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1.
A field experiment was conducted to study the effect of vegetation cover on soil spectra and relationship of spectral indices with vegetation cover. Multi-date spectral measurements were carried out on twelve wheat fields. Five sets of measurements were taken during the growth period of wheat crop. Field reflectance data were collected in the range 350 to 1800 nm using ASD spectroradiometer. Analysis of data was done to select narrow spectral bands for estimation of ground cover. The ratio of reflectance from vegetation covered soil and reflectance from bare soil indicated that spectral reflectance at 670 and 710 nm are the most sensitive bands. Two bands in visible (670 and 560 nm), three bands in near infrared (710, 870 and 1100 nm) and three bands in middle infrared (1480, 1700 and 1800 nm) were found highly correlated with fractional cover. Vegetation indices developed using narrow band spectral data have been found to be better than those developed using broad- band data for estimation of ground cover.  相似文献   

2.
Field experiments were conducted during 1998–99 and 1999–2000 at research farm of the Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar. Five wheat cultivars: WH 542, PBW 343, UP 2338, Raj 3765 and Sonak were sown on 25th November, 10th and 25th December with four nitrogen levels viz., no nitrogen. 50, 100 and 150% of recommended dose. Leaf area index, dry matter at anthesis, final dry biomass and grain yield were recorded in all the treatments. Chlorophyll and wax contents of wheat leaves were estimated at different growth stages. Multiband spectral reflectance was measured using hand-held radiometer. Spectral indices such as simple ratio, normalized difference, transformed vegetation index, perpendicular vegetation index and greenness index were computed using the multiband spectral data. Values of all the spectral indices were maximum in 25 November sown crop with maximum dose of nitrogen (180 kg N ha-1). PBW 343 showed higher values of all the spectral indices in comparison with other cultivars. The spectral indices recorded during maximum leaf area index stage were correlated with crop parameters. Using stepwise regression, empirical models for chlorophyll, leaf area index, dry biomass and yield prediction were developed. The ’R2’ values of these models ranged between 0.87 and 0.95.  相似文献   

3.
The potential usefulness of spectral properties and vegetation indices in varietal discrimination of potato genotypes was studied in the field experiment. Spectral measurements were recorded in different bands in blue (450–520 nm), green (520–590 nm), red (620–680 nm) and infrared (770–860 nm) of the electromagnetic spectrum at different stages during crop growth period. A ground based hand held multiband radiometer (Model/041) was used for the purpose. The mean per cent green reflectance value among different genotypes was lowest in genotype MS/86-89, while it was observed highest in genotype JX-216. Significant difference among these genotypes was found at all growth stages except 6 week after planting. Consequent to variation in spectral reflectance the vegetation indices like, NDVI, RVI, TVI and DVI showed significant difference among genotypes at all growth stages except at 8th week after planting. The vegetation indices are good indicators of crop growth and condition. Similarly, fresh weight, dry weight, and leaf area index were also highest in MS/86-89, followed by KUFRI Bahar and KUFRI Sutlej while in case of leaf area index it was followed by Kufri Sutlej and Kufri Bahar. JX-23 was highest in chlorophyll content and tuber yield followed by MS/86-89 and JW-160, while lowest chlorophyll content was seen in MS/89-1095 and poorest tuber yield in MS/89-60. Most of the genotypes exhibited considerable variation in their spectral response and vegetation indices thereby indicating the possibility of their discrimination through remote sensing technique.  相似文献   

4.
Spectral reflectance characteristics of jojoba (Simmondsia chinensis (Link) Schneid.), a dioecious member of Buxaceae have been studied, especially under salinity stress. Reflectance is minimum at bands 1 and 2 (450–520 nm and 520–590 run) of visible range and maximum at bands 3 and 4 (620–680 nm and 770–860 nm) of near infrared range. At all wavelength intervals, male plants have greater reflectance than females. Reflectance in near infrared range (band 4) decreases with increasing age and leaf area index (LAI). A reverse trend occurs at band 3. Absorptance increases in visible as well as Infrared ranges with increasing salinity from control to 10 PSU of sea water concentration.  相似文献   

5.
Hyperspectral sensing can provide an effective means for fast and non-destructive estimation of leaf nitrogen (N) status in crop plants. The objectives of this study were to design a new method to extract hyperspectral spectrum information, to explore sensitive spectral bands, suitable bandwidth and best vegetation indices based on precise analysis of ground-based hyperspectral information, and to develop regression models for estimating leaf N accumulation per unit soil area (LNA, g N m−2) in winter wheat (Triticum aestivum L.). Three field experiments were conducted with different N rates and cultivar types in three consecutive growing seasons, and time-course measurements were taken on canopy hyperspectral reflectance and LNA under the various treatments. Then, normalized difference spectral indices (NDSI) and ratio spectral indices (RSI) based on the original spectrum and the first derivative spectrum were constructed within the range of 350–2500 nm, and their relationships with LNA were quantified. The results showed that both LNA and canopy hyperspectral reflectance in wheat changed with varied N rates, with consistent patterns across different cultivars and seasons. The sensitive spectral bands for LNA existed mainly within visible and near infrared regions. The best spectral indices for estimating LNA in wheat were found to be NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516), and the regression models based on the above four spectral indices were formulated as Y = 26.34x1.887, Y = 5.095x − 6.040, Y = 0.609 e3.008x and Y = 0.388x1.260, respectively, with R2 greater than 0.81. Furthermore, expanding the bandwidth of NDSI (R860, R720) and RSI (R990, R720) from 1 nm to 100 nm at 1 nm interval produced the LNA monitoring models with similar performance within about 33 nm and 23 nm bandwidth, respectively, over which the statistical parameters of the models became less stable. From testing of the derived equations, the model for LNA estimation on NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) gave R2 over 0.79 with more satisfactory performance than previously reported models and physical models in wheat. It can be concluded that the present hyperspectral parameters of NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) can be reliably used for estimating LNA in winter wheat.  相似文献   

6.
Utility of Hyperspectral Data for Potato Late Blight Disease Detection   总被引：1，自引：0，他引：1  
The study was carried out to investigate the utility of hyperspectral reflectance data for potato late blight disease detection. The hyperspectral data was collected for potato crop at different level of disease infestation using hand-held spectroradiometer over the spectral range of 325–1075 nm. The data was averaged into 10-nm wide wavebands, resulting in 75 narrowbands. The reflectance curve was partitioned into five regions, viz. 400–500 nm, 520–590 nm, 620–680 nm, 770–860 nm and 920–1050 nm. The notable differences in healthy and diseased potato plants were noticed in 770–860 nm and 920–1050 nm range. Vegetation indices, namely NDVI, SR, SAVI and red edge were calculated using reflectance values. The differences between the vegetation indices for plants at different levels of disease infestation were found highly significant. The optimal hyperspectral wavebands to discriminate the healthy plants from disease infested plants were 540, 610, 620, 700, 710, 730, 780 and 1040 nm whereas upto 25% infestation could be discriminated using reflectance at 710, 720 and 750 nm.  相似文献   

7.
The results emerged out of the studies on spectral reflectance under normal and nitrogen and phosphorus stress condition in soybean (Glycine max L.) conducted at Marathwada Agricultural University experimental farm, Parbhani duringkharif 2004–05 showed that crop growth and bio-physiological parameters viz., Height, chlorophyll, leaf area index and total biomass influenced by pest and disease and nutrient stress resulted in detectable spectral reflectance variation. Poor crop growth, reduced canopy cover, chlorophyll content and biomass production are the effects observed in nutrient deficient crops. These above changes in soybean crop were related to spectral indices (RVI and NDVI) that are resulted in discrimination of stressed and normal (non-stressed) soybean crop.  相似文献   

8.
Advanced site-specific knowledge of grain protein content of winter wheat from remote sensing data would provide opportunities to manage grain harvest differently, and to maximize output by adjusting input in fields. In this study, remote sensing data were utilized to predict grain protein content. Firstly, the leaf nitrogen content at winter wheat anthesis stage was proved to be significantly correlated with grain protein content (R2 = 0.36), and spectral indices significantly correlated to leaf nitrogen content at anthesis stage were potential indicators for grain protein content. The vegetation index, VIgreen, derived from the canopy spectral reflectance at green and red bands, was significantly correlated to the leaf nitrogen content at anthesis stage, and also highly significantly correlated to the final grain protein content (R2 = 0.46). Secondly, the external conditions, such as irrigation, fertilization and temperature, had important influence on grain quality. Water stress at grain filling stage can increase grain protein content, and leaf water content is closely related to irrigation levels, therefore, the spectral indices correlated to leaf water content can be potential indicators for grain protein content. The spectral reflectance of TM channel 5 derived from canopy spectra or image data at grain filling stage was all significantly correlated to grain protein content (R2 = 0.31 and 0.37, respectively). Finally, not only this study proved the feasibility of using remote sensing data to predict grain protein content, but it also provided a tentative prediction of the grain protein content in Beijing area using the reflectance image of TM channel 5.  相似文献   

9.
The remote sensing community in geology is widely using the Multispectral Landsat Thematic Mapper (TM) data which has a wider choice of spectral bands (six between 0.45 and 2.35 μm, plus a thermal infrared channel 10.4-12.5 urn). These were evaluated for low-grade magnetite ores mapping over the high-grade granulite region of Kanjamalai area of Tamil Nadu state, India. The Fourier Transform Infrared (FTIR) spectroscopy data (0.4-4.0 μm) for powders of the magnetite ores exposed with granulite rock and published spectral reflectance data were used as guides in selecting TM band reflectance ratios, which maximize discrimination of magnetite ores on the basis of their respective mineralogies. The study shows that the weathering mineralogy of magnetite ores causes absorption features in their reflectance spectra which are particularly characteristic of the near infrared. Comparison of TM data with field and petrographic observations shows the presence of magnetite and aluminosilicate minerals & show strong absorption at 0.7-1 μ.m wavelength spectral region & increase in the product of two TM band ratios: band 5 (1.55-1.75 μm) to band 4 (0.76-0.9 μm) and band 3 (0.63-0.69 μm) to band 4 (0.76-0.9 μm). Various computer image enhancement and data extraction techniques such as interactive digital image classification techniques using color compositing stretched ratio, maximum likelihood and thresholding statistical approaches using Landsat TM data are used to map the low-grade magnetite ores of the granulite region. The field traverses and local verification enhanced to map the other rock types namely granulites and gneisses of the study area.  相似文献   

10.
The study to establish the optimum time span for distinguishing Avena ludoviciana from wheat crop based on their spectral signatures was carried out at Student’s Research Farm, Department of Agronomy during 2006–07 and 2007–08. The experimental sites during both the seasons were sandy loam in texture, with normal soil reaction and electrical conductivity, low in organic carbon and available nitrogen and medium in available phosphorus and potassium. The experiment was laid out in randomized block design with four replications and consisting of twelve treatments comprising 0, 10, 15, 25, 50, 75, 100, 125, 150, 200, 250 plants m−2 and a pure Avena ludoviciana plot (Tmax). The results revealed that in all the treatments irrespective of wheat and weeds, the red reflectance (%) value decreased from 34 to 95 DAS (days after sowing) in 2006–07 and 45 DAS to 100 DAS during 2007–08, and thereafter a sharp increase was observed in all the treatments. This trend might be due to increased chlorophyll index after 34 DAS as red reflectance was reduced by chlorophyll absorption. Among all the treatments, Tmax (Pure Avena ludoviciana plot) had the highest red reflectance and T0 (Pure wheat plot) had a lowest value of red reflectance during both the years. The highest value of IR reflectance was obtained at 95 DAS (2006–07) and 70 DAS (2007–08) in all the treatments. IR reflectance of wheat crop ranged between 24.61 and 61.21 per cent during 2006–07 and 27.33 and 67.3 per cent during 2007–08. However, IR reflectance values declined after 95 DAS and 70 DAS up to harvesting during 2006–07 and 2007–08. This lower reflectance may have been due to the onset of senescence. The highest RR and NDVI values were recorded under pure wheat treatment and minimum under pure weed plots. This may be due to dark green colour and better vigor of the wheat as compared to Avena ludoviciana. It was observed that by using RR and NDVI, pure wheat can be distinguished from pure populations of Avena ludoviciana after 34 DAS and different levels of weed populations can be discriminated amongst themselves from 68 DAS up to 107 DAS during both the years of investigation.  相似文献   

11.
利用多时相的高光谱航空图像监测冬小麦条锈病   总被引：31，自引：1，他引：31  
冬小麦发生锈病 ,叶绿素被大量破坏 ,水分蒸滕量大大增加 ,叶片细胞大小、形态、叶片结构发生了改变 ,从而改变了叶片和冠层的光学特性 ,使得遥感探测与评价成为可能。利用多时相的高光谱航空飞行图像数据 ,了解、分析和发现条锈病病害对作物光谱的影响及其光谱特征 ;设计了病害光谱指数 ,成功地监测了冬小麦条锈病病害程度与范围。对比 3个生育期的条锈病与正常生长冬小麦的PHI图像光谱及光谱特征 ,发现 :5 6 0— 6 70nm黄边、红谷波段 ,条锈病病害冬小麦的冠层反射率高于正常生长的冬小麦光谱反射率 ;近红外波段 ,条锈病病害的冠层反射率低于正常生长的冬小麦光谱反射率 ;条锈病冬小麦冠层光谱红谷吸收深度和绿峰的反射峰高度都会减小  相似文献   

12.
The objective of this study was to investigate the entire spectra (from visible to the thermal infrared; 0.390–14.0 μm) to retrieve leaf water content in a consistent manner. Narrow-band spectral indices (calculated from all possible two band combinations) and a partial least square regression (PLSR) were used to assess the strength of each spectral region. The coefficient of determination (R2) and root mean square error (RMSE) were used to report the prediction accuracy of spectral indices and PLSR models. In the visible-near infrared and shortwave infrared (VNIR–SWIR), the most accurate spectral index yielded R2 of 0.89 and RMSE of 7.60%, whereas in the mid infrared (MIR) the highest R2 was 0.93 and RMSE of 5.97%. Leaf water content was poorly predicted using two-band indices developed from the thermal infrared (R2 = 0.33). The most accurate PLSR model resulted from MIR reflectance spectra (R2 = 0.96, RMSE = 4.74% and RMSE cross validation RMSECV = 6.17%) followed by VNIR–SWIR reflectance spectra (R2 = 0.91, RMSE = 6.90% and RMSECV = 7.32%). Using thermal infrared (TIR) spectra, the PLSR model yielded a moderate retrieval accuracy (R2 = 0.67, RMSE = 13.27% and RMSECV = 16.39%). This study demonstrated that the mid infrared (MIR) and shortwave infrared (SWIR) domains were the most sensitive spectral region for the retrieval of leaf water content.  相似文献   

13.
In this study, digital images collected at a study site in the Canadian High Arctic were processed and classified to examine the spatial-temporal patterns of percent vegetation cover (PVC). To obtain the PVC of different plant functional groups (i.e., forbs, graminoids/sedges and mosses), field near infrared-green-blue (NGB) digital images were classified using an object-based image analysis (OBIA) approach. The PVC analyses comparing different vegetation types confirmed: (i) the polar semi-desert exhibited the lowest PVC with a large proportion of bare soil/rock cover; (ii) the mesic tundra cover consisted of approximately 60% mosses; and (iii) the wet sedge consisted almost exclusively of graminoids and sedges. As expected, the PVC and green normalized difference vegetation index (GNDVI; (RNIR − RGreen)/(RNIR + RGreen)), derived from field NGB digital images, increased during the summer growing season for each vegetation type: i.e., ∼5% (0.01) for polar semi-desert; ∼10% (0.04) for mesic tundra; and ∼12% (0.03) for wet sedge respectively. PVC derived from field images was found to be strongly correlated with WorldView-2 derived normalized difference spectral indices (NDSI; (Rx − Ry)/(Rx + Ry)), where Rx is the reflectance of the red edge (724.1 nm) or near infrared (832.9 nm and 949.3 nm) bands; Ry is the reflectance of the yellow (607.7 nm) or red (658.8 nm) bands with R2’s ranging from 0.74 to 0.81. NDSIs that incorporated the yellow band (607.7 nm) performed slightly better than the NDSIs without, indicating that this band may be more useful for investigating Arctic vegetation that often includes large proportions of senescent vegetation throughout the growing season.  相似文献   

14.
The present study investigates the characteristics of CO2 exchange (photosynthesis and respiration) over agricultural site dominated by wheat crop and their relationship with ecosystem parameters derived from MODIS. Eddy covariance measurement of CO2 and H2O exchanges was carried out at 10 Hz interval and fluxes of CO2 were computed at half-hourly time steps. The net ecosystem exchange (NEE) was partitioned into gross primary productivity (GPP) and ecosystem respiration (R e) by taking difference between day-time NEE and respiration. Time-series of daily reflectance and surface temperature products at varying resolution (250–1000 m) were used to derive ecosystem variables (EVI, NDVI, LST). Diurnal pattern in Net ecosystem exchange reveals negative NEE during day-time representing CO2 uptake and positive during night as release of CO2. The amplitude of the diurnal variation in NEE increased as LAI crop growth advances and reached its peak around the anthesis stage. The mid-day uptake during this stage was around 1.15 mg CO2 m−2 s−1 and night-time release was around 0.15 mg CO2 m−2 s−1. Linear and non-linear least square regression procedures were employed to develop phenomenological models and empirical fits between flux tower based GPP and NEE with satellite derived variables and environmental parameters. Enhanced vegetation index was found significantly related to both GPP and NEE. However, NDVI showed little less significant relationship with both GPP and NEE. Furthemore, temperature-greenness (TG) model combining scaled EVI and LST was parameterized to estimate daily GPP over dominantly wheat crop site. (R 2 = 0.77). Multi-variate analysis shows that inclusion of LST or air temperature with EVI marginally improves variance explained in daily NEE and GPP.  相似文献   

15.
In the present study, The Landsat 7 ETM satellite data was collected for the Sittampundi anorthosites complex and digital image analysis was carried out. The anorthositic rocks available at Sittampundi complex is considered as an equivalent of lunar highland rocks. Hence, a remote sensing study comprises of image analysis and spectral profile analysis was carried out. The satellite data was digitally processed and generated various outputs like band combinations, color composites, stretched outputs, and PCA. The suitable processed outputs were identified for delineating the anorthosite complex. The diagnostic absorption features of reflectance spectra are the sensitive indicators of mineralogy and chemical composition of rocks, which are interest to the planetary scientists. The spectral profile of Landsat ETM plotted for pure and mixed anorthosite pixels and compared with the field and lab reflectance spectra. The percentages of image spectra vary from 30% to 60% for Sittampundi anorthosite. The spectral bands 2, 4 and 6 have low reflectance and bands 3 and 5 have high reflectance. The spectral range of bands 2,3,4,5 and 6 are 525 nm–605 nm, 630 nm–690 nm, 750 nm–900 nm, 1550 nm–1750 nm and 10400 nm–12500 nm respectively. The field spectral curve has weak absorptions at 650 nm and 1000 nm due to the iron transition absorption and low ca- pyroxene respectively available in the anorthosite, matching with the image spectra. However, hyperspectal image with narrow bandwidth could be more useful in selecting the suitable spectrum for remotely mapping the anorthosite region, as equivalent test site for lunar highland region.  相似文献   

16.
Field experiment was conducted during 2009–10 and 2010–11 rabi season at research farm of IARI, New Delhi for assessing the aphid infestation in mustard. In aphid infested plant the LAI was 67 to 94% lower than healthy plant. Chlorophyll concentration decreased to 50% in infested plant as compared to healthy plant. Infestation was more severe in late sown crop and due to aphid infestation the percentage oil content and yield was reduced significantly. The spectral reflectance of aphid infested canopy and healthy canopy taken in the laboratory had significant difference in NIR region. In the visible region, the reflectance peak occurred in healthy canopy at around 550–560 nm while this peak was lower by 31% in the aphid infested canopy. The reflectance for healthy crop was found to be more in visible as well as NIR region as compared to aphid infested canopy. The most significant spectral bands for the aphid infestation in mustard are in visible (550–560 nm) and near infrared regions (700–1250 nm and 1950–2450 nm). The different level of aphid infestation can be identified in 1950–2450 nm spectral regions. Spectral indices viz NDVI, RVI, AI and SIPI had significant correlation with aphid infestation. Hence these indices could be used for identifying aphid infestation in mustard.  相似文献   

17.
Thaumastocoris peregrinus (T. peregrinus) is a sap sucking insect that feeds on Eucalyptus leaves. It poses a threat to the forest industry by reducing the photosynthetic ability of the tree, resulting in stunted growth and even death of severely infested trees. Remote sensing techniques offer the potential to detect and map T. peregrinus infestations in plantation forests using current operational hyperspectral scanners. This study resampled field spectral data measured from a field spectrometer to the band settings of the Hyperion sensor in order to assess its potential in predicting T. peregrinus damage. Normalized indices based on NDVI ratios were calculated using the resampled visible and near-infrared bands of the Hyperion sensor to assess its utility in predicting T. peregrinus damage using Partial Least Squares (PLS) regression. The top 20 normalized indices were based on specific biochemical absorption features that predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.63 on an independent test dataset. The top 20 indices were located in the near-infrared region between 803.3 nm and 894.9 nm. Twenty three previously published hyperspectral indices which have been used to assess stress in vegetation were also used to predict T. peregrinus damage and resulted in a mean bootstrapped R2 value of 0.59 on an independent test dataset. The datasets were combined to assess its collective strength in predicting T. peregrinus damage and significant indices were chosen based on variable importance scores (VIP) and were then entered into a PLS model. The indices chosen by VIP predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.71 on an independent test dataset. A greedy backward variable selection model was further tested on the VIP selected indices in order to find the best subset of indices with the best predictive accuracy. The greedy backward variable selection model identified 3 indices and performed the best by predicting damage with an R2 value of 0.74 with the lowest RMSE of 1.30% on an independent test dataset. The best three indices identified include the anthocyanin reflectance index, carotenoid reflectance index and the normalized index calculated at 864.4 and 884.7 nm. Individual relationships between these indices and T. peregrinus damage indicate that high correlations are obtained with the inclusion of a few severely infested trees in the sample size. When the severely infested trees were removed from the study, the normalized index (864.4 and 884.7 nm) and the anthocyanin reflectance index still yielded significant correlations at the 99% confidence interval. This study indicates the significance of normalized indices and spectral indices calculated from the visible and near-infrared bands in hyperspectral data for the prediction of T. peregrinus damage.  相似文献   

18.
This paper reports a study on multi-temporal polarized response of wheat crop from spaceborne ADEOS-POLDER sensor over a homogeneous wheat region of Punjab, India. Both the polarized as well as total reflectance of wheat were observed at different scattering angles for two spectral bands i.e. 670 nm and 865 nm during crop growth from November to April in rabi 1996-97 season. Results show that sun-target-viewing geometry plays an important role in polarization property. The top of atmosphere (TOA) polarized reflectance is found to decrease exponentially with increasing scattering angle. Polarized reflectance of crop was found to be an order of magnitude smaller in comparison to the total reflectance. An attempt was also made to model the observed polarized behavior over an agricultural area using a theoretical simplified crop reflectance model and accounting for atmospheric molecular (Rayleigh) contribution in the single scattering approximation. It was found that there was a decrease in the polarized reflectance at the grain filling (heading) stage of wheat crop. This is in accordance with ground- based observations and can be due to the reduction in the specular component of the reflected light during post-heading stage of the crop.  相似文献   

19.
In-situ chlorophyll concentration data and remote sensing reflectance (Rrs) measurements collected in six different ship campaigns in the Arabian Sea were used to evaluate the accuracy, precision, and suitability of different ocean color chlorophyll algorithms for the Arabian Sea. The bio-optical data sets represent the typical range of biooptical conditions expected in this region and are composed of 47 stations encompassing chlorophyll concentration, between 0.072 and 5.90 mg m-3, with 43 observations in case I water and 4 observations in case II water. Six empirical chlorophyll algorithms [i.e. Aiken-C, POLDER-C, OCTS-C, Morel-3, Ocean Chlorophyll-2 (OC2) and Ocean Chlorophyll-4 (OC4)] were selected for analysis on the Arabian Sea data set. Numerous statistical and graphical criterions were used to evaluate the performance of these algorithms. Among these six chlorophyll algorithms two chlorophyll algorithms (i.e. OC2 and OC4) performed well in the case I waters of the Arabian Sea. The OC2 algorithm, a modified cubic polynomial function which uses ratio of Rrs490 nm and Rrs555 nm (where, Rrs is remote sensing reflectance), performed well with r2=0.85; rms =0.15. The OC4 algorithm, a four-band (443, 490, 510, 555 nm), maximum band ratio formulation was found best on the basis of statistical analysis results with r2=0.85 and rms=0.14. Both OC2 and OC4 algorithms failed to estimate chlorophyll inTrichodesmium dominated waters. The OC2 algorithm was preferred over OC4 algorithm for routine processing of the OCM data to generate chlorophyll-a images, as it uses a band ratio of 490/555 nm and atmospheric correction is more accurate in 490 nm compared to 443 nm band, which is used by OC4 algorithm.  相似文献   

20.
The current development of satellite technology particularly in the sensors like POLDER and MISR, has emphasized more on directional reflectance measurements (i.e. spectral reflectance of the target measured from different view zenith and azimuth angles) of the earth surface features mainly the vegetation for retrieval of biophysical parameters at regional scale using radiative transfer models. This approach being physical process based and uses directional reflectance measurement has been found to better and more reliable compared to the conventional statistical approach used till date and takes care of anisotropic nature (i.e. reflectance from the target is different if measured from different view angles) of the target. Keeping this in view a field experiment was conducted in mustard crop to evaluate the radiative transfer model for biophysical parameter retrieval through its inversion with the objectives set as (i) to relate canopy biophysical parameters and geometry to its bidirectional reflectance, (ii) to evaluate a canopy reflectance model to best represent the radiative transfer within the canopy for its inversion and (iii) to retrieve crop biophysical parameters through inversion of the model. Two varieties of the mustard crop (Brassica juncea L) were grown with two nitrogen treatments. The bidirectional reflectance data obtained at 5 nm interval for a range of 400–1100 nm were integrated to IRS LISS–II sensor’s four band values using Newton Cotes Integration technique. Biophysical parameters like leaf area index, leaf chlorophyll content, leaf length, plant height and average leaf inclination angle, biomass etc were estimated synchronizing with the bi-directional reflectance measurements. Radiative transfer model PROSAIL model was validated and its inversion was done to retrieve LAI and ALA. Look Up Table (LUT) of Bidirectional reflectance distribution function (BRDF) was prepared simulating through PROSAIL model varying only LAI (0.2 interval from 1.2 to 5.4 ) and ALA (5° interval from 40° to 55°) parameters and inversion was done using a merit function and numerical optimization technique given by Press et al. (1986). The derived LAI and ALA values from inversion were well matched with observed one with RMSE 0.521 and 5.57, respectively.  相似文献   

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