Deep seabed mining:Frontiers in engineering geology and environment

Ocean mining activities have been ongoing for nearly 70 years,making great contributions to industrialization.Given the increasing demand for energy,along with the restructuring of the energy supply catalyzed by efforts to achieve a low-carbon economy,deep seabed mining will play an important role in addressing energy-and resource-related problems in the future.However,deep seabed mining remains in the exploratory stage,with many challenges presented by the high-pressure,low-temperature,and complex geologic and hydrodynamic environments in deep-sea mining areas,which are inaccessible to human activities.Thus,considerable efforts are required to ensure sustainable,economic,reliable,and safe deep seabed mining.This study reviews the latest advances in marine engineering geology and the environment related to deep-sea min-ing activities,presents a bibliometric analysis of the development of ocean mineral resources since the 1950s,summarizes the development,theory,and issues related to techniques for the three stages of ocean mining(i.e.,exploration,extraction,and closure),and discusses the engineering geology environment,geological disasters,in-situ monitoring techniques,envi-ronmental protection requirements,and environmental effects in detail.Finally,this paper gives some key conclusions and future perspectives to provide insights for subsequent studies and commercial mining operations.

Unscented Kalman filter for a low-cost GNSS/IMU-based mobile mapping application under demanding conditions

For the last two decades,low-cost Global Navigation Satellite System(GNSS)receivers have been used in various applications.These receivers are mini-size,less expensive than geodetic-grade receivers,and in high demand.Irrespective of these outstanding features,low-cost GNSS receivers are potentially poorer hardwares with internal signal processing,resulting in lower quality.They typically come with low-cost GNSS antenna that has lower performance than their counterparts,particularly for multipath mitigation.Therefore,this research evaluated the low-cost GNSS device performance using a high-rate kinematic survey.For this purpose,these receivers were assembled with an Inertial Measurement Unit(IMU)sensor,which actively transmited data on acceleration and orientation rate during the observation.The position and navigation parameter data were obtained from the IMU readings,even without GNSS signals via the U-blox F9R GNSS/IMU device mounted on a vehicle.This research was conducted in an area with demanding conditions,such as an open sky area,an urban environment,and a shopping mall basement,to examine the device’s performance.The data were processed by two approaches:the Single Point Positioning-IMU(SPP/IMU)and the Differential GNSS-IMU(DGNSS/IMU).The Unscented Kalman Filter(UKF)was selected as a filtering algorithm due to its excellent performance in handling nonlinear system models.The result showed that integrating GNSS/IMU in SPP processing mode could increase the accuracy in eastward and northward components up to 68.28%and 66.64%.Integration of DGNSS/IMU increased the accuracy in eastward and northward components to 93.02%and 93.03%compared to the positioning of standalone GNSS.In addition,the positioning accuracy can be improved by reducing the IMU noise using low-pass and high-pass filters.This application could still not gain the expected position accuracy under signal outage conditions.

Analysis of the effect of the 2021 Semeru eruption on water vapor content and atmospheric particles using GNSS and remote sensing

Mount Semeru,an active volcano in East Java,Indonesia,erupted on December 4,2021,following extreme rainfall that caused an avalanche of hot pyroclastic flows and lava.The tropospheric conditions and dominant particle components in the atmosphere can be monitored using Global Navigation Satellite System(GNSS)technology and remote sensing satellites.GNSS signal propagation delay in Precise Point Positioning(PPP)processing can be used to determine Zenith Tropospheric Delay(ZTD)and Precipitable Water Vapor(PWV)variables so that atmospheric conditions can be generated.In addition,by using remote sensing satellite data,it is possible to obtain rainfall data with high temporal resolution as well as the dominant particle and gas content values during eruptions.During the eruption period,the high value of PWV was dominated by the high intensity of precipitation during the rainy season.High rainfall before the eruption caused activity inside the mountain to increase,which occurred in avalanche type eruption.Apart from that,the atmosphere around Semeru was also dominated by SO_(2)content,which spreaded for tens of kilometers.SO_(2)content began to be detected significantly by remote sensing sensors on December 7,2021.In this study,deformation and atmospheric monitoring were also carried out using low-cost GNSS at the Semeru Monitoring Station on September 9-15,2022.The results of the ZTD and ZWD values show the dominance of the wet component,which is directly proportional to rainfall activity in this period.

Predicting impact forces on pipelines from deep-sea fluidized slides:A comprehensive review of key factors

Deep-sea pipelines play a pivotal role in seabed mineral resource development,global energy and resource supply provision,network communication,and environmental protection.However,the placement of these pipelines on the seabed surface exposes them to potential risks arising from the complex deep-sea hydrodynamic and geological environment,particularly submarine slides.Historical incidents have highlighted the substantial damage to pipelines due to slides.Specifically,deep-sea fluidized slides(in a debris/mud flow or turbidity current physical state),characterized by high speed,pose a significant threat.Accurately assessing the impact forces exerted on pipelines by fluidized submarine slides is crucial for ensuring pipeline safety.This study aimed to provide a comprehensive overview of recent advancements in understanding pipeline impact forces caused by fluidized deep-sea slides,thereby identifying key factors and corresponding mechanisms that influence pipeline impact forces.These factors include the velocity,density,and shear behavior of deep-sea fluidized slides,as well as the geometry,stiffness,self-weight,and mechanical model of pipelines.Additionally,the interface contact conditions and spatial relations were examined within the context of deep-sea slides and their interactions with pipelines.Building upon a thorough review of these achievements,future directions were proposed for assessing and characterizing the key factors affecting slide impact loading on pipelines.A comprehensive understanding of these results is essential for the sustainable development of deep-sea pipeline projects associated with seabed resource development and the implementation of disaster prevention measures.

Engineering Analysis of Strong Motion Data from Recent Earthquakes in Sichuan, China

Recent earthquakes in the Sichuan Province have contributed to significantly expand the existing ground-motion database for China with new,high-quality ground-motion records.This study investigated the compatibility of ground-motion prediction equations(GMPEs)established by the NGA-West2 project in the US and local GMPEs for China,with respect to magnitude scaling,distance scaling,and site scaling implied by recent Chinese strong-motion data.The NGA-West2 GMPEs for shallow crustal earthquakes in tectonically active regions are considerably more sophisticated than widely used previous models,particularly in China.Using a mixed-effects procedure,the study evaluated event terms(inter-event residuals)and intra-event residuals of Chinese data relative to the NGA-West2 GMPEs.Distance scaling was investigated by examining trends of intra-event residuals with source-to-site distance.Scaling with respect to site conditions was investigated by examining trends of intra-event residuals with soil type.The study also investigated other engineering characteristics of Chinese strong ground motions.In particular,the records were analyzed for evidence of pulse-like forward-directivity effects.The elastic median response spectra of the selected stations were compared to code-mandated design spectra for various mean return periods.Results showed that international and local GMPEs can be applied for seismic hazard analysis in Sichuan with minor modification of the regression coefficients related to the source-to-site distance and soil scaling.Specifically,the Chinese data attenuated faster than implied by the considered GMPEs and the differences were statistically significant in some cases.Near-source,pulse-like ground motions were identified at two recording stations for the 2008 Wenchuan earthquake,possibly implying rupture directivity.The median recorded spectra were consistent with the code-based spectra in terms of amplitude and shape.The new ground-motion data can be used to develop advanced ground-motion models for China and worldwide and,ultimately,for advancing probabilistic seismic hazard assessment(PSHA).

Geomatics for Rehabilitation of Mining Area in Mahis, Jordan

Mining activities often cause dramatic changes in landscapes, particularly in the dump sites and its surrounding environment. Land rehabilitation is the process of renovating damaged land to some extent of its original shape and aims to minimize and mitigate the environmental effects to allow new land uses. The success of different rehabilitation strategy and newly suggested urban and architecture modeling depends on the landscape characterization (topography of the study area and its derivatives such as slope and aspects, geological and geomorphologic nature of the study area). The aim of this study is to demonstrate the utility of different methodologies based on geomatics techniques (Photogrammetry, Remote Sensing, Global Positioning System (GPS) and three dimensional Geographic Information System (GIS)) for highlighting landscape characterization which is needed for rehabilitation of Mahis area. Photogrammetric adjustment procedures were used to create digital elevation model and Orth-Photo model for the study area using aerial images. Remote sensing data were used for land classification to provide vital information for rehabilitation planning. GPS field observations were used to build spatial network for the study area based on ground control point collections. Finally, realistic representation of the study area with three dimensional GIS was prepared for the study area considering ease and flexible updating of the geo-spatial database.

矿山生态环境数字孪生:内涵、架构与关键技术

在双碳国家战略和新一代信息技术广泛应用的时代背景下,体系化、精准化和智能化是矿山生态环境治理的重要发展方向。我国矿山生态环境治理长期以来开展了较为丰富的信息化建设,但仍然面临缺乏综合性监测体系、生态演变建模不准确、生态治理依赖专家经验、无信息化决策工具等问题。据此,提出了矿山生态环境数字孪生(Digital Twin of Mine Ecological Environment,DTME)的科学内涵,并介绍了其总体架构、功能特点与系统构建关键技术。定义了矿山生态环境数字孪生是以天-空-地多源监测、人工智能建模为基础,在虚拟空间建立与现实矿山生态环境要素一一对应、演变过程相互映射、作用机制相互匹配的孪生系统,进而通过方案优化或反馈控制支持矿山生态环境全过程科学治理。详细介绍了DTME的总体架构,包括物理矿山生态环境、监测终端、孪生数据、信息链路、云边端服务、虚拟矿山生态环境和控制终端7个组成部分。DTME以现实应用需求为导向,具有矿山生态质量动态监测与体检、生态演变模拟与影响因子解析、生态变化过程预测、生态风险预警、智能分级分区生态修复、生态修复效果评价和生态环境监管等功能。最后,归纳了构建矿山生态环境数字孪生系统涉及矿山生态数字底座搭建、矿山生态数字场景构建、矿山生态演变过程模拟与预测、矿山生态治理智能决策4方面关键技术。DTME的应用将支撑矿山生态全过程治理的感知、表达、监测、模拟、仿真、预测与控制,有望大幅提高治理质量和效率。

Rapid prediction models for 3D geometry of landslide dam considering the damming process

The geometry of a landslide dam plays a critical role in its stability and failure mode,and is influenced by the damming process.However,there is a lack of understanding of the factors that affect the 3D geometry of a landslide dam.To address this gap,we conducted a study using the smoothed particle hydrodynamics numerical method to investigate the evolution of landslide dams.Our study included 17 numerical simulations to examine the effects of several factors on the geometry of landslide dams,including valley inclination,sliding angle,landslide velocity,and landslide mass repose angle.Based on this,three rapid prediction models were established for calculating the maximum height,the minimum height,and the maximum width of a landslide dam.The results show that the downstream width of a landslide dam remarkably increases with the valley inclination.The position of the maximum dam height along the valley direction is independent of external factors and is always located in the middle of the landslide width area.In contrast,that position of the maximum dam height across the valley direction is significantly influenced by the sliding angle and landslide velocity.To validate our models,we applied them to three typical landslide dams and found that the calculated values of the landslide dam geometry were in good agreement with the actual values.The findings of the current study provide a better understanding of the evolution and geometry of landslide dams,giving crucial guidance for the prediction and early warning of landslide dam disasters.

Extrapolation of upwelling irradiance just beneath the ocean surface from the in-water radiometric profile measurements

Accurate measurements of upwelling irradiance just beneath the ocean surface,E_(u)(λ,0^(-)),can be used to calculate ocean optical parameters,and further develop retrieval algorithms for remotely sensing water component concentrations.Due to the effects of sea surface waves,perturbation from instrument platform(ship),and instrument self-shading,E_(u)(λ,0^(-))is often difficult to be accurately measured.This study presents a procedure for extrapolating the E_(u)(λ,0^(-))from the in-water radiometric profile measurements.Using the optical profile data from 13 bands(ranging from 381 to 779 nm)measured by 45 casts in the Ligurian Sea during 2003–2009,the E_(u)(λ,0^(-))was extrapolated from in-water upwelling irradiance measurements between the initial shallow depth,Z_(0),and an optimal bottom depth,Z_(1),by three linear models(linear,2-degree polynomial,and exponential)and two nonlinear models(LOESS and spline).The accumulated errors of extrapolated E_(u)(λ,0^(-))at each wavelength for the five models were calculated.It was found that the optimal Z_(1) depth for the linear and exponential models was at the depth of80%of E_(u)(λ,Z_(0)),50%of E_(u)(λ,Z_(0))for the 2-degree polynomial model,40%of E_(u)(λ,Z_(0))for the LOESS model,and 15%of E_(u)(λ,Z_(0))for the spline model.The extrapolated E_(u)(λ,0^(-))derived from the five models was in good agreement with the calculated true E_(u)(λ,0^(-)).In all bands,the 2-degree polynomial model achieved the highest accuracy,followed by the LOESS model.In the short band of 381–559 nm,the linear and exponential models had the third-best performance,and the spline model performed worst within this range.For the red band of 619–779 nm,the accuracies of the exponential and spline models had the third highest performance,and the linear model produced lowest accuracy.Hence,the 2-degree polynomial model was an optimal procedure for extrapolation of E_(u)(λ,0^(-))from the in-water radiometric profile measurements.

Analyzing geomorphological and topographical controls for the heterogeneous glacier mass balance in the Sikkim Himalayas

Glacier response patterns at the catchment scale are highly heterogeneous and defined by a complex interplay of various dynamics and surface factors.Previous studies have explained heterogeneous responses in qualitative ways but quantitative assessment is lacking yet where an intrazone homogeneous climate assumption can be valid.Hence,in the current study,the reason for heterogeneous mass balance has been explained in quantitative methods using a multiple linear regression model in the Sikkim Himalayan region.At first,the topographical parameters are selected from previously published studies,then the most significant topographical and geomorphological parameters are selected with backward stepwise subset selection methods.Finally,the contributions of selected parameters are calculated by least square methods.The results show that,the magnitude of mass balance lies between-0.003±0.24 to-1.029±0.24 m.w.e.a^(-1) between 2000 and 2020 in the Sikkim Himalaya region.Also,the study shows that,out of the terminus type of the glacier,glacier area,debris cover,ice-mixed debris,slope,aspect,mean elevation,and snout elevation of the glaciers,only the terminus type and mean elevation of the glacier are significantly altering the glacier mass balance in the Sikkim Himalayan region.Mathematically,the mass loss is approximately 0.40 m.w.e.a^(-1) higher in the lake-terminating glaciers compared to the land-terminating glaciers in the same elevation zone.On the other hand,a thousand meters mean elevation drop is associated with 0.179 m.w.e.a-1of mass loss despite the terminus type of the glaciers.In the current study,the model using the terminus type of the glaciers and the mean elevation of the glaciers explains 76% of fluctuation of mass balance in the Sikkim Himalayan region.

Identifying anthropogenic and natural causes of wildfires by maximum entropy method-based ignition susceptibility distribution models

Turkey has a high potential for wildfires along its Mediterranean coast because of its dense forest cover and mild climate.An average of 250 wildfires occurs every year with more than 10,000 hectares destroyed due to natural and human-related causes.The study area is sensitive to fires caused by lightning,stubble burning,discarded cigarette butts,electric arcing from power lines,deliberate fire setting,and traffic accidents.However,52%of causes could not be identified due to intense wildfires occurring at the same time and insufficient equipment and personnel.Since wildfires destroy forest cover,ecosystems,biodiversity,and habitats,they should be spatially evaluated by separating them according to their causes,considering environmental,climatic,topographic and forest structure variables that trigger wildfires.In this study,wildfires caused by lightning,the burning of agriculture stubble,discarded cigarette butts and power lines were investigated in the provinces of Aydin,Mugla and Antalya,where 22%of Turkey’s wildfires occurred.The MaxEnt method was used to determine the spatial distribution of wildfires to identify risk zones for each cause.Wildfires were used as the species distribution and the probability of their occurrence estimated.Additionally,since the causes of many wildfires are unknown,determining the causes is important for fire prediction and prevention.The highest wildfire occurrence risks were 9.7%for stubble burning,30.2%for lightning,4.5%for power lines and 16.9%by discarded cigarette butts.In total,1,266 of the 1,714 unknown wildfire causes were identified by the analysis of the cause-based risk zones and these were updated by including cause-as signed unknown wildfire locations for verification.As a result,the Area under the ROC Curve(AUC)values were increased for susceptibility maps.

Vertical deformation model on postseismic phase using exponential and logarithmic function based on InSAR

The Palu MW7.4 earthquake occurred on September 28, 2018, with the epicenter at 119.86°, 0.72°. The severe shaking caused severe damage in Central Sulawesi, especially in Palu. We conducted a postseismic deformation study to determine the deformation pattern and reduce future earthquakes’ impact.Interferometric Synthetic Aperture Radar(In SAR) data were processed using Li CSBAS to get the time series. The time series data were fitted to exponential and logarithmic functions to determine the mechanism of postseismic deformation. The exponential model identified the influence of the viscoelastic mechanism, and the logarithm identified the afterslip mechanism. The Palu earthquake was fitted to logarithmic and exponential, but the logarithmic was more significant than an exponential function.Afterslip mechanism predominates, and viscoelastic mechanisms play a minor role in this postseismic deformation.

Process Monitoring and Terminal Verification of Cable-Stayed Bridges with Corrugated Steel Webs under Contruction

In this paper,the construction process of a cable-stayed bridge with corrugated steel webs was monitored.Moreover,the end performance of the bridge was verified by load test.Owing to the consideration of the bridge structure safety,it is necessary to monitor the main girder deflection,stress,construction error and safety state during construction.Furthermore,to verify whether the bridge can meet the design requirements,the static and dynamic load tests are carried out after the completion of the bridge.The results of construction monitoring show that the stress state of the structure during construction is basically consistent with the theoretical calculation and design requirements,and both meet the design and specification requirements.The final measured stress state of the structure is within the allowable range of the cable-stayed bridge,and the stress state of the structure is normal and meets the specification requirements.The results of load tests show that the measured deflection values of the mid-span section of the main girder are less than the theoretical calculation values.The maximum deflection of the girder is−20.90 mm,which is less than−22.00 mm of the theoretical value,indicating that the girder has sufficient structural stiffness.The maximum impact coefficient under dynamic load test is 1.08,which is greater than 1.05 of theoretical value,indicating that the impact effect of heavy-duty truck on this type of bridge is larger.This study can provide important reference value for construction and maintenance of similar corrugated steel web cable-stayed bridges.

Evalution of the Accuracy and Performance of Multi-GNSS(MGEX)Positioning for Long Baselines by Using Different Software

The Global Positioning System(GPS)is a GNSS constellation,but GNSS is not always GPS.GPS is one of the GNSS constellations used around the world.The GNSS constellations include GPS(US),QZSS(Japan),Beidou/BDS(China),Galileo(EU),and GLONASS(Russia).In 1999,the European Commission(EC)proposed the European Galileo satellite navigation system for the first time.A four-phase development was proposed,including public and private sector finance.Galileo was intended for both civilian and government use,and is managed and controlled by civil authorities.Galileo is made up of 30 satellites,a number of globally distributed ground stations,and a ground control and monitoring system,all of which are extremely similar to the structure,format,and layout of GPS.In this study,we investigate GPS/GLONASS/Galileo/Beidou/IRNSS/QZSS Navigation Satellite System integration algorithm for long baselines ranging from 1500 km to 3000 km in China,Japan and Mongolia.The positioning performance with GPS/GLONASS/Galileo/BDS/IRNSS/QZSS,GPS-only,Galileo-only,GLONASS-only and BDS-only,etc.is compared in terms of the positioning accuracy.An improvement of positioning accuracy over long baselines can be found with GPS/GLONASS/Galileo/BDS/QZSS/IRNSS compared with that of GPS-only and that of BDS-only.The obtained differences of the two baselines(Topcon Magnet Tools Software(Multi-GNSS)-(CSRS-PPP(GPS/GLONASS),(Trimble-RTX(GPS/GLONASS),(AUSPOS(GPS/GLONASS))Online Processing Software)by using GPS/GLONASS/Galileo/BDS/QZSS/IRNSS signals is between 40 cm and 111.5 cm on three days.

Modelling the probability of presence of Aedes aegypti and Aedes albopictus in Iran until 2070

Objective:To determine the suitable ecological habitats of Aedes(Ae.)aegypti and Ae.albopictus in Iran due to climate change by the 2070s.Methods:All data relating to the spatial distribution of Ae.aegypti and Ae.albopictus worldwide,which indicated the geographical coordinates of the collection sites of these mosquitoes,were extracted from online scientific websites and entered into an Excel file.The effect of climatic and environmental variables on these mosquitoes was evaluated using the MaxEnt model in the current and future climatic conditions in the 2030s,2050s,and 2070s.Results:The most suitable areas for the establishment of Ae.aegypti are located in the southern and northern coastal areas of Iran,based on the model outputs.The modelling result for suitable ecological niches of Ae.albopictus shows that in the current climatic conditions,the southern half of Iran from east to west,and parts of the northern coasts are prone to the presence of this species.In the future,some regions,such as Gilan and Golestan provinces,will have more potential to exist/establish Ae.albopictus.Also,according to the different climate change scenarios,suitable habitats for this species will gradually change to the northwest and west of the country.The temperature of the wettest season of the year(Bio8)and average annual temperature(Bio1)were the most effective factors in predicting the model for Ae.aegypti and Ae.albopictus,respectively.Conclusions:It is required to focus on entomological studies using different collection methods in the vulnerable areas of Iran.The future modelling results can also be used for long-term planning to prevent the entry and establishment of these invasive Aedes vectors in the country.

Local geoid modeling in the central part of Java, Indonesia, using terrestrial-based gravity observations

The Global Navigation Satellite System(GNSS)positioning method has been significantly developed in geodetic surveying.However,the height obtained through GNSS observations is given in a geodetic height system that needs to be converted to orthometric height for engineering applications.Information on geoid height,which can be calculated using the global geopotential mode,is required to convert such GNSS observations into orthometric height.However,its accuracy is still insufficient for most engineering purposes.Therefore,a reliable geoid model is essential,especially in areas growing fast,e.g.,the central part of Java,Indonesia.In this study,we modeled the local geoid model in the central part of Java,Indonesia,using terrestrial-based gravity observations.The Stokes'formula with the second Helmert's condensation method under the Remove-Compute-Restore approach was implemented to model the geoid.The comparison between our best-performing geoid model and GNSS/leveling observations showed that the standard deviation of the geoid height differences was estimated to be 4.4 cm.This geoid result outperformed the commonly adopted global model of EGM2008 with the estimated standard deviation of geoid height differences of 10.7 cm.

Performance of GPS and IMU sensor fusion using unscented Kalman filter for precise i-Boat navigation in infinite wide waters

The Unmanned Surface Vehicle(USV)navigation system needs an accurate,firm,and reliable performance to avoid obstacles,as well as carry out automatic movements during missions.The Global Positioning System(GPS)is often used in these systems to provide absolute position information.However,the GPS measurements are affected by external conditions such as atmospheric bias and multipath effects.This leads to the inability of the stand-alone GPS to provide accurate positioning for the USV systems.One of the solutions to correct the errors of this sensor is by conducting GPS and Inertial Measurement Unit(IMU)fusion.The IMU sensor is complementary to the GPS and not affected by external conditions.However,it accumulates noise as time elapses.Therefore,this study aims to determine the fusion of the GPS and IMU sensors for the i-Boat navigation system,which is a USV developed by Institut Teknologi Sepuluh Nopember(ITS)Surabaya.Using the Unscented Kalman filter(UKF),sensor fusion was carried out based on the state equation defined by the dynamic and kinematic mathematical model of ship motion in 6 degrees of freedom.Then the performance of this model was tested through several simulations using different combinations of attitude measurement data.Two scenarios were conducted in the simulations:attitude measurement inclusion and exclusion(Scenarios I and II,respectively).The results showed that the position estimation in Scenario II was better than in Scenario I,with the Root Mean Square Error(RMSE)value of 0.062 m.Further simulations showed that the presence of attitude measurement data caused a decrease in the fusion accuracy.The UKF simulation with eight measurement parameters(Scenarios A,B and C)and seven measurement parameters(Scenarios D,E and F),as well as analytical attitude movement,indicated that yaw data had the largest noise accumulation compared to roll and pitch.

Water System Condition and Asset Replacement Prioritization

The goal of asset management is to identify and track the maintenance and replacement of assets that have reached their useful life. For that reason, gathering data and collecting information is a critical step when developing an asset management plan. Such data gathering includes physical and operational properties of the assets as well as collecting and tracking important events during the lifespan of the asset (i.e., pipe breaks, replacement year, maintenance performed, etc.). Critical factors in the asset management plan may be overlooked when there is no data or poor quality data. However, many utilities lack the resources for examining buried infrastructure and lack good quality work order data, so other methods of data collection are needed. The concept for this paper was to develop a means to acquire data on the assets for a condition assessment to identify pipes that were most likely to break and those with the highest consequences for same. Three utilities were used as examples. It was found that for buried infrastructure, much more information was known than anticipated but the actual predictions relied on only a few factors related to pipe type. However, there is a need to track the consequences, in this case breaks, which would indicate a failure. The latter would be useful for predicting future maintenance needs and the most at-risk assets, but is often missing in utility systems as many utilities do not adequately track breaks sufficiently. In this case two utilities were analyzed and predication on a third was developed.

3D Model Construction and Ecological Environment Investigation on a Regional Scale Using UAV Remote Sensing

The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achieve using satellite remote sensing.Considering the convenient,facilitative,and flexible characteristics of UAV(unmanned air vehicle)remote sensing tech-nology,this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral data.Using professional software,including Context Capture,ENVI,and ArcGIS,a 3D(three-dimensional)campus model,a digital orthophoto map,and multi-spectral remote sensing map drawing are realized,and the geometric accuracy of typical feature selection is evaluated.Based on a quantitative remote sensing model,the campus ecological environment assessment is performed from the perspectives of vegetation and water body.The results presented in this study could be of great significance to the scientific management and sustainable development of regional natural resources.

Mass Valuation of Unimproved Land Value Case Study: Nairobi County

The purpose of this study is to investigate mass valuation of unimproved land value using machine learning techniques. The study was conducted in Nairobi County. It is one of the 47 Kenyan Counties under the 2010 constitution. A total of 1440 geocoded data points containing the market selling price of vacant land in Nairobi were web scraped from major property listing websites. These data points were adopted as dependent variables given as unit price of vacant land per square meter. The Covariates used in this study were categorized into Accessibility, Environmental, Physical and Socio-Economic Factors. Due to multi-collinearity problem present in the covariates, PLS and PCA methods were adopted to transform the observed features using a set of vectors. These methods resulted in an uncorrelated set of components that were used in training machine learning algorithms. The dependent variable and uncorrelated components derived feature reduction methods were used as training data for training different machine learning regression models namely;Random forest, support vector regression and extreme gradient boosting regression (XGboost regression). PLS performed better than PCA because the former maximizes the covariance between dependent and independent variables while the latter maximizes variance between the independent variables only and ignores the relationship between predictors and response. The first 9 components were identified as significant both by PLS and PCA methods. The spatial distribution of vacant land value within Nairobi County was consistent for all the three machine learning models. It was also noted that the land value pattern was higher in the central business district and the pattern spread northwards and westwards relative to the CBD. A relative low vacant land value pattern was observed on the eastern side of the county and also at the extreme periphery of Nairobi County boundary. From the accuracy metrics of R-squared and MAPE, Random Forest Regression model performed better than XGBoost and SVR models. This confirms the capability of random forest model to predict valid estimates of vacant land value for purposes of property taxation in Nairobi County.