Strategy for assessment of disaster risk using typhoon hazards modeling based on chlorophyll-a content of seawater
Tóm tắt
With deterioration of the global climate situation, the frequency and uncertainty of typhoons are the major causes of their hazards in tropical coastal regions, both in terms of loss of life and economic damage. Heavy rainfall triggers massive landslides and devastating flash floods, which can entail tremendous damage. In typhoon-affected areas, the key issue is to estimate the disaster zone and to help ships avoid disaster areas in the sea. Existing studies on typhoon disasters are mainly based on the overall wind assessment or the route prediction of the typhoon, with less attention to the detailed impact in different regions along the route. We propose in this paper a new framework to assess regional disaster risk based on chlorophyll-a concentration inversion in seawater. To calculate the concentration of chlorophyll-a, we analyze Landsat-8 satellite images in typhoon weather and normal weather in the same area. The experiments on realistic samples show that our approach has major potential to improve safety via assessing the impact of a typhoon in different regions based on the level of chlorophyll-a concentration.
Tài liệu tham khảo
Y. Xiao-xia, T. Dan-ling, Location of sea surface temperature cooling induced by typhoon in South China Sea. J. Trop. Oceanogr. 29(4), 26–31 (2010)
Y.L.L. Chen, Spatial and seasonal variations of nitrate. Deep-Sea Res. I Oceanogr. Res. Pap. 52(2), 319–340 (2005)
L. Zhou, Y. Tan, L. Huang, et al., Phytoplankton growth and microzooplankton grazing in the continental shelf area of northeastern South China Sea after typhoon Fengshen. Cont. Shelf Res. 31(16), 1663–1671 (2011)
X. Lu, K. Ota, M. Dong, C. Yu, H. Jin, Predicting transportation carbon emission with urban big data. T-SUSC 2(4), 333–344 (2017)
X. Wang, X. Xing, et al., A satellite-based analysis on the seasonal variations and inter-relationships between chlorophyll and particle in the South China Sea. Acta Oceanol. Sin. 37(10), 26–38 (2016)
L.R. Lin, H. Zhao, Analysis on the relations between sea surface temperature and phytoplankton chlorophyll-a in the South China Sea. J. Mar. Sci. 4(30), 46–54 (2012)
D.J. Doong, L.Z.H. Chuang, C.C. Kao, Y.B. Lin, K.C. Jao, Statistics ofbuoy-observed waves during typhoons at Taiwanese waters from 1997 to 2008. In OCEANS 2009, MTS/IEEE Biloxi-Marine Technology for Our Future: Global and Local Challenges (pp. 1-7). IEEE. (2009)
J. He, S. Zhang, Introduction of MWHTS onboard FY-3C Satellite and Typhoon Detecting. Remote Sens. Sci. 2, 17–24 (2015)
C. Bangqian, X. Li, X. Xiao, B. Zhao, J. Dong, K. Kou, Y. Qin, "Mapping tropical forests and deciduous rubber plantations in Hainan Island, China by integrating PALSAR 25-m and multi-temporal Landsat images." International journal of applied earth observation and geoinformation 50, 117-130 (2016).
X. Liu, M. Wang, W. Shi, A study of a hurricane Katrina-induced phytoplankton bloom using satellite observations and model simulations. J. Geophys. Res. Oceans 114(C3), 819–834 (2009)
I.-I. Lin, Typhoon-induced phytoplankton blooms and primary productivity increase in the western North Pacific subtropical ocean. J. Geophys. Res. Oceans 117(117), 3039 (2012)
D.I. Wu, H. Mengxing, U.A. Bhatti, Z. Li, H. Zhang. "Typhoon early warning modeling for regional disaster evaluation." In Enterprise Systems (ES), 2017 5th International Conferenceon, pp. 26-29. IEEE, 2017.
Y. Pan, D. Tang, D. Weng, Evaluation of the SeaWiFS and MODIS chlorophyll a algorithms used for the Northern South China Sea during the summer season. Terr. Atmos. Ocean. Sci. 21(6), 997–1005 (2010)
Z.B.C.Y.S. Guangwu, Statistical Analysis of Tropical Cyclones Affecting East China Sea in Recent 45 Years [J]. Meteorological Science and Technology, 5, p.010 (2009).
Z. Yujun, Landsat8 abstract. Remote Sens. Land. Resour. 25(1), 176–177 (2013)
T. Davergne, Offshore and nearshore chlorophyll increases induced by typhoon winds and subsequent terrestrial rainwater runoff. Mar. Ecol. Prog. 333(1), 61–74 (2007)
L. Zhao, S. Shuqun, L. Caiwen, Distribution of chlorophyll-a and its correlation with the formation of hypoxia in the Changjiang River Estuary and its adjacent waters. Mar. Sci. 40(2), 1–10 (2016)
T.Y. Ho, X. Pan, H.H. Yang, et al., Controls on temporal and spatial variations of phytoplankton pigment distribution in the Northern South China Sea. Deep-Sea Res. II Top. Stud. Oceanogr. 117(6), 65–85 (2015)
D.Z. Zhao, F.S. Zhang, D.U. Fei, et al., Interpretation of sun-induced fluorescence peak of chlorophyll a on reflectance spectrum of algal waters. J. Remote. Sens. 9(3), 265–270 (2005)
G. Nofuentes, B. García-Domingo, J.V. Muñoz, et al., Analysis of the dependence of the spectral factor of some PV technologies on the solar spectrum distribution. Appl. Energy 113(2), 302–309 (2014)
B. Yang, J. Chen, L. Chen, et al., Estimation model of wheat canopy nitrogen content based on sensitive bands. Trans. Chin. Soc. Agric. Eng. 31(22), 176–182 (2015)
C. Qiong, M. Huang, H. Wang, Y. Zhang, W. Feng, X. Wang, D.I. WU, U.A. Bhatti, "A Feature Preprocessing Framework of Remote Sensing Image for Marine Targets Recognition." In 2018 OCEANS-MTS/IEEE Kobe Techno-Oceans (OTO), pp. 1-5. IEEE, (2018).
C. Hong, R.X. Bin, Distributions of three size fractions of chlorophyll-a and its controlling factors in summer in the southern South China Sea. J. Hydroecol. 33(4), 63–72 (2012)
H.-N. Dai, R.C.-W. Wong, H. Wang, On capacity and delay of multi-channel wireless networks with infrastructure support. IEEE Trans. Veh. Technol. 66(2), 1589–1604 (2017)
Y. Wu, G. Min, L.T. Yang, Performance analysis of hybrid wireless networks under Bursty and correlated traffic. IEEE Trans. Veh. Technol. 62(1), 449–454 (2013)