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.

Urbanization and Other Land Use Land Cover Change Assessment in the Greater Kumasi Area of Ghana

Urbanization posits the expression of urban expanse expansion due to population growth, rise in built-up areas, high population density and its correspondingly urban way of life. Unrestrained impetus of development and land use land cover change (LULCC) portent several issues such as unlawful urban sprawl, loss of agricultural land, forest loss and other associated complications. This study analyzed the dynamics of urbanization and other LULCC in Ghana’s Greater Kumasi area via Landsat images (TM 1986, OLI 2013 and OLI 2023) using ERDAS Imagine, Idrisi and ArcGIS software. Implementing supervised classification technique, the Maximum Likelihood Classifier (MLC) procedure was employed to categories the study area into five LULC classes. Accuracy assessment undertaken on the resultant LULC maps was deemed very satisfactory. The results from 1986-2023 pointed to an upsurge in a built-up extent as of 8% to 41%, a decrease in Closed Forest from 9% to 4%, another decrease in Open Forests from 64% to 33%, a slight increase from 16% to 20% in farmlands and a stable level of water share. Further analysis indicated that the study area had undergone LULCC within the periods 1986-2013 and 2013-2023 at 60% and 37% respectively. The findings showed uncontrolled urban sprawling along major roads and forest loss as deforestation outside protected areas and degradation in protected forest. The monitoring of urbanization and other LULCC is important for local, and national governments and other bodies charged with the implementation of programs and policies that manage and utilize natural resources. Development adapts to mitigate the effect on the environment.

Assessment of Past and Future Land Use/Land Cover Dynamics of the Old Kumasi Metropolitan Assembly and Atwima Nwabiagya Municipal Area, Ghana

Ghana like all countries in Sub-Saharan region of Africa have long been undergoing intense land use land cover changes (LULCC) which have given rise to extensive forest loss (deforestation and degradation), loss of arable land and land degradation. This study assessed the past LULCC in the Atwima Nwabiagya which contains the Barekese and Owabi Headworks) and the old Kumasi Local Assemblies’ areas in Ghana and projected the scenario in 2040 for business-as-usual (BAU). The synergies of satellite imagery of 1990, 2000, 2010 and 2020 were classified with an overall accuracy of 90%. Markov Cellular-Automata method was used to forecast the future LULC pattern after detecting main driving forces of LULCC. The findings showed an extensive increase in built up areas from 11% in 1990 to 39% in 2020 owing largely to 23% decrease in forest cover and 6% decrease in agricultural lands within the past 30 years (1990-2020). The projected LULC under the BAU scenario for 2040 showed built-up surge from 39% to 45% indicating additional forest loss from 43% in 2020 to 40% and decreasing agricultural land from 17% to 14%. The main driver for the LULCC is clearly anthropogenic driven as the human population in the study area keeps rising every censual year. This study exemplifies the fast-tracked forest loss, loss of arable land and challenges on ecosystem sustainability of the Barekese-Owabi-Kumasi landscape. The current and projected maps necessitate the apt implementation of suitable interventions such as reforestation, protection measures and policy decision in deliberate land use planning to mitigate further loss of forest cover and safeguard the Barekese and Owabi headworks.

Assessing the vulnerability of a forest ecosystem to climate change and variability in the western Mediterranean sub-region of Turkey：future evaluation

This study evaluates the multifactorial spatial modelling used to assess vulnerability of the Du¨ zlerc？am？（Antalya） forest ecosystem to climate change.This was done to produce data,to develop tools to support decisionmaking and the management of vulnerable Mediterranean forest ecosystems affected by climate change,and to increase the ability of these forest ecosystems to adapt to global change.Based on regionally averaged future climate assessments and projected climate indicators,both the study site and the western Mediterranean sub-region of Turkey will probably become associated with a drier,hotter,more continental and more water-deficient climate.This analysis holds true for all future scenarios,with the exception of RCP4.5 for the period from 2015 to 2030.However,the present dry-sub humid climate dominating this sub-region and the study area shows a potential for change towards more dry climatology and for it to become semiarid between 2031 and 2050 according to the RCP8.5 high emission scenario.All the observed and estimated results and assessments summarized in this study show clearly that the densest forest ecosystem in the southern part of the study site,characterized by mainly Mediterranean coniferous and some mixed forest and maquis vegetation,will very likely be influenced by medium and high degrees of vulnerability to future environmental degradation,climate change and variability.

Some Experiences of Resistivity and Induced Polarization Methods on the Exploration of Sulfide: A Review

Sulfide minerals are a group of compounds with the presence of sulfur. This group’s most abundant and economically members are pyrites, pyrrhotite, chalcocite, galena, sphalerite, and the group of copper sulfides minerals. Resistivity and Induced Polarization (IP) methods, which play an essential role in mineral exploration, showed great success in sulfide exploration. This paper started on reviewing sulfide formation by giving details which help to understand their genesis better. To make the reader understand the procedures and appropriate mineral exploration methods, we have briefly covered the theory, the basic principles of resistivity and IP methods, and different investigation techniques using one, two, and three-dimensional surveys. Based on many electrical surveys, we discussed with examples of resistivity and IP methods applied to the exploration of sulfide deposits: the data inversion and interpretation of the geophysical signatures of most of the sulfide deposits in various geological environments were analyzed and end by showing both successful surveys and limitations of the methods.

Evaluation of the Direct UTM Coordinates Transformation Method Based on the Standard 7-Parameters Transformation

GNSS(global navigation satellite system)observations produce the geodetic position including latitude,longitude,and altitude(or ellipsoidal height)concerning the global reference datum WGS84(Word Geodetic System 1984),which usually should be converted to another local datum to get the desired position meaning in a physical sense,coordinates of points in the local datum are usually calculated by the seven-parameter transformation method.This paper aims to validate the methods of position transformation between WGS84 and the Iraqi local datum Karbala 1979 using the UTM(universal transverse Mercator)projected coordinates directly.The proposed algorithm was tested for 10 ground control points in Erbil city and many selected points in other different cities over all Iraqi territory.The control points are measured by the CHCNAV i73 GNSS receiver.For the evaluation procedure,the RMSE(root mean square error)of the transformed coordinates is calculated with an average value of±10.715 m as an estimated uncertainty of the direct UTM coordinates transformation method over Erbil city territory,and more than±12 m over different places over Iraqi territory.

Assessing vulnerability of a forest ecosystem to climate change and variability in the western Mediterranean sub-region of Turkey

Climate change is a real, pressing and significant global problem. The concept of ‘climate change vulnerability’ helps us to better comprehend the cause/effect relationships behind climate change and its impact on human societies, socioeconomic sectors, and physiographical and ecological systems. In this study, multifactorial spatial modelling evaluated the vulnerability of a Mediterranean forest ecosystem to climate change and variability with regard to land degradation. This produced data and developed tools to support better decision-making and management. As a result, the geographical distribution of Environmental Vulnerability Areas(EVAs) of the forest ecosystem is the estimated Environmental Vulnerability Index(EVI) values. These revealed that, at current levels of environmental degradation, physical, geographical, policy enforcement, and socioeconomic conditions, the area with a ‘‘very low’’ degree of vulnerability covered mainly the town, its surrounding settlements and agricultural lands found principally over the low, flat travertine plateau and the plains to the east and southeast of the district. The spatial magnitude of the EVAs of the forest ecosystem under current environmental degradation was also determined. This revealed that the EVAs classed as ‘‘very low’’accounted for 21% of the area of the forest ecosystem,those classed as ‘‘low’’ for 36%, those classed as ‘‘medium’’ for 20%, and those classed as ‘‘high’’ for 24%.

Land Suitability Assessment and Landuse Planning： A Prerequisite for Food Security and Climate Change Adaptation

Though Ghana＇s crop yield growth rate was at 17%, 5% of every 1.2 million Ghanaians have insufficient and limited access to nutritious food. Climate change and climate variability have enormously affected the state of agricultural productivity and hence could result in food insecurity. As many ongoing projects use Boolean suitability analysis, land use planning, management recommendations sores, it still remains inadequate to support rural resource poor farmers. This then, is affecting livelihood and agricultural productivity. In this paper, a geostatistical quantitative method to support a geographic information system （GIS） based on multi-criteria decision support system （GMCDSS） for an enhanced land suitability assessment （LSA） and landuse planning （LP） was devised. Project findings indicated that, recommended farm inputs could be estimated and applied accordingly at farm plot levels Soil amendment indicators （e.g., 1.0 t/ha lime ＋ 1.0 t/ha gypsum was estimated for liming） was quantified and currently, farmers can save money in soil fertility management. It has shown that, instead of applying 5.0 t/ha poultry manure （PM） or five bags of N-P-K fertilizer （rate of 15： 15： 15 N-P2O5-K2O/ha） ＋ two bags of sulphate of ammonia （SA）, a farmer may apply 2.0 t/ha PM ＋ two bags 15：15：15 N-P2O5-K2O/ha ＋ one bag of SA. GMCDSS assessment has proved to be fundamental in： （1） urban planning; （2） ensuring food security; （3） poverty reduction and interventions to the effects of climate change and climate variability.

Analysis of River Tributaries’ Streamflow Contribution Using WEAP Model: A Case of the Ngwerere and Kanakatampa Tributaries to the Chongwe River in Zambia

Ngwerere and Kanakatampa Streams are the main tributaries of the Chongwe River. The Ngwerere stream originates from the city of Lusaka and meanders through Lusaka City and Chongwe Town for an approximate distance of 41 km before joining into the upper part of Chongwe River. The Kanakatampa Stream is a tributary of the Chongwe River. It meanders from the Kanakatampa Area for approximately 52 km before discharging into the middle of the upper part of the Chongwe River. The Chongwe River Catchment which is a sub-catchment of the Zambezi Basin drew the attention of researchers and policymakers when the Chongwe River started drying up in the dry seasons causing a water crisis particularly in the downstream regions of the middle catchment. Therefore, it is important from the water resources management perspective, to assess the contribution of tributaries into the flows of the Chongwe River. Ngwerere and Kanakatampa streams are socially, economically, and environmentally important streams for the city of Lusaka and surrounding area. This study, therefore, concentrated on evaluating the flow contribution of the two streams to the Chongwe River using the Water Evaluation And Planning (WEAP) tool. The streamflow data (1970-2010) recorded at the Chongwe Great East Road Bridge gauging station were used in the WEAP embedded Parameter ESTimation (PEST) auto-calibration tool to calibrate (1970-1999) and validate (2000-2010) the model. The monthly streamflow model calibration and validation results were assessed using the correlation coefficient (CC), Coefficient of determination (R2), Nash-Sutcliffe Coefficient of Efficiency (NSE), and Percent bias (PBIAS). The model performance results achieved were PBIAS of 1.24%, CC = 0.81, R2 = 0.66 and NSE = 0.62 during the calibration period and a positive PBIAS of 2.94%, CC = 0.81, R2 = 0.67 and NSE = 0.62 during the validation period. The median of the flows (Q50) was obtained from the historical flow duration curves (FDCs) generated in averaged intervals of 10-year from 1970 to 2019. The results showed that on average, the Ngwerere and Kanakatampa Streams contribute 52.8% and 29.6% respectively, to the flow of the Chongwe River in the upper and middle Catchment. The results also showed that the contribution of the Ngwerere and Kanakatampa Streams to the Chongwe River discharge has been reducing historically at a rate of 0.65% per decade and 1.35% per decade respectively over a period of 50 years (1970-2019). Suggestions for sustainable management of the tributaries such as the Ngwerere and Kanakatampa Streams were provided in this study.

Novel Approach of Adjustment Theory Based on ANN Backpropagation

For a long time,the observations’adjustment concepts are doing based on the principle of Least Squares(LS),which so far,is the most popular technique that is widely used for such purposes.In the current study,the author introduces a new vision of the measurements’adjustment that depends on the principle of the artificial neural network backpropagation(ANNB).However,the novel approach of the adjustment in the current study is based upon the principle of the measurement’s precision,which will be represented through the value of the variance(σ^(2)).Thus,the determination of the required residuals for the adjustment procedure can be derived from the variances of observations and the value of geometrical closure error.The evaluation of the proposed method of adjustment ANNB is done according to the parametric method of LS adjustment for two selected cases of observations,representing the equal and non-equal precision observations.The obtained results of adjustment using the new technique(ANNB)are fully agreed with the results of LS for the two evaluation cases.These results indicate good compatibility between the ANNB and the LS as two approaches for observations’adjustment.

Frequency Features Based Fuzzy System for Rotating Machinery Vibration Analysis Using Smartphones Low-Cost MEMS Sensors

Smart devices have become an important entity for many applications in daily life activities. These devices have witnessed a rapid improvement in its technology to fulfill the increasingly diverse usage demands. In the meanwhile, rotating machinery vibration analysis based on low-cost sensors has gained a considerable attraction over the last few years. For a long time, the vibration analysis of machines has been accepted as an effective solution to detect and prevent failures in complex systems to avoid the sudden malfunction. The objective of this work is to use MEMS accelerometer measurements to monitor the different level of vibration of a machine. This work presents a new technique for rotating machinery vibration analysis. It uses Fast Fourier Transformation as a feature extraction algorithm and Fuzzy Logic System (FLS) as the classifier algorithm. A smartphone accelerometer is used to collect the data from the vibrating machine. The performance of the proposed technique is tested using data from different vibration resources at a different speed of operations. The results are discussed to illustrate the various vibration levels.

Local Geoid Model Generation Using the Geometrical Approach

The global navigation satellite systems(GNSS)provide an accurate three-dimensional positioning including the geodetic(ellipsoidal)height(h),which is,in most cases,must be transformed to the local/regional orthometric height(H)to have physically the desired meaning of the elevation above the national vertical datum(e.g.,MSL(Mean Sea Level)).Usually,the local orthometric heights are determined based on the value of geoid undulation(N),which is obtained by methods of gravimetrical observations or derived by methods of interpolation utilizing the local geoid models(LGM).The current paper highlights one of the methods of generating LGM that is based on the geometrical relationship between the global datum WGS84 and the Iraqi datum Karbala 1979.The DGPS(Differential GPS)method is used to get the geodetic coordinates of about 97 selected points to cover the experimental area,within the boundaries of Erbil municipality,which has been partitioned into four parts.Therefore,four LGM were generated individually for each one of the four parts with an estimated uncertainty equal to±0.076 m.

Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone

In this research,we used the Revised Universal Soil Loss Equation(RUSLE)and Geographical Information System(GIS)to predict the annual rate of soil loss in the District Chakwal of Pakistan.The parameters of the RUSLE model were estimated using remote sensing data,and the erosion probability zones were determined using GIs.The estimated length slope(LS),crop management(C),rainfall erosivity(R),soil erodibility(K),and support practice(P)range from 0-68,227,0-66.61%,0-0.58,495.99-648.68 MJ/mm.t.ha^(-1).year^(-1),0.15-0.25 MJ/mm.t.ha^(-1).year^(-1),and 1 respectively.The results indicate that the estimated total annual potential soi loss of approximately 4,67,064.25 t.ha^(-1).year^(-1) is comparable with the measured'sediment ioss of 11,631 t.ha^(-1).year^(-1) during the water year 2020.The predicted soil erosion rate due to an increase in agricultural area is approximately 164,249.31 t.ha^(-1).year^(-1).In this study,we also used,Landsat imagery to rapidly achieve actual land use classification.Meanwhile,38.i3%of the region was threatened by very high soil erosion,where the quantity of soil erosion ranged from 365487.35 t.ha^(-1).year^(-1),Integrating GIS and remote sensing with the RUSLE model helped researchers achieve their final objectives.Land-use planners and decision-makers use the result's spatial distribution of soil erosion in District Chakwal for conservation and management planning.

顾及邻近点变形因素的高斯过程建模及预测

针对传统的变形监测建模方法一般针对单一监测点的变形预测模型,未考虑到监测点间相互作用的变形特点,该文分析了变形监测点间的相互关联性,通过相关系数法对监测点进行分类,并将邻近监测点的观测序列值作为和时间因素等同的影响因子应用到建模过程中,利用高斯过程算法进行训练,建立预测模型。为提高高斯过程算法的模型预测精度,应选择适合工程案例最优协方差函数。通过实例分析,比较GM(1,1)、多点灰色预测模型和顾及邻近点变形因素的高斯过程等3种模型在基坑围岩、滑坡等变形监测数据处理中的预测精度,表明该文算法考虑到监测点间的变形关联性,充分利用高斯过程在针对小样本、非线性数据建模时的高自适应性等优点,具有较高的预测精度。

Digital astro-geodetic camera system for the measurement of the deflections of the vertical:tests and results

This study introduces the new results of a novel low-cost digital zenith camera system operated in Turkey that uses astronomical and geodetic instrumentation.Currently,it is possible to determine deflections of the vertical(DoV)components by using a vast amount of information gathered from geo-referenced star images,tilt measurements,and Global Navigation Satellite System technology.This new design of an astro-geodetic camera system is used for calculating DoV components with 12 independent solutions on a test station in Istanbul,and additional observations were performed to investigate the external accuracy of the system on a test network.A specific leveling method is developed to align system toward the zenithal direction.The final results of the observations on a test station located in Istanbul indicate that the accuracy of the system is about±0.19 arc-seconds in latitude and±0.28 arc-seconds in longitude determination.The system has been further tested on a network with 4 control points that have averagely 20 km baselines.At the test network,the root mean square of the average value of the vertical deflections is calculated as±0.36 arc-seconds.Furthermore,DoV components are compared with the values that are calculated using global geopotential models.

Modeling the spread of spatio-temporal phenomena through the incorporation of ANFIS and genetically controlled cellular automata: a case study on forest fire

Virtual representation and simulation of spatio-temporal phenomena is a promising goal for the production of an advanced digital earth.Spread modeling,which is one of the most helpful analyses in the geographic information system(GIS),plays a prominent role in meeting this objective.This study proposes a new model that considers both aspects of static and dynamic behaviors of spreadable spatio-temporal in cellular automata(CA)modeling.Therefore,artificial intelligence tools such as adaptive neuro-fuzzy inference system(ANFIS)and genetic algorithm(GA)were used in accordance with the objectives of knowledge discovery and optimization.Significant conditions in updating states are considered so traditional CA transition rules can be accompanied with the impact of fuzzy discovered knowledge and the solution of spread optimization.We focused on the estimation of forest fire growth as an important case study for decision makers.A two-dimensional cellular representation of the combustion of heterogeneous fuel types and density on non-flat terrain were successfully linked with dynamic wind and slope impact.The validation of the simulation on experimental data indicated a relatively realistic head-fire shape.Further investigations showed that the results obtained using the dynamic controlling with GA in the absence of static modeling with ANFIS were unacceptable.

A block-based selection method for road network generalization

When road symbols are shown in a size proportionate to the reduced scale,several problems of legibility may arise concerning the urban blocks.By the method proposed in this paper,in order to overcome these problems,urban block areas are enlarged through amalgamation and the intervening roads in the amalgams are eliminated.This method includes two new approaches for computation of threshold used in determination of important roads based on the connectivity measure,and for definition of minimum block space and area requirements based on graphic limits.A block life cycle was designed for amalgamation of blocks.For the amalgamation process,a new algorithm was developed.The experimental testing indicates that important roads and the roads surrounding the urban area have been preserved.A simpler and more legible road network has been acquired.This method can be described as a more holistic approach as the buildings are taken into account.The problems arising in the experimental testing indicate that the cartographic selection/elimination process is not sufficient by itself for road network generalization,which can be assumed as one of the integral parts of Digital Earth.As well as the selection/elimination,processes such as displacement and caricaturizing are also needed.

A comparative data-fusion analysis of multi-sensor satellite images

Remote-sensing data play an important role in extracting information with the help of various sensors having different spectral,spatial and temporal resolutions.Therefore,data fusion,which merges images of different spatial and spectral resolutions,plays an important role in information extraction.This research investigates quality-assessment methods of multisensor(synthetic aperture radar[SAR]and optical)data fusion.In the analysis,three SAR data-sets from different sensors(RADARSAT-1,ALOS-PALSAR and ENVISAT-ASAR)and optical data from SPOT-2 were used.Although the PALSAR and the RADARSAT-1 images have the same resolutions and polarisations,images are gathered in different frequencies(L and C bands,respectively).The ASAR sensor also has C-band radar,but with lower(25 m)resolution.Since the frequency is a key factor for penetration depth,it is thought that the use of different SAR data might give interesting results as an output.This study describes a comparative study of multisensor fusion methods,namely the intensity-hue-saturation,Ehlers,and Brovey techniques,by using different statistical analysis techniques,namely the bias of mean,correlation coefficient,standard deviation difference and universal image quality index methods.The results reveal that Ehlers’method is superior to the others in terms of spectral and statistical fidelity.

Implementation of serverless cloud GIS platform for land valuation

Cloud computing enables performing computations and analysis tasks and sharing services in web-based computer centres instead of local desktop systems.One of the most used areas of cloud computing is geographic information systems(GIS)applications.Although Desktop GIS products are still used in the community frequently,Web GIS and Cloud GIS applications have drawn attention and have become more efficient for users.In this study,a serverless Cloud GIS framework is implemented for the land valuation platform.In order to store,analyse,and share geospatial data,the Aurora Serverless PostgreSQL database is created on Amazon Web Services(AWS).While adopting Aurora Serverless PostgreSQL as a database management system,a simple point in polygon analysis conducted to compare the performances with Amazon Relational Database Service(RDS)instance.Results showed that the serverless database responded to the query faster and scaled up during high workload to decrease latency.Hence,parcel vector data,which conveys ownership information and land values attributes,is shared directly from the PostGIS database as vector tiles.Besides S3 and AWS Lambda services are used for storing and disseminating raster-based land value map tiles.To visualize all shared data and maps through a web browser,open source web mapping library Mapbox GL JS is used.

Ontological exploration of geospatial objects in context

Structured study of spatial objects and their relationships leads to a better cognition of the geospatial information and creates the concept of context at a higher level of abstraction.This study is aimed at providing a comprehensive definition of the context for geospatial objects.A combination of binary qualitative spatial relationships(i.e.direction,distance,and topological relations)among the members of a set of spatial objects will be used accordingly.In addition,by incorporating the general concept of context,obtained from either static data(attributes in a database)or dynamic data(sensors),the compact context of spatial objects will be introduced.Our framework for presentation of the involved knowledge and conception about the objects in context is also explored using ontology and description logic because of powerful conceptualization of relationships,either spatial or non-spatial,integrally.For this purpose,the hierarchies of main structure and object properties are formed at first.The constraint and characteristics of classes,such as subclasses,equivalent classes,cardinality etc.,and object properties,such as being functional,transitive,symmetric,asymmetric,inverse functional,disjoint etc.,are discovered and presented in more detail using web ontology language in description logic mode.The implementation is then performed in the framework of semantic web and extensible markup language syntaxes.The method ultimately facilitates,spatial reasoning by effective querying in a semantic framework taking pellet reasoner and SPARQL(a recursive acronym for SPARQL Protocol and RDF Query Language).