Perpendicular Vegetation Index Research Articles

Potentials and limits of vegetation indices for LAI and APAR assessment

Most vegetation indices (VI) combine information contained in two spectral bands: red and near-infrared. These indices are established in order to minimize the effect of external factors on spectral data and to derive canopy characteristics such as leaf area index (LAI) and fraction of absorbed photosynthetic active radiation (P). The potentials and limits of different vegetation indices are discussed in this paper using the normalized difference (NDVI), perpendicular vegetation index (PVI), soil adjusted vegetation index (SAVI), and transformed soil adjusted vegetation index (TSAVI). The discussion is based on a sensitivity analysis in which the effect of canopy geometry (LAI and leaf inclination) and soil background are analyzed. The calculation is performed on data derived from the SAIL reflectance model. General semiempirical models, describing the relations between VI and LAI or P, are elaborated and used to derive the relative equivalent noise (REN) for the determination of LAI and P. The performances of VIs are discussed on the basis of the REN concept.

Use of Spectral Vegetation Indices to Infer Leaf Area, Evapotranspiration and Yield: II. Results

AbstractBetter methods of interpreting spectral observations of crop canopies in terms of agronomic characteristics such as green leaf area index (L) and aboveground dry phytomass (DM), and for estimating economic yield (Y) are needed. The equations proposed were applied to single year experiments with Triticum aestivum L. and Triticum durum Desf., Gossypium hirsutum L., and Zea mays L. in order to illustrate and further test them. As predicted, fractional photosynthetically active radiation absorption (FPAR) could be estimated from vegetation indices (VI) such as perpendicular vegetation index (PVI) and the normalized difference (ND) about as well as from L. Generally, L/VI and FPAR/L‐verbalized as L as a function of VI, and FPAR as a function of L–were exponential relations whereas FPAR/VI were linear or nearly linear functions. The DM, Y, and the harvest index (Y/DM) were linearly related to PVI averaged for several dates during late vegetative development for wheat and corn, indicating that relative yields for both crops had been set by that development stage. The functional relations L/VI, FPAR/L, FPAR/VI, Y/VI, DM/VI, ∑APAR/∑VI, DM/∑APAR, Y/∑VI and (Y/DM)/VI where APAR is daily absorbed PAR (MJ m−2 d−1) presented document that direct spectral observations and the equations incorporating them do provide additional analytical tools for interpreting crop development, growth, and yield.

A ratio vegetation index adjusted for soil brightness

Abstract Improved parameters for a soil-adjusted vegetation index (SAVI) are derived using SAIL model output for simulated wheat canopy reflectance. The SAVI is much less sensitive than the ratio vegetation index to changes in background caused by soil colour or surface soil moisture content. The parameters are developed to minimize variability due to soil brightness over the practical range of solar elevations, lear angle distributions (LAD) and leaf area indices (LAI). The parameters are added to the near-infrared (NIR) and red reflectances before calculating the NIR/red ratio. Three new versions of the SAVI are developed based on the theoretical consideration of the effects of wet and dry soils. All three are superior to the NIR/red ratio, the perpendicular vegetation index and a soil-adjusted vegetation index. Our simplest version requires the addition of a parameter to the red reflectance. The second and third versions require an iterative procedure to find the best parameters that are then added to ...

Effect of water stress on the canopy architecture and spectral indices of irrigated alfalfa

Diurnal measurements of alfalfa leaf distribution and crop canopy reflectance were made in stressed and unstressed alfalfa plots in Phoenix, AZ. Measurements were made on three dates in January, May, and November. Results showed that heliotropic leaf movements were directly affected by crop water status. Under well-watered conditions, alfalfa leaves tended to track the sun throughout the day, in both the azimuthal and zenithal directions. In the stressed plots, diurnal tracking ability diminished as the day progressed and the canopy assumed a more vertical profile due to leaflet cupping. The stressed canopy then had a lower spectral reflectance (measured at nadir) than the unstressed canopy, in both the red and near-IR wavebands. The Perpendicular Vegetation Index (PVI) decreased with the stress-induced change in architecture while the near-IR/red ratio remained relatively constant. As a result, the near-IR / red ratio was more successful in estimating alfalfa biomass than was the PVI. These results emphasize the need to account for stress-induced architectural differences in plant canopies when using remotely sensed spectral data.

Estimating rainfall and biomass for the pastureland zone of the West African Sahel

To provide an early indication of below average rainfall and pastureland biomass production, which could lead to famine conditions, methods of estimating rainfall and biomass of the Sahelian region of West Africa using satellite observations were developed. 10 and 30 day rainfall were successfully estimated from the duration of rain bearing clouds, derived from Meteosat infrared radiation measurements. Biomass was estimated from the Perpendicular Vegetation Index derived from Landsat MSS data and ground based biomass measurements for an area in the centre of the Republic of Niger. The accuracy of these estimates was found to be generally reasonable when checked against an independent set of biomass measurements. These methods are to be incorporated into an operational system for this region of Africa.

Spectral observations for estimating the growth and yield of rice.

Remote spectral observations of plant canopies provide information that may be useful for describing their growth and yield. In this paper we (1) present equations that dcscribe how spectral reflectance observations, expressed as vegetation indices (VI), relate to leaf area index (L); fractional photosynthetically active radiation, PAR, absorbed (Fp) ; daily solar PAR absorbed (Sp); above-ground dry matter (DM); and, grain yield (YIELD), and (2) apply the equations to a rice (Oryza sativa L.) experiment conducted at Tsukuba in 1987. The 13 treatments consisted of incomplete combinations of 2 transplanting dates (21 May, 11 June), 6 nitrogen application rates (0, 2, 4, 6, 8 and 12 g/m2), and 3 cultivars (Nipponbare, Koshihikari, and Shinanomochi). Over the seasonal interval transplanting to physiological maturity of the grain, grain YIELD (g/m2) and cumulative daily absorbed photosynthetically active radiation (ΣSp, MJ/m2) were linear functions of the cummulative perpendicular vegetation index (ΣPVI). The efficiency of conversion to dry matter, ec, was 2.9 g DM/MJ for transplanting to 20 days after heading and ∼2.5 g DM/MJ for transplanting to physiological maturity. YIELD was linearly related to dry matter at heading, DMh (r2=0.92) which could be better estimated by the reflectance difference vegetation index at heading, (R1100-R1650)h (r2=0.82) than by PVI at heading, PVIh, (r2 = 0.69). The functional relations suggested by the equations demonstrate how observable canopy attributes (L, DM) and plant processes (light interception, photosynthesis, growth) interrelate to VI and YIELD, and provide a basis for interpreting the variation in vegetation indices of rice canopies in terms of canopy development and grain yield.

Water turbidity and perpendicular vegetation indices for paddy rice flood damage analyses

Reflectance factors were obtained for paddy rice at two sites in calibrated TM scenes acquired on two dates for the Kanto district of Japan—1 day after a typhoon inundated the paddies (6 August 1986, when the rice was at boot stage of development) and a month later (7 September 1986, during grain filling). A water turbidity index (WTI), analogous to soil brightness, and the perpendicular vegetation index (PVI) were computed for these data as WTI = 0.91 RED + 0.43 NIR and PVI = − 0.43 RED + 0.91 NIR , respectively. Rice yield measured for the inundation-damaged paddies and experimental nondamaged paddies at Tsukuba, Japan, were pooled and related to the PVI calculated from the respective TM scene and ground-measured reflectance factors. The ground and TM data coincided well, and the regression relation YIELD (t/ha) = 0.26 PVI − 3.0 for the pooled data. The relation between flood water turbidity at boot stage and yield was also examined for the two test sites; the more turbid the flood water, the greater the damage to the crop. The results demonstrate the possibility of spectrally assessing flood damage to rice and other crops.

Soil and atmosphere influences on the spectra of partial canopies

An atmospheric radiant transfer model was used to compare ground-measured radiances over partially vegetated canopies with their simulated responses at the top of a clear (100 km meteorological range) and a turbid (10 km) atmosphere. Radiance measurements in the first four bands of the Thematic Mapper were taken over incomplete cotton ( Gossypium hirsutum L.) and Lehmann lovegrass ( Eragrostis lehmanniana Nees) canopies with different soil backgrounds separately inserted underneath. Atmospheric influences on the spectra of partial canopies were found to be significantly dependent on the “brightness” of the underlying soil. The change in canopy red and near-infrared radiance between the ground and the top of the atmosphere was such that an increase, decrease, or no change could be observed, depending on the magnitude of the canopy substrate contribution. Both increasing soil “brightness” and atmospheric turbidity lowered the ratio (RVI) and normalized difference vegetation index values (NDVI). Consequently, atmospheric-induced RVI and NDVI degradation were greatest over canopies with darker soils and were not detectable over canopies with light-colored soils. In contrast, soil and atmospheric effects on the perpendicular vegetation index were independent with atmosphere degradation being similar across all soil backgrounds. Soil influences on vegetation indices from partial canopies were found to be of similar magnitude to those attributed to the atmosphere for the range of soil and atmosphere conditions examined here.

Suitability of spectral indices for evaluating vegetation characteristics on arid rangelands

The spectral behavior of an arid, Lehmann lovegrass (Eragrostis lehmanniana), range canopy with varying quantities of live, green grass, senesced, yellow grass, weathered, gray litter, and different soil backgrounds was analyzed with a ground based radiometer. The analysis included rangeland field plots and artificial mixtures of live and dead grass. Senesced grass and weathered litter were found to significantly alter the spectral response of the range canopy in the first four Thematic Mapper wavebands (0.45–0.52; 0.52–0.60; 0.63–0.69; 0.76–0.90 μm). These influences seriously hampered the utility of spectral vegetation indices in assessing green phytomass levels. Gray litter lowered the response of the green vegetation index (GVI) and perpendicular vegetation index (PVI) while minimally influencing the ratio vegetation index (RVI) and the normalized difference vegetation index (NDVI). Yellow, senesced grass increased the greenness response of plots without green vegetation and decreased the greenness response of plots with green vegetation. Higher reflecting soils increased the GVI and PVI response and decreased the RVI and NDVI response of comparable range canopy mixtures. Small amounts of 30 cm tall, green grass (750 kg/ha) could not be detected within a 75 cm tall, senesced grass stand (5000 kg/ha). The results of this study show spectral vegetation indices to be unreliable measures of green phytomass in arid rangelands. A mixture model employing principal component analysis was used to extract a green vegetation signal, but green phytomass detection was not improved. Apparently, the green vegetation signal emerging from range canopies is diminished by the scattering influences of the vertically oriented elements of the senesced grass phytomass.

Spectral response of architecturally different wheat canopies

The spectral response of two architecturally different spring wheat canopies having similar single leaf reflectance, green leaf area index (GLAI), and total dry phytomass, was measured throughout a growing season. Experimental results and supporting model calculations showed that the more planophile canopy had a higher spectral reflectance (measured at nadir) than the erectophile canopy. During the period of peak GLAI, the ratio of near-infrared to red reflectances (IR/red) for the erectophile canopy was about 30% higher than for the planophile canopy. The perpendicular vegetation index (PVI), however, was about 30% higher for the planophile canopy than for the erectophile canopy. When ground measured reflectances were transformed to radiances exiting the top of either a clear or a turbid atmosphere, the differences between the erectophile and the planophile canopies remained for the PVI but were obscured for the IR/red ratio. The results demonstrate the importance of architectural effects on the spectral response of canopies, and the interpretation of that response for estimating GLAI and dry phytomass by use of vegetation indices.

Diurnal patterns of bidirectional vegetation indices for wheat canopies

Abstract The perpendicular vegetation index (PVI) and normalized difference vegetation index (NDVI) were calculated from Mark II radiometer RED (0.63-0.69 μm) and NIR (0.76–0.90 μ) bidirectional radiance observations for wheat canopies. Measurements were taken over the plant development interval flag leaf expansion to watery ripeness of the kernels during which the leaf area index (LAI) decreased from 40 to 2-5. Spectral data were taken on four cloudless days five times (09.30, 11.00, 12.30, 14.00 and 15.30 hours (central standard time, C.S.T.) at five view zenith, Zv (0, 15, 30,45 and 60°) and eight view azimuth angles relative to the Sun, Av (0, 45, 90, 135, 180, 225, 270 and 315°). The PVI was corrected to a common solar irradiance (PVIC) based on simultaneously observed insolation readings. The PVIC at nadir view (Ž=0°) increased as (l/cosZs) increased on all the measurement days whereas the NDVI changed little as solar zenith angle (Zs) changed. Thus, the PVIC responded to increasing path length thro...

Spectral Components Analysis: A Bridge between Spectral Observations and Agrometeorological Crop Models

Spectral observations have been acknowledged to indicate general plant conditions over large areas but have yet to be exploited in connection with agrometeorological crop models. One reason is that it is not yet appreciated how periodic spectral observations of row-cropped and natural plant canopies, as expressed by vegetation indices (VI), can provide information on important crop model parameters, such as leaf area index (LAI) and absorbed photosynthetically active radiation (APAR). Two experiments were conducted under AgRISTARS sponsorship, one with cotton and one with spring wheat, specifically to determine the relationships for each term in the spectral components identity \begin{equation*} LAI/VI \times APAR/LAI = APAR/VI.\end{equation*} LAI and APAR could, indeed, be well estimated from vegetation indices such as normalized difference(ND) and perpendicular vegetation index (PVI)?apparently because of the close relation between the VI and amount of photosynthetically active tissue in the canopy. APAR and VI measurements are similarly affected by solar zenith angle (SZA), and LAI can be divided by cos SZA at the time of the VI and APAR measurements to achieve correspondence. APAR, ND, and PVI plotted against LAI all asymptote to limiting values in the same way yield does as LAI exceeds 5, further linking canopy development to yield capability. In summary, the spectral components analysis results presented add credence to the information conveyed by spectral canopy observations about plant development and yield, and establish a bridge between remote observations and agrometeorological crop modeling through the variables of mutual concern, LAI, biomass, and yield.

Influence of rock-soil spectral variation on the assessment of green biomass

Vegetation indices can be adversely influenced by variation in rock and soil spectral characteristics. When rocks and soils yield different vegetation index values, this is misinterpreted as changes in green biomass. This spectral influence is present to some extent in all vegetation indices. Secondly, variations in rock-soil brightness have a strong influence on ratio-based vegetation indices. Variations in rock-soil brightness have the same effect on all ratio-based vegetation indices: Vegetation is overestimated on dark backgrounds relative to bright backgrounds. Overall, it is concluded that the perpendicular vegetation index is the best available vegetation index to use in multispectral imagery of arid and semiarid regions where there is wide variation in rock and soil spectral characteristics.

Visible/Infrared/Microwave Agriculture Classification, Biomass, and Plant Height Algorithms

This paper describes the results of a study to determine if visible, infrared, and microwave data is correlated to crop-canopy characteristics (biomass and crop height) and can improve estimates of crop acreage. The objectives were to 1) determine if different crops can be discriminated using multifrequency microwave data, and 2) determine which visible, infrared, and microwave spectral regions can classify crops and correlate well to plant biomass, crop height, and the perpendicular vegetation index (PVI). The study was conducted at Dalhart, Texas, in 1980. Aircraft multispectral data collected during the study included visible and infrared data and active multifrequency microwave data. Ground-truth data from each field consisted of soil moisture, total plant biomass, and crop height. Results indicated that C- (4.75 GHz), L- (1.6 GHz), and P- (0.4 GHz) band active microwave data combined with visible and infrared data maintained or improved crop-discrimination accuracy compared to models using only visible and infrared data. The active microwave frequencies were more sensitive to plant height differences than total biomass differences; the K- (13.3 GHz) and C-bands were sensitive to height variations in short plants, while the P-band was sensitive to differences between tall and short plants.

Spectral response of a plant canopy with different soil backgrounds

Abstract The spectral behavior of a cotton canopy with four soil types alternately inserted underneath was examined at various levels of vegetation density. Measured composite spectra, representing various mixtures of vegetation with different soil backgrounds, were compared with existing measures of greenness, including the NIR-red band ratios, the perpendicular vegetation index (PVI), and the greenness vegetation index (GVI). Observed spectral patterns involving constant vegetation amounts with different soil backgrounds could not be explained nor predicted by either the ratio or the orthogonal greenness measures. All greenness measures were found to be strongly dependent on soil brightness. Furthermore, soil-induced greenness changes became greater with increasing amounts of vegetation up to 60% green cover. The results presented suggests that soil and plant spectra interactively mix in a nonadditive, partly correlated manner to produce composite canopy spectra.

Utilization of vegetation indices to improve microwave soil moisture estimates over agricultural lands

Investigations concerning microwave techniques for remote estimation of soil moisture have shown Increased interest in the study of vegetation effects on the estimates of soil moisture. This paper addresses only combinations of passive microwave and visible/infrared systems. An approach is presented whereby visible/near infrared data are used to develop corrections in the microwave soil moisture signal to account for vegetation effects. Microwave brightness temperature measurements at near nadir took angles were made with 1.4- and 5-GHz systems. Visible/infrared data were collected with the NASA NS001 Thematic Mapper Simulator and the M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> S imager at the time of the microwave observations. The visible/infrared data were used to calculate Perpendicular Vegetation Index (PVI) which was then related to the change in sensitivity of the microwave measurement to surface soil moisture. It was found that effective estimation of soil moisture in the presence of vegetation can be made with L-band microwave radiometers and visible/infrared sensors when the PVI is less than 4.3. If implemented from a space platform, this technique can provide a pragmatic means of estimating moisture over many agricultural areas without the expensive necessity of collecting ground data.

The estimation of green-leaf-area index from remotely sensed airborne multispectral scanner data

Abstract Airborne multispectral scanning system (MSS) data from the Natural Environment Research Council's MSS-82 project were used to estimate the green-leaf-area index (GLAI) of an area of semi-natural and agricultural limestone grassland. This research is the pilot study of a five phase investigation which will ultimately test the feasibility of using airborne and spaceborne MSS data to estimate GLAI over large areas. The pilot study was designed around four stages: (i) derivation of the relationship between multispectral reflectance and vegetation amount using ground radiometric data collected in the field, (ii) production of a perpendicular-vegetation index (PVI) image, (iii) production of a GLAI image using the relationship between PVI and GLAI and (iv) accuracy assessment of the resultant GLAI image. Due to a number of project- and environment-specific problems the proposed methodology was modified and GLAI was predicted to an accuracy of 50-86 per cent at the 95 per cent confidence level. For the ...

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Linear combinations of n spectral bands form physically significant indices in n- dimensional space. The 2-dimensional (2-D) perpendicular vegetation index (PVI) of Richardson and Wiegand and the 4-D tasseled cap of Kauth and Thomas are special cases of n- space indices. A procedure for calculating the coefficients of n- space indices is described. Spectra from 12 wheat and two bare soil (wet and dry) plots were multiplied point by point (at 1-nm intervals) by response functions representing five satellite sensors. Reflectance values were obtained for each band for each sensor (atmospheric effects and sensor characteristics such as noise, resolution, and calibration, were not considered). N- Space indices were calculated for various band combination for the several sensors and their dynamic range for a 0–100% change in vegetation was compared. A 6-D vegetation index (greenness) calculated using six of the thematic mapper bands had the greatest dynamic range, followed closely by two 5-D and one 4-D greenness from the same sensor. The 2-D greenness using bands 4 (near-IR) and 7 (mid-IR) of the thematic mapper had a greater dynamic range than any band combination of the other four satellite sensors. The 4-D greenness of the Landsat-4 MSS and the 3-D index of the SPOT HRV were similar. The 2-D indices from the AVHRR sensors on NOAA-6 and NOAA-7 changed less with vegetation changes than did the other three.

Evaluating the Crop Coefficient Using Spectral Reflectance1

AbstractA field study was conducted in four differentially irrigated plots of alfalfa (Medicago sativa L.) planted in Shiprock sandy loam (coarseloamy, mixed, mesic Typic Haplargid) to assess spectral reflectance for estimating the crop coefficient (Kc), defined here as the ratio of actual to potential evapotranspiration (ET). A bidirectional reflectance factor was measured using a three‐channel (0.63 to 0.69 µm, 0.76 to 0.90 µm, and 1.55 to 1.75 µm) handheld radiometer, and was used to calculate a perpendicular vegetation index (PVI). Actual ET was determined by the water balance method in non‐weighing lysimeters, and potential ET was calculated using Penman's equation.Significant linear relationships were found between PVI and percent cover (r2 = 0.911), and between Kc and percent cover (r2 = 0.815). In addition, the position of the PVl intersection on the soil background line changed as a result of soil moisture increases following irrigation, even at high percent cover. Thus, once experimental relationships between Kc and crop growth are established, a mean Kc can be determined from spectral estimates of stage of development and the soil background component of PVI can be used to adjust the mean K, for increased evaporation following irrigation because the ratio of actual to potential evapotranspiration will approach 1 when the soil surface is wet.

Remotely-sensed spectral indicators of sorghum development and their use in growth modeling

Earth Resources Technology Satellite (LANDSAT) multispectral scanner (MSS) data for five overpass dates (3/5, 21/5, 8/6, 28/6 and 1/8) during the 1976 grain sorghum growing season (Bell County, Texas) and weather data were used to estimate the plant growth measurements leaf area index (LAI), biomass, plant height, plant cover, and grain yield. Vegetaton indices derived from LANDSAT data were correlated to crop development and growing conditions as measured with LAI and biomass samples. Largest LAI and perpendicular vegetation index (PVI) calculated from LANDSAT spectral data occurred at the half-bloom (HB) stage of development. The PVI was significantly correlated with sorghum PGM on the earliest sampling date (3/5/76) when vegetative ground cover was only 20%. Regression analysis indicated that the PVI explained 79% of the variaton in estimating LAI over the first four sampling dates. On the other hand, the regression of PVI, solar-thermal units, and a soil water index accounted for 90% of the variation in LAI measurements. This result indicated that plant-growth models that mimic plant response to soil and climatic environments will improve yield estimates over those arrived at from spectral data alone. Since LAI is used in growth models to partition energy between plants and soil in the evapotranspiration subroutine and to estimate light interception in the photosynthesis subroutine, LAI estimates from LANDSAT would provide this information for use either as (1) input data, or (2) feedback data to check on growth model predictions and retrack the model, if necessary.