Reading Lanyu's tourism landscape: Hybridity and identity on Orchid Island,Taiwan

This article analyses the creation and implications for cultural identity of a hybrid tourism landscape on Taiwan's Orchid Island (Lanyu). It particularly argues that Lanyu's native Tao people have begun to gain a somewhat stronger cultural identity and autonomy through this landscape. Orchid Island underwent rapid modernization within the past 60 years. The article not only shows how tourism was imposed by Taiwan's government, but also how the Tao have made greater use of tourism's landscape over time for their own purposes. Not without sociocultural problems and contradictions, Lanyu's tourism landscape has been polysemic enough to allow for gradually improving relationships between Taiwanese and Tao and for gradually increasing Tao participation in modernity on their own terms.     

旅游发展背景下周庄古镇物质文化景观变迁研究

近年来,古镇旅游发展迅猛.这一现象吸引了大批学者从不同角度对其进行了充分的研究,但关于古村镇文化景观变迁方面的研究不多,有必要弥补这一不足.利用文献分析、实地调研、遥感影像等研究方法,从文化学、历史学、地理学等角度深入探讨了周庄古镇的旅游景点的类型和分布,民居的功能和结构以及土地利用的总体特征和类型的变迁过程,指出周庄古镇文化景观的变迁受到旅游发展、经济发展、人口变动、政府干预、科技发展5种因素的影响.     

Calibrating cellular automata based on landscape metrics by using genetic algorithms

Landscape metrics have been widely used to characterize geographical patterns which are important for many geographical and ecological analyses. Cellular automata (CA) are attractive for simulating settlement development, landscape evolution, urban dynamics, and land-use changes. Although various methods have been developed to calibrate CA, landscape metrics have not been explicitly used to ensure the simulated pattern best fitted to the actual one. This article presents a pattern-calibrated method which is based on a number of landscape metrics for implementing CA by using genetic algorithms (GAs). A Pattern-calibrated GA–CA is proposed by incorporating percentage of landscape (PLAND), patch metric (LPI), and landscape division (D) into the fitness function of GA. The sensitivity analysis can allow the users to explore various combinations of weights and examine their effects. The comparison between Logistic- CA, Cell-calibrated GA–CA, and Pattern-calibrated GA–CA indicates that the last method can yield the best results for calibrating CA, according to both the training and validation data. For example, Logistic-CA has the average simulation error of 27.7%, but Pattern-calibrated GA–CA (the proposed method) can reduce this error to only 7.2% by using the training data set in 2003. The validation is further carried out by using new validation data in 2008 and additional landscape metrics (e.g., Landscape shape index, edge density, and aggregation index) which have not been incorporated for calibrating CA models. The comparison shows that this pattern-calibrated CA has better performance than the other two conventional models.     

ASSESSING THE ONSET OF SPRING: A CLIMATOLOGICAL PERSPECTIVE

This study is part of a program to examine spring plant-climate interactions in the major agricultural regions of eastern North America. The project's objectives were to: (1) document the yearly onset of the spring green wave and associated phenomena from 1908 to 1987 using phenological models, and (2) analyze regional dynamics and recent changes. Examining past variations in the green wave provides a context within which present and future variations can be assessed. Spring index dates, last -2.2°C (28°F) frost dates, and the difference between these two dates (termed the damage index) were generated for selected United States Daily Historical Climatology Network (HCN) stations between 1908 and 1987. The results show considerable geographic and temporal variations over the study period, and suggest that the threat of late spring frost damage may have decreased slightly from about 1960 to 1987. In future research, an improved version of the spring index (and associated surface phenological data) will be compared with satellite-derived vegetation condition data, in order to facilitate many kinds of atmosphere-biosphere interaction studies. [Key words: phenology, spring, “green wave” climatology.]     

Forest transition and biogeographic meaning of the current laurel forest landscape in Canary Islands,Spain

This study provides a geographical synthesis of the current natural landscape dynamics of the Canarian laurel forest based on the results of a biogeographic study of its structure, composition, and dynamics. Historical socioeconomic changes and recent environmental conservation strategies have led to natural forest dynamics that make it necessary to change our current scientific conception of the Canarian laurel forest landscape. According to the forest transition theory, in the protected areas of Anaga and Teno Rural Parks (Tenerife) and Garajonay National Park (La Gomera), the forest reaction to the gradual abandonment of economic activity reveals how strongly human activity has shaped the features of the laurel forest, which traditionally has been considered to be relatively untouched by humankind. How natural disturbances have affected this forest over the past few years has also contributed to a better understanding of its dynamics. This study explains the key patterns of spontaneous dynamics in the Canarian laurel forest to enrich our understanding of this forest and its landscape, while highlighting the importance of human activity as the catalyst for its current vigorous dynamics.     

Influence of landscape evolution on the distribution of floristic patterns in northern Amazonia revealed by δ13C data

The Amazonian lowlands include large patches of open vegetation which contrast sharply with the rainforest, and the origin of these patches has been debated. This study focuses on a large area of open vegetation in northern Brazil, where δ¹³C and, in some instances, C/N analyses of the organic matter preserved in late Quaternary sediments were used to achieve floristic reconstructions over time. The main goal was to determine when the modern open vegetation started to develop in this area. The variability in δ¹³C data derived from nine cores ranges from ?32.2 to ?19.6‰, but with nearly 60% of data above ?26.5‰. The most enriched values were detected only in ecotone and open vegetated areas. The development of open vegetation communities was asynchronous, varying between estimated ages of 6400 and 3000 cal a BP. This suggests that the origin of the studied patches of open vegetation might be linked to sedimentary dynamics of a late Quaternary megafan system. As sedimentation ended, this vegetation type became established over the megafan surface. In addition, the data presented here show that the presence of C₄ plants must be used carefully as a proxy to interpret dry paleoclimatic episodes in Amazonian areas. Copyright © 2012 John Wiley & Sons, Ltd.     

A review of assessment methods for cellular automata models of land-use change and urban growth

ABSTRACT

Cellular automata (CA) models are in growing use for land-use change simulation and future scenario prediction. It is necessary to conduct model assessment that reports the quality of simulation results and how well the models reproduce reliable spatial patterns. Here, we review 347 CA articles published during 1999–2018 identified by a Scholar Google search using ‘cellular automata’, ‘land’ and ‘urban’ as keywords. Our review demonstrates that, during the past two decades, 89% of the publications include model assessment related to dataset, procedure and result using more than ten different methods. Among all methods, cell-by-cell comparison and landscape analysis were most frequently applied in the CA model assessment; specifically, overall accuracy and standard Kappa coefficient respectively rank first and second among all metrics. The end-state assessment is often criticized by modelers because it cannot adequately reflect the modeling ability of CA models. We provide five suggestions to the method selection, aiming to offer a background framework for future method choices as well as urging to focus on the assessment of input data and error propagation, procedure, quantitative and spatial change, and the impact of driving factors.