Bio‐optical model with optimal parameter suitable for Taihu Lake in water colour remote sensing

Sixty‐seven samplings were collected, almost covering all over the Taihu Lake, in one campaign in October 2004. At each station, the backscattering coefficients and the field spectra were measured in situ, respectively, with a HS‐6 and a FieldSpec 931 spectroradiometer (ASD Inc.). Almost concurrently, water samples were fetched with Niskin water‐fetching equipment and then returned to the laboratory for concentration and absorption measurement. The whole lake was divided into different areas according to some indexes. Three models were used to calculate remote sensing reflectance R _rsc for the waters where the in situ remote sensing reflectance R _rsm was beyond the bottom effect, which was considered as optically deep waters. By comparison of R _rsc and R _rsm, the best model suitable for optically deep waters in Taihu Lake, together with its optimal experiential parameter, were selected and developed, which was very important and helpful to develop a universal model to estimate accurately remote sensing reflectance for the whole lake in the next step.     

Spectral optical and bio‐optical relationships in the Oslo Fjord compared with similar results from the Baltic Sea

The spectral shape of the attenuation coefficient c in Baltic waters along the Swedish coast is almost identical to the one in the Oslo Fjord, and there are also strong similarities between these two areas for the absorption coefficient a and the scattering coefficient b as functions of c. However, while the single‐scattering albedo b/c in the Oslo Fjord on an average is 62% and 78% at 425 and 525?nm, respectively, the corresponding numbers for the Gulf of Gdansk are 54% and 61%. Another characteristic difference is that particle absorption plays a much more significant role in the Gulf of Gdansk than in the Oslo Fjord. Thus some parts of the Baltic exhibit similarities with the Oslo Fjord while others display differences, and it cannot be assumed a priori that algorithms from one area will have a general validity in the other.

Algorithms for chlorophyll‐a and yellow substance as functions of colour indices, determined for the southern part of the Baltic Sea between the Pommerian Bight and the Gulf of Gdansk, are clearly not valid for the Oslo Fjord, but the result improves by changing their constants by a best‐fit procedure. We conclude that statistical algorithms for remote sensing are not generally interchangeable between the Baltic and the Oslo Fjord, and that the constants of the algorithms have to be locally tuned.     

Small‐footprint,waveform‐resolving lidar estimation of submerged and sub‐canopy topography in coastal environments

The experimental advanced airborne research lidar (EAARL) is an airborne lidar instrument designed to map near‐shore submerged topography and adjacent land elevations simultaneously. This study evaluated data acquired by the EAARL system in February 2003 and March 2004 along the margins of Tampa Bay, Florida, USA, to map bare‐earth elevations under a variety of vegetation types and submerged topography in shallow, turbid water conditions. A spatial filtering algorithm, known as the iterative random consensus filter (IRCF), was used to extract ground elevations from a point cloud of processed last‐surface EAARL returns. Filtered data were compared with acoustic and field measurements acquired in shallow submerged (0–2.5 m water depth) and sub‐canopy environments. Root mean square elevation errors (RMSEs) ranged from 10–14 cm for submerged topography to 16–20 cm for sub‐canopy topography under a variety of vegetation communities. The effect of lidar sampling angles and global positioning system (GPS) satellite configuration on accuracy was investigated. Results show high RMSEs for data acquired during periods of poor satellite configuration and at large sampling angles along the edges of the lidar scan. The results presented in this study confirm the cross‐environment capability of a green‐wavelength, waveform‐resolving lidar system, making it an ideal tool for mapping coastal environments.     

Ion–π interaction in impacting the nonlinear optical properties of ion–buckybowl complexes

Ion–buckybowl complexes have received considerable attention in modern chemical research due to its fundamental and practical importance. Herein, we performed density functional theory (DFT) to calculate the geometical structure, binding interactions, dipole moments and the first hyperpolarizabilities (β_tot) of ion–buckybowl complexes (ions are Cl⁻ and Na⁺, buckybowls are quadrannulene, corannulene and sumanene). It is found that the stabilities of ion–buckybowl compounds primarily originate from the interaction energy, which was proved by a new isomerization energy decomposition analysis approach. Plots of reduced density gradient mirror the ion–π weak interaction has been formed between the ions and buckybowls. Significantly, the buckybowl subunits cannot effectively impact the nonlinear optical (NLO), but the kind of ion has marked influence on the second-order NLO responses. The β_tot values of Cl⁻–buckybowl complexes are all larger as compared to that of Na⁺–buckybowl complexes, which is attributed to the large charge-transfer (CT) from Cl⁻ to buckybowl. Our present work will be beneficial for further theoretical and experimental studies on the NLO properties of ion–buckybowl compounds.     

Analysis of co‐occurrence and discrete wavelet transform textures for differentiation of forest and non‐forest vegetation in very‐high‐resolution optical‐sensor imagery

The extraction of texture features from high‐resolution remote sensing imagery provides a complementary source of data for those applications in which the spectral information is not sufficient for identification or classification of spectrally similar landscape features. This study presents the results of grey‐level co‐occurrence matrix (GLCM) and wavelet transform (WT) texture analysis for forest and non‐forest vegetation types differentiation in QuickBird imagery. Using semivariogram fitting, the optimal GLCM windows for the land cover classes within the scene were determined. These optimal window sizes were then applied to eight GLCM texture measures (mean, variance, homogeneity, dissimilarity, contrast, entropy, angular second moment, and correlation) for the scene classification. Using wavelet transformation, up to five levels of macro‐texture were computed and tested in the classification process. Comparing the classification results, (1) the spectral‐only bands classification gave an overall accuracy of 58.69%; (2) the statistically derived 21×21 optimal mean texture combined with spectral information gave the best results among the GLCM optimal windows with an accuracy of 73.70%; and (3) the combined optimal WT‐texture levels 4 and 5 gave an accuracy of 63.56%. The combined classification of these three optimal results gave an overall accuracy of 77.93%. The results indicate that even though vegetation texture was generally measured better by the GLCM‐mean texture (micro‐textures) than by WT‐derived texture (macro‐textures), the results show that the micro–macro texture combination would improve the differentiation and classification of the overall vegetation types. Overall, the results suggests that computer‐assisted classification of high‐spatial‐resolution remotely sensed imagery has a good potential to augment the present ground‐based forest inventory methods.     

The potential and challenge of remote sensing‐based biomass estimation

Remotely sensed data have become the primary source for biomass estimation. A summary of previous research on remote sensing‐based biomass estimation approaches and a discussion of existing issues influencing biomass estimation are valuable for further improving biomass estimation performance. The literature review has demonstrated that biomass estimation remains a challenging task, especially in those study areas with complex forest stand structures and environmental conditions. Either optical sensor data or radar data are more suitable for forest sites with relatively simple forest stand structure than the sites with complex biophysical environments. A combination of spectral responses and image textures improves biomass estimation performance. More research is needed to focus on the integration of optical and radar data, the use of multi‐source data, and the selection of suitable variables and algorithms for biomass estimation at different scales. Understanding and identifying major uncertainties caused by different stages of the biomass estimation procedure and devoting efforts to reduce these uncertainties are critical.     

On the link between SAR‐derived sea ice melt and development of the summer upper ocean mixed layer in the North Open Water Polynya

We examine the ability of SAR‐derived landfast sea ice thermodynamic state surrounding the North Water Polynya to predict the timing of a shallow, stably stratified summer ocean mixed layer in the region. Radarsat‐1 ScanSAR is used to derive melt and pond onset dates over landfast sea ice surrounding the polynya, describing its thermodynamic evolution. Salinity and temperature profiles, connected in time and space, are complemented by potential density profiles and mixed layer depths, which describe the evolution of the upper ocean mixed layer between 4 April and 21 July 1998. Surface salinity driven potential density stratification and summer mixed layer depths are temporally coincident. Sea ice–ocean connection is first described at the local scale, then regionally. At the local scale, a reduction in surface salinity occurs between the melt and pond onsets over landfast sea ice. At the polynya scale, interpolated pond onset date is highly effective at predicting the timing of a thin, stably stratified summer ocean mixed layer; this has consequences for the potential prediction of timing of maximum ecosystem productivity.     

Applications of Landsat‐5 TM imagery in assessing and mapping water quality in Reelfoot Lake,Tennessee

Water quality in Reelfoot Lake, Tennessee, was investigated in the field over 15 years ago. However, the spatial variations of water quality were not studied. The remote sensing technique has been proved a powerful tool in mapping spatial distributions of some water quality parameters such as chlorophyll‐a concentration. Additionally, different regression methods and various independent variables have been used to establish relationships between water quality parameters and spectral reflectance. The results from this study indicate that Landsat TM2 and TM3, as a set of independent variables in multivariate regression analysis, are good predictors of water quality in Reelfoot Lake. TM2 is positively correlated to water quality, and TM3 is negatively correlated to water quality. Poor water quality, or a high algae load, results in a high reflectance measured by TM2 and a low reflectance measured by TM3. Maps of spatial distribution of Secchi disk depth, turbidity, chlorophyll‐a, and total suspended solids present apparent spatial variations of water quality in the lake.     

Corn‐yield estimation through assimilation of remotely sensed data into the CSM‐CERES‐Maize model

One of the applications of crop simulation models is to estimate crop yield during the current growing season. Several studies have tried to integrate crop simulation models with remotely sensed data through data‐assimilation methods. This approach has the advantage of allowing reinitialization of model parameters with remotely sensed observations to improve model performance. In this study, the Cropping System Model‐CERES‐Maize was integrated with the Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) products for estimating corn yield in the state of Indiana, USA. This procedure, inversion of crop simulation model, facilitates several different user input modes and outputs a series of agronomic and biophysical parameters, including crop yield. The estimated corn yield in 2000 compared reasonably well with the US Department of Agriculture National Agricultural Statistics Service statistics for most counties. Using the seasonal LAI in the optimization procedure produced the best results compared with only the green‐up LAIs or the highest LAI values. Planting, emergence and maturation dates, and N fertilizer application rates were also estimated at a regional level. Further studies will include investigating model uncertainties and using other MODIS products, such as the enhanced vegetation index.     

Comparison of SeaWiFS,MODIS‐Terra and MODIS‐Aqua in the Southern Ocean

The surface chlorophyll‐a concentrations measured by SeaWiFS, MODIS‐Terra and MODIS‐Aqua are compared in the Southern Ocean in summer 2003. The radiometers generally agree within their estimated accuracy. Residual discrepancies could be reduced by regional calibrations of the bio‐optical algorithms.     

Landsat-satellite-based analysis of spatial–temporal dynamics and drivers of CyanoHABs in the plateau Lake Dianchi

ABSTRACT

Dianchi Lake, located in southwest China’s Yungui plateau, is facing severe eutrophication and frequent outbreaks of harmful cyanobacteria blooms (CyanoHABs). It is of great significance to monitor the occurrence and development of CyanoHABs in Dianchi Lake over a long period and analyse the main influences. Based on Landsat Thematic Mapper/Enhanced Thematic Mapper Plus/Operational Land Imager 1986–2016 data, we derived the distribution of the CyanoHABs in Dianchi Lake, and analysed spatial–temporal dynamics of the CyanoHABs by correlation with nutrition, meteorological, and humanities data. The results showed that the first outbreak of CyanoHABs in Dianchi Lake occurred in 1987, which is likely to be influenced by a rapid increase of nutrients in the lake, while the weather conditions also have some impact on the CyanoHABs occurrence. After 1990, the frequency of CyanoHABs is relatively high in the water near Longmen village, Fubao Bay, Hui Bay, and the lake inlet of the Panlong River to the north of Waihai in Dianchi Lake from June to November every year. Moreover, the CyanoHABs increased year by year until 2000. This is closely related to population growth and economic development. Furthermore, a large amount of precipitation and small wind speeds can also promote the occurrence of CyanoHABs. After 2000, the frequency of CyanoHABs decreased, as the large-scale management of water pollution in Dianchi Lake achieved certain effects. The area and frequency of CyanoHABs from 2011 to 2014 are the smallest in the last 20 years, which may be related to the large-scale planting of Eichhornia crassipes in the north of Dianchi Lake.     

Evaluation of SeaWiFS chlorophyll‐a in the Black and Mediterranean Seas

The performance of NASA's OC2 and OC4 algorithms to estimate chlorophyll‐a concentrations from SeaWiFS radiometric measurements on the global scale was tested in two contrasted bio‐optical environments, the Black Sea and the Mediterranean Sea. The in situ bio‐optical measurements were made during October 1999 at 25 stations. Comparisons of the in situ measurements with the concurrent SeaWiFS retrievals indicate that the OC2 and OC4 algorithms are not working satisfactorily in both seas. Case 2 waters dominate the Black Sea and the failure of the algorithms is expected. On the other hand, failure of the algorithms in the case 1 waters of the Mediterranean Sea may be due to their specific optical properties. Modifying the OC4 algorithm to include SeaWiFS information at 412?nm yields a better performance in the Mediterranean Sea without degrading performance in the Black Sea. Combining a local algorithm adapted to oligotrophic waters of the Mediterranean Sea and OC4 provides the best results overall.     

Optical–microphysical properties of smoke haze from Siberian forest fires in summer 2012

A comprehensive experiment on the study of dynamics of optical and microphysical characteristics of submicron aerosols in the near-ground air layer was carried out in June–August of 2012 under conditions of extremely strong smoke haze originating from vast forest fires in Siberia. Variations of the spectral angular scattering coefficients and the degree of linear polarization in the visible wavelength range are studied, as well as the mass concentrations of dry fractions of aerosol and black carbon, relative content of black carbon (BC fraction), single scattering albedo, particle size distribution function, complex refractive index of the particulate matter, and parameter of condensation activity of aerosol. Peculiarities of differences between optical and microphysical characteristics of near-ground aerosol in smoke haze and under smokeless conditions are revealed. This study is important for validation of results of remote sensing of the composition of smoke haze and background atmosphere obtained from satellite data and sun photometric measurements at the Aerosol Robotic Network (AERONET).     

Pre‐monsoon Indian Ocean SST in contrasting years of Indian summer monsoon rainfall

The anomalous change in SST of June with reference to May studied for the Indian Ocean region (0–120°E, 40°S–40°N) during 1998 to 2005. The change in monthly SST anomaly in the equatorial region were studied along with changes in water vapor and wind field in 1998 and 2002, the years that representing contrasting changes in the summer monsoon rainfall. The westward extending equatorial warm pool in the Indian Ocean was found relative weak and found relatively weak during 1998 in contrast to those in 2002. Similar analysis further extended till 2005 indicated further the influence of the equatorial warm pool on the summer monsoon rainfall over the Indian subcontinent.     

Use of a ground‐based scanning lidar for estimation of biophysical properties of western larch (Larix occidentalis)

Ground‐based laser scanners represent a relatively new technology that promises to enhance the ability to remotely sense biophysical properties of vegetation. In this study, we utilized a commercially available discrete‐return ground‐based laser scanning system to sample properties of western larch (Larix occidentalis) in a northern Idaho forest. Three young trees <5 m in height were scanned before and after leaf abscission in the autumn of 2004. Leaf areas represented by the number of laser returns were estimated by subtracting leaf‐off laser returns from leaf‐on returns. Leaf areas represented by number of laser returns were significantly correlated with manual‐based estimates of leaf area (r ² = 0.822). Ratios of woody‐to‐total tree area were estimated based on number of laser returns from woody material. Ratios of woody‐to‐total area ranged from 0.24 to 0.58 for nine one‐metre sections of tree for which estimates were made. Ratios of woody‐to‐total area were also estimated using intensity of laser returns and fell near the range of estimates made using the number of laser returns. Improved estimation of leaf area, woody‐to‐total area ratios, and other biophysical parameters using ground‐based laser scanning technology may be possible with a careful consideration of instrument specifications and sampling design.     

On the estimation of stochastic sensitivity for non-linear dynamical systems in state estimation problems†

This paper consists of two main parts. Recognizing the existence of identification errors due to variations of system parameters, the first part is devoted to the verification of the existence of a unique continuous solution of a non-linear vector stochastic differential equation with a random parameter and to the establishment of the stochastic sensitivity equation. Both the a and β-stochastic sensitivity equations are established through the precise definition of stochastic sensitivity.

The remainder of this paper deals with evaluation of quantitative aspects of the sensitivity in the state estimation by using the stochastic sensitivity equation.     

Nonlinear optical properties of rhenium(I) complexes: Influence of the extended π-conjugated connectors and proton abstraction

The photoinduced proton-coupled electron transfer chemistry is very crucial to the development of nonlinear optical (NLO) materials with large first hyperpolarizability contrast. We have performed a systematic investigation on the geometric structures, NLO switching, and simulated absorption spectra of rhenium(I) complexes via density functional theory (DFT). The results show that the first hyperpolarizabilities (β_vec) increase remarkably with further extending of the organic connectors. In addition, the solvent leads to a slight enhancement of the hyperpolarizability and frequency dependent hyperpolarizability. Furthermore, the proton abstraction plays an important role in tuning the second-order NLO response. It is found that deprotonation not only increases the absolute value of β_vec but also changes the sign of β_vec from positive to negative. This different sign can be explained by the opposite dipole moments. The efficient enhancement of first hyperpolarizability is attributed to the better delocalization of the π-electron system and the more obvious degree of charge transfer. Therefore, these kinds of complexes might be promising candidates for designed as proton driven molecular second-order NLO switching.     

Traceability of slash‐and‐burn land‐use history using optical satellite sensor imagery: a basis for chronosequential assessment of ecosystem carbon stock in Laos

This study examined the use of satellite sensor imagery for chronosequential assessment of land use and ecosystem carbon stock in slash‐and‐burn (S/B) regions of Laos. The segmentation approach was useful because the boundaries of S/B patches are subject to change due to natural or anthropogenic factors. Polygon‐based classification using six optical bands of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery showed that S/B patches could be discriminated with high accuracy (0.98). Normalized difference spectral indices, NDSI[i, j] = [R_j ?R_i ]/[R_j +R_i ], using reflectances R_j and R_i at j and i nm wavelengths for S/B polygons during four consecutive years (1999–2002) showed that NDSI[2215, 830], NDSI[1650, 830] and NDSI[660, 830] ( = the normalized difference vegetation index, NDVI) values decreased significantly in S/B years compared to those under fallow conditions (by 0.21±0.04, 0.20±0.04 and 0.17±0.03, respectively). Only slight differences were found before and after the S/B year, regardless of fallow length or biomass estimated by the allometry method. Relating reflectance signatures directly to fallow biomass was unsuitable, but these NDSIs were also useful for distinguishing S/B patches. Land‐use history, including the community age of fallow vegetation, can be traced on a pixel basis using a superimposed set of segmented classified images.     

Estimation of chlorophyll‐a concentration in Lake Tai,China using in situ hyperspectral data

Reflectance spectra of water in Lake Tai of East China were measured at 28 monitoring stations with an ASD FieldSpec spectroradiometer at an interval of 1.58 nm over five days in each month from June to August of 2004. Water samples collected at these stations were analyzed in the laboratory to determine chlorophyll‐a (chl‐a) concentration. Twenty‐eight spectral reflectance curves were standardized and correlated with chl‐a concentration. Examination of these curves reveals a peak reflectance at 719 nm. Chl‐a concentration level in the Lake was most closely correlated with the reflectance near 700 nm. If regressed against the reflectance at the wavelength of 667 nm (R ₆₆₇), chl‐a concentration was not accurately estimated at R ² = 0.494. Accuracy of estimation was improved to R ² = 0.817 using the maximum reflectance. A higher accuracy of 0.837 was achieved using the peak reflectance at 719 nm (R ₇₁₉) because it does not drift with the level of chl‐a concentration. The highest accuracy of estimation was achieved at R ² = 0.868 using R ₇₁₉/R ₆₆₇.     

Mapping the concentrations of total suspended matter in Lake Taihu,China, using Landsat‐5 TM data

Remote sensing techniques can be used to estimate and map the concentrations of suspended matter in inland water, providing both spatial and temporal information. Although an empirical approach to remote sensing of inland waters has been carried out frequently, satellite imagery has not been incorporated into routine lake monitoring programmes due in part to the lack of a standard prediction equation with multi‐temporal capacity for suspended matter. Empirical and physical models must be developed for each lake and its corresponding turbidity composition if they are to be compared over time, or with other bodies of water.

This study aimed to develop and apply multi‐temporal models to estimate and map the concentrations of total suspended matter (TSM) in Lake Taihu, China. Two Landsat‐5 Thematic Mapper (TM) images and nearly contemporaneous in situ measurements of TSM were used. A modified Dark‐Object Subtraction (DOS) method was used, and appeared to be adequate for atmospheric correction. The relationships were examined between TSM concentrations and atmospherically corrected TM band and band ratios. Results of this study show that the ratio TM4/TM1 has a strong relationship with TSM concentrations for lake waters with relatively low concentrations of phytoplankton algae. However, TM3 provided a strong predictive relationship with TSM concentrations despite varied water quality conditions. Different prediction models were developed and compared using multiple regression analysis. The Akaike Information Criteria (AIC) approach was used to choose the best models. The validation of the multi‐temporal capability of the best models indicated that it is feasible to apply the linear regression model using TM3 to estimate TSM concentrations across time in Lake Taihu, even if no in situ data were available.