Mapping and Assessing Impacts of Land Use and Land Cover Change by Means of Advanced Remote Sensing Approach:: Mapping and Assessing Impacts of Land Use and Land Cover Change by Means of Advanced Remote Sensing Approach:: A case Study of Gash Agricultural Scheme, Eastern Sudan

Risks and uncertainties are unavoidable in agriculture in Sudan, due to its dependence on climatic factors and to the imperfect nature of the agricultural decisions and policies attributed to land cover and land use changes that occur. The current study was conducted in the Gash Agricultural Scheme (GAS) - Kassala State, as a semi-arid land in eastern Sudan. The scheme has been established to contribute to the rural development, to help stability of the nomadic population in eastern Sudan, particularly the local population around the Gash river areas, and to facilitate utilizing the river flood in growing cotton and other cash crops. In the last decade, the scheme production has declined, because of drought periods, which hit the region, sand invasion and the spread of invasive mesquite trees, in addition to administrative negligence. These have resulted also in poor agricultural productivity and the displacement of farmers away from the scheme area. Recently, the scheme is heavily disturbed by human intervention in many aspects. Consequently, resources of cultivated land have shrunk and declined during the period of the study, which in turn have led to dissatisfaction and increasing failure of satisfying increasing farmer’s income and demand for local consumption. Remote sensing applications and geospatial techniques have played a key role in studying different types of hazards whether they are natural or manmade. Multi-temporal satellite data combined with ancillary data were used to monitor, analyze and to assess land use and land cover (LULC) changes and the impact of land degradation on the scheme production, which provides the managers and decision makers with current and improved data for the purposes of proper administration of natural resources in the GAS. Information about patterns of LULC changes through time in the GAS is not only important for the management and planning, but also for a better understanding of human dimensions of environmental changes at regional scale. This study attempts to map and assess the impacts of LULC change and land degradation in GAS during a period of 38 years from 1972-2010. Dry season multi-temporal satellite imagery collected by different sensor systems was selected such as three cloud-free Landsat (MSS 1972, TM 1987 and ETM+ 1999) and ASTER (2010) satellite imagery. This imagery was geo-referenced and radiometrically and atmospherically calibrated using dark object subtraction (DOS). Two approaches of classification (object-oriented and pixel-based) were applied for classification and comparison of LULC. In addition, the study compares between the two approaches to determine which one is more compatible for classification of LULC of the GAS. The pixel-based approach performed slightly better than the object-oriented approach in the classification of LULC in the study area. Application of multi-temporal remote sensing data proved to be successful for the identification and mapping of LULC into five main classes as follows: woodland dominated by dense mesquite trees, grass and shrubs dominated by less dense mesquite trees, bare and cultivated land, stabilized fine sand and mobile sand. After image enhancement successful classification of imagery was achieved using pixel and object based approaches as well as subsequent change detection (image differencing and change matrix), supported by classification accuracy assessments and post-classification. Comparison of LULC changes shows that the land cover of GAS has changed dramatically during the investigated period. It has been discovered that more significant of LULC change processes occurred during the second studied period (1987 to 1999) than during the first period (1972-1987). In the second period nearly half of bare and cultivated lands was changed from 41372.74 ha (20.22 %) in 1987 to 28020.80 ha (13.60 %) in 1999, which was mainly due to the drought that hit the region during the mentioned period. However, the results revealed a drastic loss of bare and cultivated land, equivalent to more than 40% during the entire period (1972-2010). Throughout the whole period of study, drought and invasion of both mesquite trees and sand were responsible for the loss of more than 40% of the total productive lands. Change vector analysis (CVA) as a useful approach was applied for estimating change detection in both magnitude and direction of change. The promising approach of multivariate alteration detection (MAD) and subsequent maximum autocorrelation factor (MAD/MAF) transformation was used to support change detection via assessment of maximum correlation between the transformed variates and the specific original image bands related to specific land cover classes. However, both CVA and MAD/MAD strongly prove the fact that bare and cultivated land have dramatically changed and decreased continuously during the studied period. Both CVA and MAD/MAD demonstrate adequate potentials for monitoring, detecting, identifying and mapping the changes. Moreover, this research demonstrated that CVA and MAD/MAF are superior in providing qualitative details about the nature of all kinds of change. Vegetation indices (VI) such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), modified adjusted vegetation index (MSAVI) and grain soil index (GSI) were applied to measure the quantitative characterization of temporal and spatial vegetation cover patterns and change. All indices remain very sensitive to structure variation of LULC. The results reveal that the NDVI is more effective for detecting the amount and status of the vegetation cover in the study area than SAVI, MSAVI and GSI. Therefore, it can be stated that NDVI can be used as a response variable to identify drought disturbance and land degradation in semi-arid land such as the GAS area. Results of detecting vegetation cover observed by using SAVI were found to be more reasonable than using MSAVI, although MSAVI reduces the background of bare soil better than SAVI. GSI proves high efficiency in determining the different types of surface soils, and producing a change map of top soil grain size, which is useful in assessment of land degradation in the study area. The linkage between socio-economic data and remotely sensed data was applied to determine the relationships between the different factors derived and to analyze the reasons for change in LULC and land degradation and its effects in the study area. The results indicate a strong relationship between LULC derived from remotely sensed data and the influencing socioeconomic variables. The results obtained from analyzing socioeconomic data confirm the findings of remote sensing data analysis, which assure that the decline and degradation of agricultural land is a result of further spread of mesquite trees and of increased invasion of sand during the study period. High livestock density and overgrazing, drought, invasion of sand, spread of invasive mesquite trees, overexploitation of land, improper management, and population growth were considered as the main direct factors responsible for degradation in the study area

Third Annual Earth Resources Program Review. Volume 3: Hydrology and oceanography

Conference proceedings on hydrology and meteorology investigations under Earth Resources Program - Vol.

Condition Assessment of Concrete Bridge Decks Using Ground and Airborne Infrared Thermography

Applications of nondestructive testing (NDT) technologies have shown promise in assessing the condition of existing concrete bridges. Infrared thermography (IRT) has gradually gained wider acceptance as a NDT and evaluation tool in the civil engineering field. The high capability of IRT in detecting subsurface delamination, commercial availability of infrared cameras, lower cost compared with other technologies, speed of data collection, and remote sensing are some of the expected benefits of applying this technique in bridge deck inspection practices. The research conducted in this thesis aims at developing a rational condition assessment system for concrete bridge decks based on IRT technology, and automating its analysis process in order to add this invaluable technique to the bridge inspector’s tool box. Ground penetrating radar (GPR) has also been vastly recognized as a NDT technique capable of evaluating the potential of active corrosion. Therefore, integrating IRT and GPR results in this research provides more precise assessments of bridge deck conditions. In addition, the research aims to establish a unique link between NDT technologies and inspector findings by developing a novel bridge deck condition rating index (BDCI). The proposed procedure captures the integrated results of IRT and GPR techniques, along with visual inspection judgements, thus overcoming the inherent scientific uncertainties of this process. Finally, the research aims to explore the potential application of unmanned aerial vehicle (UAV) infrared thermography for detecting hidden defects in concrete bridge decks. The NDT work in this thesis was conducted on full-scale deteriorated reinforced concrete bridge decks located in Montreal, Quebec and London, Ontario. The proposed models have been validated through various case studies. IRT, either from the ground or by utilizing a UAV with high-resolution thermal infrared imagery, was found to be an appropriate technology for inspecting and precisely detecting subsurface anomalies in concrete bridge decks. The proposed analysis produced thermal mosaic maps from the individual IR images. The k-means clustering classification technique was utilized to segment the mosaics and identify objective thresholds and, hence, to delineate different categories of delamination severity in the entire bridge decks. The proposed integration methodology of NDT technologies and visual inspection results provided more reliable BDCI. The information that was sought to identify the parameters affecting the integration process was gathered from bridge engineers with extensive experience and intuition. The analysis process utilized the fuzzy set theory to account for uncertainties and imprecision in the measurements of bridge deck defects detected by IRT and GPR testing along with bridge inspector observations. The developed system and models should stimulate wider acceptance of IRT as a rapid, systematic and cost-effective evaluation technique for detecting bridge deck delaminations. The proposed combination of IRT and GPR results should expand their correlative use in bridge deck inspection. Integrating the proposed BDCI procedure with existing bridge management systems can provide a detailed and timely picture of bridge health, thus helping transportation agencies in identifying critical deficiencies at various service life stages. Consequently, this can yield sizeable reductions in bridge inspection costs, effective allocation of limited maintenance and repair funds, and promote the safety, mobility, longevity, and reliability of our highway transportation assets

Autocalibrating vision guided navigation of unmanned air vehicles via tactical monocular cameras in GPS denied environments

This thesis presents a novel robotic navigation strategy by using a conventional tactical monocular camera, proving the feasibility of using a monocular camera as the sole proximity sensing, object avoidance, mapping, and path-planning mechanism to fly and navigate small to medium scale unmanned rotary-wing aircraft in an autonomous manner. The range measurement strategy is scalable, self-calibrating, indoor-outdoor capable, and has been biologically inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals (particularly bats), designed to assume operations in previously unknown, GPS-denied environments. It proposes novel electronics, aircraft, aircraft systems, systems, and procedures and algorithms that come together to form airborne systems which measure absolute ranges from a monocular camera via passive photometry, mimicking that of a human-pilot like judgement. The research is intended to bridge the gap between practical GPS coverage and precision localization and mapping problem in a small aircraft. In the context of this study, several robotic platforms, airborne and ground alike, have been developed, some of which have been integrated in real-life field trials, for experimental validation. Albeit the emphasis on miniature robotic aircraft this research has been tested and found compatible with tactical vests and helmets, and it can be used to augment the reliability of many other types of proximity sensors

Electronic Skin in Robotics and Healthcare: Towards Multimodal Sensing and Intelligent Analysis

Skin-interfaced electronics is gradually transforming robotic and medical fields by enabling noninvasive and continuous monitoring of physiological and biochemical information. Despite their promise, current wearable technologies face challenges in several disciplines: Physical sensors are prone to motion-induced noise and lack the capability for effective disease detection, while existing wearable biochemical sensors suffer from operational instability in biofluids, limiting their practicality. Conventional electronic skin contains only a limited category of sensors that are not sufficient for practical applications, and conventional data processing methods for these wearables necessitate manual intervention to filter noise and decipher health-related information. This thesis presents advances in electronic skin within robotics and healthcare, emphasizing multimodal sensing and data analysis through machine intelligence. Chapter 1 introduces the concept of electronic skin, outlining the emerging sensor technologies and a general machine learning pipeline for data processing. Chapter 2 details the development of multimodal physiological and biochemical sensors that enable long-term continuous monitoring with high sensitivity and stability. Chapter 3 explores the application of integrated electronic skin in robotics, prosthetics, and human machine interactions. Chapter 4 showcases practical implementations of integrated electronic skin with robust sensors for wound monitoring and treatment. Chapter 5 highlights the transformative deployment of artificial intelligence in deconvoluting health profiles on mental health. The last chapter, Chapter 6, delves into the challenges and prospects of artificial intelligence-powered electronic skins, offering predictions for the evolution of smart electronic skins. We envision that multimodal sensing and machine intelligence in electronic skin could significantly advance the field of human machine interactions and personalized healthcare.</p

NASA technology utilization applications

The work is reported from September 1972 through August 1973 by the Technology Applications Group of the Science Communication Division (SCD), formerly the Biological Sciences Communication Project (BSCP) in the Department of Medical and Public Affairs of the George Washington University. The work was supportive of many aspects of the NASA Technology Utilization program but in particular those dealing with Biomedical and Technology Application Teams, Applications Engineering projects, new technology reporting and documentation and transfer activities. Of particular interest are detailed reports on the progress of various hardware projects, and suggestions and criteria for the evaluation of candidate hardware projects. Finally some observations about the future expansion of the TU program are offered

State-of-the-Art Sensors Technology in Spain 2015: Volume 1

This book provides a comprehensive overview of state-of-the-art sensors technology in specific leading areas. Industrial researchers, engineers and professionals can find information on the most advanced technologies and developments, together with data processing. Further research covers specific devices and technologies that capture and distribute data to be processed by applying dedicated techniques or procedures, which is where sensors play the most important role. The book provides insights and solutions for different problems covering a broad spectrum of possibilities, thanks to a set of applications and solutions based on sensory technologies. Topics include: • Signal analysis for spectral power • 3D precise measurements • Electromagnetic propagation • Drugs detection • e-health environments based on social sensor networks • Robots in wireless environments, navigation, teleoperation, object grasping, demining • Wireless sensor networks • Industrial IoT • Insights in smart cities • Voice recognition • FPGA interfaces • Flight mill device for measurements on insects • Optical systems: UV, LEDs, lasers, fiber optics • Machine vision • Power dissipation • Liquid level in fuel tanks • Parabolic solar tracker • Force sensors • Control for a twin roto