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Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect. 相似文献
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Brajesh Singh Santosh Kumar Masao Ban Kazuo Nakashima 《Journal of Earth System Science》2016,125(7):1329-1352
Felsic magmatism in the southern part of Himachal Higher Himalaya is constituted by Neoproterozoic granite gneiss (GGn), Early Palaeozoic granitoids (EPG) and Tertiary tourmaline-bearing leucogranite (TLg). Magnetic susceptibility values (<3 ×10?3 SI), molar Al2 O 3/(CaO + Na2 O + K 2O) (≥1.1), mineral assemblage (bt–ms–pl–kf–qtz ± tur ± ap), and the presence of normative corundum relate these granitoids to peraluminous S-type, ilmenite series (reduced type) granites formed in a syncollisional tectonic setting. Plagioclase from GGn (An10–An31) and EPG (An15–An33) represents oligoclase to andesine and TLg (An2–An15) represents albite to oligoclase, whereas compositional ranges of K-feldspar are more-or-less similar (Or88 to Or95 in GGn, Or86 to Or97 in EPG and Or87 to Or94 in TLg). Biotites in GGn (Mg/Mg + Fet= 0.34–0.45), EPG (Mg/Mg + Fet= 0.27–0.47), and TLg (Mg/Mg + Fet= 0.25–0.30) are ferribiotites enriched in siderophyllite, which stabilised between FMQ and HM buffers and are characterised by dominant 3Fe\(\rightleftharpoons \)2Al, 3Mg\(\rightleftharpoons \)2Al substitutions typical of peraluminous (S-type), reducing felsic melts. Muscovite in GGn (Mg/Mg + Fet=0.58–0.66), EPG (Mg/Mg + Fet=0.31?0.59), and TLg (Mg/Mg + Fet=0.29–0.42) represent celadonite and paragonite solid solutions, and the tourmaline from EPG and TLg belongs to the schorl-elbaite series, which are characteristics of peraluminous, Li-poor, biotite-tourmaline granites. Geochemical features reveal that the GGn and EPG precursor melts were most likely derived from melting of biotite-rich metapelite and metagraywacke sources, whereas TLg melt appears to have formed from biotite-muscovite rich metapelite and metagraywacke sources. Major and trace elements modelling suggest that the GGn, EPG and TLg parental melts have experienced low degrees (~13, ~17 and ~13%, respectively) of kf–pl–bt fractionation, respectively, subsequent to partial melting. The GGn and EPG melts are the results of a pre-Himalayan, syn-collisional Pan-African felsic magmatic event, whereas the TLg is a magmatic product of Himalayan collision tectonics. 相似文献
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The surface morphology of a rock joint is closely related to its mechanical properties. To reasonably characterize a rock surface, two new roughness parameters were proposed in this paper. One is related to the average slope angle of asperities that contribute to the shear strength, and the other reflects the frictional behavior of asperities that is defined as the maximum possible contact area in the shear direction. Taking the standard joint roughness coefficient profiles as example, these two roughness parameters can be applied to describe the directional characteristics of shear strength. Based on their relationships with initial dilation angles, the proposed roughness parameters were incorporated into a peak shear strength criterion. It is shown that the predicted peak shear strength is consistent with experimental data, and there is a power–law relationship. The application range of new roughness parameters was determined, which may facilitate a measurement process. 相似文献
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Phenology is a sensitive and critical feature of vegetation and is a good indicator for climate change studies. The global inventory modelling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) has been the most widely used data source for monitoring of the vegetation dynamics over large geographical areas in the past two decades. With the release of the third version of the NDVI (GIMMS NDVI3g) recently, it is important to compare the NDVI3g data with those of the previous version (NDVIg) to link existing studies with future applications of the NDVI3g in monitoring vegetation phenology. In this study, the three most popular satellite start of vegetation growing season (SOS) extraction methods were used, and the differences between SOSg and SOS3g arising from the methods were explored. The amplitude and the peak values of the NDVI3g are higher than those of the NDVIg curve, which indicated that the SOS derived from the NDVIg (SOSg) was significantly later than that derived from the NDVI3g (SOS3g) based on all the methods, for the whole northern hemisphere. In addition, SOSg and SOS3g both showed an advancing trend during 1982–2006, but that trend was more significant with SOSg than with SOS3g in the results from all three methods. In summary, the difference between SOSg and SOS3g (in the multi-year mean SOS, SOS change slope and the turning point in the time series) varied among the methods and was partly related to latitude. For the multi-year mean SOS, the difference increased with latitude intervals in the low latitudes (0–30°N) and decreased in the mid- and high-latitude intervals. The GIMMS NDVI3g data-sets seemed more sensitive than the GIMMS NDVIg in detecting information about the ground, and the SOS3g data were better correlated both with the in situ observations and the SOS derived from the Moderate Resolution Imaging Spectroradiometer NDVI. For the northern hemisphere, previous satellite measures (SOS derived from GIMMS NDVIg) may have overestimated the advancing trend of the SOS by an average of 0.032 d yr–1. 相似文献