From Soda Bottles To Super Labs: An Analysis Of North America's Dual Methamphetamine Production Networks

This article uses the global production network perspective to analyze the various actors involved in the production and distribution of methamphetamine in North America. The paper analyzes the organization and operation of the two dominant network typologies at work in the United States: small toxic labs and Mexican drug‐trafficking organizations. Particular emphasis is placed on how the networks have adapted to changes in the regulatory context in which they operate. I conclude with potential policy recommendations for curtailing methamphetamine production within both networks.     

Global cities,cosmopolitanism, and geographies of tolerance

Scholarly attention devoted to global cities has emphasized their economic and political significance. Yet global cities are also deeply cultural and ideological in nature. Contrary to a long tradition of urban studies that views urban life as inherently alienating, this essay argues that the social and cultural diversity of global cities renders them mechanisms for the generation of tolerance and empathy. It opens with a brief review of global cities. Second, it traces the contours of cosmopolitanism as an ideology that fosters respect for social and cultural differences and a wider community of caring. Third, it reviews the empirical evidence of American global cities to make the case that their diversity leads them to generate a progressive cosmopolitan ethnics. It draws on the literature of social psychology, the work of Richard Florida, and indices of immigration, religious and linguistic diversity, homophobia, and voting patterns to substantiate the claim that cosmopolitan values are most evident and deeply rooted in globalized metropolitan centers.     

Multitemporal settlement and population mapping from Landsat using Google Earth Engine

As countries become increasingly urbanized, understanding how urban areas are changing within the landscape becomes increasingly important. Urbanized areas are often the strongest indicators of human interaction with the environment, and understanding how urban areas develop through remotely sensed data allows for more sustainable practices. The Google Earth Engine (GEE) leverages cloud computing services to provide analysis capabilities on over 40 years of Landsat data. As a remote sensing platform, its ability to analyze global data rapidly lends itself to being an invaluable tool for studying the growth of urban areas. Here we present (i) An approach for the automated extraction of urban areas from Landsat imagery using GEE, validated using higher resolution images, (ii) a novel method of validation of the extracted urban extents using changes in the statistical performance of a high resolution population mapping method. Temporally distinct urban extractions were classified from the GEE catalog of Landsat 5 and 7 data over the Indonesian island of Java by using a Normalized Difference Spectral Vector (NDSV) method. Statistical evaluation of all of the tests was performed, and the value of population mapping methods in validating these urban extents was also examined. Results showed that the automated classification from GEE produced accurate urban extent maps, and that the integration of GEE-derived urban extents also improved the quality of the population mapping outputs.     

Object-based class modelling for multi-scale riparian forest habitat mapping

Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m² were modelled from 938 forest stand patches (MPS = 6868.20 m²) and 43,742 tree stand patches (MPS = 140.79 m²). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.     

Early-season mapping of crops and cultural operations using very high spatial resolution Pléiades images

The aim of this study was to assess the contribution of very high spatial resolution (VHSR) Pléiades images to both early season crop identification and the mapping of bare soil surface characteristics due to cultural operations. The study region covering 21 km² is located west of the peri-urban territory of the Versailles plain and the Alluets plateau (Yvelines, France). About 100 cropped fields were observed on the ground synchronously with two Pléiades images of 3 and 24 April 2013 and one SPOT4 image of 2 April 2013. The GIS structuring of these field data along with vector information about field boundaries was used for delimitating both training and test zones for the support vector machine classifier with polynomial function kernel (pSVM). The pSVM was computed on the spectral bands and NDVI for both single-date Pléiades and the bi-temporal Pléiades pair. For the single-date classifications of crops, the overall per-pixel accuracy reached 87% for the SPOT4 image of 2 April (6 classes), 79% for the Pléiades image of 3 April (6 classes) and 82% for that of 24 April (7 classes). At the earlier date (2–3 April), the Pléiades image very well discriminated cultural operations (>77%, user’s or producer’s accuracies) as well as fallows and grasslands, while winter cereals and rapeseed were better discriminated by the SPOT4 image winter cereals (>70%, user’s or producer’s accuracies). As Pléiades images revealed within-field spatial variations of early phenological stages of winter cereals that could be critical for adjusting management of zones with delayed development during the growing season, they brought information complementary to multispectral images with high spatial resolution. For the bi-temporal Pléiades image, the overall per-pixel accuracy was about 80% (7 classes), winter crops, grasslands and fallows being very well detected while confusions occurred between spring barley at initial stages (2–3 leaves) and bare soils prepared for other spring crops. Using an additional validation field set covering ∼1/3 of the study area croplands, the crop map resulting from the bi-temporal Pléiades pair achieved correct crop prediction for about 89.7% of the validation fields when considering composite classes for winter cereals and for spring crops. Early-season Pléiades images therefore show a considerable potential for anticipating regional crop patterns and detecting soil tillage operations in spring.     

TanDEM-X双站SAR干涉测量及研究进展

较全面、系统地介绍了Tan DEM-X/Terra SAR-X双站SAR科学计划,重点涉及其科学目标、Tan DEM-X卫星参数、轨道结构以及干涉数据获取模式等相关内容,并讨论了双站SAR成像、极化In SAR和数字波束成形等干涉测量新技术及其研究进展。这些双站SAR新技术的实现将大大地推动SAR干涉测量在全球地形测绘、冰川学、海洋学及地质学等领域中的应用。     

C‐band SAR backscatter characteristics of Arctic sea and land ice during winter

Abstract

Synthetic Aperture Radar (SAR) data has become an important tool for studies of polar regions, due to high spatial resolution even during the polar night and under cloudy skies. We have studied the temporal variation of sea and land ice backscatter of twenty‐four SAR images from the European Remote Sensing satellite (ERS‐1) covering an area in Lady Ann Strait and Jones Sound, Nunavut, from January to March 1992. The presence of fast ice in Jones Sound and glaciers and ice caps on the surrounding islands provides an ideal setting for temporal backscatter studies of ice surfaces. Sample regions for eight different ice types were selected and the temporal backscatter variation was studied. The observed backscatter values for each ice type characterize the radar signatures of the ice surfaces. This time series of twenty‐four SAR images over a 3‐month period provides new insights into the degree of temporal variability of each surface. Ice caps exhibit the highest backscatter value of ‐3.9 dB with high temporal variability. Valley glacier ice backscatter values decrease with decreasing altitude, and are temporally the most stable, with standard deviations of 0.08–0.10 dB over the 90‐day period.

First‐year ice and lead ice show a negative trend in backscatter values in time and a positive correlation of up to 0.59 with air temperature over the 90‐day period. For first‐year ice and lead ice, episodes of large temperature fluctuations (±12°C) are associated with rapid changes in backscatter values (±2 dB). We attribute the backscatter increase to a temperature‐induced increase in brine volume at the base of the snow pack. Multi‐year ice, conglomerate ice and shore ice are relatively stable over the 3‐month period, with a backscatter variation of only a few dBs. An observed lag time of up to three days between backscatter increase/decrease and air temperature can be attributed to the insulation effect of the snow cover over sea ice. The net range of the backscatter values observed on the most temporally stable surface, valley glacier ice, of about 0.30 dB indicates that the ERS‐1 SAR instrument exceeds the 1 dB calibration accuracy specified for the Alaska SAR Facility processor for the three winter months.     

Influence of Changes in Solar Radiation on Changes of Surface Temperature in China

The long-term trends of total surface solar radiation(SSR),surface diffuse radiation,and surface air temperature were analyzed in this study based on updated 48-yr data from 55 observational stations in China,and then the correlation between SSR and the diurnal temperature range(DTR) was studied.The effect of total solar radiation on surface air temperature in China was investigated on the basis of the above analyses.A strong correlation between SSR and DTR was found for the period 1961-2008 in China.The highest correlation and steepest regression line slope occurred in winter,indicating that the solar radiation effect on DTR was the largest in this season.Clouds and water vapor have strong influences on both SSR and DTR,and hence on their relationship.The largest correlations between SSR and DTR occurred in wintertime in northern China,regardless of all-day(including clear days and cloudy days) or clear-day cases.Our results also showed that radiation arriving at the surface in China decreased significantly during 1961-1989(dimming period),but began to increase during 1990-2008(brightening period),in agreement with previous global studies.The reduction of total SSR offset partially the greenhouse warming during 1961-1989.However,with the increase of SSR after 1990,this offsetting effect vanished;on the contrary,it even made a contribution to the accelerated warming.Nonetheless,the greenhouse warming still played a controlling role because of the increasing of minimum and mean surface temperatures in the whole study period of 1961-2008.We estimated that the greenhouse gases alone may have caused surface temperatures to rise by 0.31-0.46℃(10 yr) 1 during 1961-2008,which is higher than previously estimated.Analysis of the corresponding changes in total solar radiation,diffuse radiation,and total cloud cover indicated that the dimming and brightening phenomena in China were likely attributable to increases in absorptive and scattering aerosols in the atmosphere,respectively.     

榆林飞播林区土壤地球化学特征

以榆林飞播林区的土壤微生物、土壤养分和土壤可溶性盐为研究对象,对林区土壤可溶性盐的变化规律及其与土壤养分、微生物的相关性进行研究,为水土资源可持续利用以及飞播造林功效的提高提供理论依据.研究表明,研究区土壤属硫酸盐型,土壤层分异特征不显著,土壤仍处于初级发育阶段.土壤总盐与养分的相关性不明显,适当增加K⁺利于真菌的存活和生物量的积累,在1 kg土壤中,每增加1 g K⁺,真菌数量就会增加14个左右.在土层表层,适量减少Cl^-能促进土壤细菌的生长,在40 cm土层的盐分上行过程中出现表聚现象,在土壤中层,出现板结现象,在土壤底层,HCO₃^-和Na⁺质量分数的增加,有利于土壤全氮质量分数的增加,且HCO₃^-的影响力最强.     

PROGRESSES AND PROSPECTS IN RESEARCH ON SEASON DIVISION AND SEASONAL CHANGES IN CHINA

Progresses in the research for season division and seasonal changes are reviewed systematically in this paper,which particularly introduces the results of a national natural science foundation project,"the nonlinear identification of seasonal changes and its responses to global warming".The project developed two objective and quantitative methods for season division:the non-linear similarity measure(NSM) method and the regional multi-element optimal dissection(RMOD) method,which differ from traditional ones for season division.Besides,the project further investigated seasonal changes and their responses to global warming,analyzed evolution characteristics of the starting date and length of seasons in history,revealed their relationships with extreme events and precipitation patterns in rainy seasons,and thereby built a research system for seasonal changes in China under the global warming background.Finally,the authors make an outlook on the research for season division and seasonal changes and put forward several issues associated with season and climate changes that need to be further explored.