Reconstructing cloudfree NDVI composites using Fourier analysis of time series

This letter describes the Harmonic ANalysis of Time Series (HANTS) algorithm. It performs two tasks: (i) screening and removal of cloud affected observations; and (ii) temporal interpolation of the remaining observations to reconstruct gapless images at a prescribed time. HANTS was applied to 36 AVHRR 10-days-maximum-NDVI composites covering most of Europe. The results show that cloud affected data are recognized successfully and replaced. Up to half the data points were rejected with no consequence for the successful reconstruction of seasonal NDVI profiles.     

Appraisal and optimization of agricultural water use in large irrigation schemes: II. Applications

In this paper, the theoretical approach presented in Part I is demonstrated by means of case studies on the irrigation schemes of Rio Mendoza and Rio Tunuyán in the Province of Mendoza, Argentina. The object of the case studies was the determination of optimal allocation of surface water to reduce the use of groundwater. Current and optimal conjunctive allocation of ground and surface water is studied by means of the developed simulation and optimization models.The second case study was designed on the basis of the experience gathered during the first one: each step of the case studies is compared. The comparison between the two case studies illustrates how to apply the proposed approach when the amount and quality of available data are different. For the more detailed Rio Tunuyán study, we determined the following physical characteristics of all terminal nodes: on-farm rotational intervals, mean water application depth, actual soil water storage capacity, crop water requirements, depth of groundwater table, aquifer transmissivity, and efficiency of groundwater use.The performance of the entire system is sensitive to changes in the water application depth, as it was shown by a simulation study.The application of our optimization approach to the conjunctive use of ground- and surface water showed that the total water requirements over a year can be met by a reassignment of water that reduces the total costs of a great amount.     

SkelTre

Terrestrial laser scanners capture 3D geometry of real world objects as a point cloud. This paper reports on a new algorithm developed for the skeletonization of a laser scanner point cloud. The skeletonization algorithm proposed in this paper consists of three steps: (i) extraction of a graph from an octree organization, (ii) reduction of the graph to a skeleton, and (iii) embedding of the skeleton into the point cloud. For these three steps, only one input parameter is required. The results are validated on laser scanner point clouds representing 2 classes of objects; first on botanic trees as a special application and secondly on popular arbitrary objects. The presented skeleton found its first application in obtaining botanic tree parameters like length and diameter of branches and is presented here in a new, generalized version. Its definition as Reeb Graph, proofs the usefulness of the skeleton for applications like shape analysis. In this paper we show that the resulting skeleton contains the Reeb Graph and investigate the practically relevant parameters: centeredness and topological correctness. The robustness of this skeletonization method against undersampling, varying point density and systematic errors of the point cloud is demonstrated on real data examples.     

Mapping mixed vegetation communities in salt marshes using airborne spectral data

The aim of this study is to evaluate a new neural network classifier using spectrally sampled image data to map mixed halophytic vegetation in tidal environments. The work is based on the concept of vegetation communities, mixtures of several species, characteristic of salt marshes. The study site is the Venice lagoon, and the material available is a spectrally sampled Compact Airborne Spectral Imager (CASI) image, in conjunction with ground truth for precise characterization of vegetation communities. Detailed observations of vegetation species and of their fractional abundance were collected for 36 Regions Of Interest (ROI): such field polygons are used for classification training and accuracy assessment. To select the most significant spectral channels, the Spectral Reconstruction method was applied to the image data: a set of 6 bands was selected as optimal for classification, out of the 15 available. The spatial heterogeneity of salt-marsh vegetation is significant and even at the spatial resolution of the airborne CASI image data, mixed pixels are observed. The Vegetation Community based Neural Network Classifier (VCNNC) is introduced to cope with a situation where no pure pixels exist, and was applied to the set of 6 selected bands. Both quantitative and qualitative comparisons of classification results of VCNNC with those of conventional Neural Network Classifier (NNC), trained and assessed on exactly the same data sets, shows that VCNNC's accuracy is substantially higher (≈ 91%) than that of NNC (≈ 84%), while the Kappa coefficient is 0.87 for VCNNC and 0.75 for the NNC method.     

A user-oriented and quantifiable approach to irrigation design

A new user-oriented approach is presented to apply marketing research techniques to quantify perceptions, preferences and utility values of farmers. This approach was applied to design an improved water distribution method for an irrigation scheme in Mendoza, Argentina. The approach comprises two subprocesses. The first one consists of a diagnostic analysis and the identification of an alternative water distribution system as a concept solution to the regional irrigation problems. In contrast to the rigid current system, the alternative system allows farmers, within some limitations, to design their own monthly allocation of water. The second, user-oriented subprocess consists of three stages: a perception, a preference and a utility analysis. Perception and preference analyses show that the farmers perceive the alternative (not yet in existence) system as the preferable one, with respect to control and sufficiency. Analysis also reveals that the flow rate and irrigation interval that farmers currently receive influence their perceptions. A utility analysis determines the utility values of farmers for different levels of flow rate, irrigation interval and the possibility of designing their own monthly allocation of water. The Mendoza case indicates that by using this approach the farmers' perceptions, preferences and utility values of technical features of the irrigation system are quantified. Thus, management and designers alike can be provided with recommendations on vital design elements.     

Appraisal and optimization of agricultural water use in large irrigation schemes: I. Theory

A new approach on the functioning of an irrigation scheme has been presented. A mathematical representation of the irrigation system based on measured system properties, such as losses due to percolation and to poor management, in only a part of the system is used. This mathematical representation is termed an equivalent irrigation network. The merit of this approach is that it reduces the number of required streamflow measurements.When water amounts are measured for a number of paths in the irrigation network, so-called path efficiencies are obtained. The path efficiency is a measure of the amount of water lost along the way. The numerical model that simulates the operation of the irrigation system is based on the path efficiencies. This simulation model in turn is used to calculate different objective functions, corresponding with different optimization goals, like uniform water distribution, minimum groundwater extraction, minimum cost of water supply.This paper gives the theoretical background of the approach. The application to an actual irrigation scheme will be discussed in a second paper.     

A MODIS-based perpendicular moisture index to retrieve leaf moisture content of forest canopies

Moisture dictates vegetation susceptibility to fire ignition and propagation. Various spectral indices have been proposed for the estimation of equivalent water thickness (EWT), which is defined as the mass of liquid water per unit of leaf surface. However, fire models use live fuel moisture content (LFMC) as a measure of vegetation moisture. LFMC is defined as the ratio of the mass of the liquid water in a leaf over the mass of dry matter, and traditional spectral indices are not as effective as with EWT in capturing LFMC variability. The aim of this research was to explore the potential of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra and Aqua satellites in retrieving LFMC from top of the canopy reflectance, and to develop a new spectral index sensitive to this parameter. All the analyses were based on synthetic canopy spectra constructed by coupling the PROSPECT (leaf optical properties model) and SAIL (Scattering by Arbitrarily Inclined Leaves) radiative transfer models. Simulated top of the canopy spectra were then convolved to MODIS ‘land’ channels 1–7 spectral response functions. All band pairs were evaluated to determine the subspace of MODIS measurements where the separability of points based on their value of LFMC was the highest. This led to the identification of isolines of LFMC in the plane defined by MODIS reflectance measurements in channels 2 and 5; the isolines are straight and parallel, and ordered from lower to higher values of LFMC. This observation allowed the construction of a novel spectral index that is directly related to LFMC – the perpendicular moisture index (PMI). This index measures the distance of a point in the plane spanned by reflectance measurements in MODIS channels 2 and 5 from a reference line, that of completely dry vegetation. Validation against simulated data showed that PMI exhibits a linear relationship with LFMC. When the vegetation cover is dense, the LFMC explains most of the variability in the PMI (R² = 0.70 when LAI > 2; R² = 0.87 when LAI > 4). When the LAI is lower, the contribution of soil background to the measured reflectance increases, and the index underestimates LFMC. The PMI was also validated against the LOPEX93 (Leaf Optical Properties Experiment 1993) data set of leaf optical and biophysical measurements, scaled to canopy reflectance with SAIL, showing acceptable results (R² = 0.56 when LAI > 2; R² = 0.63 when LAI > 4).     

Indicators of the Seasonal Cycle of Total Dissolved and Adsorbed Salts under Irrigation

This article describes the evaluation of indicators computed with a numerical simulation model of soil water and solute flow against field measurements of the amount of adsorbed and dissolved salts. In the Mediterranean environment,characterised by hot, dry summers, a field experiment on irrigation of vegetable crops with saline and tubewell water was carried out between 1988 and 1996 at a site near Naples, Italy. The investigation was carried out on a clay-loam soil classified as Argiustolls. Irrigation treatments were: tubewell water (no addition of NaCl), addition of 1.25, 2.5, 5 and 10 g_NaCl L^-1. Three irrigation intervals were applied until 1995: 2, 5 and 10 days. In 1995 all plots were irrigated on pre-selected days of the year, but the amount of water was equal to 100%, respectively 75 and 50% for the three irrigation treatments. Except 1996, all plots received consistently the same irrigation and salinity treatment, although different crops were grown on the same plot during the 8 yr experiment. In 1996, the indicator of soil salinity was used to evaluate the salt accumulation in the soil after a long time of saline irrigation. The indicator applied was the total amount of dissolved and adsorbed salts measured and simulated, in this way observation and model calculations are truly comparable. The aims were to evaluate the accuracy and relevance of salinity indicator computed by means of a numerical deterministic model describing water and solute transport SWAP. Total amount of salts were determined on soil samples, collected through the irrigation season on the treatments 0 and 5 g_NaCl L^-1. The samples were taken at three depths. The CEC and soluble salt were measured, beside the initial (prior to saturation in the laboratory) composition of the soil samples. Total dissolved and adsorbed salts were calculated throughout the irrigation season with the model SWAP. Calculated salt concentration was compared with observed soil composition to assess the accuracy of model calculations.     

Influence of range measurement noise on roughness characterization of rock surfaces using terrestrial laser scanning

The application of laser scanning in studying rock surfaces is limited by the range measurement noise inherent in the laser scanner data. In this paper we investigate the influence of range measurement noise on the quantification of rock surface roughness. Roughness measures derived from the laser scanner data are compared with those derived from manual measurements. The comparison shows that the presense of noise in range measurements leads to an overestimation of the fractal dimension and amplitude of roughness profiles. Experiments with wavelet decomposition and thresholding methods for reducing noise in the laser range data are presented. The results indicate that wavelet de-noising methods in general lead to more realistic estimates of the roughness of the laser profiles.     

Impact of rainfall anomalies on Fourier parameters of NDVI time series of northwestern Argentina

This paper describes a method to detect the impact of rainfall anomalies on vegetation phenology, in terms of timing (phase) and greenness, by using Fourier series to fit a time series of Normalized Difference Vegetation Index (NDVI) observations. The study was conducted in the northern semiarid region of Argentina, where rainfall is the driving factor of vegetation phenology. A 9‐year time series of monthly NDVI Global Area Coverage (GAC) images, obtained with the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR), was split into nine series of 12‐monthly images, each corresponding to a yearly growth cycle. A Fast Fourier Transform (FFT) algorithm was applied to each cycle, and derived parameters were analysed according to rainfall anomalies for irrigated and rainfed crops, grasslands and native forest. Derived Fourier parameters were: mean NDVI, amplitude and phase. Both negative and positive rainfall anomalies had a significant impact on the Fourier parameters. Amplitude and phase were the most sensitive parameters. Droughts modified the monomodal structure of the yearly cycle by decreasing the contribution of the 12‐month periodic component and increasing the contribution of the 6‐month component. The impact of drought on the Fourier parameters was highest for rainfed crops. Yearly values of Fourier parameters for grasslands and native forest were affected by prevailing hydrological conditions over the previous year.