This paper presents fast and effective filtering techniques for image enhancement from remote sensing Indian remote sensing satellite P6 Liss IV remotely sensed data like Near-Infrared band. There are four filtering techniques used for image enhancement based on spatial domain filters and frequency domain filters such as median filter, wiener filter, bilateral filter and Gaussian homomorphic fi...

Because of the increasing amount of remotely sensed imagery there is a growing need for efficient data analysis techniques. Here to automate the image interpretation a knowledge based approach is suggested. The presented scene interpretation system AIDA uses semantic nets for the explicit representation of the prior knowledge about objects expected in the scene. It exploits the knowledge base t...

Within-class spectral variation and between-class spectral confusion in remotely sensed imagery degrades the performance of built-up area detection when using planar texture, shape, and spectral features. Terrain slopes and building heights extracted from auxiliary data, such as Digital Surface Models (DSMs) however, can improve the results. Stereo imagery incorporates height information unlike...

structural analysis of remotely sensed data provides a method of assessing the structural significance of large-magnitude regional metallogenesis in the kerman porphyry cu belt in the southern part of the central iranian volcanic belt. the role of large-magnitude ring structures in the distribution of hydrothermal alteration zones and porphyry copper deposits in the southern part of the kerman ...

EMPs Extended morphological profiles EMPs Extended morphological profiles LDA Linear discriminant analysis LogDA Logarithmic discriminant analysis MLR Multinomial logistic regression MLRsubMRF Subspace-based multinomial logistic regression followed by Markov random fields MPs Morphological profiles MRFs Markov random fields PCA Principal component analysis QDA Quadratic discriminant analysis RH...

Natural disasters can severely impact transportation networks. In the hours and days following a major flooding event, knowing the location and extent of the damage is crucial for incident managers for a number of reasons: it allows for emergency vehicle access to affected areas; it facilitates the efficient rerouting of traffic; it raises the quality and reduces the cost of repairs; and it all...

Researchers at the University of Arizona are investigating the potential of remotely sensed data, using aerial video, to enhance existing data sources and therefore to improve traffic management. This research has developed new methods for both data collection and image processing of remotely sensed data. While the use of remotely sensed data to monitor traffic flows is not new, this research i...

GIS, remote sensing and Global positioning System are the most widely useful tools for land use planning and decision support system. Remotely sensed imagery is beneficial for agricultural production. It gives the accurate information of agricultural activities such as different crop identification and classification, crop condition monitoring, crop growth, crop area and yield estimation, mappi...

The efficiency of national forest monitoring efforts can be increased by the judicious incorporation of ancillary data. For instance, a fixed number of ground plots might be used to inform a larger set of annual estimates by observing a smaller proportion of the plots each year while augmenting each annual estimate with ancillary data in order to reduce overall costs while maintaining a desired...

The AnnAGNPS pollution model uses evapotranspiration as one of the inputs to predict runoff, sediment, nutrients, and pesticide contributions from land to streams. This modeling tool has been modified to accept evapotranspiration estimates derived from remotely sensed imagery, produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. This research evaluated the next generati...