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논문 기본 정보

자료유형
학술저널
저자정보
Nadia Abbaszadeh Tehrani (Ministry of Science, Research and Technology) Milad Janalipour (Ministry of Science, Research and Technology)
저널정보
대한환경공학회 Environmental Engineering Research Environmental Engineering Research 제26권 제4호
발행연도
2021.8
수록면
32 - 42 (11page)

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초록· 키워드

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The consequences of unsustainable human activities on the environment are often delayed, when it is too late to compensate. New approaches are based on the use of “spatial statistics” of leading indicators to measure the “critical slowing down” in a degraded ecosystem, when it is reaching to a tipping point. This research predicts the tipping points in the ecosystem of Lake Urmia Basin (LUB) based on spatial statistics. By Remote Sensing (RS) indicators, their effectiveness in assessing the state of the ecosystem was evaluated in a 16-years period (2002-2017). Seven spectral indicators (NDVI, NDWIv,NDWIw,NDSI,SRDI, NMDI and MVWR) were extracted from ten MODIS images. Ability of the indicators to identify critical point in time-series was investigated by five spatial statistic methods (Moran’s-I, Getis-Ord-Gi, Geary’s-C, variance, and skewness). The results showed that Moran’s-I is more successful in predicting the ecosystem tipping point(s) in comparison with other methods. In addition, the ability to predict ecosystem trends by the autocorrelation of MVWR is higher than other indicators. According to results, the tipping points of LUB occurred in the years of 2008 to 2010 and 2015. For further studies, it is recommended to use radar indicators for identifying tipping points of the similar vulnerable ecosystems.

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ABSTRACT
1. Introduction
2. Material and Methods
3. Results and Discussion
4. Conclusions
References

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