[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Silveira et al., 2019 - Google Patents

Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment

Silveira et al., 2019

Document ID
14719994262106137478
Author
Silveira E
Silva S
Acerbi-Junior F
Carvalho M
Carvalho L
Scolforo J
Wulder M
Publication year
Publication venue
International Journal of Applied Earth Observation and Geoinformation

External Links

Snippet

Abstract The Brazilian Atlantic Forest is a highly heterogeneous biome of global ecological significance with high levels of terrestrial carbon stocks and aboveground biomass (AGB). Accurate maps of AGB are required for monitoring, reporting, and modelling of forest …
Continue reading at www.sciencedirect.com (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
    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30181Earth observation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3155Measuring in two spectral ranges, e.g. UV and visible

Similar Documents

Publication Publication Date Title
Silveira et al. Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment
Matasci et al. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots
Kumar et al. Remote sensing for agriculture and resource management
Baumann et al. Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
Madonsela et al. Remote sensing of species diversity using Landsat 8 spectral variables
Wicaksono et al. Mangrove biomass carbon stock mapping of the Karimunjawa Islands using multispectral remote sensing
Pflugmacher et al. Using Landsat-derived disturbance and recovery history and lidar to map forest biomass dynamics
Peña-Barragán et al. Object-based crop identification using multiple vegetation indices, textural features and crop phenology
Li et al. Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass
Dube et al. Predicting Eucalyptus spp. stand volume in Zululand, South Africa: an analysis using a stochastic gradient boosting regression ensemble with multi-source data sets
Shen et al. Annual forest aboveground biomass changes mapped using ICESat/GLAS measurements, historical inventory data, and time-series optical and radar imagery for Guangdong province, China
Bordoloi et al. Satellite based integrated approaches to modelling spatial carbon stock and carbon sequestration potential of different land uses of Northeast India
Lopatin et al. Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks
Véga et al. Mapping site index and age by linking a time series of canopy height models with growth curves
Deb et al. An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India
Barbosa et al. Remotely sensed biomass over steep slopes: An evaluation among successional stands of the Atlantic Forest, Brazil
CN109063657B (en) Aboveground biomass estimation and scale conversion method facing homogeneous region spectrum unit
Choudhary et al. Random Forest for rice yield mapping and prediction using Sentinel-2 data with Google Earth Engine
Reyes-Acosta et al. Mapping dry-season tree transpiration of an oak woodland at the catchment scale, using object-attributes derived from satellite imagery and sap flow measurements
Cabacinha et al. Relationships between floristic diversity and vegetation indices, forest structure and landscape metrics of fragments in Brazilian Cerrado
Okuda et al. Estimation of aboveground biomass in logged and primary lowland rainforests using 3-D photogrammetric analysis
Viña et al. Relationship between floristic similarity and vegetated land surface phenology: Implications for the synoptic monitoring of species diversity at broad geographic regions
Barnetson et al. Mapping woody vegetation cover across Australia's arid rangelands: Utilising a machine-learning classification and low-cost Remotely Piloted Aircraft System
Pozdnyakova et al. Estimation of spatial and spectral properties of phytophthora root rot and its effects on cranberry yield
do Nascimento et al. Development of a methodological approach to estimate vegetation biomass using remote sensing in the Brazilian semiarid NE region.