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ABSTRACT CLASSIFICATION OF LAND USE LAND COVER CHANGE DETECTION USING REMOTELY SENSED DATA
"... Image classification is perhaps the most important part of digital image analysis. With supervised classification, the information classes of interest like land cover type image. These are called “training sites”. The image processing software system is then used to develop a statistical characteriz ..."
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. The profusion information of the earth surface offered by the high resolution satellite images for remote sensing applications. Using change detection methodologies to extract the target changes in the areas from high resolution images and rapidly updates geodatabase information processing.
Application of the MODIS global supervised classification model to vegetation and land cover mapping of central America.
- International JournalofRemoteSensing,21(6–7),
, 2000
"... Abstract. While mapping vegetation and land cover using remotely sensed data has a rich history of application at local scales, it is only recently that the capability has evolved to allow the application of classi cation models at regional, continental and global scales. The development of a compr ..."
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Cited by 11 (2 self)
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Abstract. While mapping vegetation and land cover using remotely sensed data has a rich history of application at local scales, it is only recently that the capability has evolved to allow the application of classi cation models at regional, continental and global scales. The development of a
Land-use
"... a b s t r a c t Over the last few decades, dramatic land-use changes have occurred throughout Israel. Previously-grazed areas have been afforested, converted to irrigated or rain-fed agriculture, turned into natural reserves, often used as large military training sites, converted to rural and urban ..."
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changes and lack of regard to rangelands in existing land-use maps, there is a need for creating a current land-use information database, to be utilized by planners, scientists, and decision makers. Remote-sensing (RS) data are a viable source of data from which land-use maps could be created and updated
Application of Self Organizing Maps to multi-resolution and multi-spectral remote sensed images
"... Abstract. In this paper we investigate the performance of the Koho-nen’s self organizing map (SOM) as a strategy for the analysis of multi-spectral and multi-resolution remote sensed images. The paper faces the problem of data fusion, by extracting and combining multi-spectral and textural features. ..."
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Abstract. In this paper we investigate the performance of the Koho-nen’s self organizing map (SOM) as a strategy for the analysis of multi-spectral and multi-resolution remote sensed images. The paper faces the problem of data fusion, by extracting and combining multi-spectral and textural features
Remote Sensing of Nearshore Vegetation in Washington State's Puget Sound
"... The Washington State Department of Natural Resources, in cooperation with other state and federal agencies, has developed a program to remotely sense nearshore vegetation (intertidal and shallow subtidal). The classified nearshore data are integrated into an existing geographic information system fo ..."
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for spatial analysis to support aquatic land use planning and management decisions. In 1996, a data set for the greater Bellingham Bay area in Northern Puget Sound was completed. Program methods incorporate advances in remote sensing technologies to overcome the constraints of the target geography, which
EXTRACTION AND CLASSIFICATION OF WETLAND FEATURES THROUGH FUSION OF REMOTE SENSING IMAGES IN THE OKAVANGO DELTA, BOTSWANA
"... The Okavango delta in northwestern Botswana is an extremely complex and dynamic wetland ecosystem. The spatial information on diverse wetland features of the delta is needed for hydrological modeling and water resources management. Due to large size and inaccessibility of the delta, satellite images ..."
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images provide the only viable means to reliably map and measure these features. For better identification and delineation of these features in the Okavango delta, efficient image analysis techniques are needed. The synergistic use of images from different sensors with varied spatial and spectral
Also: to be published on Information Fusion Combining Parametric and Non-parametric Algorithms for a Partially Unsupervised
, 2002
"... Abstract. In this paper, we propose a classification system based on a multiple-classifier architecture, which is aimed at updating land-cover maps by using multisensor and/or multisource remote-sensing images. The proposed system is composed of an ensemble of classifiers that, once trained in a sup ..."
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Abstract. In this paper, we propose a classification system based on a multiple-classifier architecture, which is aimed at updating land-cover maps by using multisensor and/or multisource remote-sensing images. The proposed system is composed of an ensemble of classifiers that, once trained in a
CLASS BASED RATIOING EFFECT ON SUB-PIXEL SINGLE LAND COVER AUTOMATIC MAPPING Anil Kumar 1*a, Suresh Saggar b,
"... Sub-pixel based digital image classification outputs from coarse spatial resolution remote sensing images can be closer to ground information as compared to hard classification outputs. This has been proven from work published by different researchers in last decade. In sub-pixel based classificatio ..."
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Sub-pixel based digital image classification outputs from coarse spatial resolution remote sensing images can be closer to ground information as compared to hard classification outputs. This has been proven from work published by different researchers in last decade. In sub-pixel based
Multi-level Land Cover Mapping of the Twin Cities (Minnesota) Metropolitan Area
"... Land cover maps, especially vegetation maps, are of increasing interest and use to resource agencies. This paper describes a three-stage hybrid classification method for regional-scale multi-level land cover mapping. The first stage involves an unsupervised classification and stratification. The sec ..."
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Cited by 4 (0 self)
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. The second stage includes supervised classification of forest types, rule-based clustering of non-forested vegetation, and estimation of percent impervious area with a regression model. The third stage is final map generation and post processing. Landsat TM/ETM+ images of three (spring, summer, fall) dates
AUTOMATED CONSTRUCTION OF LEGEND FOR LAND COVER CLASSIFICATION OF ADEOS-II GLI IMAGE
"... ABSTRACT Automated classification of land cover by ADEOS-II GLI data is one of the research topics in the framework of NASDA ADEOS-II RA released in 1996. The authors carry out this research as pre-launch algorithm development for classification of Global Imager (GLI) data. One of the issues of auto ..."
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have developed a method for automated construction of legend based on existing information on land cover categories. This method requires GLI dataset and land cover map, which was compiled by any of conventional, or remote sensing (visual interpretation, supervised or unsupervised classification
Results 1 - 10
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