Difference between revisions of "Import of kNN"
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| − | '''The ''k''NN-Sweden data''' consist of pixelwise estimates of forest states. A complete coverage is possible by using remotely sensed information, usually satellite image data. Sensors onboard, e.g., a SPOT satellite obtain spectral signatures in different wavelength bands (usually IR, R, G, and B) in each pixel, with a ground resolution approx. corresponding to 25 by 25 meters. Geo-referenced, previously inventoried NFI-plots will serve as reference data. In | + | '''The ''k''NN-Sweden data''' consist of pixelwise estimates of forest states. A complete coverage is possible by using remotely sensed information, usually satellite image data. Sensors onboard, e.g., a SPOT satellite obtain spectral signatures in different wavelength bands (usually IR, R, G, and B) in each pixel, with a ground resolution approx. corresponding to 25 by 25 meters. Geo-referenced, previously inventoried NFI-plots will serve as reference data. In a feature space, defined by the satellite image, the ''k'' Nearest Neighbours (usually with ''k'' = 10) are found among the reference plots. Estimations of volume, age, tree species composition, etc. are then derived as weighted mean values (e.g. weighted inversely proportional to the distance in the feature space). |
| − | However, such mean values are not sufficient for the long-term prognoses and the advanced forest management simulations to be analysed by the system. Single tree-data is here needed, preferably as a sample of plots with trees (or seedlings or saplings). | + | However, such mean values are not sufficient for the long-term prognoses and the advanced forest management simulations to be analysed by the system. Single tree-data is here needed, preferably as a sample of plots with trees (or seedlings or saplings). |