Automated Segmentation of Resistivity Image Logs Using Wavelet Transform

We describe a wavelet-transform-based method for automated segmentation of resistivity image logs that takes into account the apparent dip in the data and addresses the problem of discriminating lithofacies boundaries from noise and intrafacies variations. Our method can be applied to borehole measurements in general, but might have an advantage when applied to resistivity image logs as it addresses explicitly the large variability in facies segments recorded with a high-resolution multiple-sensor tool. We have developed an algorithm based on this method that might outperform other existing segmentation methods in the cases of low to moderate dip. We made a detailed comparison of the segmentation from our method with the one done by a geologist to delineate different lithofacies blocks in a well drilled in a deepwater depositional environment. Our results show considerable success rates in reproducing the geologically defined lithofacies boundaries, and the generality of our procedure suggests it could also be applied to other depositional environments.     

Relationship Between Land Cover Ratio and Urban Heat Island from Remote Sensing and Automatic Weather Stations Data

Urban heat island (UHI) effect has a close relation to land covers type. This paper investigates the relationship between land cover ratio and UHI in Guangzhou, south of China using remote sensing and automatic weather stations data. The temperature data were obtained by Automatic weather stations (AWS) of Guangzhou in October, 2004, at the same time with the CBERS remote sensing image acquired. Firstly, the hourly mean temperature was computed from hourly AWS data. Secondly, the CBERS remote sensing image was classified using support vector machine (SVM) and land covers classification were output. Thirdly, the classification result was overlapped with a round buffer with 1.5 KM radius centered on the AWS, and then the land cover ratio, Edge Density (ED) and Mean Fractal Dimension (MFRACT) of buffers were computed out. Finally, the correlation coefficient between hourly mean temperature and land cover ratio, ED and MFRACT was calculated. It concluded that UHI intensity was heavier during nighttime than daytime. Stations with higher vegetation ratio and higher ED had lower heat island effect. On the contrary, stations with higher impervious ratio and lower ED had more serious heat island effect. The positive–negative of correlation coefficient between hourly mean temperature and vegetation ratio during 11:00–17:00 h (local time) was opposite to that during other time. ED was negatively correlated with hourly mean temperature except during 11:00–17:00 h. On the contrary, MFRACT was positively correlated with hourly mean temperature. It implied that fragmentations of patches were favorable to UHI alleviation, and complexities of patch were unfavorable factors.     

Temporal and spatial dynamical simulation of groundwater characteristics in Minqin Oasis

Application scope of geostatistics has been gradually extended from original geologic field to soil science and ecological field, etc. and its successful application results have been widely demonstrated. But little information is reported as to the direct use of geostatistical method to work out the distribu- tion map of groundwater characteristics. In this paper the semivariogram of geostatistics, in combina- tion with GIS, was used to quantitatively study the spatial variation characteristics of groundwater table depth and mineralization degree and their relation to the landuse changes. F test of the used spherical model reached a very significant level, and the theoretical model can well reflect the spatial structural characteristics of groundwater table depth and mineralization degree and achieve an ideal result. This shows that the application of the method in the dynamical simulation of groundwater is feasible. And this paper also provides useful reference for the application of geostatistics in the study of the dy- namical variations of groundwater resources in the oasis.     

A Long-Term Decrease of the Mid-Size Segmentation Lengths Observed in the He <Emphasis Type="SmallCaps">ii</Emphasis> (30.4 nm) Solar EUV Emission

Power spectra of segmentation-cell length (a dominant length scale of EUV emission in the transition region) from full-disk He?ii extreme ultraviolet (EUV) images observed by the Extreme ultraviolet Imaging Telescope (EIT) onboard the Solar and Heliospheric Observatory (SOHO) and the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) during periods of quiet-Sun conditions for a time interval from 1996 to 2015 were analyzed. The spatial power as a function of the spatial frequency from about 0.04 to 0.27 (EIT) or up to 0.48 (AIA) Mm^?1 depends on the distribution of the observed segmentation-cell dimensions – a structure of the solar EUV network. The temporal variations of the spatial power reported by Didkovsky and Gurman (Solar Phys. 289, 153, 2014) were suggested as decreases at the mid-spatial frequencies for the compared spectra when the power curves at the highest spatial frequencies of 0.5 pix^?1 were adjusted to match each other. This approach has been extended in this work to compare spectral ratios at high spatial frequencies expressed in the solar spatial frequency units of Mm^?1. A model of EIT and AIA spatial responses allowed us to directly compare spatial spectral ratios at high spatial frequencies for five years of joint operation of EIT and AIA, from 2010 to 2015. Based on this approach, we represent these ratio changes as a long-term network transformation that may be interpreted as a continuous dissipation of mid-size network structures to the smaller-size structures in the transition region. In contrast to expected cycling of the segmentation-cell dimension structures and associated spatial power in the spectra with the solar cycle, the spectra demonstrate a significant and steady change of the EUV network. The temporal trend across these structural spectra is not critically sensitive to any long-term instrumental changes, e.g. degradation of sensitivity, but to the change of the segmentation-cell dimensions of the EUV network structure.     

Comparison of the spatio-temporal dynamics of vegetation between the Changbai Mountains of eastern Eurasia and the Appalachian Mountains of eastern North America

The Changbai Mountains and the Appalachian Mountains have similar spatial contexts. The elevation, latitude, and moisture gradients of both mountain ranges offer regional insight for investigating the vegetation dynamics in eastern Eurasia and eastern North America. We determined and compared the spatial patterns and temporal trends in the normalized difference vegetation index (NDVI) in the Changbai Mountains and the Appalachian Mountains using time series data from the Global Inventory Modeling and Mapping Studies 3rd generation dataset from 1982 to 2013. The spatial pattern of NDVI in the Changbai Mountains exhibited fragmentation, whereas NDVI in the Appalachian Mountains decreased from south to north. The vegetation dynamics in the Changbai Mountains had an insignificant trend at the regional scale, whereas the dynamics in the Appalachian Mountains had a significant increasing trend. NDVI increased in 55% of the area of the Changbai Mountains and in 95% of the area of the Appalachian Mountains. The peak NDVI occurred one month later in the Changbai Mountains than in the Appalachian Mountains. The results revealed a significant increase in NDVI in autumn in both mountain ranges. The climatic trend in the Changbai Mountains included warming and decreased precipitation, and whereas that in the Appalachian Mountains included significant warming and increased precipitation. Positive and negative correlations existed between NDVI and temperature and precipitation, respectively, in both mountain ranges. Particularly, the spring temperature and NDVI exhibited a significant positive correlation in both mountain ranges. The results of this study suggest that human actives caused the differences in the spatial patterns of NDVI and that various characteristics of climate change and intensity of human actives dominated the differences in the NDVI trends between the Changbai Mountains and the Appalachian Mountains. Additionally, the vegetation dynamics of both mountain ranges were not identical to those in previous broader-scale studies.     

Distribution of the indigenous microorganisms and mechanisms of their orientational activation in Daqing Oilfield

The distribution of indigenous microorganisms was surveyed in Block 1 of Daqing Oilfield. Based on this survey, the indigenous microorganisms in the formation water were activated with different activator systems at the simulated stratum ecological environment. The changes of the number of bacteria of various physiological groups were determined during the process of activation. Also changes of pH value and composition of gas productions were analyzed at the end of culturing. The results showed that the selected block formation water contained a great number of saprophytic bacteria, hydrocarbon-oxidizing bacteria, fermentative bacteria, methane-producing bacteria and sulfate-reducing bacteria. Under the conditions that the growth of sulfate-reducing bacteria was controlled the block had the potential to enhance oil recovery by activating beneficial bacteria. The growth of sulfate-reducing bacteria can be inhibited through the activation of nitrate-reducing bacteria. The number of nitrate-reducing bacteria reached 10⁶–10⁷ cells/mL, but sulfate-reducing bacteria reached only 0–45 cells/mL in A system. Methane-producing bacteria can be activated by C, D activators. The relative content of biological methane in the light hydrocarbon gas reached 80% in C, D systems. B activator was conducive to the propagation of acid-producing bacteria, so that the pH value of the culture medium decreased from 7.5 to around 5.0. Hydrocarbon-oxidizing bacteria can be activated by various activator systems. There was low molecular light hydrocarbon in gas production according to the analysis of gas chromatograph. According to the content of methane and the number of methane-producing bacteria, methane only can be generated through activating methane-producing bacteria. By choosing different activator systems, various populations of indigenous microorganisms can be activated accordingly.     

Climatic and geographic factors affect ecosystem multifunctionality through biodiversity in the Tibetan alpine grasslands

Ecosystem multifunctionality(EMF), the simultaneous provision of multiple ecosystem functions, is often affected by biodiversity and environmental factors. We know little about how the interactions between biodiversity and environmental factors affect EMF. In this case study, a structural equation model was used to clarify climatic and geographic pathways that affect EMF by varying biodiversity in the Tibetan alpine grasslands. In addition to services related to carbon, nitrogen, and water cycling, forage supply, which is related to plantproductivity and palatability, was included in the EMF index. The results showed that 72% of the variation in EMF could be explained by biodiversity and other environmental factors. The ratio of palatable richness to all species richness explained 8.3% of the EMF variation. We found that air temperature, elevation, and latitude all affected EMF, but in different ways. Air temperature and elevation impacted the aboveground parts of the ecosystem, which included plant height, aboveground biomass, richness of palatable species, and ratio of palatable richness to all species richness. Latitude affected EMF by varying both aboveground and belowground parts of the ecosystem, which included palatable speciesrichness and belowground biomass. Our results indicated that there are still uncertainties in the biodiversity–EMF relationships related to the variable components of EMF, and climatic and geographic factors. Clarification of pathways that affect EMF using structural equation modeling techniques could elucidate the mechanisms by which environmental changes affect EMF.     

Artificial light at night: implications for early life stages development in four temperate freshwater fish species

Flora and fauna have both evolved under a natural cycle of light and dark. But especially in urban areas, the night is now increasingly disturbed by artificial light. Many traits and behaviours in fish are triggered by a circadian clock, for example hatching and swim bladder inflation, which predominantly take place at dusk or night. As lighting becomes brighter and extends farther into rural areas, the distinction between day and night becomes increasingly blurred. Therefore, the loss of diurnal trigger by artificial light at night was hypothesized having deleterious effects on these traits and impact fish reproduction. To assess these effects, eggs of four native freshwater fishes, Eurasian perch Perca fluviatilis, roach Rutilus rutilus, bleak Alburnus alburnus and chub Leuciscus cephalus, were incubated under two different light conditions: a photoperiod of 14 h light:10 h darkness (LD) and continuous illumination (LL). The time to hatch and swim bladder inflation was recorded. The species showed inconsistent reactions to the light treatments. In roach and bleak, the time to 50% hatch was longer in LL, whereas continuous lighting had an accelerating effect in chub. Incubation in LL elongated the hatching period in perch and roach and, in perch, the onset of darkness seemed to trigger hatching. The swim bladder inflation was significantly promoted by continuous light in chub and bleak but was not affected in roach. In conclusion, nocturnal artificial illumination could have an effect on hatching and initial swim bladder filling by masking the day–night-change and thereby diminish the trigger effect. However, the reactions were species specific and the increase in variation indicated a lack of diurnal triggering, whilst a general deleterious effect of artificial light at night has not been identified on early life stages.     

High-resolution satellite image segmentation using Hölder exponents

Texture in high-resolution satellite images requires substantial amendment in the conventional segmentation algorithms. A measure is proposed to compute the Hölder exponent (HE) to assess the roughness or smoothness around each pixel of the image. The localized singularity information is incorporated in computing the HE. An optimum window size is evaluated so that HE reacts to localized singularity. A two-step iterative procedure for clustering the transformed HE image is adapted to identify the range of HE, densely occupied in the kernel and to partition Hölder exponents into a cluster that matches with the range. Hölder exponent values (noise or not associated with the other cluster) are clubbed to a nearest possible cluster using the local maximum likelihood analysis.