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• W2088323889 abstract "Abstract Given the increasing rate of landscape change, researchers have realized that managing natural resources sustainably requires knowledge about ecosystems over more than one temporal and spatial scale. Monitoring ecosystem integrity implies sampling over long periods of time and space to identify any significant changes. Subsequently, remote sensing has become integral to many large-scale monitoring efforts. Nonetheless, there remain aspects related to scaling which limit the ability to detect landscape change with a maximal amount of inference. While successive analyses can be used to estimate errors, it is not clear how spatial reorganization resulting from scaling has diluted the signal of the processes embodied within the observed patterns. To achieve a maximal amount of inference, it is first necessary to match three scales: spatial heterogeneity, the scales of the ecological processes creating landscape heterogeneity, and the spatial and temporal resolutions of the image used in the analysis...." @default.
• W2088323889 created "2016-06-24" @default.
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• W2088323889 date "2000-06-01" @default.
• W2088323889 modified "2023-09-26" @default.
• W2088323889 title "Landscape Heterogeneity Effects on Scaling and Monitoring Large Areas Using Remote Sensing Data" @default.
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• W2088323889 doi "https://doi.org/10.1080/10824000009480534" @default.
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