Search results for: Argos satellite telemetry

Authors: Emmanuel Dada, Adebayo-Victoria Tobi Dada

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The study evaluates land use and land cover changes in the cocoa belt of Ondo state to quantify its effect on the expanse of land occupied by cocoa plantation as the most suitable region for cocoa raisin in Nigeria. Time series of satellite imagery from Landsat-7 ETM+ and Landsat-8 TIRS covering years 2000 and 2015 respectively were used. The study area was classified into six land use themes of cocoa plantation, settlement, water body, light forest and grassland, forest, and bar surface and rock outcrop. The analyses revealed that out of total land area of 997714 hectares of land of the study area, cocoa plantation land use increased by 10.3% in 2015 from 312260.6 ha in 2000. Forest land use also increased by 6.3% in 2015 from 152144.1 ha in the year 2000, water body reduced from 2954.5 ha in the year 2000 by 0.1% in 2015, settlement land use increased by 3% in 2015 from 15194.6 ha in 2000, light forest and grassland area reduced by 10.4% between 2000 and 2015 and 9.1% reduction in bar surface and rock outcrop land use between the year 2000 and 2015 respectively. The reasons for different ranges in the changes observed in the land use and land cover in the study area could be due to increase in the incentive to cocoa farmers from both government and non-governmental organizations, developed new cocoa breed that thrive better in the light forest, rapid increased in the population of cocoa farmers’ settlements, and government promulgation of forest reserve law.

Keywords: satellite imagery, land use and land cover change, area of land

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Authors: Hao Wang, Shuguo Pan

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The Global Navigation Satellite System (GNSS) signal received by the dynamic vehicle in the harsh environment will be frequently interfered with and blocked, which generates gross error affecting the positioning accuracy of the GNSS/Inertial Navigation System (INS) integrated navigation. Therefore, this paper put forward an improved robust Cubature Kalman filter (CKF) algorithm for single-frequency GNSS/INS tightly coupled system ambiguity resolution. Firstly, the dynamic model and measurement model of a single-frequency GNSS/INS tightly coupled system was established, and the method for GNSS integer ambiguity resolution with INS aided is studied. Then, we analyzed the influence of pseudo-range observation with gross error on GNSS/INS integrated positioning accuracy. To reduce the influence of outliers, this paper improved the CKF algorithm and realized an intelligent selection of robust strategies by judging the ill-conditioned matrix. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm based on the double-differenced solution mode. The experiment has proved the improved robust algorithm can greatly weaken the influence of separate, continuous, and hybrid observation anomalies for enhancing the reliability and accuracy of GNSS/INS tightly coupled navigation solutions.

Keywords: GNSS/INS integrated navigation, ambiguity resolution, Cubature Kalman filter, Robust algorithm

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Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

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Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Muhammad Ameer Nawaz Akram

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The 21st century has been revealed that many individuals around the world are living in urban settlements than in rural zones. The evolution of numerous cities in emerging and newly developed countries is accompanied by the rise of slums. The precise definition of a slum varies countries to countries, but the universal harmony is that slums are dilapidated settlements facing severe poverty and have lacked access to sanitation, water, electricity, good living styles, and land tenure. The slum settlements always vary in unique patterns within and among the countries and cities. The core objective of this study is the spatial identification and classification of slums in Gujrat city Pakistan from very high-resolution GeoEye-1 (0.41m) satellite imagery. Slums were first identified using GPS for sample site identification and ground-truthing; through this process, 425 slums were identified. Then Object-Oriented Analysis (OOA) was applied to classify slums on digital image. Spatial analysis softwares, e.g., ArcGIS 10.3, Erdas Imagine 9.3, and Envi 5.1, were used for processing data and performing the analysis. Results show that OOA provides up to 90% accuracy for the identification of slums. Jalal Cheema and Allah Ho colonies are severely affected by slum settlements. The ratio of criminal activities is also higher here than in other areas. Slums are increasing with the passage of time in urban areas, and they will be like a hazardous problem in coming future. So now, the executive bodies need to make effective policies and move towards the amelioration process of the city.

Keywords: slums, GPS, satellite imagery, object oriented analysis, zonal change detection

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Authors: Rajkumar Ghosh

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The study presents an overview of the many uses and approaches for estimating out-of-sequence thrust movement in earthquake mitigation. The study investigates how knowing and forecasting thrust movement during seismic occurrences might assist to effective earthquake mitigation measures. The review begins by discussing out-of-sequence thrust movement and its importance in earthquake mitigation strategies. It explores how typical techniques of estimating thrust movement may not capture the full complexity of seismic occurrences and emphasizes the benefits of include out-of-sequence data in the analysis. A thorough review of existing research and studies on out-of-sequence thrust movement estimates for earthquake mitigation. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources such as GPS measurements, satellite imagery, and seismic recordings. The study also examines the use of out-of-sequence thrust movement estimates in earthquake mitigation measures. It investigates how precise calculation of thrust movement may help improve structural design, analyse infrastructure risk, and develop early warning systems. The potential advantages of using out-of-sequence data in these applications to improve the efficiency of earthquake mitigation techniques. The difficulties and limits of estimating out-of-sequence thrust movement for earthquake mitigation. It addresses data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and increase the accuracy and reliability of out-of-sequence thrust movement estimates, the authors recommend topics for additional study and improvement. The study is a helpful resource for seismic monitoring and earthquake risk assessment researchers, engineers, and policymakers, supporting innovations in earthquake mitigation measures based on a better knowledge of thrust movement dynamics.

Keywords: earthquake mitigation, out-of-sequence thrust, satellite imagery, seismic recordings, GPS measurements

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Authors: Chadlia Ounissi, Maher Gzam, Tahani Hallek, Salah Mahmoudi, Mabrouk Montacer

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This work consists of a morphological study of the coastal domain at the central fringe of the Gulf of Gabes, Southeast of Tunisia, belonging to the structural domain of the maritime Jeffara. The diachronic study of tidal mouths in the study area and the observation of morphological markers revealed the existence of hydro-sedimentary processes leading to sedimentary accumulation and filling of the estuarine system. This filling process is materialized by the genesis of a sandy cord and the lateral migration of the tidal mouth. Moreover, we have been able to affirm, by the use of satellite images, that the dominant and responsible current at this particular coastal morphology is directed to the North, having constituted a controversy on the occurrence of what is previously mentioned in the literature. The speed of the lateral displacement of the channel varies as a function of the hydrodynamic forcing. Wave-dominated sites recorded the fastest speed (18 m/year) in the image of the mouth of Wadi el Melah. Tidal dominated sites in the Wadi Zerkine satellite image recorded a very low lateral migration (2 m / year). This variation in speed indicates that the intensity of the coastal current is uneven along the coast. This general pattern of hydrodynamic circulation, to the north, of the central fringe of the Gulf of Gabes, is disturbed by hydro-sedimentary cells.

Keywords: tidal mouth, direction of current, filling, sediment transport, Gulf of Gabes

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Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad

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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.

Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments

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Authors: G. P. Gunasinghe, Lilani Ruhunage, N. P. Ratnayake, G. V. I. Samaradivakara, H. M. R. Premasiri, A. S. Ratnayake, Nimila Dushantha, W. A. P. Weerakoon, K. B. A. Silva

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Sri Lanka is affected by different natural disasters such as tsunami, landslides, lightning, and riverine flood. Out of them, riverine floods act as a major disaster in the country. Different strategies are applied to control the impacts of flood hazards, and the expansion of river mouth is considered as one of the main activities for flood mitigation and disaster reduction. However, due to this expansion process, natural sand barriers including sand spits, barrier islands, and tidal planes are destroyed or subjected to change. This, in turn, can change the hydrodynamics and sediment dynamics of the area leading to other damages to the natural coastal features. The removal of a considerable portion of naturally formed sand barrier at Kaluganga River outlet (Calido Beach), Sri Lanka to control flooding event at Kaluthara urban area on May 2017, has become a serious issue in the area causing complete collapse of river mouth barrier spit bar system leading to rapid coastal erosion Kaluganga river outlet area and saltwater intrusion into the Kaluganga River. The present investigation is focused on assessing effects due to the removal of a considerable portion of naturally formed sand barrier at Kaluganga river mouth. For this study, the beach profiles, the bathymetric surveys, and Google Earth historical satellite images, before and after the flood event were collected and analyzed. Furthermore, a beach boundary survey was also carried out in October 2018 to support the satellite image data. The results of Google Earth satellite images and beach boundary survey data analyzed show a chronological breakdown of the sand barrier at the river outlet. The comparisons of pre and post-disaster bathymetric maps and beach profiles analysis revealed a noticeable deepening of the sea bed at the nearshore zone as well. Such deepening in the nearshore zone can cause the sea waves to break very near to the coastline. This might also lead to generate new diffraction patterns resulting in differential coastal accretion and erosion scenarios. Unless immediate mitigatory measures were not taken, the impacts may cause severe problems to the sensitive Kaluganag river mouth system.

Keywords: bathymetry, beach profiles, coastal features, river outlet, sand barrier, Sri Lanka

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Authors: H. J. Liu, Y. A. Chan, C. K. Pai, K. C. Tseng, Y. H. Chen, Y. L. Chan, T. C. Kuo

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To satisfy the mission requirement of the FORMOSAT-7 project, NSPO has initialized a self-reliant development on satellite propulsion technology. A trade-off study on different types of on-board propulsion system has been done. A green propellant, high-concentration hydrogen peroxide (H2O2 hereafter), is chosen in this research because it is ITAR-free, nontoxic and easy to produce. As the components designed for either cold gas or hydrazine propulsion system are not suitable for H2O2 propulsion system, the primary objective of the research is to develop the components compatible with H2O2. By cooperating with domestic research institutes and manufacturing vendors, several prototype components, including a diaphragm-type tank, pressure transducer, ball latching valve, and one-Newton thruster with catalyst bed, were manufactured, and the functional tests were performed successfully according to the mission requirements. The requisite environmental tests, including hot firing test, thermal vaccum test, vibration test and compatibility test, are prepared and will be to completed in the near future. To demonstrate the subsystem function, an Air-Bearing Thrust Stand (ABTS) and a real-time Data Acquisition & Control System (DACS) were implemented to assess the performance of the proposed H2O2 propulsion system. By measuring the distance that the thrust stand has traveled in a given time, the thrust force can be derived from the kinematics equation. To validate the feasibility of the approach, it is scheduled to assess the performance of a cold gas (N2) propulsion system prior to the H2O2 propulsion system.

Keywords: FORMOSAT-7, green propellant, Hydrogen peroxide, thruster

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

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Authors: Sheheryar Khan, Weidong Li, Fanqian Meng

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The Urban Heat Island (UHI) effect is one of the foremost problems out of other ecological and socioeconomic issues in urbanization. Due to this phenomenon that human-made urban areas have replaced the rural landscape with the surface that increases thermal conductivity and urban warmth; as a result, the temperature in the city is higher than in the surrounding rural areas. To affect the evidence of this phenomenon in the Zhengzhou city area, an observation of the temperature variations in the urban area is done through a scientific method that has been followed. Landsat 8 satellite images were taken from 2013 to 2015 to calculate the effect of Urban Heat Island (UHI) along with the NPP-VRRIS night-time remote sensing data to analyze the result for a better understanding of the center of the built-up area. To further support the evidence, the correlation between land surface temperatures and the normalized difference vegetation index (NDVI) was calculated using the Red band 4 and Near-infrared band 5 of the Landsat 8 data. Mono-window algorithm was applied to retrieve the land surface temperature (LST) distribution from the Landsat 8 data using Band 10 and 11 accordingly to convert the top-of-atmosphere radiance (TOA) and to convert the satellite brightness temperature. Along with Landsat 8 data, NPP-VIIRS night-light data is preprocessed to get the research area data. The analysis between Landsat 8 data and NPP night-light data was taken to compare the output center of the Built-up area of Zhengzhou city.

Keywords: built-up area, land surface temperature, mono-window algorithm, NDVI, remote sensing, threshold method, Zhengzhou

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Authors: Christian Kapuku, Seung-Young Kho

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An accurate representation of the transportation system serving the region is one of the important aspects of transportation modeling. Such representation often requires developing an abstract model of the system elements, which also requires important amount of data, surveys and time. However, in some cases such as in developing countries, data deficiencies, time and budget constraints do not always allow such accurate representation, leaving opportunities to assumptions that may negatively affect the quality of the analysis. With the emergence of Internet open source data especially in the mapping technologies as well as the advances in Geography Information System, opportunities to tackle these issues have raised. Therefore, the objective of this paper is to demonstrate such application through a practical case of the development of the transportation network for the city of Kinshasa. The GIS geo-referencing was used to construct the digitized map of Transportation Analysis Zones using available scanned images. Centroids were then dynamically placed at the center of activities using an activities density map. Next, the road network with its characteristics was built using OpenStreet data and other official road inventory data by intersecting their layers and cleaning up unnecessary links such as residential streets. The accuracy of the final network was then checked, comparing it with satellite images from Google and Bing. For the validation, the final network was exported into Emme3 to check for potential network coding issues. Results show a high accuracy between the built network and satellite images, which can mostly be attributed to the use of open source data.

Keywords: geographic information system (GIS), network construction, transportation database, open source data

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Authors: Deniz Yurtoğlu

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Aerosols directly affect the radiative balance of the earth by absorbing and/or scattering the sun rays reaching the atmosphere and indirectly affect the balance by acting as a nucleus in cloud formation. The composition, physical, and chemical properties of aerosols vary depending on their sources and the time spent in the atmosphere. The Eastern Mediterranean Basin has a high aerosol load that is formed from different sources; such as anthropogenic activities, desert dust outbreaks, and the spray of sea salt; and the area is subjected to atmospheric transport from other locations on the earth. This region, which includes the deserts of Africa, the Middle East, and the Mediterranean sea, is one of the most affected areas by climate change due to its location and the chemistry of the atmosphere. This study aims to investigate the spatiotemporal deviation of aerosol load in the Eastern Mediterranean Basin between the years 2018-2022 with the help of a new pioneer satellite of ESA (European Space Agency), Sentinel-5P. The TROPOMI (The TROPOspheric Monitoring Instrument) traveling on this low-Earth orbiting satellite is a UV (Ultraviolet)-sensing spectrometer with a resolution of 5.5 km x 3.5 km, which can make measurements even in a cloud-covered atmosphere. By using Absorbing Aerosol Index data produced by this spectrometer and special scripts written in Python language that transforms this data into images, it was seen that the majority of the aerosol load in the Eastern Mediterranean Basin is sourced from desert dust and anthropogenic activities. After retrieving the daily data, which was separated from the NaN values, seasonal analyses match with the normal aerosol variations expected, which are high in warm seasons and lower in cold seasons. Monthly analyses showed that in four years, there was an increase in the amount of Absorbing Aerosol Index in spring and winter by 92.27% (2019-2021) and 39.81% (2019-2022), respectively. On the other hand, in the summer and autumn seasons, a decrease has been observed by 20.99% (2018-2021) and 0.94% (2018-2021), respectively. The overall variation of the mean absorbing aerosol index from TROPOMI between April 2018 to April 2022 reflects a decrease of 115.87% by annual mean from 0.228 to -0.036. However, when the data is analyzed by the annual mean values of the years which have the data from January to December, meaning from 2019 to 2021, there was an increase of 57.82% increase (0.108-0.171). This result can be interpreted as the effect of climate change on the aerosol load and also, more specifically, the effect of forest fires that happened in the summer months of 2021.

Keywords: aerosols, eastern mediterranean basin, sentinel-5p, tropomi, aerosol index, remote sensing

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Authors: Berhanu Terfa, Nengcheng C.

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The study deals with the analysis of urban expansion and land transformation of Hawass City using remote sensing data and landscape metrics during last three decades (1987–2017). Remote sensing data from Various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used to examine the urban expansion, growth types, and spatial isolation within the urban landscape to develop an understanding the trends of built-up growth in Hawassa City, Ethiopia. Landscape metrics and built-up density were employed to analyze the pattern, process and overall growth status. The area under investigation was divided into concentric circles with a consecutive circle of 1 km incremental radius from the central pixel (Central Business District) for analysis. The result exhibited that the built-up area had increased by 541.32% between 1987 and 2017and an extension growth types (more than 67 %) was observed. The major growth took place in north-west direction followed by north direction in haphazard manner during 1987–1995 period, whereas predominant built-up development was observed in south and southwest direction during 1995–2017 period. Land scape metrics result revealed that the of urban patches density, total edge and edge density increased, while mean nearest neighbors’ distance decreased showing the tendency of sprawl.

Keywords: landscape metrics, spatial patterns, remote sensing, multi-temporal, urban sprawl

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Authors: Keiko Shimazu, Yasuhiro Maida, Tetsuya Sugata, Daisuke Tamakoshi, Kenji Makabe, Haruki Suzuki

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In this paper, we report how to acquire serious victims’ locations in the Acute Stage of Large-scale Disasters, in an Emergency Information Network System designed by us. The background of our concept is based on the Great East Japan Earthquake occurred on March 11^th, 2011. Through many experiences of national crises caused by earthquakes and tsunamis, we have established advanced communication systems and advanced disaster medical response systems. However, Japan was devastated by huge tsunamis swept a vast area of Tohoku causing a complete breakdown of all the infrastructures including telecommunications. Therefore, we noticed that we need interdisciplinary collaboration between science of disaster medicine, regional administrative sociology, satellite communication technology and systems engineering experts. Communication of emergency information was limited causing a serious delay in the initial rescue and medical operation. For the emergency rescue and medical operations, the most important thing is to identify the number of casualties, their locations and status and to dispatch doctors and rescue workers from multiple organizations. In the case of the Tohoku earthquake, the dispatching mechanism and/or decision support system did not exist to allocate the appropriate number of doctors and locate disaster victims. Even though the doctors and rescue workers from multiple government organizations have their own dedicated communication system, the systems are not interoperable.

Keywords: crisis management, disaster mitigation, messing, MGRS, military grid reference system, satellite communication system

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Authors: K. Parandhama Gowd

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Space technologies have changed the way we live in the present day society and manage many aspects of our daily affairs through Remote sensing, Navigation & Communications. Further, defense and military usage of spacecraft has increased tremendously along with civilian purposes. The number of satellites deployed in space in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and the Geostationary Orbit (GEO) has gone up. The dependency on remote sensing and operational capabilities are most invariably to be exploited more and more in future. Every country is acquiring spacecraft in one way or other for their daily needs, and spacecraft numbers are likely to increase significantly and create spacecraft traffic problems. The aim of this research paper is to propose innovative design concepts for adaptive spacecraft. The main idea here is to improve existing design methods of spacecraft design and development to further improve upon design considerations for futuristic adaptive spacecraft with inbuilt features for automatic adaptability and self-protection. In other words, the innovative design considerations proposed here are to have future spacecraft with self-organizing capabilities for orbital control and protection from anti-satellite weapons (ASAT). Here, an attempt is made to propose design and develop futuristic spacecraft for 2030 and beyond due to tremendous advancements in VVLSI, miniaturization, and nano antenna array technologies, including nano technologies are expected.

Keywords: satellites, low earth orbit (LEO), medium earth orbit (MEO), geostationary earth orbit (GEO), self-organizing control system, anti-satellite weapons (ASAT), orbital control, radar warning receiver, missile warning receiver, laser warning receiver, attitude and orbit control systems (AOCS), command and data handling (CDH)

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Climatic factors are the subject of considerable research, both methodologically and instrumentally. Under the effect of climate change, the approach to climate parameters with precision remains one of the main objectives of the scientific community. This is from the perspective of assessing climate change and its repercussions on humans and the environment. However, many regions of the world suffer from a severe lack of reliable instruments that can make up for this deficit. Alternatively, the use of empirical methods becomes the only way to assess certain parameters that can act as climate indicators. Several scientific methods are used for the evaluation of evapotranspiration which leads to its evaluation either directly at the level of the climatic stations or by empirical methods. All these methods make a point approach and, in no case, allow the spatial variation of this parameter. We, therefore, propose in this paper the use of three sources of information (network of weather stations of Meteo France, World Databases, and Moodis satellite images) to evaluate spatial evapotranspiration (ETP) using the Turc method. This first step will reflect the degree of relevance of the indirect (satellite) methods and their generalization to sites without stations. The spatial variation representation of this parameter using the geographical information system (GIS) accounts for the heterogeneity of the behaviour of this parameter. This heterogeneity is due to the influence of site morphological factors and will make it possible to appreciate the role of certain topographic and hydrological parameters. A phase of predicting the evolution over the medium and long term of evapotranspiration under the effect of climate change by the application of the Intergovernmental Panel on Climate Change (IPCC) scenarios gives a realistic overview as to the contribution of aquatic systems to the scale of the region.

Keywords: climate change, ETP, MODIS, GIEC scenarios

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Authors: Asmamaw Yehun

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The name “TANA” is one of International Geodetic Service (IGS) Global Positioning System (GPS) station which is found in Bahir Dar University in Institute of Land Administration. The station name taken from one of big Lakes in Africa ,Lake Tana. The Institute of Land Administration (ILA) is part of Bahir Dar University, located in the capital of the Amhara National Regional State, Bahir Dar. The institute is the first of its kind in East Africa. The station is installed by cooperation of ILA and Sweden International Development Agency (SIDA) fund support. The Continues Operating Reference Station (CORS) is a network of stations that provide global satellite system navigation data to help three dimensional positioning, meteorology, space, weather, and geophysical applications throughout the globe. TANA station was as CORS since 2013 and sites are independently owned and operated by governments, research and education facilities and others. The data collected by the reference station is downloadable through Internet for post processing purpose by interested parties who carry out GNSS measurements and want to achieve a higher accuracy. We made a first observation on TANA, monitor stations on May 29th 2013. We used Leica 1200 receivers and AX1202GG antennas and made observations from 11:30 until 15:20 for about 3h 50minutes. Processing of data was done in an automatic post processing service CSRS-PPP by Natural Resources Canada (NRCan) . Post processing was done June 27th 2013 so precise ephemeris was used 30 days after observation. We found Latitude (ITRF08): 11 34 08.6573 (dms) / 0.008 (m), Longitude (ITRF08): 37 19 44.7811 (dms) / 0.018 (m) and Ellipsoidal Height (ITRF08): 1850.958 (m) / 0.037 (m). We were compared this result with GAMIT/GLOBK processed data and it was very closed and accurate. TANA station is one of the second IGS station for Ethiopia since 2015 up to now. It provides data for any civilian users, researchers, governmental and nongovernmental users. TANA station is installed with very advanced choke ring antenna and GR25 Leica receiver and also the site is very good for satellite accessibility. In order to test hydrostatic and wet zenith delay for positional data quality, we used GAMIT/GLOBK and we found that TANA station is the most accurate IGS station in East Africa. Due to lower tropospheric zenith and ionospheric delay, TANA and ADIS IGS stations has 2 and 1.9 meters 3D positional accuracy respectively.

Keywords: atmosphere, GNSS, neutral atmosphere, precipitable water vapour

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Authors: Tahir Ali Akbar, Hirra Jabbar

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Land cover change analysis plays a significant role in understanding the trends of urban sprawl and land use transformation due to anthropogenic activities. In this study, the spatio-temporal dynamics of major land covers were analyzed in the last twenty years (1988-2016) for District Lahore located in the Punjab Province of Pakistan. The Landsat satellite imageries were downloaded from USGS Global Visualization Viewer of Earth Resources Observation and Science Center located in Sioux Falls, South Dakota USA. The imageries included: (i) Landsat TM-5 for 1988 and 2001; and (ii) Landsat-8 OLI for 2016. The raw digital numbers of Landsat-5 images were converted into spectral radiance and then planetary reflectance. The digital numbers of Landsat-8 image were directly converted into planetary reflectance. The normalized difference vegetation index (NDVI) was used to classify the processed images into six major classes of water, buit-up, barren land, shrub and grassland, sparse vegetation and dense vegetation. The NDVI output results were improved by visual interpretation using high-resolution satellite imageries. The results indicated that the built-up areas were increased to 21% in 2016 from 10% in 1988. The decrease in % areas was found in case of water, barren land and shrub & grassland. There were improvements in percentage of areas for the vegetation. The increasing trend of urban sprawl for Lahore requires implementation of GIS based spatial planning, monitoring and management system for its sustainable development.

Keywords: land cover changes, NDVI, remote sensing, urban sprawl

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Authors: Walelgn Dilnesa Cherie, Fasikaw Atanaw Zimale, Bekalu W. Asres

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The most catastrophic condition for agricultural production is a drought event, which is also one of the most hydro-metrological-related hazards. According to the combined susceptibility of plants to meteorological and hydrological conditions, agricultural drought is defined as the magnitude, severity, and duration of a drought that affects crop production. The accurate and timely assessment of agricultural drought can lead to the development of risk management strategies, appropriate proactive mechanisms for the protection of farmers, and the improvement of food security. The evaluation of agricultural drought in the East Gojjam zone was the primary subject of this study. To identify the agricultural drought, soil moisture anomalies, soil moisture deficit indices, and Normalized Difference Vegetation Indices (NDVI) are used. The measured welting point, field capacity, and soil moisture were utilized to validate the soil water deficit indices computed from the satellite data. The soil moisture and soil water deficit indices in 2013 in all woredas were minimum; this makes vegetation stress also in all woredas. The soil moisture content decreased in 2013/2014/2019, and 2021 in Dejen, 2014, and 2019 in Awobel Woreda. The max/ min values of NDVI in 2013 are minimum; it dominantly shows vegetation stress and an observed agricultural drought that happened in all woredas. The validation process of satellite and in-situ soil moisture and soil water deficit indices shows a good agreement with a value of R²=0.87 and 0.56, respectively. The study area becomes drought detected region, so government officials, policymakers, and environmentalists pay attention to the protection of drought effects.

Keywords: NDVI, agricultural drought, SWDI, soil moisture

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Authors: Kamal Ameis

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This study aims to further improve our understanding of the underlying mechanism of local injury that occurs after manual acupuncture needle manipulation, and that initiates the muscle regeneration process, which is essential for muscle maintenance and adaptation. Skeletal muscle is maintained by resident stem cells called muscle satellite cells. These cells are normally in quiescent state, but following muscle injury, they re-enter the cell cycle and execute a myogenic program resulting in muscle fiber regeneration. Our previous work in young rats demonstrated that acupuncture treatment induced injury that activated resident satellite (stem) cells, which leads to muscle regeneration. Skeletal muscle regeneration is an adaptive response to injury that requires a tightly orchestrated event between signaling pathways activated by growth factor and intrinsic regulatory program controlled by myogenic transcription factor. We identified several gene expressions uniquely important for muscle regeneration in response to acupuncture treatment at different time course using different biological techniques, including Immunocytochemistry, western blotting, and Real Time PCR. This study uses a novel but non-invasive model of injury induced by manual acupuncture to further our current understanding of regenerative mechanism of muscle stem cells. From a clinical perspective, this model of injury induced by manual acupuncture may be easily translatable into a clinical tool that can be used as an alternative to physical exercise for patients challenged by bed rest or forced inactivity. Finally, the knowledge gained from this research could be useful for studies of the local effects of various modalities of induced injury, such as the traditional method of healing by cupping (hijamah), which may enhanced muscle stem cells and muscle fiber regeneration.

Keywords: acupuncture, injury, regeneration, muscle stem cells

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Authors: Su Nandar Tin, Wutjanun Muttitanon

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The availability of free global and historical satellite imagery provides a valuable opportunity for mapping and monitoring the year by year for the built-up area, constantly and effectively. Land distribution guidelines and identification of changes are important in preparing and reviewing changes in the ground overview data. This study utilizes Landsat images for thirty years of information to acquire significant, and land spread data that are extremely valuable for urban arranging. This paper is mainly introducing to focus the basic of extracting built-up area for the city development area from the satellite images of LANDSAT 5,7,8 and Sentinel 2A from USGS in every five years. The purpose analyses the changing of the urban built-up area according to the year by year and to get the accuracy of mapping built-up and bare land areas in studying the trend of urban built-up changes the periods from 1990 to 2020. The GIS tools such as raster calculator and built-up area modelling are using in this study and then calculating the indices, which include enhanced built-up and bareness index (EBBI), Normalized difference Built-up index (NDBI), Urban index (UI), Built-up index (BUI) and Normalized difference bareness index (NDBAI) are used to get the high accuracy urban built-up area. Therefore, this study will point out a variable approach to automatically mapping typical enhanced built-up and bare land changes (EBBI) with simple indices and according to the outputs of indexes. Therefore, the percentage of the outputs of enhanced built-up and bareness index (EBBI) of the sentinel-2A can be realized with 48.4% of accuracy than the other index of Landsat images which are 15.6% in 1990 where there is increasing urban expansion area from 43.6% in 1990 to 92.5% in 2020 on the study area for last thirty years.

Keywords: built-up area, EBBI, NDBI, NDBAI, urban index

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Authors: Mansa Radhakrishnan, Anwar Ali, Muhammad Rizwan Mughal

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Many universities around the world are working on modular and low budget architecture of small spacecraft to reduce the development cost of the overall system. This paper focuses on the design of a modular solar power harvesting system for a hexagonal-shaped small satellite. The designed solar power harvesting systems are composed of solar panels and power converter subsystems. The solar panel is composed of solar cells mounted on the external face of the printed circuit board (PCB), while the electronic components of power conversion are mounted on the interior side of the same PCB. The solar panel with dimensions 16.5cm × 99cm is composed of 36 solar cells (each solar cell is 4cm × 7cm) divided into four parallel banks where each bank consists of 9 solar cells. The output voltage of a single solar cell is 2.14V, and the combined output voltage of 9 series connected solar cells is around 19.3V. The output voltage of the solar panel is boosted to the satellite power distribution bus voltage level (28V) by a boost converter working on a constant voltage maximum power point tracking (MPPT) technique. The solar panel module is an eight-layer PCB having embedded coil in 4 internal layers. This coil is used to control the attitude of the spacecraft, which consumes power to generate a magnetic field and rotate the spacecraft. As power converter and distribution subsystem components are mounted on the PCB internal layer, therefore it is mandatory to do thermal analysis in order to ensure that the overall module temperature is within thermal safety limits. The main focus of the overall design is on compactness, miniaturization, and efficiency enhancement.

Keywords: small satellites, power subsystem, efficiency, MPPT

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: Dana R. Thomson, Catherine Linard, Sabine Vanhuysse, Jessica E. Steele, Michal Shimoni, Jose Siri, Waleska Caiaffa, Megumi Rosenberg, Eleonore Wolff, Tais Grippa, Stefanos Georganos, Helen Elsey

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The Sustainable Development Goals (SDGs) and Urban Health Equity Assessment and Response Tool (Urban HEART) identify dozens of key indicators to help local decision-makers prioritize and track inequalities in health outcomes. However, presentations and discussions at the International Conference on Urban Health (ICUH) 2017 suggested that additional indicators are needed to make decisions and policies. A local decision-maker may realize that malaria or road accidents are a top priority. However, s/he needs additional health determinant indicators, for example about standing water or traffic, to address the priority and reduce inequalities. Health determinants reflect the physical and social environments that influence health outcomes often at community- and societal-levels and include such indicators as access to quality health facilities, access to safe parks, traffic density, location of slum areas, air pollution, social exclusion, and social networks. Indicator identification and disaggregation are necessarily constrained by available datasets – typically collected about households and individuals in surveys, censuses, and administrative records. Continued advancements in earth observation, data storage, computing and mobile technologies mean that new sources of health determinants indicators derived from 'big data' are becoming available at fine geographic scale. Big data includes high-resolution satellite imagery and aggregated, anonymized mobile phone data. While big data are themselves not representative of the population (e.g., satellite images depict the physical environment), they can provide information about population density, wealth, mobility, and social environments with tremendous detail and accuracy when combined with population-representative survey, census, administrative and health system data. The aim of this paper is to (1) flag to data scientists important indicators needed by health decision-makers at the city and sub-city scale - ideally free and publicly available, and (2) summarize for local decision-makers new datasets that can be generated from big data, with layperson descriptions of difficulties in generating them. We include SDGs and Urban HEART indicators, as well as indicators mentioned by decision-makers attending ICUH 2017.

Keywords: health determinant, health outcome, mobile phone, remote sensing, satellite imagery, SDG, urban HEART

Procedia PDF Downloads 182

Authors: Ismail Elkhrachy

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Determination of land use changing is an important component of regional planning for applications ranging from urban fringe change detection to monitoring change detection of land use. This data are very useful for natural resources management.On the other hand, the technologies and methods of change detection also have evolved dramatically during past 20 years. So it has been well recognized that the change detection had become the best methods for researching dynamic change of land use by multi-temporal remotely-sensed data. The objective of this paper is to assess, evaluate and monitor land use change surrounding the area of Najran city, Kingdom of Saudi Arabia (KSA) using Landsat images (June 23, 2009) and ETM+ image(June. 21, 2014). The post-classification change detection technique was applied. At last,two-time subset images of Najran city are compared on a pixel-by-pixel basis using the post-classification comparison method and the from-to change matrix is produced, the land use change information obtained.Three classes were obtained, urban, bare land and agricultural land from unsupervised classification method by using Erdas Imagine and ArcGIS software. Accuracy assessment of classification has been performed before calculating change detection for study area. The obtained accuracy is between 61% to 87% percent for all the classes. Change detection analysis shows that rapid growth in urban area has been increased by 73.2%, the agricultural area has been decreased by 10.5 % and barren area reduced by 7% between 2009 and 2014. The quantitative study indicated that the area of urban class has unchanged by 58.2 km〗^2, gained 70.3 〖km〗^2 and lost 16 〖km〗^2. For bare land class 586.4〖km〗^2 has unchanged, 53.2〖km〗^2 has gained and 101.5〖km〗^2 has lost. While agriculture area class, 20.2〖km〗^2 has unchanged, 31.2〖km〗^2 has gained and 37.2〖km〗^2 has lost.

Keywords: land use, remote sensing, change detection, satellite images, image classification

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Authors: Akintunde Alo

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The incessant encroachments into the forest ecosystem by the farmers and local contractors constitute a major threat to the conservation of genetic resources and biodiversity in Nigeria. To propose a viable monitoring system, this study employed Geographic Information System (GIS) technology to assess the changes that occurred for a period of five years (between 2011 and 2016) in Ikere forest reserve. Landsat imagery of the forest reserve was obtained. For the purpose of geo-referencing the acquired satellite imagery, ground-truth coordinates of some benchmark places within the forest reserve was relied on. Supervised classification algorithm, image processing, vectorization and map production were realized using ArcGIS. Various land use systems within the forest ecosystem were digitized into polygons of different types and colours for 2011 and 2016, roads were represented with lines of different thickness and colours. Of the six land-use delineated, the grassland increased from 26.50 % in 2011 to 45.53% in 2016 of the total land area with a percentage change of 71.81 %. Plantations of Gmelina arborea and Tectona grandis on the other hand reduced from 62.16 % in 2011 to 27.41% in 2016. The farmland and degraded land recorded percentage change of about 176.80 % and 8.70 % respectively from 2011 to 2016. Overall, the rate of deforestation in the study area is on the increase and becoming severe. About 72.59% of the total land area has been converted to non-forestry uses while the remnant 27.41% is occupied by plantations of Gmelina arborea and Tectona grandis. Interestingly, over 55 % of the plantation area in 2011 has changed to grassland, or converted to farmland and degraded land in 2016. The rate of change over time was about 9.79 % annually. Based on the results, rapid actions to prevail on the encroachers to stop deforestation and encouraged re-afforestation in the study area are recommended.

Keywords: land use change, forest reserve, satellite imagery, geographical information system

Procedia PDF Downloads 332