Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Modeling the spatial pattern of farmland using GIS and multiple logistic regression: a case study of Maotiao River Basin, Guizhou Province, China

Land use change is an important topic in the field of global environmental change and sustainable development. Land use change modeling has attracted substantial attention because it helps researchers understand the mechanisms of land use change and assists regulatory bodies in formulating relevant policies. Maotiao River Basin is located in the province of Guizhou, China, which has a developed agricultural industry in the karst mountain areas. This paper selected biophysical and social–economic factors as independent variables, and constructed a multiple logistic regression of farmland spatial distribution probability by random sampling. Then, by using GIS technology and integrating the 2000 data, this study predicted the farmland spatial pattern. When the predicted map was compared with the actual farmland map for 2000, we noted that 71% of the simulation is in accordance with the 2000 farmland pattern. The result satisfactorily proves the reasonability and applicability of our model.     

Study of Meteorological Aspects and Urban Concentration of SO2 in Atmospheric Environment of La Plata, Argentina

This article presents and discusses SO₂ (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO₂ measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO₂ concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO₂ average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO₂ reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.     

Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.     

2007—2017年三亚城市景观空间格局动态特征及驱动因素分析

应用2007—2017年期间4个时间点的遥感影像数据,选取典型景观格局指数,对三亚市的景观空间格局动态特征进行分析,探求其驱动因素。研究表明：近十年来,三亚市内同种土地利用类型的空间聚集程度降低,空间分布逐渐趋向于分散,不同类型的土地之间相互融合度较高,形状趋于复杂化,景观类型分布趋势呈均衡化,景观的破碎化程度加强,景观复杂程度增高,土地利用的丰富程度逐渐加强。通过驱动因素分析,国家政策的导向、城市总体规划的实施、产业结构调整及自然环境的变化是影响三亚城市景观空间格局变化的主要驱动因素。     

乌鲁木齐市土地利用景观格局变化研究

运用GIS、RS技术及景观生态学理论和方法,基于乌鲁木齐市2006年和2010年遥感影像解译数据,对乌鲁木齐市5年间土地利用景观格局变化特征进行分析,分别从斑块类型和景观水平2个方面对研究区土地利用景观类型进行动态分析。揭示其变化原因和内在规律,为研究区生态治理提供数据支撑,对景观的规划与管理、资源的有效利用和生物多样性保护具有重要意义。     

Characteristics and driving factors of marsh changes in Zhalong wetland of China

Zhalong National Nature Reserve in the northeast of China is a large wetland and a habitat of hundreds species of fauna and flora. The rare red-crowned crane is one kind of endangered birds in it. Recently, Zhalong wetland is shrinking and it encounters many problems including occasional fires, bad water quality, human activities, etc. In order to find out a proper way to protect and restore the wetland, this study, using a geographic information system, the global positioning system and remote sensing techniques, analyses the spatial characteristics of the changes in marsh landscape pattern and examines the driving factors for these changes. Data sources include 8 Landsat Thematic Mapper satellite images of Zhalong area in the period of 1986–2002 and the investigation information on site. Based on the analysis of changes of marsh area and annual precipitation during the 16 years, it is found that there is a close correlation between annual precipitation and marsh area. It means that climate is one of driving factors of marsh pattern changes. To understand influences of other kinds of land uses on marsh spatial distribution in Zhalong wetland, this paper analyses the relationship between marsh and different kinds of land uses, such as water surface, residential area, farmland, salina land and grass land, respectively. According to the patch analysis theory, a fragmental index and a fractal dimension of the marsh are calculated with perimeter-area method. The results indicate that the marsh pattern is affected by human activities significantly. In addition, the location alteration of marsh centroid point over the 16 years is studied. The movement trace of marsh centroid point is concerned with different hydrological situation in different areas of the wetland. In summary the characteristics of the marsh landscape pattern evolution during the 16 years are affected by multiple driving factors. The main driving factors are climate, human activities, distribution of other kinds of land uses and hydrological situation in different areas.     

我国循环经济的发展模式

循环经济发展模式主要是指循环经济的产业发展模式和区域发展模式。根据我国循环经济的内涵、国际做法和国内相关实践探索经验,我国循环经济的产业发展模式涉及生产和消费两个重点领域和四个重点产业。四个重点产业是生态工业、生态农业、绿色服务业和废弃物再利用、资源化及无害化处置产业。循环经济区域发展模式是在区域基础设施体系和生态系统支撑下的两个重点领域和四个重点产业的有机组合和共生。是区域可持续发展的核心组成部分。区域基础设施体系也是应用循环经济原理的重要领域。以资源能源离效和环境影响最小为特征。在目前的实践中。我国出现了三种将发展循环经济作为推动区域可持续发展的助推器而引发的区域社会经济发展战略转型模式：东部发达地区的自发转型模式、辽宁资源型地区的转型模式和西部地区典型的跨越发展转型模式。     

泰州市建设用地扩展规律与格局演化研究

以多时相Landsat、TM/ETM卫星影像为数据源,运用GIS软件提取泰州市建设用地1988～2008年5个时相的用地信息,运用扩展强度指数、扩展速度指数、空间自相关等方法分析泰州市建设用地扩展时空特征和演化规律。结果表明:(1)泰州建设用地扩展经历了缓慢扩展、中速扩展、缓慢扩展3个阶段,显示了建设用地逐步走向集约利用的趋势;(2)在分析泰州建设用地不同扩展阶段的基础上,发现泰州建设用地扩展模式正处于从点状扩展向点轴扩展转变阶段,并出现了网络化扩展的端倪;(3)运用空间自相关分析了泰州建设用地扩展热点演化过程,发现扩展热点呈现跳跃迁移的特征,热点区与冷点区出现交替演化,Moran散点图体现了泰州市建设用地扩展处于空间极化的状态,外围城镇受中心城镇增长极带动发展的扩展模式。