Analyzing Vegetation Trends with Sensor Data from Earth Observation Satellites

Abstract This thesis aims to advance the analysis of nonlinear trends in time series of vegetation data from Earth observation satellite sensors. This is accomplished by developing fast, efficient methods suitable for large volumes of data. A set of methods, tools, and a framework are developed and verified using data from regions containing vegetation change hotspots. First, a polynomial-fitting scheme is tested and applied to annual Global Inventory Modeling and Mapping Studies (GIMMS)–Normalized Difference Vegetation Index (NDVI) observations for North Africa for the period 1982–2006. Changes in annual observations are divided between linear and nonlinear (cubic, quadratic, and concealed) trend behaviors. A concealed trend is a nonlinear change which does not result in a net change in the amount of vegetation over the period. Second, a systematic comparison between parametric and non-parametric techniques for analyzing trends in annual GIMMS-NDVI data is performed at fifteen sites (located in Africa, Spain, Italy, and Iraq) to compare how trend type and departure from normality assumptions affect each method’s accuracy in detecting long-term change. Third, a user-friendly program (Detecting Breakpoints and Estimating Segments in Trend, DBEST) has been developed which generalizes vegetation trends to main features, and characterizes vegetation trend changes. The outputs of DBEST are the simplified trend, the change type (abrupt or non-abrupt), and estimates for the characteristics (time and magnitude) of the change. DBEST is tested and evaluated using both simulated NDVI data, and actual NDVI time series for Iraq for the period 1982-2006. Finally, a decision-making framework is presented to help analysts perform comprehensive analyses of trend/change in time series of satellite sensor data. The framework is based on a conceptual model of the main aspects of trend analyses, including identification of the research question, the required data, the appropriate variables, and selection of efficient analysis methods. To verify the framework, it is applied to four case studies (located in Burkina Faso, Spain, Sweden, and Senegal) using Moderate-resolution Imaging Spectroradiometer (MODIS)–NDVI data for the period 2000–2013. Each of the case studies successfully achieved its research aim(s), showing that the framework can achieve the main goal of the study which is to advance the analysis of nonlinear changes in vegetation. The methods developed in this thesis can help to contribute more accurate information about vegetation dynamics to the field of land cover change research

Accurate fault location for power transmission lines

This thesis describes a new accurate fault location technique for power transmission lines. The technique is based on a distributed parameter line model which inherently accounts for line conductor asymmetry and shunt capacitance. The accuracy of the new technique is not significantly affected by fault resistance, source network configuration or line length. Also, in most cases no fault type identification is required. The new fault location technique uses the current and voltage phasors at power frequency measured at the line ends. These measurements are synchronised from a knowledge of the prefault phasor data. For a single-phase network the basic idea is to equate two equations obtained for the fault point voltage; one from the sending end phasor data and the other from the receiving end phasor data. The resultant equation is solved for the distance to fault. For multiphase systems the idea is 'generalised by using the theory of natural modes which involves the evaluation of eigenvalues and eigenvectors of the lines. In this way a multiphase system is decoupled into a number of single-phase modal circuits; each circuit can be solved for fault location. For perfectly transposed lines the eigenvalues can simply be evaluated from the sequence components and a real eigenvector matrix can be defined for all the lines. For untransposed lines the new algorithm maintains its high accuracy when assuming perfect transposition to simplify the evaluation of eigenvalues and eigenvectors. Also for double-circuit applications a circuit-by-circuit fault location, without any link between the two circuits, is possible. The test results for different fault conditions presented in this thesis show the higher accuracy in fault location achieved by the new,algorithm in comparison with the algorithms used in the best commercially available fault locators

Comparing parametric and non-parametric approaches for estimating trends in multi-year NDVI

The aim of this study is to systematically compare parametric and non-parametric techniques for analyzing trends in annual NDVI derived from NOAA AVHRR sensor in order to examine how trend type and departure from normality assumptions affect the accuracy of detecting long-term change. To generate annual data, the mean NDVI of a four-month long ‘green’ season was computed for fifteen sites (located in Africa, Spain, Italy, Sweden, and Iraq) from the GIMMS product for the periods 1982-2006. Trends in these time series were then estimated by Ordinary Least-Squares (OLS) regression (parametric) and the combined Mann-Kendall test with Theil-Sen slope estimator (non-parametric), and compared using slope value and statistical significance measures. We also estimated optimal polynomial model for the annual NDVI, by using Akaike Information Criterion (AIC), to determine the trend type at each site. Results indicate that slopes and their statistical significances obtained from the two approaches at sites with low degree polynomials (mostly linear) and steep monotonic (gradually increasing or decreasing) trends compare favourably with one another. At sites with weak linear slopes, the two approaches had similar results as well. Exceptions include sites with abrupt step-like changes resulting in departures from linearity and consequently high degree polynomials where the least-squares method outperformed the Mann-Kendall Theil-Sen method. In sum, we conclude that OLS is superior for detecting NDVI trends using annual data though further investigation using other techniques is recommended

Supreme audit court of auditors' insights on operational audit challenges

Operational audit plays an important role on managing governmental budget. It helps control government spending and other important budgetary issues. This paper presents an empirical study to find out the possible barriers on implementing operational audit. The proposed study distributes some questionnaires among supreme audit court of auditors and analyzes the questions. The results indicate that many governmental organizations are not strongly committed to rules and regulations. There are not sufficient standards on auditing programs and many governmental agencies do not even use operational budgeting system since they are not aware of the benefits of such system. There are some of the most important challenges of having operational budgeting and paper suggests some guidelines for having better regulation on removing the main barriers

Global evaluation of SMAP/Sentinel-1 soil moisture products

MAP/Sentinel-1 soil moisture is the latest SMAP (Soil Moisture Active Passive) product derived from synergistic utilization of the radiometry observations of SMAP and radar backscattering data of Sentinel-1. This product is the first and only global soil moisture (SM) map at 1 km and 3 km spatial resolutions. In this paper, we evaluated the SMAP/Sentinel-1 SM product from different viewpoints to better understand its quality, advantages, and likely limitations. A comparative analysis of this product and in situ measurements, for the time period March 2015 to January 2022, from 35 dense and sparse SM networks and 561 stations distributed around the world was carried out. We examined the effects of land cover, vegetation fraction, water bodies, urban areas, soil characteristics, and seasonal climatic conditions on the performance of active–passive SMAP/Sentinel-1 in estimating the SM. We also compared the performance metrics of enhanced SMAP (9 km) and SMAP/Sentinel-1 products (3 km) to analyze the effects of the active–passive disaggregation algorithm on various features of the SMAP SM maps. Results showed satisfactory agreement between SMAP/Sentinel-1 and in situ SM measurements for most sites (r values between 0.19 and 0.95 and ub-RMSE between 0.03 and 0.17), especially for dense sites without representativeness errors. Thanks to the vegetation effect correction applied in the active–passive algorithm, the SMAP/Sentinel-1 product had the highest correlation with the reference data in grasslands and croplands. Results also showed that the accuracy of the SMAP/Sentinel-1 SM product in different networks is independent of the presence of water bodies, urban areas, and soil types.Peer ReviewedPostprint (published version

Emerging Smart Meters in Electrical Distribution Systems: Opportunities and Challenges

High penetration of variable and non-programmable distributed generation has brought new challenges to the power system operation and is highlighting the need of a smarter grid. One of the key requirements in this regard is developing and deploying smart metering systems in distribution networks. In this paper we present the actual situation in the Italian distribution networks and we discuss the opportunities and challenges of applying new metering systems and introducing a flexible, multi-utility, multi-service metering architecture. Some off-the-shelf or prototype smart meters, selected to be tested in an ongoing European project, named FLEXMETER, are presented

An IoT realization in an interdepartmental real time simulation lab for distribution system control and management studies

Modern electric distribution systems with emerging operation methods and advanced metering systems bring new challenges to the system analysis, control and management. Interdependency of cyber and physical layers and interoperability of various control and management strategies require wide and accurate test and analysis before field implementation. Real-time simulation is known as a precise and reliable method to support new system/device development from initial design to implementation. However, for the study of different application algorithms, considering the various expertise requirements, the interconnection of multiple development laboratories to a real-time simulation lab, which constitutes the core of an interdepartmental real-time simulation platform, is needed. This paper presents the implemented architecture of such an integrated lab, which serves real-time simulations to different application fields within electric distribution system domain. The architecture is an implementation of an Internet-of-Things to facilitate software in-the-loop (SIL) and hardware in-the-loop (HIL) tests. A demo of the proposed architecture is presented, applied to the testing of a fault location algorithm in a portion of a realistic distribution system model. The implemented platform is flexible to integrate different algorithms in a plug-and-play fashion through a designed communication interface

The comparison of the effectiveness of contingency management and trans-theoretical model on the risk of sexual behaviors in cocaine users: A short report study

BACKGROUND: A transtheoretical model (TTM) can be considered as a cognitive and motivational view, a component which plays a significant role in addiction. Further, the theoretical basis of contingency management (CM) treatment is the origin of behaviorism and relies on operant conditioning. The present study is performed aiming to determine the effectiveness of TTM and CM on cocaine use and sexual risk behaviors in cocaine users.METHODS: In this randomized clinical trial with 6-month follow-up, which was performed from 15 December 2014 to 20 November 2015, 75 male cocaine users were selected based on a respondent-driven sampling (RDS) method and were randomly divided into three groups by block randomization. The experimental group received a 12-week CM protocol and TTM and the control group was placed on the waiting list. Pre-test, post-test (after 12 weeks of training), and follow-up (six months) were administered. Data analysis was carried out using repeated measures analysis of variance (ANOVA), Scheffe’s post hoc test, and chi-square test through SPSS software.RESULTS: The mean age of the CM group, TTM group, and control group was estimated 26.12, 25.31, and 23.91, respectively. The primary outcome showed that CM and TTM had a significant effect on decreasing the sexual thoughts, sexual hyperactivity, and high risk behaviors. This effectiveness was stable until six months (P = 0.008), however there was not a significant difference between the two treatments (P = 0.200). The secondary outcome showed that in the changing stages, TTM (F-72%) and CM (F-60%) had a significant effectiveness which maintained until the follow-up stage.CONCLUSION: The findings more enhance the hope to integrate the theoretical approaches into the clinical interventions