Huicong Jia

Maize drought disaster risk assessment of China based on EPIC model

Abstract Digital Agriculture is one of the important applications of Digital Earth. As the global climate changes and food security becomes an increasingly important issue, agriculture drought comes to the focus of attention. China is a typical monsoon climate country as well as an agricultural country with the worlds largest population. The East Asian monsoon has had a tremendous impact upon agricultural production. Therefore, a maize drought disaster risk assessment, in line with the requirements of sustainable development of agriculture, is important for ensuring drought disaster reduction and food security. Meteorology, soil, land use, and agro-meteorological observation information of the research area were collected, and based on the concept framework of ‘hazard-inducing factors assessment (hazard)-vulnerability assessment of hazard-affected body (vulnerability curve)-risk assessment (risk),’ importing crop model EPIC (Erosion-Productivity Impact Calculator), using crop model simulation and digital mapping techniques, quantitative assessment of spatio-temporal distribution of maize drought in China was done. The results showed that: in terms of 2, 5, 10, and 20 year return periods, the overall maize drought risk decreased gradually from northwest to southeast in the maize planting areas. With the 20 year return period, high risk value regions (drought loss rate ≥0.5) concentrate in the irrigated maize region of Northwest china, ecotone between agriculture and animal husbandry in Northern China, Hetao Irrigation Area, and north-central area of North China Plain, accounting for 6.41% of the total maize area. These results can provide a scientific basis for the governments decision-making in risk management and drought disaster prevention in China.

Risk mapping of integrated natural disasters in China

We explored the regional shifts in hazards at the county level in China for three different time periods (1956–1965, 1976–1985, and 1996–2005). The frequency of natural disasters was used as the assessment index. Based on the probability of natural disasters in each county, the spatial change in risk with increasing intensity of natural disasters was studied. The results show that the frequency of natural disasters is increasing and the area affected by natural disasters extends across the whole country. The patterns of risk distribution in the periods 1956–1965, 1976–1985, and 1996–2005 are defined as Eastern-intensive, National-dispersed, and National-intensive, respectively. The high-risk areas are located in the north of the Tianshan Mountains in Xinjiang Province, the Silim Gol Plateau and the Hulun Buir Plateau in Inner Mongolia Autonomous Region, the eastern coastal provinces (Jiangsu, Zhejiang, Fujian, and Guangdong Provinces), and most parts of the Yunnan–Guizhou Plateau. This research offers a scientific basis for the regionalization of disaster risk and a disaster reduction policy for highly vulnerable regions.

Using a BP Neural Network for Rapid Assessment of Populations with Difficulties Accessing Drinking Water Because of Drought

ABSTRACT Accurately predicting the populations with difficulties accessing drinking water because of drought and taking appropriate mitigation measures can minimize economic loss and personal injury. Taking the 2013 Guizhou extreme summer drought as an example, on the basis of collecting meteorological, basic geographic information, socioeconomic data, and disaster effect data of the study area, a rapid assessment model based on a backpropagation (BP) neural network was constructed. Six factors were chosen for the input of the network: the average monthly precipitation, Digital Elevation Model (DEM), river density, population density, road density, and gross domestic product (GDP). The population affected by drought was the models output. Using samples from 50 drought-affected counties in Guizhou Province for network training, the models parameters were optimized. Using the trained model, the populations in need were predicted using the other 74 drought-affected counties. The accuracy of the prediction model, represented by the coefficient of determination (R2) and the normalized root mean square error (N-RMSE), yielded 0.7736 for R2 and 0.0070 for N-RMSE. The method may provide an effective reference for rapid assessment of the population in need and disaster effect verification.

The retrieval of shrub fractional cover based on a geometric-optical model in combination with linear spectral mixture analysis

Vegetation fractional cover, which defines the amount of vegetation on the surface of the land, is a key parameter in land surface models. Based on a geometric-optical model in combination with a linear spectral mixture analysis, the retrieval of shrub fractional cover in Wushen Banner of Inner Mongolia in the Mu Us Sandland using HJ-1B multispectral images is discussed. We acquired the surface reflectance based on geometric correction and atmospheric correction of the HJ-1B image. Then we assumed that the reflectance of a mixed pixel is a simple linear combination of two components, namely illuminated background and illuminated canopy, and further calculated the areal proportion of the illuminated background within each pixel based on the linear spectral mixture analysis. Then, combined with the measured shrub structural parameters, the shrub fractional cover was estimated using an inverted geometric-optical model. Finally, the result was validated through the measured shrub cover of 13 sample plots and a comparison study was done with the NDVI regression method and simple linear spectral mixture analysis. The R 2 of the three methods are 0.898, 0.614, and 0.659, with corresponding root-mean-squared errors of 0.136, 0.154, and 0.175, which indicate the reliability of the combined method.

Application of CCD data of HJ-1 satellite in PM 10 evaluation in Shenzhen, China

The main missions of HJ-1 satellite are to monitor pollution, ecosystem destruction and natural disasters. In recent years, Inhalable particle (PM10) has become the primary pollutant of major cities in China, which seriously affects the living environment of its residents. In this paper, we made use of high-resolution CCD data of HJ-1 satellite to monitor atmospheric inhalable particle (PM10) in Shenzhen. Firstly, we inversed the aerosol optical depth (AOD) of CCD data of HJ-1 satellite. Then we analyzed the correlation between AOD and PM10 using PM10 data in six districts of Shenzhen and the AOD data. The conclusions are as follows. 1) The AOD and PM10 are significantly related in spring-summer. 2) The correlation between AOD and PM10 has been improved greatly after considering the variation of aerosol scale height.

Health assessment of the water-level-fluctuation zone (WLFZ) in the Three Gorges area based on spatial information technology

The WLFZ in the Three Gorges area is alternately controlled and influenced by both water ecosystem and terrestrial ecosystem. Its ecological vulnerability and instability are significant. Taking small watershed as a unit of assessment, we select population density, urbanization intensity, temperature, precipitation, and humidity and vegetation coverage to construct the fluctuating zone wetland ecosystem assessment index system. The comprehensive health index is calculated after extracting the main information of the six variables using principal component analysis. It is ranged into three levels: good, medium and poor. The results show that the health state of the entire Three Gorges area is at medium and poor levels. Regions at medium health state account for 58% of the entire area, and the remaining regions are at poor health. Taking Wanzhou District as the boundary, the health state of the southwest region is better than the northeast region.

The analysis on the accuracy of DEM retrieval by the ground lidar point cloud data extraction methods in mountain forest areas

LiDAR data contains the elevation and brightness information of land surface, vegetation cover and construction. Ground filtering and interpolation method are the key for extracting the DEM accuracy based on the point clouds. This paper takes Zhangye City, Gansu Province in western mountainous areas as the study area, based on the point clouds of 0.7 points/m2, uses 5 m * 5 m grid screening method and the lowest Thiessen polygon point screening method to extract the ground point. Ordinary kriging interpolation method was used to retrieve Digital Elevation Model (DEM). Referring to the elevations of 1466 sample points, we analysed the accuracy for extracting DEM by the two selected methods of extracting ground point. The results showed that the DEM extracting accuracy by the near lowest point screening method is better than the grid screening method.

Tornado disaster impacts and management: learning from the 2016 tornado catastrophe in Jiangsu Province, China

As a key component of disaster reduction management, disaster emergency relief and reconstruction is an important process. Based on disaster system theory, this study analyzed the Jiangsu tornado from the formation mechanism of disasters, through to the economic losses, loss of life, and social infrastructure losses along the tornado disaster chain. The study then assessed the emergency relief and reconstruction efforts, based on an analytic hierarchy process method. The results were as follows: (1) An unstable weather system was the root cause of the tornado. The potentially hazardous local environment, acting in concert with the terrain and the river network, was able to gather energy from the unstable atmosphere. The wind belt passed through a densely populated district, with vulnerable infrastructure and other hazard-prone elements, which led to an accumulative disaster situation and the triggering of a catastrophe. (2) The tornado was accompanied by a hailstorm, which is an important triggering factor for a tornado catastrophe chain reaction. (3) The evaluation index (EI) of the emergency relief and reconstruction effect for the “6.23” tornado disaster in Yancheng was 91.5. Compared to other relief work in areas affected by disasters of the same magnitude, there was a more successful response than has previously been experienced. The results provide new insights for studies of disaster systems and the recovery measures in response to tornado catastrophe in China.

Droughts in China

China is a country frequently hit by droughts and enormous losses, particularly in agriculture, were claimed in the past years. This chapter discusses drought in China. It first explores the spatial and temporal patterns and dynamic change of historical droughts based on statistical data. Causal factors and mechanisms of agricultural drought, which substantially differ from region to region, are carefully examined through regional cases studies. Agricultural drought risks of China, including those for paddy rice, maize, and wheat, are mapped based on a quantitative assessment of physical vulnerability function of crops to drought stresses. Last but not the least, the Chinese strategies for drought disaster response is discussed via three major drought disaster cases.

Research on urban heat island effect during Beijing urbanization process by remote sensing and its impact on environmental health

The urban heat island (UHI) effect is becoming an influential factor on the citys environment along with the rapid development of urbanization process. This paper uses Landsat-5 TM RS image of the year 1988, 2007 and 2010 based on NDVITEM model and land temperature retrieval method to obtain Beijing land surface temperature distribution map through digital image processing and land surface temperature (LST) retrieval calculating using thermal infrared (TIR) remotely sensed satellite observation. The analysis showcases that urban heat island effect in Beijing has been dramatically intensified since 1988. Especially in recent years, the urban heat island effect has become increasingly apparent and seriously affected humans health in the way of changing temperature, barometric pressure, humidity, wind as well as air.