图像的比例尺与分辨率 Aerial photographs:Mapmakers have come to associate the type of information that can be reliably extracted from aerial photographs with the photographic scale. Digital satellite imagery:GSD GSI GIFOV 11
11 图像的比例尺与分辨率 Aerial photographs: Mapmakers have come to associate the type of information that can be reliably extracted from aerial photographs with the photographic scale. Digital satellite imagery: GSD / GSI / GIFOV UESTC-RSIP
Classification:Critical Point LAND COVER not necessarily equivalent to LAND USE We focus on what's there:Land Cover Many users are interested in how what's there is being used:Land use 分 Example: Grass is land cover,pasture and recreational parks are land uses of grass 12
12 Classification: Critical Point LAND COVER not necessarily equivalent to LAND USE We focus on what’s there: Land Cover Many users are interested in how what’s there is being used: Land use Example: Grass is land cover; pasture and recreational parks are land uses of grass UESTC-RSIP
Spectral or Information Classes When talking about classes,we need to distinguish between Information classes Spectral classes 13
13 Spectral or Information Classes ? • When talking about classes, we need to distinguish between – Information classes – Spectral classes UESTC-RSIP
Information Spectral Classes Information classes are those categories of interest that the analyst is actually trying to identify in the imagery,such as: different kinds of crops,different forest types or tree species, different geologic units or rock types,etc. Spectral classes are groups of pixels that are uniform (or near- similar)with respect to their brightness or reflectance values in the different spectral channels of the data. The objective is to match the spectral classes in the data to the information classes of interest
Information & Spectral Classes • Information classes are those categories of interest that the analyst is actually trying to identify in the imagery, such as: different kinds of crops, different forest types or tree species, different geologic units or rock types, etc. • Spectral classes are groups of pixels that are uniform (or nearsimilar) with respect to their brightness or reflectance values in the different spectral channels of the data. • The objective is to match the spectral classes in the data to the information classes of interest. UESTC-RSIP
Land-cover classification system LEVEL I CLASSES LEVEL IⅡCLASSES Water 11 Open Water 12 Perennial Ice/Snow Developed 21Low Intensity Residential 22 High Intensity Residential 23 Commercial/Industrial/Transportation Barren 31 Bare Rock/Sand/Clay 32 Quarries/Strip Mines/Gravel Pits 33 Transitional Forested Upland 41 Deciduous Forest 42 Evergreen Forest 43 Mixed Forest Shrubland 51 Shrubland Non-Natural Woody 61 Urchards/Vineyards/Other Herbaceous Upland Natural/Semi-natural Vegetation 71 Grasslands/Herbaceous Herbaceous Planted/Cultivated 81 Pasture/Hay 82 Row Crops 83 Small Grains 84 Fallow 85 Urban/Recreational Grasses Wetlands 91 Woody Wetlands 92 Emergent Herbaceous Wetlands
15 Land-cover classification system UESTC-RSIP