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This higher resolution land use classification allows investigation of hydrologic fluxes in pasture‐sized parcels on the ranch.
The classification approach builds on random forest classification with learning data extracted from higher resolution land cover maps.
The 100-meter resolution land cover data were developed to portray the land cover of the United States at 1 1,000,000 scale.
Two applied assessments of these data are also explored to examine the strengths and limitations of these alternate sources of moderate resolution land imagery with specific application domains.
A need also exists for data sets and methods that link ground-based observations of phenology to moderate resolution land surface phenology products.
In this paper, we propose a fully automated rule-based algorithm to develop a 1 m resolution land cover classification from LiDAR data and multispectral imagery.
Similar(35)
A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data.
Erb, K.-H. et al. A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data.
A 1 m resolution land-cover map is used to calculate land architecture metrics at the parcel level, and 6.8 m resolution MODIS/ASTER data are employed to retrieve LST.
When forced to prioritize in future studies, obtaining complete traffic data would therefore be preferred over obtaining higher resolution land-use data.
We performed a multivariate calibration of the large-scale information in the proxy data network (documentary evidence, natural proxies) against 20th century gridded (0.5° resolution) land-based meteorological data (CRU TS3.0).
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