40 resultados para SPRING-GIS
Resumo:
This paper presents a unique 517-yr long documentary data-based reconstruction of spring-summer (MAMJJ) temperatures for northern Switzerland and southwestern Germany from 1454 to 1970. It is composed of 25 partial series of winter grain (secale cereale) harvest starting dates (WGHD) that are partly based on harvest related bookkeeping of institutions (hospitals, municipalities), partly on (early) phenological observations. The resulting main Basel WGHD series was homogenised with regard to dating style, data type and altitude. The calibration and verification approach was applied using the homogenous HISTALP temperature series from 1774–1824 for calibration (r = 0.78) and from 1920–1970 for verification (r = 0.75). The latter result even suffers from the weak data base available for 1870– 1950. Temperature reconstructions based on WGHD are more influenced by spring temperatures than those based on grape harvest dates (GHD), because rye in contrast to vines already begins to grow as soon as sunlight brings the plant to above freezing. The earliest and latest harvest dates were checked for consistency with narrative documentary weather reports. Comparisons with other European documentarybased GHD and WGHD temperature reconstructions generally reveal significant correlations decreasing with the distance from Switzerland. The new Basel WGHD series shows better skills in representing highly climate change sensitive variations of Swiss Alpine glaciers than available GHD series.
Resumo:
Existing evidence of plant phenological change to temperature increase demonstrates that the phenological responsiveness is greater at warmer locations and in early-season plant species. Explanations of these findings are scarce and not settled. Some studies suggest considering phenology as one functional trait within a plant's life history strategy. In this study, we adapt an existing phenological model to derive a generalized sensitivity in space (SpaceSens) model for calculating temperature sensitivity of spring plant phenophases across species and locations. The SpaceSens model have three parameters, including the temperature at the onset date of phenophases (Tp), base temperature threshold (Tb) and the length of period (L) used to calculate the mean temperature when performing regression analysis between phenology and temperature. A case study on first leaf date of 20 plant species from eastern China shows that the change of Tp and Tb among different species accounts for interspecific difference in temperature sensitivity. Moreover, lower Tp at lower latitude is the main reason why spring phenological responsiveness is greater there. These results suggest that spring phenophases of more responsive, early-season plants (especially in low latitude) will probably continue to diverge from the other late-season plants with temperatures warming in the future.
Resumo:
Eine vom Centre for Develpment and Environment (CDE) der Universität Bern gestaltete Karte der südsudanesischen Region East Equatoria hat den „New Mapmaker Award 2009“ gewonnen. Der Preis wird gemeinsam von der britischen Kartografiegesellschaft und der amerikanischen National Geographic Society vergeben. Die im Rahmen eines Capacity-Development- Programms für Geoinformationsmanagement entworfene Karte wurde vollumfänglich in ArcMap aufgebaut, ohne Einsatz von Graphiksoftware.
Resumo:
GIS layers on Human-Elephant conflicts in Laikipia District: aerial counts, wildlife distribution, land-use, Human-Elephant conflicts hotspots and temporal patterns, and conflict deterrence activities
Resumo:
An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.