Remotely Sensed Data
Object tracking in remotely sensed data
... in remotely sensed data Henke, Daniel Abstract: Die Fernerkundung ist heutzutage eine der wertvollsten Methoden, um verschiedenste grossräu- mige Phänomene und Prozesse konsistent, repetitiv und ...
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Meeting the challenge of mapping peatlands with remotely sensed data
... 5. Remotely sensed data provides a globally consistent source of information from which a globally consistent and spatially explicit data on distribution of peatlands can be ...
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Multimodal learning from visual and remotely sensed data
... visual data at feature learning time leads to better remote sensing features, which enables more accurate, large-scale semantic ...the remotely sensed data, which enables multimodal queries ...
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VISUALIZATION OF A CROP SEASON THE INTEGRATION OF REMOTELY SENSED DATA AND SURVEY DATA
... OF REMOTELY SENSED DATA AND SURVEY DATA The 1999 crop season displayed some good examples of geographic variability due to weather ...survey data provides a good visual illustration of ...
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Development and Assessment of Advanced Data Fusion Algorithms for Remotely Sensed Data
... satellite data has long been an ongoing discussion among ...from remotely sensed data, such as the error matrix model to evaluate land use / land cover (LULC) classification ...truth ...
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RVM based multi class classification of remotely sensed data
... 1. Introduction Supervised classification is one of the most commonly undertaken analyses of remotely sensed data. Despite the importance and long history of classification analysis within remote ...
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Analysis of Change Detection Techniques using Remotely Sensed Data
... times. Data from remote sensing with its synoptic and regular coverage at short interval and consistent image quality provides a viable source of updated land cover information which can be extracted efficiently ...
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A REVIEW OF GEOTHERMAL MAPPING TECHNIQUES USING REMOTELY SENSED DATA
... Using Remotely Sensed Data dramatically increases the precision of identification of minerals through unique spectral ...hyperspectral data has several ...hyperspectral data and even in ...
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Enhancing spatial resolution of remotely sensed data for mapping freshwater environments
... using remotely sensed data requires the selection of suitable sensors capable of detecting and differentiating narrow and elongated margins of diverse and heterogeneous vegetation with surrounding ...
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Species and Ecosystems Stages of Biodiversity Evaluation Using Remotely-Sensed Data
... of remotely sensed data requires the each pixel assignment of the image to the ...classified data into three (3) classes with 30m cell size of 8-bit binary images, 316 number of rows and 282 ...
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A Proactive Approach for ROW VM Using GIS and Remotely Sensed Data
... information systems (GIS) technology provide an efficient and cost-effective method to analyze and display remotely sensed data. By identifying predetermined and/or custom land cover classes and ...
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Detection of logging infrastructure in the state of Rondônia using remotely sensed data
... on remotely sensed data using three different spatial resolutions to detect logging lands under forest management at the Jamari National Forest, state of Rondônia, ...
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Using the Opposition Effect in Remotely Sensed Data to Assist in the Retrieval of Bulk Density
... from remotely sensed ...from remotely sensed data that are transparent and ...controlled. Remotely sensed data that are measured in both a field setting and a ...
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Using the Opposition Effect in Remotely Sensed Data to Assist in the Retrieval of Bulk Density
... from remotely sensed ...from remotely sensed data that are transparent and ...controlled. Remotely sensed data that are measured in both a field setting and a ...
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Classification techniques for remotely sensed data
... hyperspectral data cube digital ...Hyperspectral data contain extremely rich spectral attributes, which offer the potential to discriminate more detailed classes with classification ...
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Estimating grassland curing with remotely sensed data
... NDVI max − NDVI min , (2) where the NDVI min and NDVI max are the minimum and max- imum NDVI value over a specified time range. Note that we did not attempt to compare the other proposed alternative, the spread-based RG, ...
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Merging remotely sensed data with geophysical models
... the data set and emphasize specific properties in the model, without ignoring other, less-known variables that are important to the ...reference data set in the initial design of the model, the developer ...
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Modeling crop phenology using remotely sensed data
... SMOS data product, τ , contains signal and noise from multiple ...the data to reduce ...the data in order to better understand the seasonal patterns of τ in respect to crop ...
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QuakeSim: Integrated Modeling and Analysis of Geologic and Remotely Sensed Data
... GPS data to determine earthquake and after-slip fault movements, finite element models of earthquake cycles, and new methods for GPS data processing on ...
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Rivers Hydromorphological Characterization from High Resolution Remotely Sensed Data
... The second main goal of the research was focused on bathymetry retrieval where the proposed MODPA provided robust retrievals with respect to changes in bottom types, IOPs and atmospheric effects. This research suggests ...
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