![]() ![]() The results of this study show a possibility of a simple but well-built image analysis procedure that can be followed in related research areas. Remote Sensing for the Characterization of Covers and Meteorological. IDRISI ERDAS ENVI ERMapper ArcGIS PCI Multispec. This study used MultiSpec software as a tool to find out a more accurate image. Kappa coefficient for this study is 0.94 which validate a good agreement as in the scale for Kappa a highly reliable range is in between 0.80 to 1.00. package that students in remote sensing classes could easily use on campus and/or their own personal computers to learn the fundamentals of remote sensing analyses. Geological remote sensing Vegetation studies Forest canopy research Water body studies. Each acquires one digital image (in remote. Usually, Earth observation satellites have three or more radiometers. Dividing the spectrum into many bands, multispectral is the opposite of panchromatic, which records only the total intensity of radiation falling on each pixel. In this study the confusion matrix gives 95.9% overall accuracy, Kappa Statistic of 94% and Kappa Variance of 0.000043 which in combine means a good statistical and scientifically reliable result for image classification. Most radiometers for remote sensing (RS) acquire multispectral images. Confusion Matrix is a key focus of this research as the table shows accuracy level, Kappa Statistic, actual & predicted classifications. It results from an on-going multiyear research effort which is intended to define robust and fundamentally based technology for analyzing multispectral and hyperspectral image data, and to transfer this technology to the user community in as rapid a manner as possible. This study followed the Maximum Likelihood classification procedure for image classification that assumes the statistics for each class in each band as normally distributed and calculates the probability of a given pixel belongs to a specific class. MultiSpec was employed to find out the classification which is a processing system for multispectral image data such as the one produced for the study area from Landsat image. LARSYS was one of the first remote sensing multispectral data processing systems. MultiSpec is a freeware multispectral image data analysis system (latest release. MultiSpec is intended for the analysis of multispectral image data. The broad objective of this study is to clarify an image classification system of LULC for the study area that can be explained easily with strong scientific justification. Education in remote sensing and GIS is based on software utilization. Image classification for land use/ land cover is an important tool for many policy planning and management activities related to human-environment relationship. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |