Nothing Special   »   [go: up one dir, main page]

Ma et al., 2018 - Google Patents

Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: a case study in the Sierra Nevada Mountains, California

Ma et al., 2018

View PDF @Full View
Document ID
6846043854542779680
Author
Ma Q
Su Y
Tao S
Guo Q
Publication year
Publication venue
International Journal of Digital Earth

External Links

Snippet

Improved monitoring and understanding of tree growth and its responses to controlling factors are important for tree growth modeling. Airborne Laser Scanning (ALS) can be used to enhance the efficiency and accuracy of large-scale forest surveys in delineating three …
Continue reading at www.tandfonline.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20Handling natural language data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10032Satellite or aerial image; Remote sensing

Similar Documents

Publication Publication Date Title
Ma et al. Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: a case study in the Sierra Nevada Mountains, California
Solberg Mapping gap fraction, LAI and defoliation using various ALS penetration variables
Latifi et al. Evaluation of most similar neighbour and random forest methods for imputing forest inventory variables using data from target and auxiliary stands
Vepakomma et al. Response of a boreal forest to canopy opening: assessing vertical and lateral tree growth with multi‐temporal lidar data
Ciuti et al. An efficient method to exploit Li DAR data in animal ecology
Gelabert et al. Forest structural diversity characterization in Mediterranean landscapes affected by fires using Airborne Laser Scanning data
Ahmed et al. Interpretation of forest disturbance using a time series of Landsat imagery and canopy structure from airborne lidar
Goodbody et al. Airborne laser scanning for quantifying criteria and indicators of sustainable forest management in Canada
Vastaranta et al. Aboveground forest biomass derived using multiple dates of WorldView-2 stereo-imagery: quantifying the improvement in estimation accuracy
Huang et al. North Carolina’s forest disturbance and timber production assessed using time series Landsat observations
Duarte et al. Digital mapping of soil organic carbon stocks in the forest lands of Dominican Republic
Nyström et al. Change detection of mountain birch using multi-temporal ALS point clouds
Zhou et al. Integration of Landsat time-series vegetation indices improves consistency of change detection
Whelan et al. Improving generalized models of forest structure in complex forest types using area-and voxel-based approaches from lidar
Sumnall et al. Analysis of a lidar voxel-derived vertical profile at the plot and individual tree scales for the estimation of forest canopy layer characteristics
Bulut et al. Modelling some stand parameters using Landsat 8 OLI and Sentinel-2 satellite images by machine learning techniques: a case study in Türkiye
Tinkham et al. Development of height-volume relationships in second growth Abies grandis for use with aerial LiDAR
Xu et al. Algorithmic characterization of lake stratification and deep chlorophyll layers from depth profiling water quality data
Jones et al. Assessing the utility of LiDAR to differentiate among vegetation structural classes
Moan et al. Detecting and excluding disturbed forest areas improves site index determination using bitemporal airborne laser scanner data
Chen et al. Fractional monitoring of desert vegetation degradation, recovery, and greening using optimized multi-endmembers spectral mixture analysis in a dryland basin of Northwest China
Valbuena et al. Most similar neighbor imputation of forest attributes using metrics derived from combined airborne LIDAR and multispectral sensors
Liu et al. Analysis of coastline changes and the socio-economic driving mechanisms in Shenzhen, China
Hubert-Moy et al. Contribution of SPOT-7 multi-temporal imagery for mapping wetland vegetation
Guo et al. A new index for mapping the ‘blue steel tile’roof dominated industrial zone from Landsat imagery