Przeszlowska et al., 2006 - Google Patents
Near-ground remote sensing of green area index on the shortgrass prairiePrzeszlowska et al., 2006
View PDF- Document ID
- 13815671085433781780
- Author
- Przeszlowska A
- Trlica M
- Weltz M
- Publication year
- Publication venue
- Rangeland Ecology & Management
External Links
Snippet
Accurate and efficient leaf area measurements of shortgrass prairie vegetation are difficult to obtain. Few studies have considered the green area index (GAI) as an approximation of the total area of photosynthetically active tissue per unit of ground area. The main objective of …
- 241000235935 Hilaria belangeri 0 title abstract description 30
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/314—Investigating 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
- G01N2021/3155—Measuring in two spectral ranges, e.g. UV and visible
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
- G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wang et al. | Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images | |
| Liu et al. | Estimating biomass of winter oilseed rape using vegetation indices and texture metrics derived from UAV multispectral images | |
| Lussem et al. | Estimating biomass in temperate grassland with high resolution canopy surface models from UAV-based RGB images and vegetation indices | |
| Ali et al. | Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest | |
| Kitić et al. | A new low-cost portable multispectral optical device for precise plant status assessment | |
| Daughtry et al. | Remote sensing of crop residue cover and soil tillage intensity | |
| Zheng et al. | Remote sensing of crop residue and tillage practices: Present capabilities and future prospects | |
| Olsoy et al. | Estimation of big sagebrush leaf area index with terrestrial laser scanning | |
| López-Granados et al. | Using remote sensing for identification of late-season grass weed patches in wheat | |
| Lamb | The use of qualitative airborne multispectral imaging for managing agricultural crops-a case study in south-eastern Australia | |
| Luedeling et al. | Remote sensing of spider mite damage in California peach orchards | |
| Porter et al. | Estimating biomass on CRP pastureland: A comparison of remote sensing techniques | |
| Hoyos‐Villegas et al. | Ground‐based digital imaging as a tool to assess soybean growth and yield | |
| Pearse et al. | Comparison of optical LAI measurements under diffuse and clear skies after correcting for scattered radiation | |
| Starks et al. | Measuring eastern redcedar (Juniperus virginiana L.) mass with the use of satellite imagery | |
| Mašková et al. | Normalized difference vegetation index (NDVI) in the management of mountain meadows. | |
| Fitzgerald | Characterizing vegetation indices derived from active and passive sensors | |
| PEÑA‐BARRAGÁN et al. | Spectral discrimination of Ridolfia segetum and sunflower as affected by phenological stage | |
| Qi et al. | Impact of understorey on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China | |
| Rodionov et al. | Proximal field Vis-NIR spectroscopy of soil organic carbon: A solution to clear obstacles related to vegetation and straw cover | |
| Hardin et al. | In situ measurement of pecan leaf nitrogen concentration using a chlorophyll meter and vis-near infrared multispectral camera | |
| Jayasinghe et al. | Image‐based high‐throughput phenotyping for the estimation of persistence of perennial ryegrass (Lolium perenne L.)—A review | |
| Liu et al. | Application of UAV-retrieved canopy spectra for remote evaluation of rice full heading date | |
| Przeszlowska et al. | Near-ground remote sensing of green area index on the shortgrass prairie | |
| An et al. | Using hyperspectral radiometry to predict the green leaf area index of turfgrass |