搜索结果: 1-15 共查到“Remotely Sensed Imagery”相关记录17条 . 查询时间(0.087 秒)
OBJECT-BASED RANDOM FOREST CLASSIFICATION OF LAND COVER FROM REMOTELY SENSED IMAGERY FOR INDUSTRIAL AND MINING RECLAMATION
Reclamation Area Classification of Land Use Random Forest Grid-search Object-based Multi-resolution Segmentation Multi-feature Variables
2018/5/11
The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification ...
A DATA FIELD METHOD FOR URBAN REMOTELY SENSED IMAGERY CLASSIFICATION CONSIDERING SPATIAL CORRELATION
Data Field Spatial Correlation High-Spatial-Resolution Urban Remotely Sensed Imagery Classification
2016/11/23
Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and mode...
CHANGE DETECTION OF WETLAND IN HONGZE LAKE USING A TIME SERIES OF REMOTELY SENSED IMAGERY
Multi-spectral remote sensing Change detection Image understanding Feature recognition Dynamic Change Pattern recognition Feature extraction Cluster Analysis
2016/1/3
The main aim of the study was to assess the potential of a time series of remotely sensed data for the change detection of wetland in Hongze Lake in the Northern Jiangsu Province. The raw data compris...
MODELLING SPATIO-TEMPORAL PATTERN OF LANDUSE CHANGE USING MULTITEMPORAL REMOTELY SENSED IMAGERY
Multitemporal Image Processing Change Detection Change Trajectory Analysis Land Cover Aridzone
2015/12/31
Remotely sensed data is the most important data source for environmental change study over the past 40 years. Since large collections of remote sensing imagery have been acquired in a time frame of su...
USE OF NEURAL NETWORKS FOR LAND COVER CLASSIFICATION FROM REMOTELY SENSED IMAGERY
Land Cover Classification Neural Networks Topology Activation Function Neural Training Accuracy
2015/12/31
Remote sensing has been increasingly used to derive land cover information by manual interpretation or automated classification. As promising automated classifiers, artificial neural networks are diff...
AUTOMATIC ROAD EXTRACTION OF URBAN AREA FROM HIGH SPATIAL RESOLUTION REMOTELY SENSED IMAGERY
road extraction road connection K-mean cluster high spatial resolution
2015/12/23
For the significance of road information to the city management, urban roads are subjects of great concern to be extracted from remotely sensed images. With the availability of high spatial resolution...
Quantitative Textural Parameter Selection for Residential Extraction from High-Resolution Remotely Sensed Imagery
Texture Residential Area JM-Distance Window Size Quantization Level
2015/12/18
Residential areas show plenty of texture information on high resolution remotely sensed imagery. Appropriate description about this texture information for discriminating residential class and its bac...
Semi-Automatic Extraction of Ribbon Road from High Resolution Remotely Sensed Imagery by Cooperation of Angular Texture Signature and Template Matching
Road extraction Semi-automatic Angular texture signature Template matching
2015/12/9
Road tracking is a promising technique to increase the efficiency of road mapping. In this paper an improved road tracker, based on cooperation between angular texture signature and template matching,...
Simulating Remotely Sensed Imagery for Classification Evaluation
Simulation Remote Sensing Image Classification Accuracy Assessment Simulated Annealing
2015/12/2
The remote sensing community has long been active in developing, evaluating, and comparing different classification algorithms using a variety of remotely sensed imagery. As an integral component of i...
Gaussian Mixture Model of Texture for Extracting Residential Area from High-resolution Remotely Sensed Imagery
Extraction of Residential Area Gaussian Mixture Model Texture High-Resolution Remotely Sensed Imagery
2015/10/12
Using high-resolution remotely sensed imagery to timely detect distribution and expansion of residential area is one of most
important jobs of national 1:5 spatial database updating. In view of comp...
Change Detection of Wetland in Hongze Lake Using a Time Series of Remotely Sensed Imagery
A Time Series Hongze Lake Wetland Change Detection Rule-based Inferring Core cluster
2015/10/9
The main aim of the study was to assess the potential of a time series of remotely sensed data for the change detection of wetland in
Hongze Lake in the Northern Jiangsu Province. The raw data compr...
A strategy of change detection based on remotely sensed imagery and gis data
Change detection remote sensing GIS
2015/8/21
Geometric co-registration errors and results of object extraction (such as classification and pattern recognition) are the two main
factors, which greatly affect the results of change detection in tr...
AN INTEGRATED SYSTEM FOR SEMI-AUTOMATED SEGMENTATION OF REMOTELY SENSED IMAGERY
Field-Based Image Segmentation Perceptual Grouping Classification Agriculture
2015/8/17
The recent trend in image classification of agricultural areas is towards the use of per-field approaches that work in a manner that a
crop label is assigned to each field. The existing field bounda...
CHANGE-DETECTION IN WESTERN KENYA – THE DOCUMENTATION OF FRAGMENTATION AND DISTURBANCE FOR KAKAMEGA FOREST AND ASSOCIATED FOREST AREAS BY MEANS OF REMOTELY-SENSED IMAGERY
Remote Sensing Multisensor Imagery Landsat Classification Land Cover Change-Detection GIS
2015/6/1
In order to understand causes and effects of disturbance and fragmentation on flora and fauna, a time series on land cover change is needed as basis for the BIOTA-East Africa project partners working ...
CLASSIFIER FOR REMOTELY SENSED IMAGERY USING KOHONEN ’S SELF-ORGANIZING FEATURE MAP WITH REGION GROWING
Remotely Sensed Imagery Self-Organizing Feature Map Region Growing Polar coordinate System
2015/2/4
Applying the region growing to the Kohonen’s self-organizing feature map, a non-supervised classifier for remotely
sensed imagery data is proposed. If the self-organizing feature map is made large e...