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131.
Sonali Saha Keith Bradley Michael S. Ross Phillip Hughes Thomas Wilmers Pablo L. Ruiz Chris Bergh 《Climatic change》2011,107(1-2):169-184
We investigate the effects of Hurricane Wilma??s storm surge (23?C24 October 2005) on the dominant tree Pinus elliottii var densa (South Florida slash pine) and rare plant species in subtropical pine rocklands of the Lower Florida Keys. We examine the role of elevation on species abundance in 1995 (Hurricane Betsy in 1965), 2005 (Hurricane Georges in 1998), and 2008 (Hurricane Wilma in 2005) to investigate if hurricanes influence abundance by eliminating plants at lower elevation on Big Pine Key, the largest island in the Lower Florida Keys. We compare densities before and after Hurricane Wilma over the 2005?C2008 sampling period and examine the role of elevation on changes in pine and rare species densities three years after Hurricane Wilma. We use elevation to assess the impact of hurricanes because elevation determined whether a location was influenced by storm surge (maximum surge of 2 m) in the Lower Florida Keys, where pine rocklands occur at a maximum elevation of 3 m. In 1995 (30 years after a major storm), elevation did not explain the abundance of South Florida slash pine or Chamaecrista lineata, but explained significant variation in abundance of Chamaesyce deltoidea. The latter two species are rare herbaceous plants restricted to pine rocklands. In 2008, 3 years after Hurricane Wilma, the positive relationship between elevation and abundance was strongest for South Florida slash pine, C. deltoidea, and C. lineata. Effects of Hurricane Wilma were not significant for rare species with wider distribution, occurring in plant communities adjacent to pine rocklands and in disturbed rocklands. Our results suggest that hurricanes drive population dynamics of South Florida slash pine and rare species that occur exclusively in pine rocklands at higher elevations. Rare species restricted to pine rocklands showed dramatic declines after Hurricane Wilma and were eliminated at elevations <0.5 m. Widely distributed rare species did not show significant changes in density after Hurricane Wilma. Abundance increased with elevation for South Florida slash pine and C. lineata after the hurricane. In an environment influenced by sea level rise, concrete plans to conserve pine ecosystems are warranted. Results from this study will help define conservation strategies by strengthening predictive understanding of plant responses to disturbance in the backdrop of sea level rise. 相似文献
132.
Yong Ge Sanping Li V. Chris Lakhan Arko Lucieer 《International Journal of Applied Earth Observation and Geoinformation》2009
The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic Mapper (TM) data classified by the Maximum Likelihood Classifier (MLC) and Fuzzy C-Means (FCM). The Landsat TM data are from the Yellow River Delta, Shandong Province, China. Image classification with MLC and FCM provides the probability vector and fuzzy membership vector of each pixel. Based on these vectors, the Shannon's entropy (S.E.) of each pixel is calculated. PCPs are then produced for each classification output. The PCP axes denote the posterior probability vector and fuzzy membership vector and two additional axes represent S.E. and the associated degree of uncertainty. The PCPs highlight the distribution of probability values of different land cover types for each pixel, and also reflect the status of pixels with different degrees of uncertainty. Brushing functionality is then added to PCP visualization in order to highlight selected pixels of interest. This not only reduces the visualization uncertainty, but also provides invaluable information on the positional and spectral characteristics of targeted pixels. 相似文献
133.
Qingmin Meng Chris Cieszewski Marguerite Madden 《ISPRS Journal of Photogrammetry and Remote Sensing》2009,64(1):27-36
Large area forest inventory is important for understanding and managing forest resources and ecosystems. Remote sensing, the Global Positioning System (GPS), and geographic information systems (GIS) provide new opportunities for forest inventory. This paper develops a new systematic geostatistical approach for predicting forest parameters, using integrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, GPS, and GIS. Forest parameters, such as basal area, height, health conditions, biomass, or carbon, can be incorporated as a response variable, and the geostatistical approach can be used to predict parameter values for uninventoried points. Using basal area as the response and Landsat ETM+ images of pine stands in Georgia as auxiliary data, this approach includes univariate kriging (ordinary kriging and universal kriging) and multivariable kriging (co-kriging and regression kriging). The combination of bands 4, 3, and 2, as well as the combination of bands 5, 4, and 3, normalized difference vegetation index (NDVI), and principal components (PCs) were used in this study with co-kriging and regression kriging. Validation based on 200 randomly sampling points withheld field inventory was computed to evaluate the kriging performance and demonstrated that band combination 543 performed better than band combination 432, NDVI, and PCs. Regression kriging resulted in the smallest errors and the highest R-squared indicating the best geostatistical method for spatial predictions of pine basal area. 相似文献
134.
A New Combined Assessment of Mixed Uncertainty in Spatial Models: Conceptualization and Implementation 下载免费PDF全文
Uncertainty quantification is not often performed in spatial modeling applications, especially when there is a mixture of probabilistic and non‐probabilistic uncertainties. Furthermore, the effect of positional uncertainty is often not assessed, despite its relevance to geographical applications. Although there has been much work in investigating the aforementioned types of uncertainty in isolation, combined approaches have not been much researched. This has resulted in a lack of tools for conducting mixed uncertainty analyses that include positional uncertainty. This research addresses the issue by first presenting a new, flexible, simulation‐oriented conceptualization of positional uncertainty in geographic objects called F‐Objects. F‐Objects accommodates various representations of uncertainty, while remaining conceptually simple. Second, a new Python‐based framework is introduced, termed Wiggly and capable of conducting mixed uncertainty propagation using fuzzy Monte Carlo simulation (FMCS). FMCS combines both traditional Monte Carlo with fuzzy analysis in a so‐called hybrid approach. F‐Objects is implemented within the Wiggly framework, resulting in a tool capable of considering any combination of: (1) probabilistic variables; (2) fuzzy variables; and (3) positional uncertainty of objects (probabilistic/fuzzy). Finally, a realistic GIS‐based groundwater contamination problem demonstrates how F‐Objects and Wiggly can be used to assess the effect of positional uncertainty. 相似文献
135.
Muhammad Al-Amin Hoque Stuart Phinn Chris Roelfsema Iraphne Childs 《International Journal of Digital Earth》2018,11(3):246-263
Tropical cyclones and their devastating impacts are of great concern to coastal communities globally. An appropriate approach integrating climate change scenarios at local scales is essential for producing detailed risk models to support cyclone mitigation measures. This study developed a simple cyclone risk-modelling approach under present and future climate change scenarios using geospatial techniques at local scales, and tested using a case study in Sarankhola Upazila from coastal Bangladesh. Linear storm-surge models were developed up to 100-year return periods. A local sea level rise scenario of 0.34?m for the year 2050 was integrated with surge models to assess the climate change impact. The resultant storm-surge models were used in the risk-modelling procedures. The developed risk models successfully identified the spatial extent and levels of risk that match with actual extent and levels within an acceptable limit of deviation. The result showed that cyclone risk areas increased with the increase of return period. The study also revealed that climate change scenario intensified the cyclone risk area by 5–10% in every return period. The findings indicate this approach has the potential to model cyclone risk in other similar coastal environments for developing mitigation plans and strategies. 相似文献
136.
137.
Agricultural Census data is summarised over spatially coarse reporting units for reasons of farm confidentiality. This is problematic for research at a local level. This article describes an approach combining dasymetric and volume preserving techniques to create a national land use dataset at 1 km2 resolution. The results for an English county are compared with contemporaneous aggregated habitat data. The results show that the accurate estimates of local agricultural land use (Arable and Grass) patterns can be estimated when individual 1 km squares are combined into blocks of > 9 squares, thereby providing local estimates of agricultural land use. This in turn allows more detailed modelling of land uses related to specific livestock and cropping activities. The dataset created by this work has been subject to extensive external validation through its incorporation into a number of other national models: nitrate leaching (e.g. MAGPIE, NEAP‐N), waste, and pathogen modelling related to agricultural activity. 相似文献
138.
Location-based services: technical and business issues 总被引:13,自引:0,他引:13
Geographical Information System (GIS) and Global Positioning System (GPS) technologies are expanding their traditional applications
to embrace a stream of consumer-focused, location-based applications. Through an integration with handheld devices capable
of wireless communication and mobile computing, a wide range of what may be generically referred to as 'Location-Based Services'
(LBS) may be offered to mobile users. A location-based service is able to provide targeted spatial information to mobile workers
and consumers. These include utility location information, personal or asset tracking, concierge and route-guidance information,
to name just a few of the possible LBS. The technologies and applications of LBS will play an ever increasingly important
role in the modern, mobile, always-connected society. This paper endeavours to provide some background to the technology underlying
location-based services, and to discuss some issues related to developing and launching LBS. These include whether wireless
mobile technologies are ready to support LBS, which mobile positioning technologies can be used and what are their shortcomings,
and how GIS developers manipulate spatial information to generate appropriate map images on mobile devices (such as cell phones
and PDAs). In addition, the authors discuss such issues as interoperability, privacy protection and the market demand for
LBS.
Electronic Publication 相似文献
139.
DAI LiwenHAN ShaoweiChris Rizos 《地球空间信息科学学报》2001,4(4):9-18
1 IntroductionReal_timekinematicGPSprecisepositioninghasbeenplayinganincreasingroleinbothsurveyingandnavigation ,andhasbecomeanessentialtoolforpreciserelativepositioning .However,reliableandcorrectambiguityresolutiondependsonobserva tionsuponalargenumbe… 相似文献
140.