remotely sensed imagery
A hybrid OSVM OCNN Method for Crop Classification from Fine Spatial Resolution Remotely Sensed Imagery
... recently, remotely sensed imagery from fine spatial resolution (FSR) (<10 m) satellite systems ...FSR imagery has fewer multispectral bands (around four) in comparison to medium resolution ...
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Multivariate texture based segmentation of remotely sensed imagery for extraction of objects and their uncertainty
... Most research on color texture focused on images of different materials with a clear texture. In standard color images, the pattern in different bands is often highly correlated. This makes it possible to summarize ...
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Quantifying river form variations in the Mississippi Basin using remotely sensed imagery
... Abstract. Geographic variations in river form are often es- timated using the framework of downstream hydraulic ge- ometry (DHG), which links spatial changes in discharge to channel width, depth, and velocity through ...
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Neural Network Combination by Fuzzy Integral for Robust Change Detection in Remotely Sensed Imagery
... networks for change detection in remotely sensed imagery. Our contribution was twofold. First, extensive experiments were carried out to obtain the optimal architectural selec- tion for the neural ...
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Spatial variability of mean daily estimates of actual evaporation from remotely sensed imagery and surface reference data
... higher-resolution imagery and surface reference data would be valuable to better examine potential impacts of local variations in evaporation on upscaled ...
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Investigating the Temporal and Spatial Distribution of Phragmites in River Canard using Remotely Sensed Imagery
... The main focus of this thesis was to delineate Phragmites stands within River Canard, and to assess the accuracy of the delineation process with the use of remote sensing imagery. This required using the ...
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Assessment of Urban Heat Island Using Remotely Sensed Imagery over Greater Cairo, Egypt
... In the absence and nonuniform distribution of ground weather stations, remotely sensed data have a great im- portance to monitor impacts of different environmental issues such as heat islands. The thermal ...
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Scaling effects on landscape function analysis of rangelands using remotely sensed imagery
... resolution imagery because of its 10m resolution and its capture on the same date at which the MODIS image was captured and a month from the nearest Landsat image capture ...MODIS imagery at both 250m and ...
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Scaling effects on landscape function analysis of rangelands using remotely sensed imagery
... Catchment and sub-catchments were defined from DEMs at scales matching the imagery. A high resolution DEM matching the SPOT resolution was extracted from an aerial photograph stereo model. The SRTM 1s DEM and the ...
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Using Boosted Regression Trees and Remotely Sensed Data to Drive Decision Making
... and remotely sensed ...spreadsheets, remotely sensed imagery stored as raster data, and vector data from a Geographic Infor- mation System (GIS), directly observed and measured data in ...
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Linking remote sensing, land cover and disease
... of imagery and landscapes, neural networks can provide the most accurate classification of land cover (Benediktsson et ...from remotely sensed data (Figure ...the remotely sensed ...
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Intelligent Methods Used for Obtaining Weather Derivatives: A Review
... from Remotely Sensed Imagery using an Artificial Neural Network Cloud Classification (PERSIANN-CCS) algorithm is modified by incorporation of LCE which involves segmentation of infrared cloud images ...
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A hybrid MLP CNN classifier for very fine resolution remotely sensed image classification
... for the classification of very fine spatial resolution VFSR remotely sensed imagery... The decision fusion rules, designed primarily based on the classification confidence.[r] ...
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QuakeSim: Integrated Modeling and Analysis of Geologic and Remotely Sensed Data
... must be focused on identifying and tackling grand challenges that span areas of expertise. Collaboration alone is not enough: the field needs a common framework designed to foster the desired connections. This is ...
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Multi Temporal Analysis of Remotely Sensed Information Using Wavelets
... methodology must separate changes in ecosystems into three frequency components: seasonal changes (e.g. suc- cession, seasonal precipitation), gradual changes (e.g. interannual temperatures tendencies, land degradation) ...
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Performance Analysis of K Means Clustering For Remotely Sensed Images
... Table 3: Accuracy of clustering by referring to ground truth data Distance Choosing of Initial Accuracy% Measure Centroid Sample 89.91% Square Uniform 95.55% Euclidean Cluster 88.88% Cit[r] ...
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Fast Registration of Remotely Sensed Images for Earthquake Damage Estimation
... multispectral remotely sensed images of the areas destroyed by an earthquake is proved to be a helpful tool for destruction ...for remotely sensed images and analyze its ...
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CLASSIFICATION OF REMOTELY SENSED IMAGE USING RELEVANCE VECTOR MACHINE
... a remotely sensed image classification method based on relevance vector machines ...the remotely sensed image are extracted and the classification is done[4] with the help of those ...
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Object Shadow Detection and Removal from Remotely Sensed Images
... Abstract— In accordance with the characteristics of urban high-resolution color remote sensing images, we put forward an object shadow detection and removal method from remotely sensed images. In object ...
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A REVIEW OF GEOTHERMAL MAPPING TECHNIQUES USING REMOTELY SENSED DATA
... Improvements in shallow (two-meter) temperature measurements and data interpretation. Geothermal Resources Council Transactions. Land surface temperature retrieval from L[r] ...
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