Industrialization and Economic Development in Advanced Placement Human Geography

Abstract

This article discusses the contents and significance of the industrialization and economic development section of the Advanced Placement human geography course. It also describes how the course outline breaks into four sections the concern of economic geographers with the analysis of the spatial character of economic activity. In summarizing the content of these sections attention is given to links with other course modules and to the use of effective pedagogies for articulating key concepts.     

Photochemical Degradation of Hydrophilic Xenobiotics in the UV/H2O2-process. Influence of Humic Matter on the Degradation Rate of 2-Amino-1-naphthalenesulfonate and Ethylenediaminetetraacetate

Photochemical oxidation methods are able to eliminate hydrophilic xenobiotics with a high efficiency. In waters with high DOC values caused by humic substances (HS) which are able to absorb UV light, problems can result. The degradation rates of the micropollutants using irradiation wavelengths in the range between λ = 200 nm to λ = 260 nm are significantly influenced by HS. This is mainly caused by the high absorption of the HS at shorter wavelength. In the presence of HS, the photolytic degradation of EDTA and FeEDTA was slowed down by an inner filter effect. A similar tendency could be seen for the photolytic degradation of 2-amino-1-naphthalenesulfonate where additional effects to the inner filter effect were also operating. In the UV/H₂O₂-process, the decrease of the degradation rate could be assigned to the ability of the HS to scavenge HO radicals.     

地下坑道开挖前方结构面超前探测

本文在分析总结现有地球物理勘探方法的基础上, 提出了一种适合地下工程开挖前方结构面探测的新的方法--TVSP法, 同时对该方法进行了必要的分析。     

Advanced Marginality as a comparative research strategy in praxis: the Danish “Grey Belt” in conversation with the French “Red Belt”

Urban Outcast and advanced marginality belongs to a theory culture rarely engaged in comparative urban studies. Here the potential of advanced marginality as a comparative research strategy is explored paying special attention to the concepts of epistemic reflexivity, analogical reasoning and homology. These concepts are applied as the foundation of a comparative research design comprising three necessary and interconnected analytical moments linking reflexivity, theory and empirical analysis. Empirically this strategy and design is confronted in the case of four Danish “Grey belt” housing estates. The empirical confrontation demonstrates that both strategy and design are relevant and productive. Nevertheless, there is a need to question, adapt and extent the six original properties of advanced marginality. Secondly the empirical confrontation demonstrates that both strategy and design can contribute to the current conversations on the comparative in urban studies empirically and conceptually, underscoring the curiosity of its eclipse in these conversations.     

The 1997 eruption of Okmok Volcano, Alaska: a synthesis of remotely sensed imagery

Okmok Volcano, in the eastern Aleutian Islands, erupted in February and March of 1997 producing a 6-km-long lava flow and low-level ash plumes. This caldera is one of the most active in the Aleutian Arc, and is now the focus of international multidisciplinary studies. A synthesis of remotely sensed data (AirSAR, derived DEMs, Landsat MSS and ETM+ data, AVHRR, ERS, JERS, Radarsat) has given a sequence of events for the virtually unobserved 1997 eruption. Elevation data from the AirSAR sensor acquired in October 2000 over Okmok were used to create a 5-m resolution DEM mosaic of Okmok Volcano. AVHRR nighttime imagery has been analyzed between February 13 and April 11, 1997. Landsat imagery and SAR data recorded prior to and after the eruption allowed us to accurately determine the extent of the new flow. The flow was first observed on February 13 without precursory thermal anomalies. At this time, the flow was a large single lobe flowing north. According to AVHRR Band 3 and 4 radiance data and ground observations, the first lobe continued growing until mid to late March, while a second, smaller lobe began to form sometime between March 11 and 12. This is based on a jump in the thermal and volumetric flux determined from the imagery, and the physical size of the thermal anomalies. Total radiance values waned after March 26, indicating lava effusion had ended and a cooling crust was growing. The total area (8.9 km²), thickness (up to 50 m) and volume (1.54×10⁸ m³) of the new lava flow were determined by combining observations from SAR, Landsat ETM+, and AirSAR DEM data. While the first lobe of the flow ponded in a pre-eruption depression, our data suggest the second lobe was volume-limited. Remote sensing has become an integral part of the Alaska Volcano Observatory’s monitoring and hazard mitigation efforts. Studies like this allow access to remote volcanoes, and provide methods to monitor potentially dangerous ones.     

Modelling of piping collapses and gully headcut landforms:Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)tech-niques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable's importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model's result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.     

A neurofuzzy system to analyze liquefaction-induced lateral spread

Lateral spreads of liquefied granular soil masses have caused severe damages to many engineered structures. Accordingly, many empirical procedures have been developed from field-direct observations and from multiple regression analyses carried out on the database gathered from many case histories. The intricacy and nonlinearity of the underlying phenomena makes the above approaches somewhat unreliable for estimating liquefaction-induced lateral spreads. The database has inconsistencies and contradictions because of inevitable subjective interpretations and neural network approaches have been proposed for dealing with these.To overcome these difficulties in this paper a hybrid system named neurofuzzy, which profits from fuzzy and neural paradigms, is advanced. The resulting model called NEFLAS (NEuroFuzzy estimation of liquefaction induced LAteral Spread) is shown to yield a much improved forecasting than both multiple regression and neural network procedures. The corresponding software can be obtained from the first author.     

Assimilating ASAR data for estimating soil moisture profile using an ensemble Kalman filter

Active microwave remote sensing data were used to calculate the near-surface soil moisture in the vegetated areas. In this study, Advanced Synthetic Aperture Radar （ASAR） observations of surface soil moisture content were used in a data assimilation framework to improve the estimation of the soil moisture profile at the middle reaches of the Heihe River Basin, Northwest China. A one-dimensional soil moisture assimilation system based on the ensemble Kalman filter （EnKF）, the forward radiative transfer model, crop model, and the Distributed Hydrology-Soil-Vegetation Model （DHSVM） was developed. The crop model, as a semi-empirical model, was used to estimate the surface backscattering of vegetated areas. The DHSVM is a distributed hydrology-vegetation model that explicitly represents the effects of topography and vegetation on water fluxes through the landscape. Numerical experiments were con- ducted to assimilate the ASAR data into the DHSVM and in situ soil moisture at the middle reaches of the Heihe River Basin from June 20 to July 15, 2008. The results indicated that EnKF is effective for assimilating ASAR observations into the hydrological model. Compared with the simulation and in situ observations, the assimilated results were significantly improved in the surface layer and root layer, and the soil moisture varied slightly in the deep layer. Additionally, EnKF is an efficient approach to handle the strongly nonlinear problem which is practical and effective for soil moisture estimation by assimilation of remote sensing data. Moreover, to improve the assimilation results, further studies on obtaining more reliable forcing data and model parameters and increasing the efficiency and accuracy of the remote sensing observations are needed, also improving estimation accuracy of model operator is important.