List of reference, applications of common Vegetation Indices for Multi-spectral, hyper-spectral and UAV images. (contribution are welcome)
- Literature Reviews
- Multispectral Vegetation Index
- Hyperspectral Vegetation Index
- Vegetation Index for UAV images
- Community
- Software
- Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications (li et al. 2017)
- Research on Vegetation Information Extraction from Visible UAV Remote Sensing Images (yuan et al. 2018)
- Hyperspectral vegetation indices and their relationships with agricultural crop characteristics(Thenkabail et al.2000)
- Evaluating Multispectral Images and Vegetation Indices for Precision Farming Applications from UAV Images (Candiago et al. 2015)
Broadband greenness measures the health of vegetation leaf area index (LAI) and canopy chlorophyll density (CCD) vegetation cover, LAI, biomass, growth, and vigor assessment. It is worthy noting that the selection of proper wavebands in hyperspectral data could partly compensate the limitations of some VI formulas.(Zhao et al.2007)
Name | Abbrev. | Formula | Atmospheric Effects Parameters | Soil Adjustment Parameters | Reference |
---|---|---|---|---|---|
Normalized Difference Vegetation Index | NDVI | Pigment, Canopy | paper) | ||
The Wide Dynamic Range Vegetation Index | WDRVI | ||||
Simple Ratio | SR | ||||
Atmospherically Resistant Vegetation Index | ARVI | γ | |||
soil and atmosphere resistant vegetation | SARVI | γ | L | ||
modified soil and atmosphere resistant vegetation | MSARVI | γ | |||
atmosphere effect resistant vegetation | IAVI | γ | L | ||
Enhanced Vegetation Index | EVI | C1 | L | ||
Perpendicular Vegetation Index | PVI | M,I | |||
Soil Adjusted Vegetation Index | SAVI | L | |||
Transformed Soil Adjusted Vegetation Index | TSAVI | M,L | |||
Modified Soil Adjusted Vegetation Index | MSAVI | L' | |||
Optimized Soil Adjusted Vegetation Index | OSAVI | θ | |||
generalized soil-adjusted vegetation index | GESAVI | L,M,Z | |||
Global Environmental Monitoring Index | GEMI | n | |||
Chlorophyll Absorption Ratio Index | CARI | ||||
Modified Chlorophyll Absorption Ratio Index | MCARI | ||||
Difference Vegetation Index | DVI | ||||
weighted Difference Vegetation Index | WDVI | L | |||
Renormalized Difference Vegetation Index | RDVI |
Parameter: M: Slope of soil baseline I: Intercept of soil baseline L: Soil conditioning index L': A formula need to be added θ: SAIL constant 0.16 n: Atmospheric Regulation Factor(C =6、C =7.5) y: Atmospheric radiation correction coefficient
The overall amount and quality of photosynthetic material in vegetation.
With specific camera, UAV images can be used to calculate all kind of hyperspectral and multi-band vegetation index, where RGB only images can be used to calculate following indices.
Name | Abbrev. | Formula | Atmospheric Effects Parameters | Soil Adjustment Parameters | Reference |
---|---|---|---|---|---|
Normalized Difference Vegetation Index | NDVI | Pigment, Canopy | paper) | ||
Visible-band difference vegetation index | VDVI | ||||
Normalized green-blue difference index | NGBDI | ||||
Normalized green-red difference index | NGRDI | ||||
Red-green ratio index | RGRI | ||||
Blue Green ratio index | BGRI | ||||
Excess green | EXG | ||||
Excess red | EXR | ||||
excess green minus excess red | EXGR | ||||
color index of vegetation extraction | CIVE | ||||
Red green blue vegetation index | RGBVI |
- Index Database - An Index-Data-Base (IDB) could be an useful tool to find indices for a required application, adapted to a selected sensor.
- LandscapeToolbox - The Vegetation/Greenness Indices part provides a detailed descriptions and applications of 9 common indices.
There are currently a large number of software with Vegetation Index tools, and we have a brief summary of them,
Name | Description | Customed Calculation | Pre definition Indices | Pre definition Satellite |
---|---|---|---|---|
ERDAS IMAGINE | √ | |||
ArcGIS | 15 Image indices are computed from multiband images | √ | 15 | |
ENVI | ENVI exposes 27 of these indices which were selected based upon their robustness, scientific basis, and applicability. | √ | 27 | |
Idrisi | A full suite of mathematical and relational modeling tools for deriving new data layers as a function of existing layers. | √ | ||
Pix4Dfields | Dedicated software for agriculture | √ | ||
opendronemap | https://opendronemap.org/webodm/ | √ |
Name | Description | Customed Calculation | Pre definition Indices | Pre definition Satellite |
---|---|---|---|---|
QGIS | √ |
This list will be updated in time, and volunteer contributions are welcome. For questions or sharing, please feel free to contact us or make issues.