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51.
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. 相似文献
52.
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. 相似文献
53.
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 = PM2.5). 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. PM2.5, 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 PM2.5 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 PM2.5 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. PM2.5/PM10 values were also calculated to determine PM2.5 contribution. At Satna, PM2.5 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, PM2.5, 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. 相似文献
54.
Temporal Trends in the Spatial Distribution of Impervious Cover Relative to Stream Location
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J. Wickham A. Neale M. Mehaffey T. Jarnagin D. Norton 《Journal of the American Water Resources Association》2016,52(2):409-419
Use of impervious cover is transitioning from an indicator of surface water condition to one that also guides and informs watershed planning and management, including Clean Water Act (33 U.S.C. §1251 et seq.) reporting. Whether it is for understanding surface water condition or planning and management, impervious cover is most commonly expressed as summary measurement (e.g., percentage watershed in impervious cover). We use the National Land Cover Database to estimate impervious cover in the vicinity of surface waters for three time periods (2001, 2006, 2011). We also compare impervious cover in the vicinity of surface waters to watershed summary estimates of impervious cover for classifying the spatial pattern of impervious cover. Between 2001 and 2011, surface water shorelines (streams and water bodies) in the vicinity of impervious cover increased nearly 10,000 km. Across all time periods, approximately 27% of the watersheds in the continental United States had proximally distributed impervious cover, i.e., the percentage of impervious cover in the vicinity of surface waters was higher than its watershed summary expression. We discuss how impervious cover spatial pattern can be used to inform watershed planning and management, including reporting under the Clean Water Act. 相似文献
55.
综合运用变异系数、泰尔指数及ESDA-GIS多种方法,在充分考虑传统经济影响因子的基础上,尝试引入经济发展生态成本指标,分析长江中游城市群经济综合发展水平与生态成本的空间匹配及演化模式。研究表明:经济综合发展水平高低聚集特征明显,空间极化现象是导致区域经济发展不平衡的主要原因;生态成本空间集聚现象以高高集聚和低低集聚为主,且呈现出高高集聚减少、低低集聚增多的现象,生态成本消耗有所改善;2001~2012年长江中游城市群市域经济综合发展水平与生态成本表现出越来越显著的差异化空间格局,呈现出由低经济综合发展水平-低生态成本过渡到高经济综合发展水平-高生态成本,进而发展到高经济综合发展水平-低生态成本的空间匹配模式的阶段性特征;高经济综合发展水平-高生态成本的经济发展模式仍在大部分城市中存在,经济与生态空间协调发展的潜力仍然很大。 相似文献
56.
基于GIS的乌梁素海水体富营养化状况的模糊模式识别 总被引:14,自引:7,他引:7
利用基于MATLAB 7.0实现的模糊模式识别交叉迭代模型对2006年5—10月分布于乌梁素海各水体功能区的21个水质监测点的富营养化等级进行了模糊模式识别,并在GIS技术支持下,用Arcview的空间分析功能绘制富营养化等级识别结果、对富营养化状态影响权重最大的评价指标总氮(TN)含量和富营养化状态控制元素总磷(TP)含量对应的富营养化等级水体和地表水质等级水体的空间分布月变化Grid专题图.将富营养化状态变化及其分布区域与乌梁素海同期水质监测指标浓度变化及其分布区域进行对比分析及验证.结果表明,富营养化等级识别结果的时空分布与实际情况相符,能够比较准确地反映富营养化等级定量的时空变化趋势. 相似文献
57.
58.
59.
Bryan BA 《Environmental management》2006,37(1):126-140
The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC)
for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions
has become the search for the best classification that optimally trades off classification complexity for class homogeneity.
In this study, three techniques are investigated for their ability to find the best classification of the physical environments
of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network,
and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally
trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free
because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that
there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity
acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract
parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure
and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing
Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information
upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive
classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure
of the landscape and to use this knowledge to select the best ELC at the required scale of analysis. 相似文献
60.
Assessing Impacts of Typhoons and the Chi-Chi Earthquake on Chenyulan Watershed Landscape Pattern in Central Taiwan Using Landscape Metrics 总被引:3,自引:1,他引:2
The Chi-Chi earthquake (ML = 7.3) occurred in the central part of Taiwan on September 21, 1999. After the earthquake, typhoons Xangsane and Toraji produced
heavy rainfall that fell across the eastern and central parts of Taiwan on November 2000 and July 2001. This study uses remote
sensing data, landscape metrics, multivariate statistical analysis, and spatial autocorrelation to assess how earthquake and
typhoons affect landscape patterns. It addresses variations of the Chenyulan watershed in Nantou County, near the earthquake’s
epicenter and crossed by Typhoon Toraji. The subsequent disturbances have gradually changed landscape of the Chenyulan watershed.
Disturbances of various types, sizes, and intensities, following various tracks, have various effects on the landscape patterns
and variations of the Chenyulan watershed. The landscape metrics that are obtained by multivariate statistical analyses showed
that the disturbances produced variously fragmented patches, interspersed with other patches and isolated from patches of
the same type across the entire Chenyulan watershed. The disturbances also affected the isolation, size, and shape-complexity
of patches at the landscape and class levels. The disturbances at the class level more strongly affected spatial variations
in the landscape as well as patterns of grasslands and bare land, than variations in the watershed farmland and forest. Moreover,
the earthquake with high magnitude was a starter to create these landscape variations in space in the Chenyulan watershed.
The cumulative impacts of the disturbances on the watershed landscape pattern had existed, especially landslides and grassland
in the study area, but were not always evident in space and time in landscape and other class levels. 相似文献