DEIGN
发表于 2025-3-21 16:13:15
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Arthr-
发表于 2025-3-21 23:09:30
Mark A. Friedl,Kenneth C. McGwire,Douglas K. McIver
Guaff豪情痛饮
发表于 2025-3-22 01:17:55
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Commentary
发表于 2025-3-22 05:11:28
The Use and Uncertainties of Spatial Data for Landscape Models: An Overview with Examples from the Fstribution of weather stations, kriging techniques, data collection errors, the influence of scale, or knowledge of meteorological models, yet these things and more are all factors that contribute to the spatial uncertainty of this .. These uncertainties become extremely important when one tries to
手段
发表于 2025-3-22 10:57:50
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Carcinoma
发表于 2025-3-22 14:59:39
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无可争辩
发表于 2025-3-22 20:09:20
An Overview of Uncertainty in Optical Remotely Sensed Data for Ecological Applicationsechnologies (e.g., radar, laser altimeter, and lidar systems, which provide detailed information regarding topography and vegetation structure in three dimensions) suggest that the use of remote sensing by ecologists is likely to increase in the future.
过于光泽
发表于 2025-3-22 23:05:29
Modeling Forest Net Primary Productivity with Reduced Uncertainty by Remote Sensing of Cover Type an forest growth assessment, is increasingly clear. For example, the models can be used to estimate stand or site net primary production (NPP) when the necessary information on species, soils, topography, and climate are available. Improved ecosystem process models in the future may replace empirical
COW
发表于 2025-3-23 04:28:38
Spatially Variable Thematic Accuracy: Beyond the Confusion Matrix1988a; Steele et al. 1998), and standard methods have not been adopted for presenting the spatial distribution of error in thematic maps. The confusion matrix is the most commonly accepted method for assessing the accuracy of thematic maps, but it is entirely devoid of spatial context. This chapter
改正
发表于 2025-3-23 09:36:07
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