From the past epoch, there have been great hard work and researches are undertaken for mounting land-cover classification in data mining. Whereas the essential uses of the remotely-sensed images is for mainly land-cover classification, for the purpose of applications like monitoring the forest and agricultural areas. Through remote sensing technology an extensive diversity of digital imagery is...

YUAN, HUI. Development and Evaluation of Advanced Classification Systems using Remotely Sensed Data for Accurate Land-Use/Land-Cover Mapping. (Under the direction of Dr. Siamak Khorram.) Our general objective in this research was to design, develop, implement, and evaluate advanced classification approaches for more accurate land-use/land-cover mapping using remotely sensed data. The overall re...

Inventories of past and present land cover changes form the basis for future conservation strategies and landscape management. In this study Landsat images of a mountainous area in Mexico are used in an objectbased and pixel-based image classification. The land cover categories with the highest individual classification accuracies determined with these two methods are extracted and merged into ...

Accurate mapping of land cover on a regional scale is useful for climate and environmental modeling. In this study, we present a novel land cover classification product based on spectral and phenological information for the Xinjiang Uygur Autonomous Region (XUAR) in China. The product is derived at a 500 m spatial resolution using an innovative approach employing moderate resolution imaging spe...

This article discusses how computational intelligence techniques are applied to fuse spectral images into a higher level image of land cover distribution for remote sensing, specifically for satellite image classification. We compare a fuzzy-inference method with two other computational intelligence methods, decision trees and neural networks, using a case study of land cover classification fro...

In this study, a survey of land cover mapping and their classification techniques is done. Land cover mapping plays a very important role in making land policy, land management and land analysis. In this survey different approaches are studied that were applied for land cover mapping such as an Artificial Neural Network (ANNs), Fuzzy Logic, Supervised, Unsupervised and Maximum Likelihood. The o...

Land cover type is a crucial parameter that is required for various land surface models that simulate water and carbon cycles, ecosystem dynamics, and climate change. Many land use/land cover maps used in recent years have been derived from field investigations and remote-sensing observations. However, no land cover map that is derived from a single source (such as satellite observation) proper...

The main objective of this project was to derive digital land use and land cover information from satellite remote sensing data for Connecticut, Long Island, and those watersheds contributing to Long Island Sound. In doing so, four methods of land use and land cover classification were evaluated on two test quadrangles to determine which method was best suited, in terms of time and costs balanc...