Qisheng He

Change detection of an earthquake-induced barrier lake based on remote sensing image classification

The earthquake-induced barrier lakes that are caused by landslides are at risk of bursting after excessive rainfall, and they are a serious threat to the surrounding residents. This paper proposes a change detection approach of the barrier lake using the method of post-classification comparison combined with background subtraction. The case studied in the paper is the detection of the Tangjiashan barrier lake, which is one of the largest lakes induced by the Wenchuan Earthquake on 12 May 2008. Both the pre- (31 March 2007) and post-earthquake (16 May 2008) images of the Advanced Land Observing Satellite (ALOS) Advanced Visible and Near Infrared Radiometer type 2 (AVINER-2) were collected in the paper. The results show that the river widened through the Zhangping area, increasing from 90 m pre-earthquake to 545 m post-earthquake, and the surface area of the barrier lake increased from 0.945 km2 to 1.471 km2.

Forest stand biomass estimation using ALOS PALSAR data based on LiDAR-derived prior knowledge in the Qilian Mountain, western China

Studies are needed to evaluate the ability of Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) for forest aboveground biomass (AGB) extraction in mountainous areas. In this article, forest biomass was estimated at plot and stand levels, and different biomass grades, respectively. Light detection and ranging (LiDAR) data with about one hit per m2 were first used for forest biomass estimation at the plot level, with R 2 of 0.77. Then the LiDAR-derived biomass, as prior knowledge, was used to investigate the relationship between ALOS PALSAR data and biomass. The results showed that at each biomass level, the range of the back-scatter coefficient in HH and HV polarization (where H and V represent horizontal and vertical polarizations, respectively, and the first of the two letters refers to the transmission polarization and the second to the received polarization) was very large and there was no obvious relationship between the synthetic aperture radar (SAR) back-scatter coefficient and biomass at plot level. At stand level and in different biomass grades, the back-scatter coefficient increased with the increase of forest biomass, and a logarithm equation can be used to describe the relationship. The main reason may be that forest structure is complex at the plot level, while the average value could partly decrease the influence of forest structure at stand level. Meanwhile, terrain radiometric correction (TRC) was investigated and found effective for forest biomass estimation.

Risk analysis for the highly pathogenic avian influenza in Mainland China using meta-modeling

A logistic model was employed to correlate the outbreak of highly pathogenic avian influenza (HPAI) with related environmental factors and the migration of birds. Based on MODIS data of the normalized difference vegetation index, environmental factors were considered in generating a probability map with the aid of logistic regression. A Bayesian maximum entropy model was employed to explore the spatial and temporal correlations of HPAI incidence. The results show that proximity to water bodies and national highways was statistically relevant to the occurrence of HPAI. Migratory birds, mainly waterfowl, were important infection sources in HPAI transmission. In addition, the HPAI outbreaks had high spatiotemporal autocorrelation. This epidemic spatial range fluctuated 45 km owing to different distribution patterns of cities and water bodies. Furthermore, two outbreaks were likely to occur with a period of 22 d. The potential risk of occurrence of HPAI in Mainland China for the period from January 23 to February 17, 2004 was simulated based on these findings, providing a useful meta-model framework for the application of environmental factors in the prediction of HPAI risk.

Epidemic risk analysis after the Wenchuan Earthquake using remote sensing

On 12 May 2008, Wenchuan Earthquake, magnitude 8.0, destroyed thousands of buildings, and resulted in thousands of people being buried in the collapsed buildings. In order to investigate the potential epidemic disease risk after earthquake, a Backward Propagation Neural Network (BPNN) was constructed to assess the potential epidemic risks by applying remote sensing technology to obtain Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) values, as well as by using a geographic information system (GIS) to gain ambient epidemic-related spatial factors over the earthquake region. In this study, a relationship was established between the change in environmental factors after earthquake and potential epidemic risks, which was found to be statistically significant. The result might be explained for three change perspectives, namely environmental risks, medical risks and psychological risks. The corresponding strategies for preparedness in case of epidemic disease were given.

The novel H1N1 Influenza A global airline transmission and early warning without travel containments

A novel influenza A (H1N1) has been spreading worldwide. Early studies implied that international air travels might be key cause of a severe potential pandemic without appropriate containments. In this study, early outbreaks in Mexico and some cities of United States were used to estimate the preliminary epidemic parameters by applying adjusted SEIR epidemiological model, indicating transmissibility infectivity of the virus. According to the findings, a new spatial allocation model totally based on the real-time airline data was established to assess the potential spreading of H1N1 from Mexico to the world. Our estimates find the basic reproductive number R0 of H1N1 is around 3.4, and the effective reproductive number fall sharply by effective containment strategies. The finding also implies Spain, Canada, France, Panama, Peru are the most possible country to be involved in severe endemic H1N1 spreading.

Wetland changes and droughts in southwestern China

The five provinces of southwestern China, Sichuan, Chongqing, Guizhou, Yunnan and Guangxi, frequently suffer from droughts, especially the recent severe drought of five consecutive months from autumn 2009 to spring 2010, which caused serious water shortages, huge economic losses and adverse social consequences. With increasing human activity in the last 200 years, the wetland areas have decreased and their ecological functions such as water conservation, climate regulation have declined, which has a direct impact on climate and the ecological environment. Using satellite images, changes in wetland areas of the five provinces of southwestern China have been mapped from 1970 to 2008. Our detailed analysis shows that the wetland area in the 1970s, 1990, 2000 and 2008 occupy an area of 20822.9, 18386.16, 19904.22 and 17269.72 km2, respectively, which indicate that the wetland areas have a downtrend, at an accelerating rate, from 2000 to 2008. Considering the complexity between wetland change and drought, the correlation between spatial and temporal wetland change and drought have been analysed using monthly ground meteorological data from 1971 to 2009, obtained from the China Meteorological Data Sharing Service Network. The analysed results show that the decrease of the wetland area, damage to biological resources and decline in climate regulation function are closely related to serious drought problems in the five provinces of southwestern China. Finally the corresponding solutions are discussed by analysing the problems faced by the wetland ecological system.

Change detection of the Tangjiashan barrier lake based on multi-source remote sensing data

The paper uses the approach of NDWI model to extract the water bodies of the Tangjiashan barrier lake from the multi-source satellite images of ALOS AVNIR-2 and CBERS-02B CCD and detects the changes of the barrier lake pre- and post-earthquake. The result shows that the river widen through Zhangping area increased from 92 m on Mar. 31, 2007 for per-earthquake to 420 m on May 16, 2008 and 474 m on May 18, 2008 for post-earthquake. And the area of barrier lake in the study area increased from an surface area of 0.6938 km2 on Mar. 31, 2007 for pre-earthquake to 1.2842 km2 on May 16, 2008 and 1.3658 km2 on May 18, 2008 for post-earthquake.

Relationship between SAR and biomass derived from LiDAR in Mountain areas

In this paper, the response of ALOS (the Advanced Land Observing Satellite) PALSAR (the Phased Array type L-band Synthetic Aperture Radar) data to the forest biomass was analyzed in the Qilian Mountain area within Gansu province, western China. Due to not enough field biomass, the Light Detection and Ranging (LiDAR) data was used to extract biomass in 20m × 20m cell. Then, the relationship between PALSAR backscattering coefficient in HH and HV polarization and Lidar-derived forest aboveground biomass was analyzed. The result showed that at each biomass level, the range of backscatter coefficient in HH and HV polarization was very big and there was no obvious relationship between SAR backscatter coefficient and biomass in pixel scale, while after averaging backscatter coefficients in different biomass level, backscatter coefficient in HV polarization increased with the increase of forest biomass and following one logarithm equation. The reason may be that forest structure is complex in pixel scale, while the average value partly removes he forest structure difference.