Abstract: The coordination and development of ecological-living-industrial land uses are the premise foundations for the formulation and implementation of the current land space planning, and more attention should be paid to plateau mountainous areas. This research is based on spatial analysis technology and landscape pattern index method taking Yuxi city, a typical mountainous plateau as the research area. By using relevant software such as ArcGIS10.5, Fragstats 4.2 and the four remote sensing images of Yuxi city in 1980, 1995, 2005 and 2015, the temporal-spatial evolution and differentiation pattern of ecological-living-industrial land applications have been discussed. The research results show that: (1) From the perspective of land use type change, ecological land of Yuxi city has been the main source of land from 1980 to 2015, which totally occupies more than 78%. During this period, the spatial structure of the ecological-living-industrial land changed significantly, namely, the living land. Its land area increased significantly from 0.83% of the total area in 1980 to 1.25% in 2015, the change range of ecological land and industrial land is relatively small. (2) In terms of land use landscape pattern transfer matrix, from 1980 to 2015, the industrial land and ecological land in Yuxi city have been gradually transferred to living land. (3) In the aspect of landscape pattern changes, various landscape pattern indexes of Yuxi city indicate that the fragmentation degree of landscape pattern of the ecological-living-industrial land in this region is increasing. The degree of agglomeration goes down, and the landscape types have changed from being relatively simple to relatively rich. The landscape is more diverse, but the patch size is uneven, meanwhile, the integrity of the ecological space is destroyed.
Abstract: In this paper we introduce a novel method for
the characterization of synchronziation and coupling effects
in multivariate time series that can be used for the analysis
of EEG or ECoG signals recorded during epileptic seizures.
The method allows to visualize the spatio-temporal evolution
of synchronization and coupling effects that are characteristic
for epileptic seizures. Similar to other methods proposed for
this purpose our method is based on a regression analysis.
However, a more general definition of the regression together
with an effective channel selection procedure allows to use the
method even for time series that are highly correlated, which
is commonly the case in EEG/ECoG recordings with large
numbers of electrodes. The method was experimentally tested
on ECoG recordings of epileptic seizures from patients with
temporal lobe epilepsies. A comparision with the results from
a independent visual inspection by clinical experts showed
an excellent agreement with the patterns obtained with the
proposed method.