GIS-based Village Layout Planning in Towns: A Case Study of Fengyang Town, Fenxi County, Jiangxi Province

Village layout planning is a fundamental work in the construction of beautiful countryside, and also a global work involving vital interests of vast farmers. Taking Fengyang Town of Fenxi County, Jiangxi Province for example, this paper applied Arc GIS to analyze natural facors, social economy, and construction factors quantitatively by evaluating development and construction conditions of each village comprehensively from the perspective of urban-rural integration. Classifying the villages into 4 types, namely urban reform type, concentrated development type, controlled construction type and relocation type, this paper tried to guide the scattered rural settlements to the intensive development.

Geo-Spatial Analysis of Oil Spill Distribution and Susceptibility in the Niger Delta Region of Nigeria

Oil spill occurrence during exploration, production and distribution can cause deleterious impact on the environment. Contamination of local streams/rivers, farmlands, forest resources and biodiversity in oil producing areas presents strong significant possibility of significant harm to human health. Geo-information technologies present new opportunities for assessing stress environment and ways of determining exposure susceptibility in such areas. The study assesses the geographical distribution of oil-spills cluster and pattern using three geospatial techniques with ground data at 443 oil-spill incident sites from 1985-2008. The places with high (high-volume/ large impact/close proximity to communities) and low incident (low-volume/less impact/far-distance) are related to the quantity of oil-spills identified within those communities considered susceptible to spill impact and possible exposure. While the average nearest neighborhood analysis showed a probability that oil-spill distribution in the area is clustered (ratio < 1 with index value 0.19), the Getis-Ord General G test indicated that the oil-spill with high quantities (volume) discharge are significantly clustered within every 400 m. The Moran’s I index indicted that there is <1% likelihood that the clusters are as a result of random chance. These findings will help to combat the environmental problems and risks of prolong exposure to petroleum hydrocarbons by addressing future incidents or relocating oil facilities/communities and positioning of rapid response strategies.

Research on runoff variations based on wavelet analysis and wavelet neural network model： A case study of the Heihe River drainage basin （1944-2005）

The Heihe River drainage basin is one of the endangered ecological regions of China. The shortage of water resources is the bottleneck, which constrains the sustainable development of the region. Many scholars in China have done researches concerning this problem. Based on previous researches, this paper analyzed characteristics, tendencies, and causes of annual runoff variations in the Yingluo Gorge （1944-2005） and the Zhengyi Gorge （1954-2005）, which are the boundaries of the upper reaches, the middle reaches, and the lower reaches of the Heihe River drainage basin, by wavelet analysis, wavelet neural network model, and GIS spatial analysis. The results show that： （1） annual runoff variations of the Yingluo Gorge have principal periods of 7 years and 25 years, and its increasing rate is 1.04 m^3/s.10y; （2） annual runoff variations of the Zhengyi Gorge have principal periods of 6 years and 27 years, and its decreasing rate is 2.25 m^3/s.10y; （3） prediction results show that： during 2006-2015, annual runoff variations of the Yingluo and Zhengyi gorges have ascending tendencies, and the increasing rates are respectively 2.04 m^3/s.10y and 1.61 m^3/s.10y; （4） the increase of annual runoff in the Yingluo Gorge has causal relationship with increased temperature and precipitation in the upper reaches, and the decrease of annual runoff in the Zhengyi Gorge in the past decades was mainly caused by the increased human consumption of water resources in the middle researches. The study results will provide scientific basis for making rational use and allocation schemes of water resources in the Heihe River drainage basin.

Spatial-temporal differences in in-stream flow requirement based on GIS： A case study of Yan＇an region, northern Shaanxi

Although water has the central function of the bloodstream in the biosphere especially in arid or semi-arid regions such as Yah＇an region in northwestern China, yet the very limited attention is paid to the role of the water-related processes in ecosystem. In this research, based on continuous nearly 50-year data including runoff volume, sediment discharge as well as sediment accretion from hydrographic stations, and 10-year information of water quality from pollution monitoring stations, the method for measuring in-stream flow requirement has been put forward supported by experiential models and GIS spatial analysis. Additionally, the changes of in-stream flow requirement for environment and economic development have been addressed from spatial-temporal dimensions. The results show that： （1） According to the central streams in Yan＇an region, mean annual in-stream flow requirement reaches 1.0619 billion m^3, and the surface water for economic exploitation is 0.2445 billion m3 （2） Mean annual in-stream flow requirement for sediment transfers in flood period occupies over 80% of the integrated volume in a year. （3） From the 1950s to 1970s, in-stream flow requirement for sediment transfers is comparatively higher, while from the 1980s to 1990s, this requirement presents a decreasing tendency.

Changes in Mediterranean Coastline According to the Coastal Type and Land Cover under Climate Change:The Case of South-east Spain

Coastline changes were analyzed considering the land cover types and the analysis of the causes that have deter­mined these changes during the past decades.Through the overlapping of aerial photographs and GIS analysis,the results showed that the land surface increased with respect to the previous stage,gaining terrain to the sea,but this increment was caused by anthropogenic processes.In fact,without human pressure,the land surface beside the coastal line would have decreased,especially on the sandy beaches and coastal dunes.Therefore,the beaches are one of the most vulnerable ecosystems and geomorphological systems due to erosion and lack of sediment supply associated with the modified river courses(i.e.by the construction of reservoirs,concrete channeling,etc.),the inner land use changes,and the effects of global warming on the sea level.Climate change studies predict specific increases in the sea level along the coast.The aim of this work is to know if anthropic activity can reverse the effects of sea level rise and coast­al erosion.In fact,it has been done for decades with measures aimed to correct impacts and favour economic activity(i.e.maintaining tourism resources)and not from the environmental issues.

Factors driving surface deformations in plain area of eastern Zhengzhou City,China

With the rapid socio-economic development and urban expansion,land subsidence has emerged as a major environmental issue,impeding the high-quality development of the plain area in eastern Zhengzhou City,Henan Province,China.However,effective prevention and control of land subsidence in this region have been challenging due to the lack of comprehensive surface deformations monitoring and the quantitative analysis of the factors driving these deformations.In order to accurately identify the dominant factor driving surface deformations in the study area,this study utilized the Persistent Scattered Interferometric Synthetic Aperture Radar(PS-InSAR)technique to acquire the spatio-temporal distribution of surface deformations from January 2018 to March 2020.The acquired data was verified using leveling data.Subsequently,GIS spatial analysis was employed to investigate the responses of surface deformations to the driving factors.The findings are as follows:Finally,the geographical detector model was utilized to quantify the contributions of the driving factors and reveal the mechanisms of their interactions.The findings are as follows:(1)Surface deformations in the study area are dominated by land subsidence,concentrated mainly in Zhongmu County,with a deformation rate of−12.5–−37.1 mm/a.In contrast,areas experiencing surface uplift are primarily located downtown,with deformation rates ranging from 0 mm to 8 mm;(2)Groundwater level,lithology,and urban construction exhibit strong spatial correlations with cumulative deformation amplitude;(3)Groundwater level of the second aquifer group is the primary driver of spatially stratified heterogeneity in surface deformations,with a contributive degree of 0.5328.The contributive degrees of driving factors are significantly enhanced through interactions.Groundwater level and the cohesive soil thickness in the second aquifer group show the strongest interactions in the study area.Their total contributive degree increases to 0.5722 after interactions,establishing them as the primary factors influencing surface deformation patterns in the study area.The results of this study can provide a theoretical basis and scientific support for precise prevention and control measures against land subsidence in the study area,as well as contributing to research on the underlying mechanisms.

Peatland area change in the southern Altay Mountains over the last twenty years based on GIS and RS analysis

Analyses results of total peatland area changes in the southern AItay Mountain region over the past 20 years are discussed in this paper. These analyses were based on remote sensing （RS） and geographical information system （GIS） studies. Possible control methods are evaluated by comparing these results to other regional records and climate data. The area of the peatland zones was calculated by overlaying a peatland layer of Landsat TM （Thematic Map） image constructed by using supervised classification with a layer of slope based on a digital elevation model （DEM）. The results show that slope layer is crucial to improving the accuracy of peatland extracted from TM images. The peatland area of the Altay Mountains increased from 931.5km^2 in 1990 to 977.7 km^2 in 2010. This trend is consistent with the climate change in this region, due in part to increasing temperatures and precipitation, suggesting possible climate controls on peatland expansion. The increase in the peatland area in the Altay Mountains over the last 20 years has been influenced by the westerlies. Alternatively, changes in the largest highland peatland area of the Zoige Basin, located in the eastern Tibetan Plateau have been influenced by the intensity of the Asian summer monsoons. In addition to increased temperatures, decreased precipitation in the Zoige Basin and increased precipitation in the Altay Mountains, due to varied patterns of atmospheric circulation, are the probable causes for driving the change differences in these two peatland areas.

Potential availability of non-woody biomass feedstock for pellet production within the Republic of Ireland

The threat of increasing fuel prices and climate change necessitates the need for clean,renewable and independent energy sources.A GIS(Geographical Information Systems)model was developed using ArcGIS 9.2 to analyze the availability of non-woody biomass(wheat,oat,barley and rape straw,willow and miscanthus)for pellet production in Ireland.Utilization within the heating and electricity sector would displace currently used fossil fuels with cleaner,carbon neutral non-woody residues.The aim of the analysis was to determine the total hectares of biomass within Ireland and compute the potential non-woody biomass yield.The greatest potential source of biomass for pelleting is cereal straw.Within the Republic of Ireland the South-East,South-West and Mid-East of Ireland have the greatest biomass yield for pellet production and likely to be most economically viable.Non-woody biomass has a realistic potential to displace fossil fuels within the heating and electricity sector resulting in CO2 mitigation.

Multi-identity planning process in a studio course： Integrative planning in multiidentity environments

The ptanning process in a planning studio demonstrates a microcosm of diverse concepts of ideotogies and identities seeking acknowtedgment and spatial recognition. In the modern world of muitipte and dynamic identities and ideologies, aspiring for the self-recognition of regions, towns, and communities, a place-based identity has become a core aspect that needs to be taken into planning consideration. The anatytic planning method used is iterative of both topdown and bottom-up approaches, thereby creating multi-dimension and coherent planning atternatives where spatial sotutions arise from communities along their changing processes. We present two spatiat atternative plans that were developed in the studio course and are based on this fine of thinking. Resutts were very dynamic aspiring complex plans, which are also highty appticable and flexible, thereby addressing a wide range of ideotogies and identities.

PyLUR:Efficient software for land use regression modeling the spatial distribution of air pollutants using GDAL/OGR library in Python

Land use regression(LUR)models have been widely used in air pollution modeling.This regressionbased approach estimates the ambient pollutant concentrations at un-sampled points of interest by considering the relationship between ambient concentrations and several predictor variables selected from the surrounding environment.Although conceptually quite simple,its successful implementation requires detailed knowledge of the area,expertise in GIS,statistics,and programming skills,which makes this modeling approach relatively inaccessible to novice users.In this contribution,we present a LUR modeling and pollution-mapping software named PyLUR.It uses GDAL/OGR libraries based on the Python platform and can build a LUR model and generate pollutant concentration maps efficiently.This self-developed software comprises four modules:a potential predictor variable generation module,a regression modeling module,a model validation module,and a prediction and mapping module.The performance of the newly developed PyLUR is compared to an existing LUR modeling software called RLUR(with similar functions implemented on R language platform)in terms of model accuracy,processing efficiency and software stability.The results show that PyLUR out-performs RLUR for modeling in the Bradford and Auckland case studies examined.Furthermore,PyLUR is much more efficient in data processing and it has a capability to handle detailed GIS input data.