Retrieval of total suspended matter concentration from Gaofen-1 Wide Field Imager (WFI) multispectral imagery with the assistance of Terra MODIS in turbid water – case in Deep Bay

This study proposed a method for developing high spatial resolution Gaofen-1 satellite (GF-1) Wide Field Imager (WFI)-based total suspended matter concentration (C_TSM) retrieval model with the assistance of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using the Deep Bay in China as a case. Based on long-term calibrated C_TSM measurements of optical backscatter (OBS) 3A turbidity and temperature monitoring system of two stationary stations from January 2007 through November 2008, 33 match-ups were selected to build an exponential retrieval model for MODIS atmospherically corrected remote-sensing reflectance (R_rs) ratio (R_rs,645/R_rs,555). Validation of the MODIS model showed well agreement with the seven in situ C_TSM measurements with a root mean squared error (RMSE) of 5.06 mg l^?1 and a coefficient of determination R² of 0.80. Aided with six MODIS retrieved C_TSM products, different band combinations (single band (R_rc,660), band subtraction (R_rc,660–R_rc,560), band ratio (R_rc,660/R_rc,560), and total suspended matter index at 660 nm band (TSMI₆₆₀) were evaluated for simultaneous GF-1 WFI Rayleigh-corrected reflectance (R_rc). The results showed that the exponential model based on the Rayleigh-corrected reflectance ratio (R_rc,660/R_rc,560) could achieve acceptable accuracy, with RMSE of 14.80 mg l^?1 and R² of 0.62. The proposed method would be helpful for dynamic monitoring in the Deep Bay, and more important could also provide an alternative approach for studies when in situ measurements are unreachable.     

Retrieval of remotely sensed sea surface salinity using MODIS data in the Chinese Bohai Sea

Salinity dominates seawater density and directly affects physical and biochemical processes. Having a reliable retrieval model is essential to providing frequent and accurate sea surface salinity (SSS) data for marine research. Remote-sensing techniques provide alternatives for SSS data retrieval with its advantages of wide area surveys and real-time monitoring. In the present study, inverse relationship between SSS and coloured dissolved organic matter (CDOM) concentration in the Chinese Bohai Sea was verified. Thus, four simple band ratios of the original remote-sensing reflectance (R_rs) used to retrieve the CDOM concentration were compared and tested during SSS retrieval. R_rs (531)/R_rs (551) performed best among the four given band ratios. The model employed here can be applied to derive SSS with a root mean square error (RMSE) of 0.26 practical salinity units (psu) (R² = 0.76). A calibration model was verified using a discrete dataset of the measured SSS and was tested further during mapping of SSS in the Chinese Bohai Sea during 2010–2014. The yielded spatial patterns of SSS were satisfactory and an inverse relationship between SSS and the Yellow River discharge was confirmed.     

Numerical simulation-aided MODIS capture of sediment transport for the Bohai Sea in China

Traditionally, the establishment of a remote-sensing retrieval model depends on in situ data acquired by expensive and considerably labour-intensive field surveys, but now we can benefit from numerical simulation. In this study, after considering the advantages of numerical simulation in extending the spatial and temporal suspended sediment concentration (SSC), we propose an approach to establish an SSC retrieval model from remotely sensed images with the aid of a numerical model for the Bohai Sea in China. First, significant correlation, between simulated SSC and atmosphere-corrected water-leaving reflectance derived from Moderate Resolution Imaging Spectroradiometer (MODIS) band-1 images, was investigated to demonstrate a novel SSC retrieval model. The synchronous data from remote sensing and numerical simulations enabled the removal of spatial and temporal differences between satellite and in situ measurements. Based on this retrieval model, the SSC distribution pattern was simulated in two scenarios to separate river sediment discharge from the overall process of resuspension. The results indicate that the distribution pattern of the simulated surface SSC without sediment discharge from the Yellow River in most study areas generally matched that derived from MODIS images, except for the estuarine area. The surface SSC 30–40 km away from the estuaries are dominated by sediment discharge from rivers. The proposed method, the numerical simulation-aided SSC retrieval MODIS model, can efficiently capture the sediment transport in the Bohai Sea, which is helpful for operational monitoring of the water environment in estuary and coastal waters.     

Estimation of chlorophyll‐a concentration and trophic states for inland lakes in Northeast China from Landsat TM data and field spectral measurements

Landsat TM data and field spectral measurements were used to evaluate chlorophyll‐a (Chl‐a) concentration levels and trophic states for three inland lakes in Northeast China. Chl‐a levels were estimated applying regression analysis in the study. The results obtained from the field reflectance spectra indicate that the ratio between the reflectance peak at 700 nm and the reflectance minimum at 670 nm provides a relatively stable correlation with Chl‐a concentration. Their determination of coefficients R ² is 0.69 for three lakes in the area. From Landsat TM data, the results show that the most successful Chl‐a was estimated from TM3/TM2 with R ² = 0.63 for the two lakes on 26 July 2004, from TM4/TM3 with R ² = 0.89 for the two lakes on 14 October 2004, and from the average of TM2, TM3 and TM4 with R ² = 0.72 for the three lakes tested on 13 July 2005. These results are applicable to estimate Chl‐a from satellite‐based observations in the area. We also evaluate the trophic states of the three lakes in the region by employing Shu's modified trophic state index (TSI_M) for the Chinese lakes' eutrophication assessment. Our study presents the TSI_M from different TM data with R ² more than 0.73. The study shows that satellite observations are effectively applied to estimate Chl‐a levels and trophic states for inland lakes in the area.     

Influence of the canopy BRDF characteristics and illumination conditions on the retrieval of solar-induced chlorophyll fluorescence

The Fraunhofer line discrimination (FLD) principle is the main approach used for the retrieval of solar-induced chlorophyll fluorescence (SIF). The basic assumption of the FLD principle is that the apparent reflectance spectra without SIF in-filling are smooth in the region of the absorption bands. However, in fact, this assumption is not valid due to the so-called ‘direct radiation in-filling’ effect caused by the nonlinear contribution of direct and diffuse radiation at the oxygen absorption bands, which are widely used for ground-based SIF retrieval. In this study, we first analysed the physical mechanism of the direct radiation in-filling effect on the oxygen absorption bands and found that the bias in the SIF retrieval caused by the direct radiation in-filling effect at the oxygen-A (O₂-A) band was less than 20% based on the use of a simulated data set. Second, we established a simple correction model of the direct radiation in-filling effect. We found that the direct radiation in-filling effect at the O₂-A band was directly proportional to the difference between the reflectance of the direct and diffuse radiation, and that the coefficient of proportionality was well correlated with the diffuse-to-global radiation ratio in the form of a quadratic function, with a coefficient of determination (R²) of 0.97. Finally, the model was validated using both simulated and field data sets. The validation results show that the bias in the SIF retrieval caused by the direct radiation in-filling effect can be efficiently corrected using the model proposed in this article. This study thus provides a possible approach to estimating and correcting for the direct radiation-infilling effect using prior knowledge of the bidirectional reflectance distribution function characteristics of direct and diffuse radiation for specific targets.     

An algorithm for the retrieval of suspended sediment concentrations in the Irish Sea from SeaWiFS ocean colour satellite imagery

A study was conducted in the Irish Sea with the aim of deriving an algorithm for the retrieval of suspended sediment concentrations from ocean colour imagery obtained from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). In situ observations of the diffuse attenuation coefficient, K_d , and irradiance reflectance, R, were obtained at wavelengths coincident with the SeaWiFS visible wavebands using a Profiling Reflectance Radiometer (PRR600, Biospherical Instruments Inc., San Diego). Results showed that surface reflectance at 665 nm (R₆₆₅ ), rather than variations in the intrinsic colour of the ocean (using colour ratios), was the most widely applicable method of obtaining suspended sediment concentrations from ocean colour imagery in this region. The derived algorithm enabled the estimation of mineral suspended sediment (MSS) concentrations from ocean colour in the Irish Sea, accurate to within 1 mg l^?1 (see equation below). Furthermore, the application of this algorithm to a SeaWiFS image of the Irish Sea accurately reproduced known regions of high turbidity with realistic MSS concentrations.

MSS=0.0441R ² ₆₆₅ + 1.1392R ₆₆₅ + 1.7459

(R ²=0.9105, n=124, RMS error=0.907)

Specific absorption and scattering coefficients were derived for all optically active in-water constituents, namely yellow substance (YS), mineral suspended sediments (MSS) and phytoplankton pigments (C). An optical model based on the empirically derived absorption and scattering coefficients reproduced the observed relationship between MSS and R ₆₆₅. Model results highlighted the relative insensitivity of reflectance at 665 nm to variations in the concentrations of other in-water constituents, suggesting that the algorithm may be applicable to the Irish Sea throughout the year.     

Quantifying suspended sediment concentration in subglacial sediment plumes discharging from two Svalbard tidewater glaciers using Landsat-8 and in situ measurements

Marine-terminating outlet glaciers discharge mass through iceberg calving, submarine melting, and meltwater run-off. While calving can be quantified by in situ and remote-sensing observations, meltwater run-off, the subglacial transport of meltwater, and submarine melting are not well constrained due to inherent difficulties observing the subglacial and proglacial environments at tidewater glaciers. Remote-sensing and in situ measurements of surface sediment plumes, and their suspended sediment concentration (SSC), have been used as a proxy for glacier meltwater run-off. However, this relationship between satellite reflectance and SSC has predominantly been established using land-terminating glaciers. Here, we use two Svalbard tidewater glaciers to establish a well-constrained relationship between Landsat-8 surface reflecance and SSC and argue that it can be used to measure relative meltwater run-off at tidewater glaciers throughout a summer melt season. We find the highest correlation between SSCs and Landsat-8 surface reflectance by using the red + NIR band combination (r² = 0.76). The highest correlation between SSCs and in situ field spectrometer measurements is in the 740–800 nm wavelength range (r² = 0.85), a spectral range not currently measured by Landsat. Additionally, we find that in situ and Landsat-8 measurements for surface reflectance of SSCs are not interchangeable and therefore establish a relationship for each detection method. We then use the Landsat-8 relationship to calculate total surface sediment load, finding a strong correlation between total surface sediment load and a proxy for meltwater run-off (r² ≥ 0.89). Our results establish a new metric to calculate SSCs from Landsat-8 surface reflectance and demonstrate how the SSC of subglacial sediment plumes can be used to monitor relative seasonal meltwater discharge at tidewater glaciers.     

Bio‐optical properties and estimation of the optically active substances in Lake Tianmuhu in summer

Bio‐optical properties in an optically complex and biologically productive region of Lake Tianmuhu were determined in three cruises from June to August 2006. The concentrations of three optically active substances, tripton C _Tripton (calculated from total suspended matter and chlorophyll‐a (Chla) and phaeophytin‐a (Pa)), phytoplankton pigment C _Chla+Pa , and chromophoric dissolved organic matter (CDOM) a _CDOM(440), were predicted from the estimated irradiance reflectance based on in situ measurements and laboratory analyses. The total relative contributions of phytoplankton, tripton, CDOM and pure water over the range of photosynthetically active radiation (PAR) (400–700 nm) were 36.1%, 24.2%, 15.9% and 23.8%, respectively. The dominant contribution of phytoplankton to the total absorption was due to high phytoplankton pigment concentration. The range and variation in irradiance reflectance and diffuse attenuation coefficient derived from a bio‐optical model, based on inherent optical properties, compared well with the measured variability. A reasonably strong relationship (R² = 0.92) was observed between irradiance reflectance at 780 nm R(780) and C _Tripton. For our data set, the best algorithm for C _Chla+Pa used the three‐band reflectance model [R ^?1(688)?R ^?1(717)]×R(747). The a _CDOM(440) could be estimated using the ratio of irradiance reflectance R(682)/R(555). The retrieval accuracy (R²) of tripton, phytoplankton pigment and CDOM was 0.92, 0.87 and 0.91, respectively, while the rms. error was 0.90 mg l^?1 (18.2%), 3.27 µg l^?1 (14.8%) and 0.073 m^?1 (15.3%), respectively. Estimation of the concentrations of the three optically active substances was reasonably accurate based on inherent optical properties measurement.     

Inverting a forest canopy reflectance model to retrieve the overstorey and understorey leaf area index for forest stands

In this article, the Kuusk–Nilson forest reflectance and transmittance (FRT) model was inverted to retrieve the overstorey and understorey leaf area index (OU-LAI) of forest stands in the Longmenhe forest nature reserve in China. Data from detailed sample sites were collected in 30 forest stands representing the typical vegetation community in the study area. An uncertainty and sensitivity matrix (USM) was used to analyse the sensitivity of the FRT model parameters based on these data. The results indicated that overstorey LAI strongly influenced stand reflectance, whereas understorey LAI had a much lower impact. To predict OU-LAI in forest stands, FRT model inversion is carried out by minimizing a merit function that provides a measure of the difference between the reflectance simulated by the FRT model and the reflectance originating from optimal band selection of Hyperion data. Various combinations of Hyperion bands were tested to evaluate the most effective wavelengths for the inversion of OU-LAI. The best estimates from 17 Hyperion bands (5 VIS, 8 NIR, 4 SWIR) by the FRT model inversion showed an R ²?=?0.41 and RMSE/mean?=?0.21 for overstorey LAI and R ²?=?0.49 and RMSE/mean?=?0.91 for understorey LAI. Advantages and disadvantages of FRT inversion for retrieval OU-LAI combined with Hyperion data are discussed.     

Evaluation of the Geostationary Ocean Color Imager (GOCI) to monitor the dynamic characteristics of suspension sediment in Taihu Lake

To accurately observe the dynamic concentration of total suspended matter (C_TSM) by geostationary satellite, Geostationary Ocean Color Imager (GOCI), a new, regionally empirical combination algorithm, was developed based on the in situ measurement of water properties. Also, the ability of GOCI (with a 1 h temporal resolution) to capture dynamic change in C_TSM was evaluated using in situ buoy-measured data. The validation results indicate that the combination algorithm (combination of two- and three-band ratio algorithms) can achieve acceptable retrieval results for C_TSM, with 34.52% root mean square error percentage (RMSP) for validation data and 45.01% RMSP for GOCI match-up points. The depth of reflectance valley at 680 nm (R_rs-depth,680) is considered as an index for deciding whether to utilize a two- (R_rs-depth,680 ≤ 0.005) or three-band (R_rs-depth,680 > 0.005) algorithm in the combination algorithm. This combination algorithm overcomes some shortcomings of two- and three-band ratio algorithms of C_TSM in turbid productive water. The results show that sediment resuspension will significantly change the optical properties of water and decrease the universality of the C_TSM retrieval algorithm in the presence of a large area of algae. The influence of sediment resuspension on the C_TSM retrieval algorithm is significant in the central lake but less so in the other four lakes studied due to lake morphology and algal biomass.     

Coupling remote sensing data with in-situ optical measurements to estimate suspended particulate matter under the Evros river influence (North-East Aegean sea,Greece)

ABSTRACT

Monitoring the riverine output of Suspended Particulate Matter (SPM) distribution in marine embayment is a crucial factor for the water quality of neighbouring coastal regions. This study presents satellite-derived SPM calculations against in-situ measurements in the continental shelf of North-East Aegean surrounding the transboundary Evros river mouth. Surface SPM, Inherent Optical Properties (IOPs) and remote sensing reflectance (R_rs) data were collected in a field campaign during low river discharge period (June 2016). The relationship between the optical backscattering coefficient (b_bp) and the in-situ SPM concentrations was investigated. Subsequently, an empirical single band model was applied for estimating SPM concentrations by using the Landsat-8 Operational Land Imager (L8/OLI) red band and the model was then locally tuned within the study area. Furthermore, a multi-band SPM-retrieval algorithm was developed using the in-situ surface reflectance R_rs for calibration and it was validated using the Leave-One-Out Cross Validation technique (LOOCV). The relationship between in-situ SPM and backscattering coefficient values showed good proportionality, thus, nominating the predominance of terrestrial mineral particles. Validation against field measurements indicated that the SPM concentrations derived from the newly-developed multi-band algorithm had an improved significance correlation (96%), compared to both the single band model (not-tuned) (coefficient of determination, R² = 0.82) and its locally tuned version (R² = 0.83). Most importantly, the generated multi-band model apart from exhibiting the best performance (R² = 0.93), it revealed high SPM spots which were not detected by the locally tuned single band model, indicating additional processes originating from river outflows, coastal erosion and subaqueous thermal springs in the area. In contrast, the locally tuned single band model overestimated SPM values in offshore waters, where low concentrations are encountered under the influence of the clear Black Sea Water (BSW).     

Remote-sensing reflectance characteristics of highly turbid estuarine waters – a comparative experiment of the Yangtze River and the Yellow River

An outdoor tank experiment is carried out to analyse the interrelationships between remote-sensing reflectance and sediment characteristics in the highly turbid waters of the Yangtze River and the Yellow River estuaries. The results show that the sensitivity of remote-sensing reflectance to water turbidity is inversely related to suspended sediment concentration (SSC). SSC estimation in the highly turbid waters (SSC > 0.15 g l^?1) is best achieved by using ocean colour ratios, especially the ratio at 810 nm: 700 nm. The effect of particle size of suspended sediment matter (SSM) on the observed remote-sensing reflectance is significant and depends on wavelengths and a SSC range. The mineral composition of SSM has a weak effect on observed reflectance in comparison to that of particle size.     

The spectral responses of algal chlorophyll in water with varying levels of suspended sediment

The purpose of this paper is to investigate the spectral responses of algal chlorophyll and water, under natural sunlight with varying suspended sediment concentrations (SSC). Twenty levels of SSC with each of two sediment types were generated, ranging from 50 to 1000 mgl^?1, in 75101 of water containing chlorophyll-a concentrations of 718 μgl^?1 and 295 μgl^?1. Results indicate that suspended sediments do not eliminate the prominent spectral patterns of algal chlorophyll, even as SSC reached 1000 mgl^?1. Between 400 and 900 nm, the relation between reflectance and SSC satisfies the expression: d²R(λ)/dS²<0. The effects of varying SSC on the positions and magnitudes of pronounced chlorophyll features were investigated. The ratio between the NIR and red wavelengths was totally independent of SSC. Thus, our finding supports using it as an index for measuring chlorophyll in natural surface water containing suspended sediments.     

Remote sensing reflectance and its relationship to optical properties of natural waters

Monte Carlo simulations of photon propagation through natural water have been utilized to determine the sub-surface remote sensing reflectance, R _RSW (the sub-surface value of the ratio of upwelling radiance from the nadir to the downwelling irradiance) as a function of water type (defined by the ratio of the backscattering coefficient to the absorption coefficient Bb/a), solar zenith angle, and incident radiation distribution (direct or diffuse). R _RSW, as opposed to volume reflectance, R _V (the sub-surface value of the ratio of upwelling to downwelling vector irradiance), is directly applicable to remotely sensed data collected over natural waters. It is shown that, for a nadir viewing direction, (a) R _RSW is essentially independent of solar zenith angle and incident radiation distribution and (b) the dominant factor in determining R _RSW is the optical nature of the water body itself (expressed as Bb/a). A relationship between the sub-surface remote sensing reflectance averaged over solar zenith angle between 15° and 89°, R _RSW and water type is found to predict R _RSW with an r.m.s. error of 9 per cent. Also addressed is the determination of the aquatic optical property, Bb/a, from the sub-surface remote sensing reflectance, R _RSW This capability along with the specific absorption and scattering coefficients of aquatic constituents can, through bio-optical models, be used to estimate the concentrations of these aquatic constituents in non-Case I waters. The empirical relationship obtained to estimate Bb/a (with a r.m.s. error of 9·3 per cent) from the nadir value of the sub-surface remote sensing reflectance is Bb/a = 0·0027 + 987R _RSW ? 34·5( R _RSW)² + 1534( R _RSW)³.     

Distinguishing mangrove species with laboratory measurements of hyperspectral leaf reflectance

As a first step in developing classification procedures for remotely acquired hyperspectral mapping of mangrove canopies, we conducted a laboratory study of mangrove leaf spectral reflectance at a study site on the Caribbean coast of Panama, where the mangrove forest canopy is dominated by Avicennia germinans, Laguncularia racemosa, and Rhizophora mangle. Using a high‐resolution spectrometer, we measured the reflectance of leaves collected from replicate trees of three mangrove species growing in productive and physiologically stressful habitats. The reflectance data were analysed in the following ways. First, a one‐way ANOVA was performed to identify bands that exhibited significant differences (P value<0.01) in the mean reflectance across tree species. The selected bands then formed the basis for a linear discriminant analysis (LDA) that classified the three types of mangrove leaves. The contribution of each narrow band to the classification was assessed by the absolute value of standardised coefficients associated with each discriminant function. Finally, to investigate the capability of hyperspectral data to diagnose the stress condition across the three mangrove species, four narrow band ratios (R ₆₉₅/R ₄₂₀, R ₆₀₅/R ₇₆₀, R ₆₉₅/R ₇₆₀, and R ₇₁₀/R ₇₆₀ where R ₆₉₅ represents reflectance at wavelength of 695nm, and so on) were calculated and compared between stressed and non‐stressed tree leaves using ANOVA.

Results indicate a good discrimination was achieved with an average kappa value of 0.9. Wavebands at 780, 790, 800, 1480, 1530, and 1550 nm were identified as the most useful bands for mangrove species classification. At least one of the four reflectance ratio indices proved useful in detecting stress associated with any of the three mangrove species. Overall, hyperspectral data appear to have great potential for discriminating mangrove canopies of differing species composition and for detecting stress in mangrove vegetation.     

On the correlation of indices of vegetation and surface temperature over south-eastern Australia

Abstract

Relationships between radiant surface temperature (T _R) and vegetation indices for scenes with equal areas of forest and agricultural land use were studied using a Landsat Thematic Mapper (TM) scene during spring and a NOAA-Advanced Very High Resolution Radiometer (AVHRR) scene during summer. The relationships between TR and the Normalized Difference (ND) index of vegetation for agricultural land use were different from those for forests. At the same T _R, the forests had lower near infrared reflectance. This caused the ND of forests to fall below the T _R/ND relationships formed by agricultural land use. This difference between forest and agricultural land use did not exist when visible reflectance (VIS) was used as the index of vegetation. When the two land use systems were combined VIS accounted for about 86 per cent of the variance in T _R. The slope of the relationships between VIS and T _R differed for TM and AVHRR scenes. This was explained by differences in the T _R and VIS reflectance of surfaces with near-zero evaporation. These surfaces were predominantly bare soil in the TM scene and senesced vegetation in the AVHRR scene.     

Regional algorithms for remote-sensing estimates of total suspended matter in the Beaufort Sea

The large and variable riverine inflow to Arctic continental shelves strongly influences their chemical, biological, and optical properties. The Beaufort Sea receives the largest amount of suspended sediments amongst all Arctic shelves, with sediment-laden Mackenzie river waters strongly influencing bio-optical properties on the shelf. Here, we developed two regional algorithms for the estimation of total suspended matter (TSM) concentration using Medium Resolution Imaging Spectrometer (MERIS) spectral bands, based on in situ optical and suspended particulate data collected in the summer during the Canadian Arctic Shelf Exchange Study (CASES) in 2004 and during the Arctic Coastal Ecosystem Study (ACES) in 2010. The band ratio (where R _rs is remote-sensing reflectance) R _rs,560/R _rs,490 was best correlated with low TSM concentrations (less than 3.0 g m^?3), while higher TSM concentrations were well correlated to R _rs,681/R _rs,560. An empirical piecewise algorithm is thus proposed with the switch between the ratios being triggered by R _rs,681/R _rs,560 at a threshold value of 0.6. The second algorithm made use of support vector machines (SVMs) as a nonlinear transfer function between TSM concentrations and remote-sensing reflectance ratios R _rs,681/R _rs,560, R _rs,665/R _rs,560, and R _rs,560/R _rs,490. Results show that both algorithms perform better (31% and 25%, respectively) than other published TSM algorithms including the MERIS Case 2 water processor (C2R) neural network algorithm in the study area.     

Remote sensing used to detect moisture status of pecan orchards grown in a desert environment

Remote-sensing techniques can detect and up-scale leaf-level physiological responses to large areas, and provide significant and reliable information on water use and irrigation management. The objectives of this study were to screen leaf-level physiological changes that occur during the cyclic irrigation of pecan orchards to determine which responses best represent changes in moisture status of plants and link plant physiological changes to remotely sensed surface reflectance data derived from the Landsat Thematic Mapper and Enhanced Thematic Mapper Plus (ETM+). The study was conducted simultaneously on two southern New Mexico mature pecan orchards. For both orchards, plant physiological responses and remotely sensed surface reflectance data were collected from trees that were either well watered or in water deficit. Remotely sensed variables included reflectance in band 1, the ratio between shortwave infrared (SWIR) bands (B5:B7), the normalized difference vegetation index, and SWIR moisture indices. Midday stem water potential (Ψ_smd) was the best performing leaf-level physiological response variable for detecting moisture status in pecans. The B5:B7 ratio positively and significantly correlated with Ψ_smd in five of six irrigation cycles while multiple linear regression weighted with six remotely sensed surface reflectance variables revealed a significant relationship with moisture status in all cycles in both orchards (R² > 0.73). Because changes in the B5:B7 band ratio and multiple regression of spectral variables correlate with the moisture status of pecan orchards, we conclude that remotely sensed data hold promise for detecting the moisture status of pecans.     

Spatio-temporal remote sensing of vertical and seasonal chlorophyll-a:b ratio in Tamarix ramosissima

Remotely sensed spectral reflectance data have provided avenues for large-scale non-destructive estimation of temporal and spatial variations of physiological processes in plants. This study established the potential for tracking (chlorophyll) chl-a:b ratio in Tamarix ramosissima based on -leaf-scale photochemical reflectance index (PRI) at Fukang Station of Desert Ecology in the hinterland of the Junggar Basin, Xinjiang, northwest China. Leaves were sampled on a monthly basis over a 3-year growing period. T. ramosissima tolerance to the fragile arid conditions revealed higher coefficient of determination (R² > 0.6) between chl-a:b ratio and N content at each light condition. This implied a higher potential for irradiance acclimation through plasticity in photosynthetic apparatus, and hence an important attribute for colonizing wider desert ecological range. PRI was negatively correlated to chl-a:b ratio regardless of season but was more sensitive to changes in light condition. The modified PRI (PRI_mod, R₅₁₀–R₅₇₀ nm) performed better than the original PRI (PRI, R₅₃₁–R₅₇₀ nm) with R² improvement in all data sets of this species. These results implied that seasonality and leaf age, within canopy resource variation and the individual species must be considered when applying PRI_mod to estimate chl-a:b ratio. Application of empirical indices avails a non-destructive timely leaf-level, species and site-specific avenue of detecting vegetation status in arid ecosystems. Remote estimation of chl-a:b ratio obtained at leaf scale in this study could be scaled to ecosystem and global scale by effective estimation of spatial distribution and seasonal variation using other pigment-related vegetation index such as the normalized difference vegetation index, or combination of PRI and the water band index.