Spectral reflectance of multispecies herbaceous and moss canopies in the boreal forest understory and open field (original) (raw)
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A soil-adjusted vegetation index (SAVI)
Remote Sensing of Environment, 1988
A transformation technique is presented to minimize soil brightness influences from spectral vegetation indices involving red and near-infrared (NIR) wavelengths. Graphically, the transformation involves a shifting of the origin of reflectance spectra plotted in NIR-red wavelength space to account for first-order soil-vegetation interactions and differential red and NIR flux extinction through vegetated canopies. For cotton (Gossypium hirsutum L. var DPI-70) and range grass (Eragrosticslehmanniana Nees) canopies, underlain with different soil backgrounds, the transformation nearly eliminated soil-induced variations in vegetation indices. A physical basis for the soil-adjusted vegetation index (SAVI) is subsequently presented. The SAVI was found to be an important step toward the establishment of simple °lobal” that can describe dynamic soil-vegetation systems from remotely sensed data.
On the terminology of the spectral vegetation index (NIR − SWIR)/(NIR + SWIR)
International Journal of Remote Sensing, 2011
The spectral vegetation index (ρ NIR − ρ SWIR )/(ρ NIR + ρ SWIR ), where ρ NIR and ρ SWIR are the near-infrared (NIR) and shortwave-infrared (SWIR) reflectances, respectively, has been widely used to indicate vegetation moisture condition. This index has multiple names in the literature, including infrared index (II), normalized difference infrared index (NDII), normalized difference water index (NDWI), normalized difference moisture index (NDMI), land surface water index (LSWI) and normalized burn ratio (NBR). After reviewing each term's definition, associated sensors and channel specifications, we found that the index consists of three variants, differing only in the SWIR region (1.2-1.3, 1.55-1.75 or 2.05-2.45 µm). Thus, three terms are sufficient to represent these three SWIR variants; other names are redundant and therefore unnecessary. Considering the spectral representativeness, the term's popularity and the 'rule of priority' in scientific nomenclature, NDWI, NDII and NBR, each corresponding to the three SWIR regions, are more preferable terms.
A Modified Soil Adjusted Vegetation Index
There is currently a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science and global change. Spectral models and indices are being developed to improve vegetation sensitivity by accounting for atmosphere and soil effects. The
Journal of Plant Physiology, 2004
The Normalized Difference Vegetation Index (NDVI) is widely used for monitoring, analyzing, and mapping temporal and spatial distributions of physiological and biophysical characteristics of vegetation. It is well documented that the NDVI approaches saturation asymptotically under conditions of moderate-to-high aboveground biomass. While reflectance in the red region (ρred) exhibits a nearly flat response once the leaf area index (LAI) exceeds 2, the near infrared (NIR) reflectance (ρNIR) continue to respond significantly to changes in moderate-to-high vegetation density (LAI from 2 to 6) in crops. However, this higher sensitivity of the ρNIR has little effect on NDVI values once the ρNIR exceeds 30 %. In this paper a simple modification of the NDVI was proposed. The Wide Dynamic Range Vegetation Index, WDRVI = (a * ρNIR-ρred)/(a * ρNIR+ρred), where the weighting coefficient a has a value of 0.1–0.2, increases correlation with vegetation fraction by linearizing the relationship for typical wheat, soybean, and maize canopies. The sensitivity of the WDRVI to moderate-to-high LAI (between 2 and 6) was at least three times greater than that of the NDVI. By enhancing the dynamic range while using the same bands as the NDVI, the WDRVI enables a more robust characterization of crop physiological and phenological characteristics. Although this index needs further evaluation, the linear relationship with vegetation fraction and much higher sensitivity to change in LAI will be especially valuable for precision agriculture and monitoring vegetation status under conditions of moderate-to-high density. It is anticipated that the new index will complement the NDVI and other vegetation indices that are based on the red and NIR spectral bands.
Interpretation of the modified soil-adjusted vegetation index isolines in red-NIR reflectance space
2007
Abstract. In red-NIR reflectance space, the Modified Soil Adjusted Vegetation Index (MSAVI) isolines, representing similar vegetation biophysical quantities, are neither convergent to a point nor parallel to each other. Consequently, the treatment of the MSAVI isolines is distinctly different from those of other vegetation index isolines, such as the normalized difference vegetation index (NDVI), the perpendicular vegetation index (PVI), and the soil-adjusted vegetation index (SAVI).
Optical–Biophysical Relationships of Vegetation Spectra without Background Contamination
Remote Sensing of Environment, 2000
ing biophysical parameters, a "true" VI value attributed only to the vegetation signal andfree of any contamination is needed. In this article, pure vegetation spectra were extractedfrom a set of open and closed canopies by unmixing the green vegetation signalfrom the background component. Canopy model-simulation and reflectances derived from graph-based linear extrapolation were used to unmix and derive a "true" vegetation signal, equivalent to a perfect absorber (free boundary) canopy background reflectance condition. Optical-biophysical relationships were then derived for a variety of canopy structures with differences infoliage clumping, horizontal heterogeneity, and leaftype. A 3-dimensional canopy radiative transfer model and a hybrid geometric optical-radiative transfer model (GORT) were used to simulate the directional-hemispherical reflectances from agricultural, grassland, andforested canopies (cereal and broadleaf crop, grass, needleleafi and broadleaf forest). The relationships of the extracted red and nearinfrared reflectances and derived vegetation indices (VIs) to various biophysical parameters (leaf area index,fraction of absorbed photosynthetically active radiation, and percent ground cover) were examinedfor the pure vegetation spectra. The results showed normalized difference vegetation index (NDVI) relationships with biophysical parameters to become more asymptotic over the pure vegetation condition. The extraction of pure vegetation signals had little effect on the soil-adjusted vegetation index (SAVI), which had values equivalent to those obtained with the presence of a background signal. NDVI values were fairly uniform across the different canopy types, whereas the SAVI values had pronounced differences among canopy types,
Candidate high spectral resolution infrared indices for crop cover
Remote Sensing of Environment, 1993
he sensitivity of near-infrared 1 red ratio vegetation in dices to sail reflectance and plant color result in ambigu ous interpretation of plant condition and productivity. Measurements of the reflectance of crop canopies were made at high spectral resolution to investigate candidate vegetation indices, in the near-and middle-infrared (800-2500 nm), for their ability to unambiguously estimate foliage caver independently of the extraneous ef fects of variations in canopy color and sail background bright ness. Reflectances were measured with an IRIS spectrora diometer over plots of sugar beet (Beta vulgaris L.) sown on different dates and at different densities to produce a wide range in canopy caver. Vegetation, color was varied by infecting selected plots with sugar beet yellows virus. Soil brightness was varied by placing trays of peat be tween the plant rows. Selected narrow-band near-and middle-infrared reflectances were tested for their relation ship with canopy caver and their sensitivity to variations in canopy color and sail brightness. The relationship between canopy caver and traditional near-infrared 1 red ratio indices was found to be sensitive to bath canopy color and sail brightness. Most infrared indices were insensitive to the effects of canopy color, but those showing the highest correlations with caver tended to be signifi cantly influenced by soil brightness. The most promising NIR reflectances were those beyond the range (760-900 204 nm) of near-infrared refl ectance detected by current space-borne systems, such as Landsat TM and SPOT HRV.
Modified Vegetation Detection Index Using Different-Spectral Signature
Iraqi journal of science, 2021
The Normalization Difference Vegetation Index (NDVI), for many years, was widely used in remote sensing for the detection of vegetation land cover. This index uses red channel radiances (i.e., 0.66 μm reflectance) and near-IR channel (i.e., 0.86 μm reflectance). In the heavy chlorophyll absorption area, the red channel is located, while in the high reflectance plateau of vegetation canopies, the Near-IR channel is situated. Senses of channels (Red & Near-IR) read variance depths over vegetation canopies. In the present study, a further index for vegetation identification is proposed. The normalized difference vegetation shortwave index (NDVSI) is defined as the difference between the cubic bands of Near-IR and Shortwave infrared radiation (SWIR) divided by their sums. The radiances or reflectances are included in this index from the Near-IR channel and WSIR2 channel (2.1 μm). The NDVSI is less sensitivite to atmospheric effects as compared to NDVI. By comparing the one NDVSI index with the two indexes (NDVI, SAVI) of vegetation cover, good correlations were found between NDVI and NDVSI (R 2 =0.917) and between SAVI and NDVSI (R 2 =0.809. Accordingly, the proposed index can be taken into consideration as an independent vegetation index