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BALANCED VS IMBALANCED TRAINING DATA:CLASSIFYING RAPIDEYE DATA WITH SUPPORT VECTOR MACHINES
Land cover classification Imbalanced training data Support Vector Machines RapidEye Agriculture
2016/11/23
The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imager...
A INTEGRATED CLASSIFIER FOR LARGE REGIONAL-SCALE LAND-COVER CLASSIFYING
Remote sensing Land Cover Classification Algorithms
2015/12/31
With a lot of successful applications of neural network-based classification, it has been recognized the classification can produce more accurate results than conventional approaches for remotely-sens...
Integrating Object-Based Classification and One-Class Support Vector Machines in Classifying a Specific Land Class from High Spatial Resolution Images
Object-Based Classification One-Class Support Vector Machines High Spatial Resolution Imagery
2015/12/17
Remote sensing techniques have been commonly used to map land cover and land use types. For many applications, users may only be interested in a specific land class in an image such as extracting urba...
UNMANNED AERIAL VEHICLES PRODUCE HIGH-RESOLUTION, SEASONALLY-RELEVANT IMAGERY FOR CLASSIFYING WETLAND VEGETATION
Unmanned aerial vehicle habitat mapping vegetation classification wetlands multi-rotor mapping
2015/9/10
With recent advances in technology, personal aerial imagery acquired with unmanned aerial vehicles (UAVs) has transformed the way ecologists can map seasonal changes in wetland habitat. Here, we use a...
Classifying microwave radar images using decision based data fusion
Classification Land Cover Fusion
2015/8/21
Four different data fusion methods for classifying SAR images with different spatial resolutions were tested and compared. Test area
was Helsinki region in Southern Finland and test data 14 ERS-1/2 T...
TWO STRUCTURE-RELATED STRATEGIES FOR AUTOMATICALLY DELINEATING AND CLASSIFYING HABITATS IN AN ALPINE ENVIRONMENT
object-based image analysis automated habitat delineation MSS/ORM OLR
2015/8/19
This paper presents a study on automated habitat delineation and classification using very high spatial resolution (VHSR) optical remote sensing data in an alpine environment. Two overlapping study si...
CLASSIFYING WILDLIFE HABITAT WITH PAN-SHARPENED LANDSAT 7 IMAGERY
Land cover land condition images merged images wildlife habitat mapping
2015/5/13
We compared three multi-resolution merging techniques for classifying land cover and land condition in the
central coast of California using Landsat7 imagery. We preferred the Principal Components t...
A COMPARISON OF A VISUAL INTERPRETATION AND A TWO STAGE APPROACH FOR CLASSIFYING URBAN DEVELOPMENT USING SPOT.
Urban Interpretation Classifi cation SPOT
2015/2/4
The growth of Dar es Salaam, Tanzania’s largest city, occurs predominantly through unplanned development. Given
population growth rates that are estimated to be currently above 5% and the lack of res...
Classifying historical remotely sensed imagery using a tempo-spatial feature evolution (T-SFE) model
Classification GIS History Landsat Vegetation
2015/2/4
Large and growing archives of orbital imagery of the earth’s surface collected over the past 40 years provide an important resource for documenting past and current land cover and environmental change...
Remote Measurements of Chlorophyll a and Gelbstoff for Classifying Tidal Flats by Means of Laser Fluorosensors
Remote Measurements Chlorophyll a Gelbstoff Classifying Tidal Flats Means of Laser Fluorosensors
2014/4/15
Remote Measurements of Chlorophyll a and Gelbstoff for Classifying Tidal Flats by Means of Laser Fluorosensors.