The Knowledge-Based Analysis on Medium Resolution Images of Remote Sensing to Extraction Information Land use Type SCS-CN, the Case Study on Grompol Watershed

Remote sensing imagery Landsat-8 is one image that has a good temporal resolution; in addition to the availability of data, this image can be obtained free of charge. Land cover type SCS-CN is part of a unit of land that affects runoff. The use of medium resolution imagery in reducing the SCS-CN land use type is considered relatively difficult, and it yields less good accuracy. Limitations on multispectral classification only rely on facts derived from spectral reflection, so that the two data are the same since different characteristic results are not so good. This study aims to determine the accuracy of precision medium-resolution imagery in reducing parameter land use type SCS-CN by using the knowledge-based analysis. The importance of understanding the landscape-ecology can be used to assist the translation from land cover in the form of land use. Vegetation factors and ecosystems are often used to generate metrics-based landscape. Accuracy from the interpretation of remote sensing image medium-resolution is obtained by 85.17%. Therefore, Landsat-8, in addition to easy retrieval of data, can also be used to identify the type of land cover SCS-CN, which is useful for the interests of surface water resources.