Search results for: remote areas

Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, Rebecca K. Rossi, Yanmin Yuan, Xianpei Li

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The fiscal growth of any country hinges on the prudent administration of water resources. The river Yamuna and Ganga are measured as the life line of India as it affords the needs for life to endure. Earth observation over remote sensing images permits the precise description and identification of ingredients on the superficial from space and airborne platforms. Multiple and heterogeneous image sources are accessible for the same geographical section; multispectral, hyperspectral, radar, multitemporal, and multiangular images. In this paper, a taxonomical learning of the fluvial geomorphological features of river Yamuna and Ganga over doon valley using color fusion of multispectral remote sensing images was performed. Experimental results exhibited that the segmentation based colorization technique stranded on pattern recognition, and color mapping fashioned more colorful and truthful colorized images for geomorphological feature extraction.

Keywords: color fusion, geomorphology, fluvial processes, multispectral images, pattern recognition

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Authors: Safaa M. Hassan; Safwat S. Gabr, Mohamed F. Sadek

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This study is proposed for the lithological and iron oxides detection in the old mine areas of El-Bahariya Depression, Western Desert, using ASTER and Landsat-8 remote sensing data. Four old iron ore occurrences, namely; El-Gedida, El-Haraa, Ghurabi, and Nasir mine areas found in the El-Bahariya area. This study aims to find new high potential areas for iron mineralization around El-Baharyia depression. Image processing methods such as principle component analysis (PCA) and band ratios (b4/b5, b5/b6, b6/b7, and 4/2, 6/7, band 6) images were used for lithological identification/mapping that includes the iron content in the investigated area. ASTER and Landsat-8 visible and short-wave infrared data found to help mapping the ferruginous sandstones, iron oxides as well as the clay minerals in and around the old mines area of El-Bahariya depression. Landsat-8 band ratio and the principle component of this study showed well distribution of the lithological units, especially ferruginous sandstones and iron zones (hematite and limonite) along with detection of probable high potential areas for iron mineralization which can be used in the future and proved the ability of Landsat-8 and ASTER data in mapping these features. Minimum Noise Fraction (MNF), Mixture Tuned Matched Filtering (MTMF), pixel purity index methods as well as Spectral Ange Mapper classifier algorithm have been successfully discriminated the hematite and limonite content within the iron zones in the study area. Various ASTER image spectra and ASD field spectra of hematite and limonite and the surrounding rocks are compared and found to be consistent in terms of the presence of absorption features at range from 1.95 to 2.3 μm for hematite and limonite. Pixel purity index algorithm and two sub-pixel spectral methods, namely Mixture Tuned Matched Filtering (MTMF) and matched filtering (MF) methods, are applied to ASTER bands to delineate iron oxides (hematite and limonite) rich zones within the rock units. The results are validated in the field by comparing image spectra of spectrally anomalous zone with the USGS resampled laboratory spectra of hematite and limonite samples using ASD measurements. A number of iron oxides rich zones in addition to the main surface exposures of the El-Gadidah Mine, are confirmed in the field. The proposed method is a successful application of spectral mapping of iron oxides deposits in the exposed rock units (i.e., ferruginous sandstone) and present approach of both ASTER and ASD hyperspectral data processing can be used to delineate iron-rich zones occurring within similar geological provinces in any parts of the world.

Keywords: Landsat-8, ASTER, lithological mapping, iron exploration, western desert

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Authors: Rabia Shabbir, Sheikh Saeed Ahmad, Amna Butt

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Rapid land use changes have taken place in Islamabad, the capital city of Pakistan, over the past decades due to accelerated urbanization and industrialization. In this study, land use changes in the metropolitan area of Islamabad was observed by the combined use of GIS and satellite remote sensing for a time period of 15 years. High-resolution Google Earth images were downloaded from 2000-2015, and object-based classification method was used for accurate classification using eCognition software. The information regarding urban settlements, industrial area, barren land, agricultural area, vegetation, water, and transportation infrastructure was extracted. The results showed that the city experienced a spatial expansion, rapid urban growth, land use change and expanding transportation infrastructure. The study concluded the integration of GIS and remote sensing as an effective approach for analyzing the spatial pattern of urban growth and land use change.

Keywords: land use change, urban growth, Islamabad, object-based classification, Google Earth, remote sensing, GIS

Procedia PDF Downloads 127

Authors: Danika Tynes

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Telehealth is a promising advancement in health care, though there are certain conditions under which telehealth has a greater chance of success. This research sought to further the understanding of what conditions compel the success of telehealth adoption at the systems level applying Diffusion of Innovations (DoI) theory (Rogers, 1962). System-level indicators were selected to represent four components of DoI theory (relative advantage, compatibility, complexity, and observability) and regressed on 5 types of telehealth (teleradiology, teledermatology, telepathology, telepsychology, and remote monitoring) using multiple logistic regression. The analyses supported relative advantage and compatibility as the strongest influencers of telehealth adoption, remote monitoring in particular. These findings help to quantitatively clarify the factors influencing the adoption of innovation and advance the ability to make recommendations on the viability of state telehealth adoption. In addition, results indicate when DoI theory is most applicable to the understanding of telehealth diffusion. Ultimately, this research may contribute to more focused allocation of scarce health care resources through consideration of existing state conditions available foster innovation.

Keywords: adoption, diffusion of innovation theory, remote monitoring, system-level indicators

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Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Catalina Albornoz, Giacomo Barbieri

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Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

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Authors: J. L. Oliver, T. Agryzkov, L. Tortosa, J. F. Vicent, J. Santacruz

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This paper aims to demonstrate how a system of indicators can be used in order to evaluate some heritage areas which can be understood as minor ones. We mean by that those urban areas with high heritage interest from an academical point of view, but never properly valued. The reasons for this situation may be diverse, either they are not old enough, or they may show the modest architecture, the fact is these areas have not been considered deserving of protection, as the historical ones. As a result of this reality, they usually show now a very degraded urban space, which in addition contribute to accelerate a process of deterioration. Using a technic well known in urban design, we propose here a system of indicators for patrimonial purposes, as a tool to identify and quantify the heritage value of these kinds of areas. As a case study, we apply this system in some part of the City of Quito (El Ecuador).

Keywords: heritage cities, indicators, spatial analysis, historic sites

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Authors: Rekioua D., Mohammedi A., Rekioua T., Mehleb Z.

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Photovoltaic water pumping systems is considered as one of the most promising areas in photovoltaic applications, the economy and reliability of solar electric power made it an excellent choice for remote water pumping. Two conventional techniques are currently in use; the first is the directly coupled technique and the second is the battery buffered photovoltaic pumping system. In this paper, we present different performances of a three operation modes of photovoltaic pumping system. The aim of this work is to determine the effect of different parameters influencing the photovoltaic pumping system performances, such as pumping head, System configuration and climatic conditions. The obtained results are presented and discussed.

Keywords: batteries charge mode, photovoltaic pumping system, pumping head, submersible pump

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Authors: Shuen-Tai Wang, Ying-Chuan Chen, Hsi-Ya Chang

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Cloud computing is a paradigm of computing that shifts the way computing has been done in the past. The users can use cloud resources such as application software or storage space from the cloud without needing to own them. This paper is focused on solutions that are anticipated to introduce IaaS idea to build cloud base services and enable the individual remote user's applications in cloud environments, which appear as if they are running on the end user's local computer. The available features of application delivery solution have been developed based on our previous research on the virtualization technology to offer applications independent of location so that the users can work online, offline, anywhere, with appropriate device and at any time. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud service. Users no longer need to burden the system managers and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote application virtualization service represents the next significant step to the mobile workplace, and it lets users access their applications remotely through cloud services anywhere. This is also made possible by the low administrative costs as well as relatively inexpensive end-user terminals and reduced energy expenses.

Keywords: cloud computing, IaaS, virtualization, application delivery

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Authors: Jamie Wong, Daisy Sang, Chang-Shyh Peng

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Geofence is a virtual fence defined by a preset physical radius around a target location. Geofencing App provides location-based services which define the actionable operations upon the crossing of a geofence. Geofencing requires continual location tracking, which can consume noticeable amount of battery power. Additionally, location updates need to be frequent and accurate or order so that actions can be triggered within an expected time window after the mobile user navigate through the geofence. In this paper, we build an Android mobile geofencing Application to remotely and autonomously control a power switch.

Keywords: location based service, geofence, autonomous, remote switch

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Authors: Arturo S. Daag, Ira Karrel D. L. San Jose, Mike Gabriel G. Pedrosa, Ken Adrian C. Villarias, Rayfred P. Ingeniero, Cyrah Gale H. Rocamora, Margarita P. Dizon, Roland Joseph B. De Leon, Teresito C. Bacolcol

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The province of Leyte consists of various geomorphological landforms: These are: a) landforms of tectonic origin transect large part of the volcanic centers in upper Ormoc area; b) landforms of volcanic origin, several inactive volcanic centers located in Upper Ormoc are transected by Philippine Fault; c) landforms of volcano-denudational and denudational slopes dominates the area where most of the earthquake-induced landslide occurred; and d) Colluvium and alluvial deposits dominate the foot slope of Ormoc and Jaro-Pastrana plain. Earthquake ground acceleration and geotechnical properties of various landforms are crucial for landslide studies. To generate the landslide critical acceleration model of sliding block, various data were considered, these are: geotechnical data (i.e., soil and rock strength parameters), slope, topographic wetness index (TWI), landslide inventory, soil map, geologic maps for the calculation of the factor of safety. Horizontal-to-vertical spectral ratio (HVSR) surveying methods, refraction microtremor (ReMi), and three-component microtremor (3CMT) were conducted to measure site period and surface wave velocity as well as to create a soil thickness model. Critical acceleration model of various geomorphological unit using Remote Sensing, field geotechnical, geophysical, and geospatial data collected from the areas affected by the 06 July 2017 M6.5 Leyte earthquake. Spatial analysis of earthquake-induced landslide from the 06 July 2017, were then performed to assess the relationship between the calculated critical acceleration and peak ground acceleration. The observed trends proved helpful in establishing the role of critical acceleration as a determining factor in the distribution of co-seismic landslides.

Keywords: earthquake-induced landslide, remote sensing, geomorphology, seismic response

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Authors: Ntungamili Kenosi, Moatlhodi W. Letshwenyo

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Negative environmental impacts due to construction of large projects such as dams have become an important aspect of land degradation. This paper will review the previous literature on the previous researches or study in the same area of study in the other parts of the world. After dam has been constructed, the actual environmental impacts are investigated and compared to the predicted results of the carried out Environmental Impact Assessment. GIS and Remote Sensing, play an important role in generating automated spatial data sets and in establishing spatial relationships. Results from other sources shows that the normalized vegetation index (NDVI) analysis was used to detect the spatial and temporal change of vegetation biomass in the study area. The result indicated that the natural vegetation biomass is declining. This is mainly due to the expansion of agricultural land and escalating human made structures in the area. Urgent environmental conservation is necessary when adjoining projects site. Less study on the evaluation of EIA on dam has been conducted in Botswana hence there is a need for the same study to be conducted and then it will be easy to be compared to other studies around the world.

Keywords: Botswana, dam, environmental impact assessment, GIS, normalized vegetation index (NDVI), remote sensing

Procedia PDF Downloads 384

Authors: M. Humayun Kabir, Mahamuda Afroze, K. Maudood Elahi

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Since the late 1900s, unplanned and rapid urbanization processes have drastically altered the land, reduced water bodies, and decreased vegetation cover in the capital city of Bangladesh, Dhaka. The capitalist modes of urbanization results in the encroachment of the surface water bodies in this city. The main goal of this study is to investigate the change detection of water bodies in Dhaka city, analyzing spatial distribution of water bodies and calculating the changing rate of it. This effort aims to influence public policy for environmental justice initiatives around protecting water bodies for ensuring proper function of the urban ecosystem. This study accomplishes research goal by compiling satellite imageries into GIS software to understand the changes of water bodies in Dhaka city. The work focuses on the late 20th century to early 21st century to analyze this city before and after major infrastructural changes occurred in unplanned manner. The land use of the study area has been classified into four categories, and the areas of the different land use have been calculated using MS Excel and SPSS. The results reveal that the urbanization expanded from central to northern part and major encroachment occurred at the western and eastern part of the city. It has also been found that, in 1988, the total area of water bodies was 8935.38 hectares, and it gradually decreased, and in 1998, 2008, 2017, the total areas of water bodies reached 6065.73, 4853.32, 2077.56 hectares, respectively. Rapid population growth, unplanned urbanization, and industrialization have generated pressure to change the land use pattern in Dhaka city. These expansion processes are engulfing wetland, water bodies, and vegetation cover without considering environmental impact. In order to regain the wetland and surface water bodies, the concern authorities must implement laws and act as a legal instrument in this regard and take action against the violators of it. This research is the synthesis of time series data that provides a complete picture of the water body’s status of Dhaka city that might help to make plans and policies for water body conservation.

Keywords: ecosystem, GIS, industrialization, land use, remote sensing, urbanization

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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: ȘercăIanu Mihai, Aldea Mihaela, Iacoboaea Cristina, Luca Oana, Nenciu Ioana

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The rise and mitigation of unauthorized illegal waste dumps are a significant global issue within waste management ecosystems, impacting disadvantaged communities. Globally, including in Romania, many individuals live in houses without legal recognition, lacking ownership or construction permits, in areas known as "informal settlements". An increasing number of regions and cities in Romania are struggling to manage their illegal waste dumps, especially in the context of increasing poverty and lack of regulation related to informal settlements. One such informal settlement is located at the end of Bistra Street in Câlnic, within the Reșița Municipality of Caras Severin County. The article presents a case study that focuses on employing remote sensing techniques and spatial data to monitor and map illegal waste practices, with subsequent integration into a geographic information system tailored for the Reșița community. In addition, the paper outlines the steps involved in devising strategies aimed at enhancing waste management practices in disadvantaged areas, aligning with the shift toward a circular economy. Results presented in the paper contain a spatial mapping and visualization methodology calibrated with in situ data collection applicable for identifying illegal landfills. The emergence and neutralization of illegal dumps pose a challenge in the field of waste management. These approaches, which prove effective where conventional solutions have failed, need to be replicated and adopted more wisely.

Keywords: waste dumps, waste management, monitoring, GIS, informal settlements

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Authors: Chih-Yuan Weng

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It may be a common sense that indigenous people in Taiwan, like their counterparts in the rest of the world, are generally more disadvantaged than other citizens in terms of all sorts of socioeconomic indicators. However, it has also been well-documented in the literature that there is always significant variation in the level of indigenous poverty, both among individuals and among tribes, which can be obscured by a national survey that does not take into account the heterogeneity, such as tribal locations, among indigenous people. Thus, using a Truku tribe in a remote county of Taiwan (i.e., Hualien County) as an example, this study aims at investigating whether and how the socioeconomic livelihood of the indigenous residents would be damaged by the remoteness of their tribal community.

Keywords: indigenous people, tribal community, poverty, socioeconomic livelihood, remoteness

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Authors: Santosh Kumar Biswal, Ramakar Jha

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Soil erosion is a slow and continuous process and one of the prominent problems across the world leading to many serious problems like loss of soil fertility, loss of soil structure, poor internal drainage, sedimentation deposits etc. In this paper remote sensing and GIS based methods have been applied for the determination of soil erosion and sediment yield. Tel River basin which is the second largest tributary of the river Mahanadi laying between latitude 19° 15' 32.4"N and, 20° 45' 0"N and longitude 82° 3' 36"E and 84° 18' 18"E chosen for the present study. The catchment was discretized into approximately homogeneous sub-areas (grid cells) to overcome the catchment heterogeneity. The gross soil erosion in each cell was computed using Universal Soil Loss Equation (USLE). Various parameters for USLE was determined as a function of land topography, soil texture, land use/land cover, rainfall, erosivity and crop management and practice in the watershed. The concept of transport limited accumulation was formulated and the transport capacity maps were generated. The gross soil erosion was routed to the catchment outlet. This study can help in recognizing critical erosion prone areas of the study basin so that suitable control measures can be implemented.

Keywords: Universal Soil Loss Equation (USLE), GIS, land use, sediment yield,

Procedia PDF Downloads 282

Authors: T. M. Tawfik, M. A. Badr, E. Y. El-Kady, O. E. Abdellatif

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Electric power shortage is a serious problem in remote rural communities in Egypt. Over the past few years, electrification of remote communities including efficient on-site energy resources utilization has achieved high progress. Remote communities usually fed from diesel generator (DG) networks because they need reliable energy and cheap fresh water. The main objective of this paper is to design an optimal economic power supply from hybrid standalone energy system (HSES) as alternative energy source. It covers energy requirements for reverse osmosis desalination unit (DU) located in National Research Centre farm in Noubarya, Egypt. The proposed system consists of PV panels, Wind Turbines (WT), Batteries, and DG as a backup for supplying DU load of 105.6 KWh/day rated power with 6.6 kW peak load operating 16 hours a day. Optimization of HSES objective is selecting the suitable size of each of the system components and control strategy that provide reliable, efficient, and cost-effective system using net present cost (NPC) as a criterion. The harmonization of different energy sources, energy storage, and load requirements are a difficult and challenging task. Thus, the performance of various available configurations is investigated economically and technically using iHOGA software that is based on genetic algorithm (GA). The achieved optimum configuration is further modified through optimizing the energy extracted from renewable sources. Effective minimization of energy charging the battery ensures that most of the generated energy directly supplies the demand, increasing the utilization of the generated energy.

Keywords: energy management, hybrid system, renewable energy, remote area, optimization

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Authors: Xuan Dinh Vu, Elmar Csaplovics

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There has been an increasing need for methods to define priority areas for biodiversity conservation since the effectiveness of biodiversity conservation in protected areas largely depends on the availability of material resources. The identification of priority areas requires the integration of biodiversity data together with social data on human pressures and responses. However, the deficit of comprehensive data and reliable methods becomes a key challenge in zoning where the demand for conservation is most urgent and where the outcomes of conservation strategies can be maximized. In order to fill this gap, the study applied an environmental model Condition–Pressure–Response to suggest a set of criteria to identify priority areas for biodiversity conservation. Our empirical data has been compiled from 185 respondents, categorizing into three main groups: governmental administration, research institutions, and protected areas in Vietnam by using a well - designed questionnaire. Then, the Analytic Hierarchy Process (AHP) theory was used to identify the weight of all criteria. Our results have shown that priority level for biodiversity conservation could be identified by three main indicators: condition, pressure, and response with the value of the weight of 26%, 41%, and 33%, respectively. Based on the three indicators, 7 criteria and 15 sub-criteria were developed to support for defining priority areas for biodiversity conservation and zoning protected areas. In addition, our study also revealed that the groups of governmental administration and protected areas put a focus on the 'Pressure' indicator while the group of Research Institutions emphasized the importance of 'Response' indicator in the evaluation process. Our results provided recommendations to apply the developed criteria for identifying priority areas for biodiversity conservation in Vietnam.

Keywords: biodiversity conservation, condition–pressure–response model, criteria, priority areas, protected areas

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Authors: Alicja Starczewska, Aleksander Nawrat, Krzysztof Daniec, Jarosław Homa, Kacper Hołda

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Border Gateway Protocol is the main routing protocol that enables routing establishment between all autonomous systems, which are the basic administrative units of the internet. Due to the poor protection of BGP, it is important to use additional BGP security systems. Many solutions to this problem have been proposed over the years, but none of them have been implemented on a global scale. This article describes a system capable of building images of real-time BGP network topology in order to detect BGP anomalies. Our proposal performs a detailed analysis of BGP messages that come into local network cards supplemented by information collected by remote collectors in different localizations.

Keywords: BGP, BGP hijacking, cybersecurity, detection

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Authors: Bhogendra Mishra, Andy Nelson, Mirco Boschetti, Lorenzo Busetto, Alice Laborte

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Rice is grown on over 100 million hectares in almost every country of Asia. It is the most important staple crop for food security and has high economic and cultural importance in Asian societies. The combination of genetic diversity and management options, coupled with the large geographic extent means that there is a large variation in seasonality (when it is grown) and cropping intensity (how often it is grown per year on the same plot of land), even over relatively small distances. Seasonality and intensity can and do change over time depending on climatic, environmental and economic factors. Detecting where and when these changes happen can provide information to better understand trends in regional and even global rice production. Remote sensing offers a unique opportunity to estimate these trends. We apply the recently published PhenoRice algorithm to 14 years of moderate resolution remote sensing (MODIS) data (utilizing 250m resolution 16 day composites from Terra and Aqua) to estimate seasonality and cropping intensity per year and changes over time. We compare the results to the surveyed data collected by International Rice Research Institute (IRRI). The study results in a unique and validated dataset on the extent and change of extent, the seasonality and change in seasonality and the cropping intensity and change in cropping intensity between 2003 and 2016 for the Philippines. Observed trends and their implications for food security and trade policies are also discussed.

Keywords: rice, cropping intensity, moderate resolution remote sensing (MODIS), phenology, seasonality

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: Mohamed Bualhamam

Abstract:

Due to the complex nature of tourism resources of the Northern part of the United Arab Emirates (UAE), the potential of Geographical Information Systems (GIS) and Remote Sensing (RS) in resolving these issues was used. The study was an attempt to use existing GIS data layers to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth and give some specific recommendations to protect the area. By identifying sensitive natural environment and archaeological heritage resources, public agencies and citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas. The paper concludes that applications of GIS and RS in study of urban growth impact in tourism resources are a strong and effective tool that can aid in tourism planning and decision-making. The study area is one of the fastest growing regions in the country. The increase in population along the region, as well as rapid growth of towns, has increased the threat to natural resources and archeological sites. Satellite remote sensing data have been proven useful in assessing the natural resources and in monitoring the changes. The study used GIS and RS to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth. The result of GIS analyses shows that the Northern part of the UAE has variety for tourism resources, which can use for future tourism development. Rapid urban development in the form of small towns and different economic activities are showing in different places in the study area. The urban development extended out of old towns and have negative affected of sensitive tourism resources in some areas. Tourism resources for the Northern part of the UAE is a highly complex resources, and thus requires tools that aid in effective decision making to come to terms with the competing economic, social, and environmental demands of sustainable development. The UAE government should prepare a tourism databases and a GIS system, so that planners can be accessed for archaeological heritage information as part of development planning processes. Applications of GIS in urban planning, tourism and recreation planning illustrate that GIS is a strong and effective tool that can aid in tourism planning and decision- making. The power of GIS lies not only in the ability to visualize spatial relationships, but also beyond the space to a holistic view of the world with its many interconnected components and complex relationships. The worst of the damage could have been avoided by recognizing suitable limits and adhering to some simple environmental guidelines and standards will successfully develop tourism in sustainable manner. By identifying sensitive natural environment and archaeological heritage resources of the Northern part of the UAE, public agencies and private citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas.

Keywords: GIS, natural environment, UAE, urban growth

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Authors: Aliyu J. Abubakar, Mazlan Hashim, Amin B. Pour

Abstract:

Exploiting geothermal resources for either power, home heating, Spa, greenhouses, industrial or tourism requires an initial identification of suitable areas. This can be done cost-effectively using remote sensing satellite imagery which has synoptic capabilities of covering large areas in real time and by identifying possible areas of hydrothermal alteration and minerals related to Geothermal systems. Earth features and minerals are known to have unique diagnostic spectral reflectance characteristics that can be used to discriminate them. The focus of this paper is to investigate the applicability of mapping hydrothermal alteration in relation to geothermal systems (thermal springs) at Yankari Park Northeastern Nigeria, using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data for resource exploration. The ASTER Short Wave Infrared (SWIR) bands are used to highlight and discriminate alteration areas by employing sophisticated digital image processing techniques including image transformations and spectral mapping methods. Field verifications are conducted at the Yankari Park using hand held Global Positioning System (GPS) monterra to identify locations of hydrothermal alteration and rock samples obtained at the vicinity and surrounding areas of the ‘Mawulgo’ and ‘Wikki’ thermal springs. X-Ray Diffraction (XRD) results of rock samples obtained from the field validated hydrothermal alteration by the presence of indicator minerals including; Dickite, Kaolinite, Hematite and Quart. The study indicated the applicability of mapping geothermal anomalies for resource exploration in unmapped sparsely vegetated savanna environment characterized by subtle surface manifestations such as thermal springs. The results could have implication for geothermal resource exploration especially at the prefeasibility stages by narrowing targets for comprehensive surveys and in unexplored savanna regions where expensive airborne surveys are unaffordable.

Keywords: geothermal exploration, image enhancement, minerals, spectral mapping

Procedia PDF Downloads 335

Authors: Habib Abida, Noura Dahri

Abstract:

Flash floods are among the most serious natural hazards that have disastrous environmental and human impacts. They are associated with exceptional rain events, characterized by short durations, very high intensities, rapid flows and small spatial extent. Flash floods happen very suddenly and are difficult to forecast. They generally cause damage to agricultural crops and property, infrastructures, and may even result in the loss of human lives. The city of Gabes (South-eastern Tunisia) has been exposed to numerous damaging floods because of its mild topography, clay soil, high urbanization rate and erratic rainfall distribution. The risks associated with this situation are expected to increase further in the future because of climate change, deemed responsible for the increase of the frequency and the severity of this natural hazard. Recently, exceptional events hit Gabes City causing death and major property losses. A major flooding event hit the region on June 2nd, 2014, causing human deaths and major material losses. It resulted in the stagnation of storm water in the numerous low zones of the study area, endangering thereby human health and causing disastrous environmental impacts. The characterization of flood risk in Gabes Watershed (South-eastern Tunisia) is considered an important step for flood management. Analytical Hierarchy Process (AHP) method coupled with Monte Carlo simulation and geographic information system were applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin. Moreover, a survey was conducted from different areas of the city in order to understand and explore the different causes of this disaster, its extent and its consequences.

Keywords: analytical hierarchy process, flash floods, Gabes, remote sensing, Tunisia

Procedia PDF Downloads 79

Authors: Valdir Moura, FranciléIa De Oliveira E. Silva, Erivelto Mercante, Ranieli Dos Anjos De Souza, Jerry Adriani Johann

Abstract:

Several colonization projects were implemented in the Brazilian Legal Amazon in the 1970s and 1980s. Among all of these colonization projects, the most prominent were those with the Fishbone and Topographic models. Within this scope, the projects of settlements known as Anari and Machadinho were created, which stood out because they are contiguous areas with different models and structure of occupation and colonization. The main objective of this work was to evaluate the dynamics of Land-Use and Land-Cover (LULC) in two different colonization models, implanted in the State of Rondonia in the 1980s. The Fishbone and Topographic models were implanted in the Anari and Machadinho settlements respectively. The understanding of these two forms of occupation will help in future colonization programs of the Brazilian Legal Amazon. These settlements are contiguous areas with different occupancy structures. A 32-year Landsat time series (1984-2016) was used to evaluate the rates and trends in the LULC process in the different colonization models. In the different occupation models analyzed, the results showed a rapid loss of primary and secondary forests (deforestation), mainly due to the dynamics of use, established by the Agriculture/Pasture (A/P) relation and, with heavy dependence due to road construction.

Keywords: land-cover, deforestation, rate fragments, remote sensing, secondary succession

Procedia PDF Downloads 112

Authors: Jigg Pelayo, Ricardo Villar, Einstine Opiso

Abstract:

The rampant and unintended spread of urban areas resulted in increasing artificial component features in the land cover types of the countryside and bringing forth the urban heat island (UHI). This paved the way to wide range of negative influences on the human health and environment which commonly relates to air pollution, drought, higher energy demand, and water shortage. Land cover type also plays a relevant role in the process of understanding the interaction between ground surfaces with the local temperature. At the moment, the depiction of the land surface temperature (LST) at city/municipality scale particularly in certain areas of Misamis Oriental, Philippines is inadequate as support to efficient mitigations and adaptations of the surface urban heat island (SUHI). Thus, this study purposely attempts to provide application on the Landsat 8 satellite data and low density Light Detection and Ranging (LiDAR) products in mapping out quality automated LST model and crop-level land cover classification in a local scale, through theoretical and algorithm based approach utilizing the principle of data analysis subjected to multi-dimensional image object model. The paper also aims to explore the relationship between the derived LST and land cover classification. The results of the presented model showed the ability of comprehensive data analysis and GIS functionalities with the integration of object-based image analysis (OBIA) approach on automating complex maps production processes with considerable efficiency and high accuracy. The findings may potentially lead to expanded investigation of temporal dynamics of land surface UHI. It is worthwhile to note that the environmental significance of these interactions through combined application of remote sensing, geographic information tools, mathematical morphology and data analysis can provide microclimate perception, awareness and improved decision-making for land use planning and characterization at local and neighborhood scale. As a result, it can aid in facilitating problem identification, support mitigations and adaptations more efficiently.

Keywords: LiDAR, OBIA, remote sensing, local scale

Procedia PDF Downloads 253

Authors: S. S. Rwanga, J. M. Ndambuki

Abstract:

Groundwater quantification needs a method which is not only flexible but also reliable in order to accurately quantify its spatial and temporal variability. As groundwater is dynamic and interdisciplinary in nature, an integrated approach of remote sensing (RS) and GIS technique is very useful in various groundwater management studies. Thus, the GIS water balance model (WetSpass) together with remote sensing (RS) can be used to quantify groundwater recharge. This paper discusses the concept of WetSpass in combination with GIS on the quantification of recharge with a view to managing water resources in an integrated framework. The paper presents the simulation procedures and expected output after simulation. Preliminary data are presented from GIS output only.

Keywords: groundwater, recharge, GIS, WetSpass

Procedia PDF Downloads 426

Authors: Kirubasankar, Sanjeevkumar, Aravindh Nagappan

Abstract:

This paper addresses a system for monitoring patients using biomedical sensors and displaying it in a remote place. The main challenges in present health monitoring devices are lack of remote monitoring and logging for future evaluation. Typical instruments used for health parameter measurement provide basic information regarding health status. This paper identifies a set of design principles to address these challenges. This system includes continuous measurement of health parameters such as Heart rate, electrocardiogram, SpO2 level and Body temperature. The accumulated sensor data is relayed to a processing device using a transceiver and viewed by the implementation of cloud services.

Keywords: bio-medical sensors, monitoring, logging, cloud service

Procedia PDF Downloads 486