scholarly journals Flooding hazard mapping for Poyang Lake Region with remote sensing and water level records

2009 ◽  
Vol 21 (5) ◽  
pp. 720-724 ◽  
Author(s):  
QI Shuhua ◽  
◽  
SHU Xiaobo ◽  
Daniel Brown ◽  
JIANG Luguang
Keyword(s):  
Remote Sensing ◽  
Water Level ◽  
Poyang Lake ◽  
Hazard Mapping ◽  
Flooding Hazard ◽  
Poyang Lake Region ◽  
Lake Region

scholarly journals Potential Impact of Flood on Schistosomiasis in Poyang Lake Regions Based on Multi-Source Remote Sensing Images

2020 ◽  
Author(s):  
Jing-Bo Xue ◽  
Xin-Yi Wang ◽  
Li-Juan Zhang ◽  
Yu-Wan Hao ◽  
Zhe Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Body ◽  
Poyang Lake ◽  
Transmission Risk ◽  
Schistosomiasis Japonica ◽  
Landsat 8 ◽  
Remote Sensing Images ◽  
Poyang Lake Region ◽  
Lake Region ◽  
Dual Polarized

Abstract BackgroundFlooding may be the most important factors contributing to the rebound of Oncomelania hupensis in endemic foci. This study aimed to assess the risk of schistosomiasis japonica transmission impacted by flooding around the Poyang Lake region using multi-source remote sensing images.MethodsNormalized Difference Vegetation Index (NDVI) data collected by the Landsat 8 satellite was used as an ecological and geographical suitability indicator of O. hupensis snail habitats in the Poyang Lake region. The flood-affected water body expansion was estimated using dual polarized threshold calculations based on the dual polarized synthetic aperture radar (SAR). The image data were captured from Sentinel-1B satellite in May 2020 before the flood and in July 2020 during the flood. The spatial database of snail habitats distribution was created by using the 2016 snail survey in Jiangxi Province. The potential spread of O. hupensis snails after the flood was predicted by an overlay analysis of the NDVI maps of flood-affected water body areas. In addition, the risk of schistosomiasis transmission was classified based on O. hupensis snail density data and the related NDVI. ResultsThe surface area of Poyang Lake was approximately 2,207 km2 in May 2020 before the flood and 4,403 km2 in July 2020 during the period of the flood peak, and the flood-caused expansion of water body was estimated as 99.5%. After the flood, the potential snail habitats were predicted to be concentrated in areas neighboring the existing habitats in marshlands of the Poyang Lake. The areas with high risk of schistosomiasis transmission were predicted to be mainly distributed in Yongxiu, Xinjian, Yugan and Poyang (District) along Poyang Lake. By comparing the predictive results and actual snail distribution, the predictive accuracy of the model was estimated as 87%, which meant the 87% of actual snail distribution were correctly identified as the snail habitats in the model predictions. ConclusionsFlood-affected water body expansion and environmental factors pertaining to snail breeding may be rapidly extracted from Landsat 8 and Sentinel-1B remote sensing images. The applications of multi-source remote sensing data are feasible for the timely and effective assessment of the potential schistosomiasis transmission risk caused by snail spread during the flood disaster, which is of great significance for precision control of schistosomiasis.

scholarly journals Full Lifecycle Monitoring on Drought-Converted Catastrophic Flood Using Sentinel-1 SAR: A Case Study of Poyang Lake Region during Summer 2020

2021 ◽  
Vol 13 (17) ◽  
pp. 3485
Author(s):  
Haoxiao Yang ◽  
Hongxian Wang ◽  
Jianzhong Lu ◽  
Zhenzhong Zhou ◽  
Qi Feng ◽  
...  
Keyword(s):  
Water Level ◽  
Poyang Lake ◽  
Water Volume ◽  
Lake Area ◽  
Sar Images ◽  
Catastrophic Flood ◽  
Poyang Lake Region ◽  
Lake Region ◽  
Study Results ◽  
Land Types

During summer 2020, the most catastrophic flood in the 21st century attacked the Poyang Lake region, one of the flood-prone areas in China. To explore the occurrence mechanism and evolution patterns of this drought-converted flood better, a full lifecycle model is developed in this article. Employing Sentinel-1 Synthetic Aperture Radar (SAR) images, with the advantages of high spatial–temporal resolution and all-day and all-weather working capacity, a bimodal threshold was applied to efficiently extract flood inundation mapping. Thus, 61 Sentinel-1 SAR images in 2020 were used to establish inundation sequences for full lifecycle monitoring. This flood presented an abrupt transformation from drought, a long duration, and the slow receding of water, and its area exceeded 3000 km2 from July to early October. In addition, inundation models that reflect the lake area and water level relationship were introduced to assist near-real-time monitoring. Through hydrological and meteorological analysis, compared with results of previous years (from 2010 to 2019), this study found that the water level from July to October in 2020 was at least 17% higher than the mean level at the same period in history and water volume had increased about 44.13 billion m3 during the flooding period. Similarly, the average precipitation from June to September was significantly higher than the same period of previous years. It was the abnormal sustained heavy precipitation and sharp rising of the water level that caused this catastrophic flood. In particular, the Standardized Precipitation Index (SPI) increased from −1.02 in April to 1.31 in July, indicating that the flood was abruptly converted from drought. The inundated areas of several land types during different periods of the full lifecycle were calculated for damage assessment. It was found that cropland was the most heavily impaired with a maximum inundated area of 1375.67 km2, while other land types including forest, grassland, wetland, and impervious surface were relatively less damaged. The study results demonstrate that flood full lifecycle monitoring based on SAR data is helpful to explore the patterns of flood evolution, analyze causes, and assess damage. Simultaneously, focusing on drought-converted floods contributes to the understanding of flood patterns, which provides relevant management departments with decision support for disaster prevention and mitigation.

scholarly journals Assessing habitat suitability and habitat fragmentation for endangered Siberian cranes in Poyang Lake region, China

2021 ◽  
Vol 125 ◽  
pp. 107594
Author(s):  
Zhengtao Zhu ◽  
Wenxin Huai ◽  
Zhonghua Yang ◽  
Da Li ◽  
Yisen Wang
Keyword(s):  
Habitat Fragmentation ◽  
Habitat Suitability ◽  
Poyang Lake ◽  
Poyang Lake Region ◽  
Lake Region

Eco-Efficiency Evaluation of Poyang Lake Region Based on DEA Method

2011 ◽  
Vol 181-182 ◽  
pp. 118-123
Author(s):  
Hai Tao Su ◽  
Hai Qing Guo ◽  
Jin Feng Hu ◽  
Hui Zeng
Keyword(s):  
Technical Efficiency ◽  
Poyang Lake ◽  
Scale Efficiency ◽  
Maximum Output ◽  
Efficiency Evaluation ◽  
Economic Region ◽  
Poyang Lake Region ◽  
Lake Region ◽  
Decision Making Unit ◽  
Dea Method

The eco-efficiency and sustainable development have become the focus of world and the issues to be resolved urgently. In this paper, the recent research status of eco-economic region of Poyang Lake in China is analyzed, and the multi-level evaluation index system of eco-efficiency of Poyang Lake is constructed. The minimum input and maximum output method based on DEA(Data Envelopment Analysis) is proposed, the mathematical model of validity evaluation of eco-economic region of Poyang Lake is set up and programmed by MATLAB. Efficiency evaluation of a complex system with the cases from nine districts of Poyang Lake region in China is realized, which is more than one homogeneous decision-making unit of multi-input and multi-output. The MDEA (Modified DEA) method resolves the problems of ranking DEA efficient units of Poyang Lake, The DEAP2.1 software differentiates the technical efficiency and scale efficiency of eco-economic region of Poyang Lake, and adjusts the DEA inefficient units to become technical efficiency. The model can be used to analyze efficiency and diagnose different units at the same time or same unit at different time. It can be more accurate and convenient for the management process of eco-economic region of Poyang Lake and the similar eco-economic region.

Identification of a novel reassortant A (H9N6) virus in live poultry markets in Poyang Lake region, China

2017 ◽  
Vol 162 (12) ◽  
pp. 3681-3690 ◽  
Author(s):  
Heng Zhang ◽  
Mingbin Liu ◽  
Xiaoxu Zeng ◽  
Xiang Zhao ◽  
Zhiqiang Deng ◽  
...  
Keyword(s):  
Poyang Lake ◽  
Poyang Lake Region ◽  
Lake Region ◽  
Live Poultry ◽  
Live Poultry Markets

scholarly journals Familial aggregation of human infection with Schistosoma japonicum in the Poyang Lake region, China

2006 ◽  
Vol 36 (1) ◽  
pp. 71-77 ◽  
Author(s):  
Magda K. Ellis ◽  
Yuesheng Li ◽  
Zhu Rong ◽  
Honggen Chen ◽  
Donald P. McManus
Keyword(s):  
Schistosoma Japonicum ◽  
Poyang Lake ◽  
Familial Aggregation ◽  
Human Infection ◽  
Poyang Lake Region ◽  
Lake Region
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