Haixia He

Integrating Global Open Geo-Information for Major Disaster Assessment: A Case Study of the Myanmar Flood

Major disasters typically impact large areas, cause considerable damages, and result in significant human and economic losses. The timely and accurate estimation of impacts and damages is essential to better understand disaster conditions and to support emergency response operations. Geo-information drawn from various sources at multi spatial-temporal scales can be used for disaster assessments through a synthesis of hazard, exposure, and post disaster information based on pertinent approaches. Along with the increased availability of open sourced data and cooperation initiatives, more global scale geo-information, including global land cover datasets, has been produced and can be integrated with other information for disaster dynamic damage assessment (e.g., impact estimation immediately after a disaster occurs, physical damage assessment during the emergency response stage, and comprehensive assessment following an emergency response). Residential areas and arable lands affected by the flood disaster occurring from July to August 2015 in Myanmar were assessed based on satellite images, GlobeLand30 data, and other global open sourced information as a study case. The results show that integrating global open geo-information could serve as a practical and efficient means of assessing damage resulting from major disasters worldwide, especially at the early emergency response stage.

Estimating the Numbers and the Areas of Collapsed Buildings by Combining VHR Images, Statistics and Survey Data: a Case Study of the Lushan Earthquake in China

Accurately obtaining the structures and damage types of buildings in earthquake stricken areas is fundamental to supporting rescue forces and estimating economic losses and casualties. As the stricken areas are often much larger than the areas covered by very high resolution (VHR) images, the information obtained from VHR images cannot satisfy practical needs. This study developed a method for estimating the structures and types of damaged buildings by combining VHR images, statistics and ground survey data. First, the rates of damaged buildings with different structures and damage types were manually interpreted from VHR images covering a small part of the stricken area, and further corrected by ground survey data. Second, the corrected rates were reallocated to the seismic intensity zones. Third, the rates in the seismic intensity zones and the statistical data were combined to estimate the numbers and areas of damaged buildings in villages, towns and counties. The presented method was applied to estimate the damages caused by the Lushan earthquake in China. The results indicated that our method can efficiently estimate the amount of the damages and complement existing work on only automatic extracting damaged buildings from VHR images.

Application of HJ-1A/B and ZY-3 remote sensing data for drought monitoring in Hubei Province China

Drought is one kind of nature disasters in the world. It has characteristics of temporal-spatial inhomogeneity, wide affected areas and periodic happening. The economic loss and affected population caused by different droughts are the largest in all natural disasters. Remote sensing has the advantages of large coverage, frequent observation, repeatable observation, reliable information source and low cost. These advantages make remote sensing a vital contributor for drought disaster risk assessment and monitoring. In this paper, three drought monitoring models, such as Vegetation Condition Index (VCI), Temperature Vegetation Dryness Index (TVDI), and Water Supplying Vegetation Index (WSVI) had been selected to monitor the drought occurred from January 2012 to June 2012 in Hubei province, China. Two kinds of remote sensing data, including HJ-1A/B CCD/IRS and ZY-3, had been employed to assess the integrated risk of Hubei drought based on three drought monitoring models. The results shown that the risk of northwest regions and middle regions in Hubei province were higher than that in the other regions. The results also indicated that the extreme risk regions were located in Shiyan, Xiangyang, Suizhou and Jingmen.

Drought monitoring in Hubei province based on HJ-1 CCD data and real-time precipitation

Droughts caused great economic and social losses in the world. The purpose of drought monitoring is to analyze the origin, evolution and hazard of drought and determine possible drought losses using qualitative and quantitative method. Real-time precipitation data and HJ-1 CCD data offer a good way to evaluate the severity, duration, and extent of drought because drought is caused by lack of precipitation in more general terms. The proposed technology provides the following functionalities: (i) accumulation of real-time precipitation for a long time (ii) assessment of water supply by reservoirs (iii) determination drought intensity. The methodology is applied to monitoring drought losses in Hubei province as an example.

Capacity analysis of GF—4 on the disaster management

Satellite remote sensing can provide repeat and detail observations, which has played an important role on the disaster management. Different with the existing satellites, GF-4, which works on the geosynchronous orbit and carry on a camera with 50 meter spatial resolution in visible and NIR bands, can give a continuous earth observation. It is the highest spatial resolution among the civil satellite on the geosynchronous orbit, and have 4 operation mode: general, continuous, regional and maneuvering, which is very suitable for disaster management. In this paper, based on those characteristics of GF-4, the capacity for disaster management in disaster risk analysis, emergency response, disaster loss and recovery assessment was analyzed. It would be very useful for the rapid emergency monitoring on drought, flood, snow disaster and forest fires and can be important complement data source for the risk analysis, loss and recovery assessment.

Joint use of soil moisture and vegetation growth condition by remote sensing on the agricultural drought monitoring

Remote sensing is one of important methods on the agricultural drought monitoring for its long-term and wide-area observations. The detection of soil moisture and vegetation growth condition are two widely used remote sensing methods on that. However, because of the time lag in the impact of water deficit on the crop growth, it is difficulty to indicate the severity of drought by once monitoring. It also cannot distinguish other negative impact on crop growth such as low temperature or solar radiation. In this paper, the joint use of soil moisture and vegetation growth condition detections was applied on the drought management during the summer of 2013 in Liaoning province, China, in which 84 counties were affected by agricultural drought. MODIS vegetation indices and land surface temperature (LST) were used to extract the drought index. Vegetation Condition Index (VCI), which only contain the change in vegetation index, and Vegetation Supply Water Index (VSWI), which combined the information of vegetation index and land surface temperature, were selected to compare the monitoring ability on drought during the drought period in Liaoning, China in 2014. It was found that VCI could be a good method on the loss assessment. VSWI has the information on the change in LST, which can indicate the spatial pattern of drought and can also be used as the early warning method in the study.

High Resolution Remote Sensing Images Based Catastrophe Assessment Method

In recent years, there seems to be more and more occurrences of natural disasters happening around the world due to abnormal climate change. To deal with natural disasters, disaster assessment technology will provide technical support and help facilitate decision making for disaster relief, disaster prevention and reduction, post-disaster recovery and reconstruction (The six editing room of Press of China Standards, 2010). Airborne remote sensing and satellite remote sensing, which feature no time limitation, no geographical restriction, wide coverage and high accuracy, are widely used in disaster assessment scenario, because they can provide prompt and accurate information (Xie & Zhang, 2000). After several earthquakes happened around China (Xingtai, Haicheng, Tangshan, Longling, Datong) during 1970s and 1980s, China had widely implemented airborne remote sensing photography and seismic damage interpretation (Zhang, 1993). Remote sensing had also played an important role in disaster assessment of recent occurring disasters, including Wenchuan Earthquake, Yushu Earthquake, Zhouqu Debris flow and Yingjiang Earthquake (Chen et al., 2008; Shi et al., 2010). This chapter will mainly discuss the catastrophe assessment method and technical flow used by National Disaster Reduction Center of China (NDRCC) during Wenchuan Earthquake(2008), Yushu Earthquake(2010), Zhouqu Debris Flow(2010). Further discussion and advises are also given.

Processing of HJ-1A hyperspectral data

In the paper, the parameters of hyperspectral data of the environment disaster reduction satellites have been introduced, firstly. Then the pro-processing methods for hyperspectral data have been elaborated according to the characteristics of the hyperspectral sensor of the environment disaster reduction satellites. After analysis the problems existing in the pre-processing of hyperspectral data, the hyperspectral data have been employed to classify the land features. The experimental evaluation shows that the performance of classifying the hyperspectral data of environment disaster reduction satellites is excellent.