high resolution images. Three satellite imagery systems which could supply the required data were the Landsat Multi-Spectral Scanner MSS; Landsat Thematic Mapper and SPOT MSS.
Land cover maps provide information to help managers best understand the current landscape. To see change over time, land cover maps for several different years are needed. With this
information, managers can evaluate past management decisions as well as gain insight into the possible effects of their current decisions before they are implemented.
2.1.2 Land cover classification system
The types of land cover categorization developed in the classification system can be related to systems for classifying land capability, vulnerability to certain management practices, and
potential for any particular activity or land value, either intrinsic or speculative. Anderson 1976 mentioned about a land cover classification system for use with remote sensor data. He
classified land cover
classification system what is shown in table 2.1.
Table 2.1 Land use and land cover classification system for use with remote sensor data
Level I Level II
1. Urban or Built-up Land 1.1. Residential
1.2. Commercial and Services 1.3. Industrial
1.4. Transportation, Communications, and Utilities 1.5. Industrial and Commercial Complexes
1.6. Mixed Urban or Built-up Land 1.7. Other Urban or Built-up Land
2. Agricultural Land 2.1. Cropland and Pasture
2.2. Orchards, Groves, Vineyards, Nurseries, and Ornamental Horticultural Areas
2.3. Confined Feeding Operations 2.4. Other Agricultural Land
3. Rangeland 3.1. Herbaceous Rangeland
3.2. Shrub and Brush Rangeland 3.3. Mixed Rangeland
4. Forest Land 4.1. Deciduous Forest Land
4.2. Evergreen Forest Land 4.3. Mixed Forest Land
5. Water 5.1. Streams and Canals
5.2. Lakes 5.3. Reservoirs
5.4. Bays and Estuaries
6. Wetland 6.1. Forested Wetland
6.2. Nonforested Wetland 7. Barren Land
7.1. Dry Salt Flats. 7.2. Beaches
7.3. Sandy Areas other than Beaches 7.4. Bare Exposed Rock
7.5. Strip Mines Quarries, and Gravel Pits 7.6. Transitional Areas
7.7. Mixed Barren Land
8. Tundra 8.1. Shrub and Brush Tundra
8.2. Herbaceous Tundra 8.3. Bare Ground Tundra
8.4. Wet Tundra 8.5. Mixed Tundra
9. Perennial Snow or Ice 9.1. Perennial Snowfields
9.2. Glaciers
Source: Anderson, 1976.
National Land Cover Dataset 1992 NLCD1992 is a 21 class land cover classification scheme that has been applied consistently across the lower 48 United States at a spatial
resolution of 30 meters. NLCD92 is based primarily on the unsupervised classification of Landsat Thematic Mapper TM circa 1990s satellite data. Other ancillary data sources used to
generate these data included topography, census, and agricultural statistics, soil characteristics, and other types of land cover and wetland maps. The classification system used for NLCD 92 is
modified from the Anderson land use and land cover classification system is shown in Table 2.2. Table 2.2
Land cover classification system
Level I Level II
1. Water 1.1. Open Water
1.2. Perennial IceSnow 2. Developed
2.1. Low Intensity Residential 2.2. High Intensity Residential
2.3. CommercialIndustrialTransportation
3. Barren 3.1. Bare RockSandClay
3.2. QuarriesStrip MinesGravel Pits 3.3. Transitional
4. Forested Upland 4.1. Deciduous Forest
4.2. Evergreen Forest 4.3. Mixed Forest
5. Shrubland 5.1. Shrubland
6. Non – Natural Woody
6.1. OrchardsVineyardsOther 7. Herbaceous Upland NaturalSemi
Natural Vegetation 7.1. GrasslandsHerbaceous
8. Herbaceous PlantedCultivated 8.1. PastureHay
8.2. Row Crops 8.3. Small Grains
8.4. Fallow 8.5. UrbanRecreational Grasses
9. Wetlands 9.1. Woody Wetlands
9.2. Emergent Herbaceous Wetlands Source: http:landcover.usgs.gov
A land cover classification system which can effectively employ orbital and high altitude remote sensor data should meet the following criteria Anderson, 1971:
1. The minimum level of interpretation accuracy in the identification of land use and land cover categories from remote sensor data should be at least 85 percent.
2. The accuracy of interpretation for the several categories should be about equal. 3. Repeatable or repetitive results should be obtainable from one interpreter to another and from
one time of sensing to another. 4. The classification system should be applicable over extensive areas.
5. The categorization should permit vegetation and other types of land cover to be used as surrogates for activity.
6. The classification system should be suitable for use with remote sensor data obtained at different times of the year.
7. Effective use of subcategories that can be obtained from ground surveys or from the use of larger scale or enhanced remote sensor data should be possible.
8. Aggregation of categories must be possible. 9. Comparison with future land use data should be possible.
10. Multiple uses of land should be recognized when possible.
2.2 Remote sensing
