Environmental variables modeling based on remote sensing data using time series analysis: forestry and agricultural applications

En la actualidad, el seguimiento de la dinámica de los procesos medio ambientales está considerado como un punto de gran interés en el campo medioambiental. La cobertura espacio temporal de los datos de teledetección proporciona información continua con una alta frecuencia temporal, permitiendo el análisis de la evolución de los ecosistemas desde diferentes escalas espacio-temporales. Aunque el valor de la teledetección ha sido ampliamente probado, en la actualidad solo existe un número reducido de metodologías que permiten su análisis de una forma cuantitativa. En la presente tesis se propone un esquema de trabajo para explotar las series temporales de datos de teledetección, basado en la combinación del análisis estadístico de series de tiempo y la fenometría. El objetivo principal es demostrar el uso de las series temporales de datos de teledetección para analizar la dinámica de variables medio ambientales de una forma cuantitativa. Los objetivos específicos son: (1) evaluar dichas variables medio ambientales y (2) desarrollar modelos empíricos para predecir su comportamiento futuro. Estos objetivos se materializan en cuatro aplicaciones cuyos objetivos específicos son: (1) evaluar y cartografiar estados fenológicos del cultivo del algodón mediante análisis espectral y fenometría, (2) evaluar y modelizar la estacionalidad de incendios forestales en dos regiones bioclimáticas mediante modelos dinámicos, (3) predecir el riesgo de incendios forestales a nivel pixel utilizando modelos dinámicos y (4) evaluar el funcionamiento de la vegetación en base a la autocorrelación temporal y la fenometría. Los resultados de esta tesis muestran la utilidad del ajuste de funciones para modelizar los índices espectrales AS1 y AS2. Los parámetros fenológicos derivados del ajuste de funciones permiten la identificación de distintos estados fenológicos del cultivo del algodón. El análisis espectral ha demostrado, de una forma cuantitativa, la presencia de un ciclo en el índice AS2 y de dos ciclos en el AS1 así como el comportamiento unimodal y bimodal de la estacionalidad de incendios en las regiones mediterránea y templada respectivamente. Modelos autorregresivos han sido utilizados para caracterizar la dinámica de la estacionalidad de incendios y para predecir de una forma muy precisa el riesgo de incendios forestales a nivel pixel. Ha sido demostrada la utilidad de la autocorrelación temporal para definir y caracterizar el funcionamiento de la vegetación a nivel pixel. Finalmente el concepto “Optical Functional Type” ha sido definido, donde se propone que los pixeles deberían ser considerados como unidades temporales y analizados en función de su dinámica temporal. ix SUMMARY A good understanding of land surface processes is considered as a key subject in environmental sciences. The spatial-temporal coverage of remote sensing data provides continuous observations with a high temporal frequency allowing the assessment of ecosystem evolution at different temporal and spatial scales. Although the value of remote sensing time series has been firmly proved, only few time series methods have been developed for analyzing this data in a quantitative and continuous manner. In the present dissertation a working framework to exploit Remote Sensing time series is proposed based on the combination of Time Series Analysis and phenometric approach. The main goal is to demonstrate the use of remote sensing time series to analyze quantitatively environmental variable dynamics. The specific objectives are (1) to assess environmental variables based on remote sensing time series and (2) to develop empirical models to forecast environmental variables. These objectives have been achieved in four applications which specific objectives are (1) assessing and mapping cotton crop phenological stages using spectral and phenometric analyses, (2) assessing and modeling fire seasonality in two different ecoregions by dynamic models, (3) forecasting forest fire risk on a pixel basis by dynamic models, and (4) assessing vegetation functioning based on temporal autocorrelation and phenometric analysis. The results of this dissertation show the usefulness of function fitting procedures to model AS1 and AS2. Phenometrics derived from function fitting procedure makes it possible to identify cotton crop phenological stages. Spectral analysis has demonstrated quantitatively the presence of one cycle in AS2 and two in AS1 and the unimodal and bimodal behaviour of fire seasonality in the Mediterranean and temperate ecoregions respectively. Autoregressive models has been used to characterize the dynamics of fire seasonality in two ecoregions and to forecasts accurately fire risk on a pixel basis. The usefulness of temporal autocorrelation to define and characterized land surface functioning has been demonstrated. And finally the “Optical Functional Types” concept has been proposed, in this approach pixels could be as temporal unities based on its temporal dynamics or functioning.

3D + t Morphological Processing: Applications to Embryogenesis Image Analysis

We propose to directly process 3D + t image sequences with mathematical morphology operators, using a new classi?cation of the 3D+t structuring elements. Several methods (?ltering, tracking, segmentation) dedicated to the analysis of 3D + t datasets of zebra?sh embryogenesis are introduced and validated through a synthetic dataset. Then, we illustrate the application of these methods to the analysis of datasets of zebra?sh early development acquired with various microscopy techniques. This processing paradigm produces spatio-temporal coherent results as it bene?ts from the intrinsic redundancy of the temporal dimension, and minimizes the needs for human intervention in semi-automatic algorithms.

Acrobats in the rooftops of Tehran

This paper seeks to analyze the political dimension of the body, and consequently the inherently political dimension of space, through the instrumental notion of situation, understood as an spatio-temporal mesh configured by bodies, practices and discourses. The political understood as the potential for action (or non-action) underlying the individual body, implies a renewed definition of a landscape that results from the body’s doing. Landscape becomes a multiple corporeality, a field of relations in which we discover ourselves enmeshed, not just placed; a field in which the limit is not frontier but bond and common dimension. A disquieting ambiguous zone appears there where the individual spatiality is born out of the body through the actualization of its political potential and entangles with others to constitute a common spatiality, political action of the multitude. The article is organized through the description of a back-and-forth movement between the revolts of Tehran in 2009 and the Iranian revolution of 1979. Also, a detour into the works of Robert Morris and Trisha Brown is required in order to understand the link between the body and the constitution of a common spatiality.

Simulación de componentes no estacionarias de viento en orografías complejas

Realistic operation of helicopter flight simulators in complex topographies (such as urban environments) requires appropriate prediction of the incoming wind, and this prediction should be made in real time. Unfortunately, the wind topology around complex topographies shows time-dependent, fully nonlinear, turbulent patterns (i.e., wakes) whose simulation cannot be made using computationally inexpensive tools based on corrected potential approximations. Instead, the full Navier-Stokes plus some kind of turbulent modeling is necessary, which is quite computationally expensive. The complete unsteady flow depends on two parameters, namely the velocity and orientation of the free stream flow. The aim of this MSc thesis is to develop a methodology for the real time simulation of these complex flows. For simplicity, the flow around a single building (20 mx20 m cross section and 100 m height) is considered, with free stream velocity in the range 5-25 m/s. Because of the square cross section, the problem shows two reflection symmetries, which allows for restricting the orientations to the range 0° < a. < 45°. The methodology includes an offline preprocess and the online operation. The preprocess consists in three steps: An appropriate, unstructured mesh is selected in which the flow is sim¬ulated using OpenFOAM, and this is done for 33 combinations of 3 free stream intensities and 11 orientations. For each of these, the simulation proceeds for a sufficiently large time as to eliminate transients. This step is quite computationally expensive. Each flow field is post-processed using a combination of proper orthogonal decomposition, fast Fourier transform, and a convenient optimization tool, which identifies the relevant frequencies (namely, both the basic frequencies and their harmonics) and modes in the computational mesh. This combination includes several new ingredients to filter errors out and identify the relevant spatio-temporal patterns. Note that, in principle, the basic frequencies depend on both the intensity and the orientation of the free stream flow. The outcome of this step is a set of modes (vectors containing the three velocity components at all mesh points) for the various Fourier components, intensities, and orientations, which can be organized as a third order tensor. This step is fairly computationally inexpensive. The above mentioned tensor is treated using a combination of truncated high order singular value, decomposition and appropriate one-dimensional interpolation (as in Lorente, Velazquez, Vega, J. Aircraft, 45 (2008) 1779-1788). The outcome is a tensor representation of both the relevant fre¬quencies and the associated Fourier modes for a given pair of values of the free stream flow intensity and orientation. This step is fairly compu¬tationally inexpensive. The online, operation requires just reconstructing the time-dependent flow field from its Fourier representation, which is extremely computationally inex¬pensive. The whole method is quite robust.

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

Toward a climate-dependent paradigm of ammonia emission & deposition.

Existing descriptions of bi-directional ammonia (NH3) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission–deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28–67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45–85) Tg N in 2008 to reach 132 (89–179) Tg by 2100.

New generation of human machine interfaces for controlling UAV through depth based gesture recognition

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

Iron distribution through the developmental stages of Medicago truncatula nodules.

Paramount to symbiotic nitrogen fixation (SNF) is the synthesis of a number of metalloenzymes that use iron as a critical component of their catalytical core. Since this process is carried out by endosymbiotic rhizobia living in legume root nodules, the mechanisms involved in iron delivery to the rhizobia-containing cells are critical for SNF. In order to gain insight into iron transport to the nodule, we have used synchrotron-based X-ray fluorescence to determine the spatio-temporal distribution of this metal in nodules of the legume Medicago truncatula with hitherto unattained sensitivity and resolution. The data support a model in which iron is released from the vasculature into the apoplast of the infection/differentiation zone of the nodule (zone II). The infected cell subsequently takes up this apoplastic iron and delivers it to the symbiosome and the secretory system to synthesize ferroproteins. Upon senescence, iron is relocated to the vasculature to be reused by the shoot. These observations highlight the important role of yet to be discovered metal transporters in iron compartmentalization in the nodule and in the recovery of an essential and scarce nutrient for flowering and seed production.

Climatic factors control rodent seed predation in Pinus pinea L. stands in Central Spain

- Context: Pinus pinea L. presents serious problems of natural regeneration in managed forest of Central Spain. The species exhibits specific traits linked to frugivore activity. Therefore, information on plant–animal interactions may be crucial to understand regeneration failure. - Aims: Determining the spatio-temporal pattern of P. pinea seed predation by Apodemus sylvaticus L. and the factors involved. Exploring the importance of A. sylvaticus L. as a disperser of P. pinea. Identifying other frugivores and their seasonal patterns. - Methods: An intensive 24-month seed predation trial was carried out. The probability of seeds escaping predation was modelled through a zero-inflated binomial mixed model. Experiments on seed dispersal by A. sylvaticus were conducted. Cameras were set up to identify other potential frugivores. - Results: Decreasing rodent population in summer and masting enhances seed survival. Seeds were exploited more rapidly nearby parent trees and shelters. A. sylvaticus dispersal activity was found to be scarce. Corvids marginally preyed upon P. pinea seeds. - Conclusions: Survival of P. pinea seeds is climate-controlled through the timing of the dry period together with masting occurrence. Should germination not take place during the survival period, establishment may be limited. A. sylvaticus mediated dispersal does not modify the seed shadow. Seasonality of corvid activity points to a role of corvids in dispersal.

Moving object detection for real-time augmented reality applications in a GPGPU

The last generation of consumer electronic devices is endowed with Augmented Reality (AR) tools. These tools require moving object detection strategies, which should be fast and efficient, to carry out higher level object analysis tasks. We propose a lightweight spatio-temporal-based non-parametric background-foreground modeling strategy in a General Purpose Graphics Processing Unit (GPGPU), which provides real-time high-quality results in a great variety of scenarios and is suitable for AR applications.

Knowledge-based spatiotemporal linear abstraction

We present a theoretical framework and a case study for reusing the same conceptual and computational methodology for both temporal abstraction and linear (unidimensional) space abstraction, in a domain (evaluation of traffic-control actions) significantly different from the one (clinical medicine) in which the method was originally used. The method, known as knowledge-based temporal abstraction, abstracts high-level concepts and patterns from time-stamped raw data using a formal theory of domain-specific temporal-abstraction knowledge. We applied this method, originally used to interpret time-oriented clinical data, to the domain of traffic control, in which the monitoring task requires linear pattern matching along both space and time. First, we reused the method for creation of unidimensional spatial abstractions over highways, given sensor measurements along each highway measured at the same time point. Second, we reused the method to create temporal abstractions of the traffic behavior, for the same space segments, but during consecutive time points. We defined the corresponding temporal-abstraction and spatial-abstraction domain-specific knowledge. Our results suggest that (1) the knowledge-based temporal-abstraction method is reusable over time and unidimensional space as well as over significantly different domains; (2) the method can be generalized into a knowledge-based linear-abstraction method, which solves tasks requiring abstraction of data along any linear distance measure; and (3) a spatiotemporal-abstraction method can be assembled from two copies of the generalized method and a spatial-decomposition mechanism, and is applicable to tasks requiring abstraction of time-oriented data into meaningful spatiotemporal patterns over a linear, decomposable space, such as traffic over a set of highways.

Time scales in cognitive neuroscience

Cognitive neuroscience boils down to describing the ways in which cognitive function results from brain activity. In turn, brain activity shows complex fluctuations, with structure at many spatio-temporal scales. Exactly how cognitive function inherits the physical dimensions of neural activity, though, is highly non-trivial, and so are generally the corresponding dimensions of cognitive phenomena. As for any physical phenomenon, when studying cognitive function, the first conceptual step should be that of establishing its dimensions. Here, we provide a systematic presentation of the temporal aspects of task-related brain activity, from the smallest scale of the brain imaging technique's resolution, to the observation time of a given experiment, through the characteristic time scales of the process under study. We first review some standard assumptions on the temporal scales of cognitive function. In spite of their general use, these assumptions hold true to a high degree of approximation for many cognitive (viz. fast perceptual) processes, but have their limitations for other ones (e.g., thinking or reasoning). We define in a rigorous way the temporal quantifiers of cognition at all scales, and illustrate how they qualitatively vary as a function of the properties of the cognitive process under study. We propose that each phenomenon should be approached with its own set of theoretical, methodological and analytical tools. In particular, we show that when treating cognitive processes such as thinking or reasoning, complex properties of ongoing brain activity, which can be drastically simplified when considering fast (e.g., perceptual) processes, start playing a major role, and not only characterize the temporal properties of task-related brain activity, but also determine the conditions for proper observation of the phenomena. Finally, some implications on the design of experiments, data analyses, and the choice of recording parameters are discussed.

Competitive exclusion in a two-especies chemotasis model

We consider a mathematical model for the spatio-temporal evolution of two biological species in a competitive situation. Besides diffusing, both species move toward higher concentrations of a chemical substance which is produced by themselves. The resulting system consists of two parabolic equations with Lotka–Volterra-type kinetic terms and chemotactic cross-diffusion, along with an elliptic equation describing the behavior of the chemical. We study the question in how far the phenomenon of competitive exclusion occurs in such a context. We identify parameter regimes for which indeed one of the species dies out asymptotically, whereas the other reaches its carrying capacity in the large time limit.

Unravelling past flash flood activity in a forested mountain catchment of the Spanish Central System

Flash floods represent one of the most common natural hazards in mountain catchments, and are frequent in Mediterranean environments. As a result of the widespread lack of reliable data on past events, the understanding of their spatio-temporal occurrence and their climatic triggers remains rather limited. Here, we present a dendrogeomorphic reconstruction of past flash flood activity in the Arroyo de los Puentes stream (Sierra de Guadarrama, Spanish Central System). We analyze a total of 287 increment cores from 178 disturbed Scots pine trees (Pinus sylvestris L.) which yielded indications on 212 growth disturbances related to past flash flood impact. In combination with local archives, meteorological data, annual forest management records and highly-resolved terrestrial data (i.e., LiDAR data and aerial imagery), the dendrogeomorphic time series allowed dating 25 flash floods over the last three centuries, with a major event leaving an intense geomorphic footprint throughout the catchment in 1936. The analysis of meteorological records suggests that the rainfall thresholds of flash floods vary with the seasonality of events. Dated flash floods in the 20th century were primarily related with synoptic troughs owing to the arrival of air masses from north and west on the Iberian Peninsula during negative indices of the North Atlantic Oscillation. The results of this study contribute considerably to a better understanding of hazards related with hydrogeomorphic processes in central Spain in general and in the Sierra de Guadarrama National Park in particular.

Metodología para deducir relaciones de linaje en el catastro de España.

En España, los datos catastrales de acceso público, obtenidos a través de la Sede Electrónica del Catastro (SEC), no incluyen información sobre la genealogía o las relaciones de linaje existente entre las parcelas, de forma que la gestión de la información histórica es muy limitada. Este artículo presenta un método para obtener las relaciones de linaje más frecuentes entre las parcelas (agregación y segregación) y propone un prototipo de estructura relacional para el almacenamiento y la gestión histórica de los datos catastrales de acceso público. El proceso de análisis para deducir el linaje se basa en superposiciones espacio-temporales junto con secuencias de sentencias SQL. El método proporciona un 70% de relaciones de agregación y segregación correctas; el resto presentan errores debidos, en general, a anomalías presentes en los propios datos catastrales. ABSTRACT Public cadastral data in Spain, available through the Electronic Office of Cadastre, do not include any information on the genealogy or lineage relationship among the parcels, so the management of historical information becomes very limit ed. This paper presents a method for obtaining the most common lineage relationships between plots (aggregation and segregation) and proposes a relational structure prototype for the storage and historic management of public cadastral data. The analysis process to deduce the lineage is based on spatio-temporal overlaps coupled with SQL statements sequences. This method provides a 70% of correct aggregation and segregation relationships; the wrong cases are mainly caused by errors existing in the cadastral data themselves.