DBpedia – Linked Data Fragments

Matches in DBpedia 2015-10 for { ?s ?p "Collocation is a procedure used in remote sensing to match measurements from two or more different instruments.This is done for two main reasons: for validation purposes when comparing measurements of the same variable, and to relate measurements of two different variables either for performing retrievals or for prediction.In the second case the data is later fed into some type of statistical inverse methodsuch as a neural network, statistical classification algorithm, kernel estimator or a linear least squares. In principle, most collocation problems can be solved by a nearest neighbor search,but in practice there are many other considerations involved and the best method ishighly specific to the particular matching of instruments.Here we deal with some of the most important considerations along with specific examples.There are at least two main considerations when performing collocations.The first is the sampling pattern of the instrument.Measurements may be dense and regular, such as those from a cross-trackscanning satellite instrument. In this case, some form of interpolationmay be appropriate. On the other hand, the measurements may besparse, such as a one-off field campaign designed for someparticular validation exercise.The second consideration is the instrument footprint, whichcan range from something approaching a point measurementsuch as that of a radiosonde, or it might be severalkilometers in diameter such as that of a satellite-mounted,microwave radiometer. In the latter case, it is appropriateto take into account the instrument antenna pattern whenmaking comparisons with another instrument having both a smallerfootprint and a denser sampling, that is, several measurementsfrom the one instrument will fit into the footprint of the other.Just as the instrument has a spatial footprint, it will also havea temporal footprint, often called the integration time.While the integration time is usually less than a second,which for meteorological applications is essentially instantaneous,there are many instances where some form of time averaging can considerablyease the collocation process.The collocations will need to be screened based on both the timeand length scales of the phenomenon of interest.This will further facilitate the collocation process since remote sensing and other measurement data is almost always binned in some way.Certain atmospheric phenomena such as clouds or convection are quite transientso that we need not consider collocations with a time error of more than an hour or so.Sea ice, on the other hand, moves and evolves quite slowly, so thatmeasurements separated by as much as a day or more might still be useful."@en }

• Collocation_(remote_sensing) abstract "Collocation is a procedure used in remote sensing to match measurements from two or more different instruments.This is done for two main reasons: for validation purposes when comparing measurements of the same variable, and to relate measurements of two different variables either for performing retrievals or for prediction.In the second case the data is later fed into some type of statistical inverse methodsuch as a neural network, statistical classification algorithm, kernel estimator or a linear least squares. In principle, most collocation problems can be solved by a nearest neighbor search,but in practice there are many other considerations involved and the best method ishighly specific to the particular matching of instruments.Here we deal with some of the most important considerations along with specific examples.There are at least two main considerations when performing collocations.The first is the sampling pattern of the instrument.Measurements may be dense and regular, such as those from a cross-trackscanning satellite instrument. In this case, some form of interpolationmay be appropriate. On the other hand, the measurements may besparse, such as a one-off field campaign designed for someparticular validation exercise.The second consideration is the instrument footprint, whichcan range from something approaching a point measurementsuch as that of a radiosonde, or it might be severalkilometers in diameter such as that of a satellite-mounted,microwave radiometer. In the latter case, it is appropriateto take into account the instrument antenna pattern whenmaking comparisons with another instrument having both a smallerfootprint and a denser sampling, that is, several measurementsfrom the one instrument will fit into the footprint of the other.Just as the instrument has a spatial footprint, it will also havea temporal footprint, often called the integration time.While the integration time is usually less than a second,which for meteorological applications is essentially instantaneous,there are many instances where some form of time averaging can considerablyease the collocation process.The collocations will need to be screened based on both the timeand length scales of the phenomenon of interest.This will further facilitate the collocation process since remote sensing and other measurement data is almost always binned in some way.Certain atmospheric phenomena such as clouds or convection are quite transientso that we need not consider collocations with a time error of more than an hour or so.Sea ice, on the other hand, moves and evolves quite slowly, so thatmeasurements separated by as much as a day or more might still be useful.".