No abstract

Amenity, Hedonic pricing, Landscape, View,

No abstract

Methods of interpolation, whether based on regressions or on kriging, are global methods in which all the available data for a given study area are used. But the quality of results is affected when the study area is spatially very heterogeneous. To overcome this difficulty, a method of local interpolation is proposed and tested here with temperature in France. Starting from a set of weather stations spread across the country and digitized as 250 m-sided cells, the method consists in modelling local spatial variations in temperature by considering each point of the grid and the n weather stations that are its nearest neighbours. The procedure entails a series of steps: recognition of the n stations closest to the cell to be evaluated and subdivision of the study area into polygons defined by a neighbourhood rule, elaboration of a local model by multiple regression for each polygon, and application of the parameter estimate from the regression to obtain a predicted value of temperature at each point of the polygon under consideration.These results are compared with results from three global interpolation methods: (1) regression, (2) ordinary kriging, and (3) regression with kriging of residuals. We then develop the original results from local interpolation such as mapping of the coefficients of determination and of the parameter estimate related to altitude and to distance to the sea. These developments highlight the processes that dictate the spatial variation of climate.

Vegetation and environmental data were collected at 266 sampling points distributed in a regular manner along transects covering the Brù ggerhalvù ya peninsula, on the north-western coast of Spitsbergen. Transects with sampling points were drawn in advance on aerial photographs. The analysis of releve  s and collection of ground data along transects represent an e cient, representative and precise way of sampling. The vegetation data were classi® ed and 19 plant communities distinguished. The plant communities were subjected to detrended correspondence analysis (DCA). Among the recorded variables, moisture is the one with the highest correlation along axes one and two, and re¯ects a coincidental moisture and vegetation cover gradient. The vegetation component responsible for this positive correlation is the bryophytes. Likewise, the TWINSPAN classi® cation con® rms this gradient in a dendrogram re¯ecting the hierarchical structure of the plant communities.Plant communities constitute the base of a statistical model that links the communities and the SPOT satellite data. The model then classi® es and maps plant communities by means of satellite data, covering the entire Brù ggerhalvù ya peninsula. Satellite data and environmental data were analysed regarding their ability to distinguish the plant communities in a discriminant function analysis (DFA). The results of the DFA indicate that it may be reasonable to include all the information from the di erent satellite channels when using satellite data for vegetation classi® cation purposes. Among the satellite data the panchromatic channel is the one adding the most unique information to the power of the model in separating plant communities.The classi® cation of satellite data using the probability model indicates that plant communities with less than 30% vegetation cover could be classi® ed with the same degree of con® dence or better, as compared with plant communities with more than 30% vegetation cover. The overall percentage of correctly classi-® ed releve  s increased by 13% when using probability level two instead of level one (57.8 to 71.1%). The probability classi® cation model makes it possible

A major environmental concern regarding the Arctic is how global change effects can influence vegetation and ecosystems. The amount of summer warmth is the single most important variable for biological processes in the Arctic, and the one that is most likely to be affected by climate change. A major task is to establish how temperature conditions are modified at a very high spatial resolution.In order to build up scenarios that are as relevant as possible concerning vegetation development, the key point is to know how the spatial distribution of temperature varies and can be related to different environment factors at different spatial scales. A method is suggested for modelling the temperature distribution at a high resolution (2 × 2 m 2 ) and with high accuracy. In step one, a polynomial equation is established for modelling the distribution of temperature values measured in the field at low spatial resolution (1 × 1 km 2 ), with latitude and longitude defining the general trend surface of the temperature distribution. In step two, residue values from the previous step are explained by environment factors stored as numerical information layers in a geographical information system. These environmental data are derived from a high-resolution digital elevation model and from a digitized infrared aerial photograph. Finally, the combination of these kilometric and micro-scale models make it possible to restore the thermic field of the study area and to represent it through different maps at a very fine-grained resolution. The method is tested on two glacier forefields in Svalbard, covering an area of 8 km 2 .

No abstract

The landscape. Three definitions, one mode of analysis and cartography. — Landscape involves three definitions to get of it a complete conceptual framework : it is a sign of acting forces system (divided in abiotic, biotic and anthropogenic subsystems), a more or less discerned mind-object for different user's categories, a sight considered as a scientific object and called "visible landscape". That leads to a specific methodology, the aim of which is to emphasize how objects are forming images. So, it is necessary to take in count the main following points : visible landscape inscribed in a volumnic space (R3) is to be projected on a mapping space (R2). On that basis, with the help of sampling photos, some procedures are suggested and attempted to geographical approaches; i.e. mainly : geographer's own sensitivity, visual content of landscape, spatial organization of landscape components.