Analysis of Land Cover and Landscape Pattern Change in Beijing-Tianjin-Hebei Region Based on Globeland30 Data

With the rapid economic development and urbanization process in Beijing-Tianjin-Hebei region, land use and landscape pattern have been changed. In order to reveal the temporal and spatial changes and provide scientific basis for the local land use planning and landscape pattern optimization made by government, based on the classification results of Globeland 30 land cover data in 2000 and 2010, this paper quantitatively analyzed the land use transfer status and the dynamic change of landscape pattern in Beijing-Tianjin-Hebei by adopting the method of land use transfer matrix and landscape index. The results show that the land use and landscape patterns in Beijing-Tianjin-Hebei have been changed significantly from 2000 to 2010. Overall, land use in Beijing-Tianjin-Hebei region has been changed greatly, which shows that the cultivated land area has been decreased by 3721.67 km2, while the artificial surface area and grassland area have increased by 2721.29 km2 and 657.09 km2, respectively. From the six partitions of Beijing-Tianjin-Hebei, it can be seen that the subareas with significant changes are Sand Control Farmland Protection Zone in Yellow River Flood Plain, Water Conservation Area for Sand Control in Mountain and Hilly Areas of Northwest Taihang Mountains, and Human Settlement Environment Maintenance and Farmland Protection Zone of Beijing-Tianjin-Hebei Urban Agglomeration. The arable land area of these three zones has decreased 572.77 km2, 1553.94 km2 and 1359.53 km2, respectively. From the perspective of landscape pattern change, patch density and fragmentation degree in the southeast and northwest of Beijing-Tianjin-Hebei region increase;and the dominant patches in the southeast of Beijing-Tianjin-Hebei region have formed a good connectivity;the whole Beijing-Tianjin-Hebei region shows irregular shape and discontinuous enhancement of landscape types, the landscape patch types increase and enrich, and the dominance shows a downward trend.

Impact of climate factors on runoff in the Kaidu River watershed:path analysis of 50-year data

Runoff formation is a complex meteorological-hydrological process impacted by many factors,especially in the inland river basin.Based on the data of daily mean air temperature,precipitation and runoff during the period of 1958-2007 in the Kaidu River watershed,this paper analyzed the changes in air temperature,precipitation and runoff and revealed the direct and indirect impacts of daily air temperature and precipitation on daily runoff by path analysis.The results showed that mean temperature time series of the annual,summer and autumn had a significant fluctuant increase during the last 50 years（P 0.05）.Only winter precipitation increased significantly（P 0.05） with a rate of 1.337 mm/10a.The annual and winter runoff depthes in the last 50 years significantly increased with the rates of 7.11 mm/10a and 1.85 mm/10a,respectively.The driving function of both daily temperature and precipitation on daily runoff in annual and seasonal levels is significant in the Kaidu River watershed by correlation analysis.The result of path analysis showed that the positive effect of daily air temperature on daily runoff depth is much higher than that of daily precipitation in annual,spring,autumn and winter,however,the trend is opposite in summer.

A novel traditional Chinese medicine combination for radiation

Objective:To formulate an efficacious radioprotective combination of Chinese medicines with minimal toxicity.Methods:Aqueous and alcoholic extracts from 38 traditional Chinese herbs were prepared.To produce drugcontaining sera,rats received six doses of each extract via oral gavage at 12-h intervals.Subsequently,human lung epithelial BEAS-2B cells were cultured in these drug-containing sera.The cell viability was assessed after different doses of irradiation to identify the radioprotective effects of Chinese herbal extracts.The efficacy of a selected Chinese herbal extract combination was further confirmed through cell viability analysis via in vitro colony formation and survival rate assessments in C57BL/6 mice post-irradiation.Results:Extracts from Angelicae Sinensis Radix(ASR;two extracts),Citri Reticulatae Pericarpium(CRP),Platycladi Cacumen(PC),Schisandrae chinensis Fructus(SF),Scutellariae Radix(SR),and Glycyrrhizae Radix et Rhizome(GRR)demonstrated radioprotective effects.The combination of the seven Chinese herbal extracts notably increased the survival and viability of the BEAS-2B cells exposed to varying doses of X-rays.Moreover,the group of mice receiving Chinese medicine combination and irradiation exhibited prolonged survival after exposure to 6.5 Gy Xrays with a median survival of(14=2)d compared to(11=2)d in the irradiated group without the herbal treatment.Additionally,the Chinese medicine combination group displayed a significantly higher 28 d survival rate(30%)compared to the irradiation-only group(16.6%,P<0.05).Conclusion:The novel combination of Chinese herbal extracts from ASR,CRP,PC,SF,SR,and GRR has the potential for radiation protection applications.

Object-based image analysis of suburban landscapes using Landsat-8 imagery

Many experiments of object-based image analysis have been conducted in remote sensing classification.However,they commonly used highresolution imagery and rarely focused on suburban area.In this research,with the Landsat-8 imagery,classification of a suburban area via the object-based approach is achieved using four classifiers,including decision tree(DT),support vector machine(SVM),random trees(RT),and naive Bayes(NB).We performed feature selection at different sizes of segmentation scale and evaluated the effects of segmentation and tuning parameters within each classifier on classification accuracy.The results showed that the influence of shape on overall accuracy was greater than that of compactness,and a relatively low value of shape should be set with increasing scale size.For DT,the optimal maximum depth usually varied from 5 to 8.For SVM,the optimal gamma was less than or equal to 10^(-2),and its optimal C was greater than or equal to 10^(2).For RT,the optimal active variables was less than or equal to 4,and the optimal maximum tree number was greater than or equal to 30.Furthermore,although there was no statistically significant difference between some classification results produced using different classifiers,SVM has a slightly better performance.