搜索结果: 1-15 共查到“Random Forest”相关记录16条 . 查询时间(0.062 秒)
Fractional Vegetation Cover Estimation Algorithm for FY-3B Reflectance Data Based on Random Forest Regression Method
fractional vegetation cover FY-3B reflectance data random forest regression method
2023/12/8
As an important land surface vegetation parameter, fractional vegetation cover (FVC) has been widely used in many Earth system ecological and climate models. In particular, high-quality and reliable F...
Site Quality Classification Models of Cunninghamia Lanceolata Plantations Using Rough Set and Random Forest West of Zhejiang Province, China
Cunninghamia lanceolata plantations site quality classification models site quality evaluation rough set random forest
2023/12/1
The site quality evaluation of plantations has consistently been the focus in matching tree species with sites. This paper studied the site quality of Chinese fir (Cunninghamia lanceolata) plantations...
3D SEMANTIC LABELING OF ALS DATA BASED ON DOMAIN ADAPTION BY TRANSFERRING AND FUSING RANDOM FOREST MODELS
3D semantic labelling ALS data random forest domain adaption decision fusion
2018/5/15
Labeling 3D point cloud data with traditional supervised learning methods requires considerable labelled samples, the collection of which is cost and time expensive. This work focuses on adopting doma...
SHIP DETECTION BASED ON MULTIPLE FEATURES IN RANDOM FOREST MODEL FOR HYPERSPECTRAL IMAGES
Hyperspectral Image Ship Detection Multiple Feature Spectral Feature Texture Feature Random Forest (RF)
2018/5/14
A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in ...
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 ...
EXPLORING CAPABILITIES OF SENTINEL-2 FOR VEGETATION MAPPING USING RANDOM FOREST
Vegetation mapping Sentinel-2 Landsat-8 OLI Random Forest Maximum Likelihood Classifier
2018/5/15
Accurate vegetation mapping is essential for monitoring crop and sustainable agricultural practice. This study aims to explore the capabilities of Sentinel-2 data over Landsat-8 Operational Land Image...
SALIENCY-GUIDED CHANGE DETECTION OF REMOTELY SENSED IMAGES USING RANDOM FOREST
Remote Sensing Change Detection Segmentation Super-pixel Saliency Random Forest
2018/5/14
Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more in...
APPLYING RANDOM FOREST CLASSIFICATION TO MAP LAND USE/LAND COVER USING LANDSAT 8 OLI
Classification Landsat 8 OLI Land use Land cover Random Forest Decision Tree
2018/4/18
This study used the Random Forest classifier (RF) running in R environment to map Land use/Land cover (LULC) of Dak Lak province in Vietnam based on the Landsat 8 OLI. The values of two RF parameters ...
APPLYING RANDOM FOREST CLASSIFICATION TO MAP LAND USE/LAND COVER USING LANDSAT 8 OLI
Classification Landsat 8 OLI Land use Land cover Random Forest Decision Tree
2018/5/8
This study used the Random Forest classifier (RF) running in R environment to map Land use/Land cover (LULC) of Dak Lak province in Vietnam based on the Landsat 8 OLI. The values of two RF parameters ...
RANDOM FOREST CLASSIFICATION OF SEDIMENTS ON EXPOSED INTERTIDAL FLATS USING ALOS-2 QUAD-POLARIMETRIC SAR DATA
Coastal Zones Surveillance SAR Polarimetric Decomposition Optical Channels Random Forest
2016/12/1
Coastal zones are one of the world’s most densely populated areas and it is necessary to propose an accurate, cost effective, frequent, and synoptic method of monitoring these complex ecosystems. Howe...
COMBINING SPECTRAL AND TEXTURE FEATURES USING RANDOM FOREST ALGORITHM: EXTRACTING IMPERVIOUS SURFACE AREA IN WUHAN
Impervious surface area Random forest Texture features
2016/11/23
Impervious surface area (ISA) is one of the most important indicators of urban environments. At present, based on multi-resolution remote sensing images, numerous approaches have been proposed to extr...
URBAN ROAD DETECTION IN AIRBONE LASER SCANNING POINT CLOUD USING RANDOM FOREST ALGORITHM
ALS Random Forest classification road detection
2016/7/27
The objective of this research is to detect points that describe a road surface in an unclassified point cloud of the airborne laser scanning (ALS). For this purpose we use the Random Forest learning ...
MODELING URBAN DYNAMICS USING RANDOM FOREST: IMPLEMENTING ROC AND TOC FOR MODEL EVALUATION
Random Forest Urban Growth Modelling Relative Operating Characteristics
2016/7/8
The importance of spatial accuracy of land use/cover change maps necessitates the use of high performance models. To reach this goal, calibrating machine learning (ML) approaches to model land use/cov...
RANDOM FOREST AND OBJECTED-BASED CLASSIFICATION FOR FOREST PEST EXTRACTION FROM UAV AERIAL IMAGERY
Superpixel Simple Linear Iterative Cluster (SLIC) texture Forest Pest Random Forest unmanned aerial vehicle (UAV) aerial imagery
2016/7/5
Forest pest is one of the most important factors affecting the health of forest. However, since it is difficult to figure out the pest areas and to predict the spreading ways just to partially control...
MERGING RANDOM FOREST CLASSIFICATION WITH AN OBJECT-ORIENTED APPROACH FOR ANALYSIS OF AGRICULTURAL LANDS
land use agriculture Landsat imagery segmentation Random Forest
2015/12/31
Machine learning algorithms recently have made major advances, with decision tree classifiers gaining wide acceptance. Boosting and bagging of decision trees have added to the predictive capabilities ...