Classification of rice cropping systems by empirical mode decomposition and linear mixture model for time-series MODIS 250 m NDVI data in the Mekong Delta,Vietnam

Estimating the area of rice planting is vital for production prediction. This study utilizes time-series MODIS NDVI data from 2002 to 2007 to discriminate rice cropping systems in the Mekong Delta (MD), Vietnam. Data are processed using Empirical Mode Decomposition (EMD) and the Linear Mixture Model (LMM). Various spatial and non-spatial data are also collected for accuracy validation. The results indicate that EMD acts as a well-fitted filter for noise reduction of the time-series NDVI data. The classification results derived from the LMM for 2002 showed an overall classification accuracy of 71.6% and a Kappa coefficient of 0.6. The provincial level area estimates were strongly correlated with the rice statistics. An examination of the change in cropping patterns between 2002 and 2007 showed that 29.0% of the triple irrigated-rice cropping systems had been changed to double irrigated-rice cropping systems and that 12.0% and 9.0% of the double irrigated and rainfed-rice cropping systems, respectively, had been changed to triple rice cropping systems. These changes were verified by visual comparisons with Landsat images.     

Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology

Remote sensing provides spatially and temporally continuous measures of forest reflectance, and vegetation indices calculated from satellite data can be useful for monitoring climate change impacts on forest tree phenology. Monitoring of evergreen coniferous forest is more difficult than monitoring of deciduous forest, as the new buds only account for a small proportion of the green biomass, and the shoot elongation process is relatively slow. In this study, we have analyzed data from 186 coniferous monitoring sites in Sweden covering boreal, southern-boreal, and boreo-nemoral conditions. Our objective was to examine the possibility to track seasonal changes in coniferous forests by time-series of MODIS eight-day vegetation indices, testing the coherence between satellite monitored vegetation indices (VI) and temperature dependent phenology. The relationships between two vegetation indices (NDVI and WDRVI) and four phenological indicators (length of snow season, modeled onset of vegetation period, tree cold hardiness level and timing of budburst) were analyzed.The annual curves produced by two curve fitting methods for smoothening of seasonal changes in NDVI and WDRVI were to a large extent characterized by the occurrence of snow, producing stable seasonal oscillations in the northern part and irregular curves with less pronounced annual amplitude in the southern part of the country. Measures based on threshold values of the VI-curves, commonly used for determining the timing of different phenological phases, were not applicable for Swedish coniferous forests. Evergreen vegetation does not have a sharp increase in greenness during spring, and the melting of snow can influence the vegetation indices at the timing of budburst in boreal forests. However, the interannual variation in VI-values for specific eight-day periods was correlated with the phenological indicators. This relation can be used for satellite monitoring of potential climate change impacts on northern coniferous spring phenology.     

Detecting temporal changes in the extent of annual flooding within the Cambodia and the Vietnamese Mekong Delta from MODIS time-series imagery

This paper presents the methodology used to detect temporal changes in the extent of annual flooding within the Cambodia and the Vietnamese Mekong Delta (VMD) based on MODIS time-series imagery (Wavelet-based Filter for detecting spatio-temporal changes in Flood Inundation; WFFI). This methodology involves the use of a wavelet-based filter to interpolate missing information and reduce the noise component in the time-series data, as proposed in a previous study. The smoothed time profiles of Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI), and the Difference Value between EVI and LSWI (DVEL) are obtained from MOD09 8-day composite time-series data (resolution: 500 m; time period: 2000-2005). The proposed algorithm was applied to produce time-series inundation maps (WFFI products) for the five annual flood seasons over the period from 2000 to 2004. The WFFI products were validated via comparisons with Landsat-derived results and inundation maps based on RADARSAT images, hydrological data, and digital elevation model data. Compared with the RADARSAT-derived inundation maps at the province level, the obtained RMSE range from 364 to 443 km² and the determination coefficients [R²] range from 0.89 to 0.92. Compared with Landsat-derived results at the 10-km grid level, the obtained RMSE range from 6.8 to 15.2 km² and the determination coefficients [R²] range from 0.77 to 0.97. The inundated area of flooded forests/marsh to the northeast of Tonle Sap Lake were underestimated, probably because of extensive vegetation cover in this area. The spatial characteristics of the estimated start dates, end dates, and duration of inundation cycles were also determined for the period from 2000 to 2004. There are clear contrasts in the distribution of the estimated end dates and duration of inundation cycles between large-scale floods (2000-2002) and medium- and small-scale floods (2003 and 2004). At the regional scale, the estimated start dates for the southern part of An Giang Province during 2003 and 2004 was distinctly later than that for surrounding areas. The results indicate that these triple-cropping areas enclosed by dikes increased in extent from 2003 to 2004. In contrast, the estimated end dates of inundation at the Co Do and Song Hau State Farms were clearly earlier than those for surrounding areas, although the estimated start dates were similar. Temporal changes in the inundation area of Flood pixels in the Dong Thap and Long An Provinces are in excellent agreement with daily water-level data recorded at Tan Chau Station. The estimated area of Long-term water body increased in size from 2000 to 2004, especially in coastal areas of the Ca Mau and Bac Lieu Provinces. Statistical data for Vietnam indicate that this trend may reflect the expansion of shrimp-farming areas. The WFFI products enable an understanding of seasonal and annual changes in the water distribution and environment of the Cambodia and the VMD from a global viewpoint.     

A methodology and an optimization tool to calibrate phenology of short-day species included in the APSIM PLANT model: Application to soybean

We developed a methodology and an optimization tool that simplifies calibration of the APSIM PLANT multi parameter input phenology module. The methodology and the tool were successfully applied to estimate phenological parameters for 40 soybean cultivars covering maturity groups from 00 to 6. Our approach utilized information on flowering, physiological maturity and soybean maturity group, and provided a complete set of phenological parameters for APSIM that accounted also for temperature × photoperiod interactions throughout the crop cycle. The model predicted flowering (root mean square error, RMSE = 3.1 d) and physiological maturity (RMSE = 5.5 d) very well in a range of environments across the USA (33–46°N latitude, n = 280). The relative absolute error was below 3% in all cases indicating the robustness of our approach. The APSIM PLANT phenology module is generic, thus our approach can be applied to all the short-day species included in the modelling platform.     

Model development in DNDC for the prediction of evapotranspiration and water use in temperate field cropping systems

This paper integrates recent research to improve, test, and verify the process based DeNtrification DeComposition (DNDC) model to estimate evapotranspiration (ET) through a revised FAO Penman–Monteith approach. ET estimates along with biomass and soil water content for spring wheat and corn were improved and found to be in good agreement with the observations at three field sites in eastern Canada (Ottawa). The statistical evaluations (RMSE (mm day⁻¹) and R²) of ET for the newly revised model (0.88 and 0.76 for corn and 0.93 and 0.78 for wheat) showed improvements over DNDC93 (1.95 and 0.22 for corn and 1.62 and 0.09 for wheat) which used the Thornthwaite equation for estimating potential evapotranspiration. In addition, evaluations of water use efficiency for corn and wheat showed good agreement between observations and the modified model. The study demonstrates the inter-dependencies of ET with biomass production and soil/atmosphere water balance.     

Expected impact of the future SMOS and Aquarius Ocean surface salinity missions in the Mercator Ocean operational systems: New perspectives to monitor ocean circulation

Sea Surface Salinity (SSS) has never been observed from space. The SSS from planned satellite missions such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius is a key to better understanding how ocean circulation is related to water cycle and how both these systems are changing through time.The Observing System Simulation Experiments (OSSEs) presented in this paper has been carried out with an ocean forecasting system developed within the French oceanographic Mercator Ocean context. They consist in hindcast experiments assimilating an operational dataset (Sea Surface Temperature (SST), in-situ profiles of temperature and salinity and Sea Level Anomalies (SLA)) and various simulated SMOS and Aquarius Sea Surface Salinity (SSS) data. These experiments use an eddy permitting model (1/3°) covering the North Atlantic from 20°S to 70°N. The new generation of fully multivariate assimilation system referred to as SAM2v1 which is being developed from the SEEK (Singular Evolutive Extended Kalman) algorithm is used. This scheme is a Reduced Order Kalman Filter using a 3D multivariate modal decomposition of the forecast error covariance.The OSSEs enabled us to show the positive impact of SSS assimilation on the Mercator Ocean operational forecasting system. These experiments particularly show the importance to specify appropriated observation errors and the impact of having and/or combining different observing system. Several conclusions can be highlighted such as the importance of the space/time scales consistency between the data products and our ocean prediction systems. This study has to be considered as an important step for assimilation of SSS measured from space. Further studies have to be conducted with other simulated data, other oceanic configurations and other improved assimilation schemes.     

Using a three-dimensional particle-tracking model to estimate the residence time and age of water in a tidal estuary

A three-dimensional hydrodynamic model that includes a Lagrangian particle-tracking simulation was applied to the Danshuei River estuarine system in northern Taiwan. The model's accuracy was validated with data from 1999; the results from the model agreed well with empirical observations of water surface elevation, tidal currents, and salinity. The validated model was then used to investigate the residence time and water age in response to different levels of freshwater discharge. A regression analysis of the model results revealed that an exponential equation best explained the correlation between residence time and freshwater input. We found that the residence times during the low and high freshwater discharge episodes were 4.4 and 2.5 days, respectively. The water age during the low-flow periods was greater than that during the high-flow periods. The modelled residence time and water age values without density-induced circulation were higher than those with density-induced circulation, which indicates that density-induced estuarine circulation may play a significant role in the estuary.     

A computational software tool for the minimization of costs and greenhouse gas emissions associated with water distribution systems

While evolutionary algorithms have been applied extensively to water resource problems, there remains a need to unify and consolidate computational and software approaches to solving these problems. In order to facilitate this for the minimization of costs and greenhouse gas emissions of water distribution systems, the water distribution cost-emissions nexus (WCEN) computational software framework is introduced in this paper. The software is freely available and can be easily modified in order to facilitate consistency of modeling, simulation and evaluation within different research studies. In addition, it enables consideration of the time-dependent variation of operational choices, such as emissions factors, electricity tariffs and water demands, which has not been done previously. The utility of the framework is demonstrated for a case study, the results of which show that consideration of such variations can significantly affect optimal design and operational decisions, as well as their costs and GHG emissions.     

Subpixel monitoring of the seasonal snow cover with MODIS at 250 m spatial resolution in the Southern Alps of New Zealand: Methodology and accuracy assessment

This study describes a comprehensive method to produce routinely regional maps of seasonal snow cover in the Southern Alps of New Zealand (upper Waitaki basin) on a subpixel basis, and with the MODerate Resolution Imaging Spectroradiometer (MODIS). The method uses an image fusion algorithm to produce snow maps at an improved 250 m spatial resolution in addition to the 500 m resolution snow maps. An iterative approach is used to correct imagery for both atmospheric and topographic effects using daily observations of atmospheric parameters. The computation of ground spectral reflectance enabled the use of image-independent end-members in a constrained linear unmixing technique to achieve a robust estimation of subpixel snow fractions. The accuracy of the snow maps and performance of the algorithm were assessed carefully using eight pairs of synchronic MODIS/ASTER images. ‘Pixel-based’ metrics showed that subpixel snow fractions were retrieved with a Mean Absolute Error of 6.8% at 250 m spatial resolution and 5.1% after aggregation at 500 m spatial resolution. In addition, a ‘feature-based’ metric showed that 90% of the snowlines were depicted generally within 300 m and 200 m of their correct position for the 500-m and 250-m spatial resolution snow maps, respectively. A dataset of 679 maps of subpixel snow fraction was produced for the period from February 2000 to May 2007. These repeated observations of the seasonal snow cover will benefit the ongoing effort to model snowmelt runoff in the region and to improve the estimation and management of water resources.     

Integration of recurrent convolutional neural network and optimal encryption scheme for intrusion detection with secure data storage in the cloud

Data communication security is growing day after day with the proliferation of cloud computing. It is primarily because of the few security constraints and challenges occurring in the cloud environment during data transmission. Existing research has shown that the intrusion detection system (IDS) centered on the cloud is more complicated. In this article, we address the above issues by proposing an attention‐based recurrent convolutional neural network (RCNN). This proposed RCNN is used to detect whether the text data are intrusion or nonintrusion. The nonintrusion text information is then used for further processing and encrypted using a two‐way encryption scheme. We introduce the elliptical curve cryptography (ECC) approach to increase the security‐level performance of nonintrusion data. Moreover, the integration of ECC with the modified flower pollination algorithm (MFP‐ECC) creates the two‐way encryption scheme, and it is used to produce an optimal private key. The encrypted data are then stored in a cloud environment by steganography and the data with the sensitive information are replaced by some other text, thus providing security to the data at rest. The proposed MFP‐ECC approach shows maximum breaking time results and can also withstand different classical attacks when compared with other methods. As a result, the proposed intrusion detection and secure data storage mechanism is highly secured and it is never affected by any kinds of conspiracy attacks.     

Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil

Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km² were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km². We observe an increase of 2000 km² of agricultural intensification, where areas of single crops were converted to double crops during the study period.     

Embedding linear programming in multi objective genetic algorithms for reducing the size of the search space with application to leakage minimization in water distribution networks

This paper shows how embedding a local search algorithm, such as the iterated linear programming (LP), in the multi-objective genetic algorithms (MOGAs) can lead to a reduction in the search space and then to the improvement of the computational efficiency of the MOGAs. In fact, when the optimization problem features both continuous real variables and discrete integer variables, the search space can be subdivided into two sub-spaces, related to the two kinds of variables respectively. The problem can then be structured in such a way that MOGAs can be used for the search within the sub-space of the discrete integer variables. For each solution proposed by the MOGAs, the iterated LP can be used for the search within the sub-space of the continuous real variables. An example of this hybrid algorithm is provided herein as far as water distribution networks are concerned. In particular, the problem of the optimal location of control valves for leakage attenuation is considered. In this framework, the MOGA NSGAII is used to search for the optimal valve locations and for the identification of the isolation valves which have to be closed in the network in order to improve the effectiveness of the control valves whereas the iterated linear programming is used to search for the optimal settings of the control valves. The application to two case studies clearly proves the reduction in the MOGA search space size to render the hybrid algorithm more efficient than the MOGA without iterated linear programming embedded.     

A generic model for assessing the effects of countermeasures to reduce the radionuclide contamination levels in abiotic components of fresh water systems and complex catchments

This paper describes a generic model for predicting the migration of ¹³⁷Cs and ⁹⁰Sr through complex catchments and the effects of countermeasures to reduce the contamination levels. The model provides assessments of radionuclide behaviour in water systems comprised of rivers, lakes and reservoirs. It makes use of aggregate, “collective” parameters which summarise the overall effects of competing migration processes occurring in fresh water bodies. The model accounts for the radionuclide fluxes from the water column to the sediment and vice-versa, for the radionuclide migration from the catchment and for the transport of contaminated matter through the water body. It has been applied to several European fresh water systems contaminated by ⁹⁰Sr and ¹³⁷Cs due to nuclear weapon tests in the atmosphere of past decades and to the Chernobyl accident. The model can predict the effects of the following countermeasures: (a) Sediment removal; (b) Diversion of water from sub-catchments; and (c) Decontamination of sub-catchments. The results of the sensitivity and uncertainty analyses are described. Some examples of countermeasure applications are described and discussed.     

Analysis of TRIPS Agreement and the justification of international IP rights protection in the WTO's multilateral trading system,with particular reference to pharmaceutical patents

The entry of the Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement has seen the developing countries and the least developed countries (LDCs) suffer from the excessive burden of obligations imposed under the Agreement to embrace and implement a higher standard of intellectual property (IP) protection. One of the areas where the impact of the measures is most felt is on accessibility to affordable medicines for frontline treatment of diseases in developing countries and LDCs, where the majority of the HIV/AIDS sufferers come from. This inevitable plight, although well known, and posited by the developing countries and LDCs during the Uruguay round of negotiations, was overlooked. This also necessitated the Doha Deceleration, which does not seem to have addressed the problem. The developed countries have also successfully utilised the TRIPS Agreement's IP rights protection criteria as a benchmark, to develop a much higher IP rights protection agenda through the introduction of TRIPS-plus provisions in bilateral and other multilateral agreements entered into with developing countries. The winners in the game are the patent-holding pharmaceutical corporations, software corporations, media corporations, and the developed countries where they are incorporated. The ones at the receiving end are the developing countries and the LDCs who were promised technology transfer to build a modern economy by the developed countries, but are faced with multiple problems of non-availability of affordable medicines for health care, besides others. This article seeks to study the justification for an extended IP rights protection under the TRIPS Agreement through an analysis of the philosophical underpinnings of the IP rights and the patent regime. It will be argued that the TRIPS Agreement is a major obstacle that the developing countries and the LDCs have been made to face as Members of the WTO (World Trade Organisation), with no end in sight for their miseries, and that the only possible solution is a review or an amendment of the TRIPS Agreement.