量呈现出相对较高的正相关性。虽然与较粗的 DDI 地图相比,较细的 DDI 地图显示出更高的精确度,但 MODIS DDI 地图的精确度在均质地貌中显示出更高的精确度。因此,荒漠化严重程度的多尺度同步评估不仅受到空间分辨率的影响,还受到地貌异质性和所使用的卫星传感器类型的影响。本研究采用的多尺度方法可提供有关尺度依赖性荒漠化的见解,有助于制定总体缓解战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A multi-scale assessment of desertification severity in the Eastern Mediterranean region based on albedo-MSAVI feature space

A multi-scale assessment of desertification severity in the Eastern Mediterranean region based on albedo-MSAVI feature space

Resampling the same satellite image to conduct a multi-scale assessment of desertification can be accompanied by distortion of terrestrial objects and spectral information, which can lead to uncertainty in the generated information. To address this, this study assesses desertification severity in an area of arid and semi-arid climate in the Eastern Mediterranean (Jordan) that is characterised by cloudless scenes using multi-sensor data of the same scene at the same time. To this end, Sentinel-2 at 10 m and 60 m, Landsat-8 at 30 m and MODIS at 250 m and 500 m were collected to extract albedo and modified soil adjusted vegetation index (MSAVI), and subsequently to construct albedo-MSAVI feature space. Using the negative correlation between albedo and MSAVI, desertification degree index (DDI) was generated. The resulting multi-scale DDI maps bear a relative resemblance in terms of spatial distribution, patterns, and proportions. The DDI maps indicate that extremely serious and serious desertification are widespread, accounting for 50% of the study area, primarily in the eastern portions. However, finer DDI maps (10 m, 30 m and 60 m) are essential for detecting small-scale desertification characteristics due to their ability to capture local spatial variabilities, while coarser ones (250 m and 500 m) are better suited for capturing broad-scale desertification patterns driven by climatic factors, in which MODIS data exhibit a relatively higher positive correlation with seasonal average precipitation. Although finer DDI maps show higher accuracy compared to coarser ones, the accuracy of DDI maps of MODIS has shown an increase within a homogeneous landscape. Accordingly, synchronised multi-scale assessment of desertification severity is not only influenced by the spatial resolution but also by the landscape heterogeneity and the type of satellite sensor utilised. The multi-scale approach applied in this study can provide insights on scale-dependent desertification that help in devising overarching mitigation strategies.

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来源期刊
Environmental Monitoring and Assessment
Environmental Monitoring and Assessment 环境科学-环境科学
CiteScore
4.70
自引率
6.70%
发文量
1000
审稿时长
7.3 months
期刊介绍: Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.
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