Xinliang Xu

Changes in the Potential Multiple Cropping System in Response to Climate Change in China from 1960-2010

The multiple cropping practice is essential to agriculture because it has been shown to significantly increase the grain yield and promote agricultural economic development. In this study, potential multiple cropping systems in China are calculated based on meteorological observation data by using the Agricultural Ecology Zone (AEZ) model. Following this, the changes in the potential cropping systems in response to climate change between the 1960s and the 2010s were subsequently analyzed. The results indicate that the changes of potential multiple cropping systems show tremendous heterogeneity in respect to the spatial pattern in China. A key finding is that the magnitude of change of the potential cropping systems showed a pattern of increase both from northern China to southern China and from western China to eastern China. Furthermore, the area found to be suitable only for single cropping decreased, while the area suitable for triple cropping increased significantly from the 1960s to the 2000s. During the studied period, the potential multiple cropping index (PMCI) gap between rain-fed and irrigated scenarios increased from 18% to 24%, which indicated noticeable growth of water supply limitations under the rain-fed scenario. The most significant finding of this research was that from the 1960s to the 2000s climate change had led to a significant increase of PMCI by 13% under irrigated scenario and 7% under rain-fed scenario across the whole of China. Furthermore, the growth of the annual mean temperature is identified as the main reason underlying the increase of PMCI. It has also been noticed that across China the changes of potential multiple cropping systems under climate change were different from region to region.

A Simple Semi-Automatic Approach for Land Cover Classification from Multispectral Remote Sensing Imagery

Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience.

Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in China. The identification of the spatiotemporal pattern of HFRS will provide a foundation for the effective control of the disease. Based on the incidence of HFRS, as well as environmental factors, and social-economic factors of China from 2005–2012, this paper identified the spatiotemporal characteristics of HFRS distribution and the factors that impact this distribution. The results indicate that the spatial distribution of HFRS had a significant, positive spatial correlation. The spatiotemporal heterogeneity was affected by the temperature, precipitation, humidity, NDVI of January, NDVI of August for the previous year, land use, and elevation in 2005–2009. However, these factors did not explain the spatiotemporal heterogeneity of HFRS incidences in 2010–2012. Spatiotemporal heterogeneity of provincial HFRS incidences and its relation to environmental factors would provide valuable information for hygiene authorities to design and implement effective measures for the prevention and control of HFRS in China.

The influences of temperature on spatiotemporal trends of hand-foot-and-mouth disease in mainland China.

Understanding the influence of temperature on hand-foot-and-mouth disease (HFMD) is an important public health concern as well as being a major climate-infection issue in mainland China. City-scale data of incidence rates (IRs) of HFMD and temperature from 2008 to 2009 in mainland China has been analyzed. There were two peak periods for HFMD prevalence from April to July and August to November. Regions with higher monthly IR of HFMD periodically shifted following the pattern of south–north–south from March to December. Monthly IR of HFMD at city scale were closely associated with both average monthly temperature and monthly temperature range. Our study shows that spatiotemporal trends of HFMD infection were sensitive to temperature variation, and suggest that preventive measures should be considered for limiting the epidemic of HFMD in the cities with higher monthly IR during the peak periods.

The Impact of Urbanization on the Annual Average Temperature of the Past 60 Years in Beijing

Global warming, which is representatively caused by CO2-based greenhouse gases, has caused widespread concern in the global scientific community and gets the high attention of each government in the world. Human activities impact climate change through greenhouse gas emissions and land use changes. The current study on the impact of urbanization on the annual average temperature of the recent 60 years in Beijing was conducted using 1951–2012 temperature data. Anomaly analysis, quadratic polynomial trend method, and moving average method were employed to indicate the temporal variation of temperature. The results showed that average temperature increased both in urban and rural areas. The temperature of urban Beijing increased during the period from 1951 to 2012, especially from 1971 to 1994. The temperature of rural Beijing showed a faster increase than that of the urban area from 1989 to 1998. However, the rate of temperature increase slowed down in recent years. This type of change was temporally consistent with the process of land use change and urbanization in Beijing. Economic restructuring and improvement of urban planning may have been one of the reasons that the regional warming has been slowed down in the rural area.

Spatiotemporal variation of surface water quality for decades: a case study of Huai River System, China

Characterization of spatiotemporal variation of water quality is a basic environmental issue with implications for public health in China. Trends in the temporal and spatial distribution of water quality in the Huai River System (HRS) were analyzed using yearly surface water quality data collected from 1982 to 2009. Results showed that the water quality of the main stream deteriorated in the 1990s and early 2000s but has been ameliorated since 2005. The sections that were classified as severely polluted from the monitoring data were located largely in the middle reach. The water quality of HRS fluctuated during the period 1997-2009; it has improved and stabilized since 2005. In terms of spatialized frequency of serious pollution, heavily polluted regions were mostly concentrated in the area along several tributaries of the Ying, Guo and New Sui Rivers as well as the area north of Nansi Lake. These regions decreased from 1997 to 2009, especially after 2005. Our analysis indicated that water pollution in HRS had a close relation with population and primary industry during the period 1997-2009, and implied that spatiotemporal variation of surface water quality could provide a scientific foundation for human health risk assessment of the Huai River Basin.

Changes in Production Potential in China in Response to Climate Change from 1960 to 2010

From the Global Agro-Ecological Zone (GAEZ) model, changes in the three climate factors (temperature, precipitation, and solar radiation) over the past five decades showed different trends and that production potential was impacted significantly by the geographic heterogeneity of climate change. An increase of approximately 1.58 million tons/decade in production potential correlated with climate change. Regions with increased production potential were located mainly in the Northeast China Plain, the northern arid and semiarid region, and the Huang-Huai-Hai Plain. Regions with decreased production potential were located mainly in the Middle-lower Yangtze Plain and southern China. The climate factors that impacted production potential varied by region. In the Northeast China Plain, increased temperature was the major cause of the increased production potential. In the northern arid and semiarid region, temperature and precipitation were the major factors affecting production potential, but their effects were in opposition to each other. In southern China, increased temperature and decreased solar radiation caused a decreased production potential. In the Middle-lower Yangtze Plain, a decrease in solar radiation was the major factor resulting in decreased production potential. In the Huang-Huai-Hai Plain, changes in temperature and solar radiation had large but opposite effects on production potential.

Dynamic monitoring of drought using HJ-1 and MODIS time series data in northern China

From early November 2008 to February 2009, lack of rainfall led to severe drought in northern China. More than 9.3 million ha of wheat in six major crop production provinces, including Henan, Anhui, Shandong, Shanxi, Gansu, and Shaanxi, were hit by drought. Supported by Chinese HJ-1 satellite images together with NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data, dynamic monitoring of the drought was conducted. HJ-1 CCD data with 30-m resolution were used to identify cropland information. Spatial–temporal variation of drought was detected using Vegetation Index and Water Index time series data derived from MODIS visible, infrared, and short-wave infrared bands. The influences of drought were classified into five levels based on MODIS-derived 8-day composite Anomaly Water Index (AWI) and field survey data. The results indicated that the drought deteriorated beginning in November 2008 and became most serious in late January 2009. HJ-1 data together with MODIS data proved to be valuable data sources for monitoring soil moisture and drought at a both regional and national scale.