Spatiotemporal characteristics of droughts and floods in northeastern China and their impacts on agriculture

Fu, Qiang; Zhou, Zhaoqiang; Li, Tianxiao; Liu, Dong; Hou, Renjie; Cui, Song; Yan, Peiru

doi:10.1007/s00477-018-1543-z

Cited by 59 publications

(26 citation statements)

References 43 publications

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“…In addition, the model based on the GEE platform can be used for large-scale spatiotemporal pattern analysis and real-time monitoring. The results are basically consistent with the spatial and temporal distributions of drought and flood events based on the monthly precipitation data of meteorological stations using the standardized precipitation index (SPI), principal component analysis, Mann Kendall trend analysis, and Morlet wavelet analysis [57]. This method can be used to improve CropWatch because of the improvement of the uncertainty caused by the annual changes of crop rotation and phenology [64].…”

Section: Discussionsupporting

confidence: 72%

“…The average annual temperature in the province generally ranges from −5 to 5 • C, and its annual precipitation varies from 400 to 650 mm, with uneven spatial and temporal distributions. Agricultural disasters are frequent, and the frequencies of the representative disasters of droughts, floods, windstorms, hailstorms, low temperatures, and freezing, as well as disease and insect disasters, are increasing [57,58].…”

Section: Study Areamentioning

confidence: 99%

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Rapid Extraction of Regional-scale Agricultural Disasters by the Standardized Monitoring Model Based on Google Earth Engine

Liu

Luo

et al. 2020

Sustainability

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Remote sensing has been used as an important tool for disaster monitoring and disaster scope extraction, especially for the analysis of spatial and temporal disaster patterns of large-scale and long-duration series. Google Earth Engine provides the possibility of quickly extracting the disaster range over a large area. Based on the Google Earth Engine cloud platform, this study used MODIS vegetation index products with 250-m spatial resolution synthesized over 16 days from the period 2005–2019 to develop a rapid and effective method for monitoring disasters across a wide spatiotemporal range. Three types of disaster monitoring and scope extraction models are proposed: the normalized difference vegetation index (NDVI) median time standardization model (RNDVI_TM(i)), the NDVI median phenology standardization model (RNDVI_AM(i)(j)), and the NDVI median spatiotemporal standardization model (RNDVI_ZM(i)(j)). The optimal disaster extraction threshold for each model in different time phases was determined using Otsu’s method, and the extraction results were verified by medium-resolution images and ground-measured data of the same or quasi-same period. Finally, the disaster scope of cultivated land in Heilongjiang Province from 2010–2019 was extracted, and the spatial and temporal patterns of the disasters were analyzed based on meteorological data. This analysis revealed that the three aforementioned models exhibited high disaster monitoring and range extraction capabilities, with verification accuracies of 97.46%, 96.90%, and 96.67% for RNDVI_TM(i), RNDVI_AM(i), and (j)RNDVI_ZM(i)(j), respectively. The spatial and temporal disaster distributions were found to be consistent with the disasters of the insured plots and the meteorological data across the entire province. Moreover, different monitoring and extraction methods were used for different disasters, among which wind hazard and insect disasters often required a delay of 16 days prior to observation. Each model also displayed various sensitivities and was applicable to different disasters. Compared with other techniques, the proposed method is fast and easy to implement. This new approach can be applied to numerous types of disaster monitoring as well as large-scale agricultural disaster monitoring and can easily be applied to other research areas. This study presents a novel method for large-scale agricultural disaster monitoring.

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Section: Discussionsupporting

confidence: 72%

Section: Study Areamentioning

confidence: 99%

Rapid Extraction of Regional-scale Agricultural Disasters by the Standardized Monitoring Model Based on Google Earth Engine

Liu

Luo

et al. 2020

Sustainability

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“…Floods have been identified as a serious global threat and have the potential to affect lives and livelihoods, change ecosystem properties, cause serious damage to agricultural and other water resource systems, spread epidemics, and have an everlasting emotional and physical effect on their human victims [1,2,3,4]. Over the last two decades, floods have accounted for 47% of all weather-related disasters, impacting over 2.1 billion people, causing major environmental disruption, and resulting in over 1 trillion USD of economic losses globally [5].…”

Section: Introductionmentioning

confidence: 99%

Understanding the Operational Concept of a Flood-Resilient Urban Community in Jakarta, Indonesia, from the Perspectives of Disaster Risk Reduction, Climate Change Adaptation and Development Agencies

Dwirahmadi

Rutherford

Phung

et al. 2019

IJERPH

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Climate change-related extreme events such as floods have and will continue to present a great challenge to disaster risk management. There is a pressing need to develop a robust management strategy via enhancing the resiliency of the community, particularly in the context of complex urban environments, like Jakarta. Resilience is conceptualized within specific contexts and uniquely tailored to the targeted setting, yet research regarding the operational concept of a flood-resilient community in the context of Jakarta remains limited. This paper will elaborate this operational concept through understanding the desirable features and influential barriers of a flood-resilient community through the lenses of three main stakeholder groups: disaster risk reduction (DRR), climate change adaptation (CCA), and development. It will also discuss the ways in which the synergies that exist across these groups can be enhanced. Both quantitative and qualitative approaches were applied in this study, and multiple sources of data were used. The findings indicate that these groups share common views regarding the importance of human aspects being central to resilience building efforts. We argue there is an urgent need to shift the flood resilience building paradigm towards building community resilience from the people and to apply a collaborative governance approach to facilitate effective partnership between the actors involved.

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“…Previous studies have focused on a single drought characteristic or the relationship between several types of drought (Fu et al, 2018;J. F. Wu, Liu, et al, 2018).…”

mentioning

confidence: 99%

Characteristics of Propagation From Meteorological Drought to Hydrological Drought in the Pearl River Basin

Zhou

Shi

et al. 2021

JGR Atmospheres

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Spatiotemporal characteristics of droughts and floods in northeastern China and their impacts on agriculture

Cited by 59 publications

References 43 publications

Rapid Extraction of Regional-scale Agricultural Disasters by the Standardized Monitoring Model Based on Google Earth Engine

Rapid Extraction of Regional-scale Agricultural Disasters by the Standardized Monitoring Model Based on Google Earth Engine

Understanding the Operational Concept of a Flood-Resilient Urban Community in Jakarta, Indonesia, from the Perspectives of Disaster Risk Reduction, Climate Change Adaptation and Development Agencies

Characteristics of Propagation From Meteorological Drought to Hydrological Drought in the Pearl River Basin

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