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Moreover, large microphone spacing may cause spatial aliasing.
In our case, the geographic clustering of narrowly distributed subspecies of P. polionotus may cause spatial autocorrelation and thus inflate AUC values (see Figure 4 and 5).
Genetically determined variations in cattle susceptibility, as well as between-farm variation in age-specific animal replacement probabilities are examples of population heterogeneity that may cause spatial clustering of BSE cases.
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This may cause many spatial design conflicts with other systems due to a lack of the third dimension in the design space, and lead to unnecessary overlapping of CCTV coverage.
The worsening of environmental conditions (i.e., increase of temperature and drought events) may cause large-spatial scale tree mortality and forest decline.
This hints at the presence of environmental gradients within aggregations that may cause small-scale spatial heterogeneity.
For instance, household socioeconomic characteristics may cause such local spatial variation.
Thus, the temporal context needs to be more emphasised; however it may cause the loss of spatial context because of the fixed-length context window scenario, which has been adopted in this paper for a fair comparison among different approaches, as discussed in Section 3.2.
This problem potentially takes two forms: short-term (minute scale) temporal autocorrelation that may contribute to violations of standard regression assumptions, and long-term (across a sampling shift) time trends that may cause difficulty in differentiating spatial from temporal trends.
Both methods account for spatial variation in population density, which may cause deviations from a completely random spatial point pattern.
Hence, the drop in spatial resolution may cause failure in detecting essential image structures.
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