Integration Of GIS Research Articles

Multicriteria land suitability assessment for cassava and bean production using integration of GIS and AHP

Multicriteria land suitability assessment for cassava and bean production using integration of GIS and AHP

Geological mapping of kimberlite magmatism as an assessment of diamond-bearing objects in Western Yakutia

Тhe results of generalization and GIS integration of the results of the study of all known indigenous deposits and manifestations of diamonds located in the distributed and undistributed fund of the subsoil of the Russian Federation are presented. The work takes into account the results of prospecting, exploration and exploitation works, minutes of meetings of regional (TKZ) and federal (RKZ and GKZ) commissions on mineral reserves and published data. As a result, a GIS-integrated database was created containing 1,319 objects, for each of which key parameters were determined: coordinates, shape, size, age, average diamond content, forecast resources, and diamond reserves. It was established that the indigenous diamond deposits are concentrated in the Central Siberian subprovincia and account for 2.3 % of all known kimberlite bodies, diamond-bearing kimberlite bodies in the Yakut diamond-bearing province – 282, the predominant body shape is a pipe (59 %). There is no correlation between the size of kimberlite bodies and their diamond content, small pipes, as well as large diatremes, can be industrially diamondiferous, the prevailing absolute age of industrially diamondiferous kimberlites is 329-382 million years.

Integration of RS and GIS in assessing flood risk: A Case Study on Istanbul - Esenyurt

Floods, exacerbated by escalating urbanization, pose significant threats to life and property globally. Over the past decade, the Esenyurt district in Istanbul has witnessed a series of floods, highlighting existing flood risks. Rapid population growth in this area and dense urbanization caused by intensive construction increase flood risks. Given these factors, the study focuses on examining the historical impact of urbanization on flood risks, considering spatial and temporal changes. Landsat-8 satellite data, specifically examining NDVI, NDBI, and BU, was employed to detect building imprints and reveal their historical backgrounds for temporal risk calculations. The analysis showed a sudden increase in urbanization rates in 2016, 2017, and 2021. In the flood risk calculations, 2014 data for a return period of 100 years were used and flood inundation depth, economic damages, affected population and depth-damage function were taken into consideration. The results indicate that from 2014 to 2022, increasing urbanization led to a 32.9% increase in the population affected by floods, a 22.3% rise in potential economic damage, and a 13.6% increase in total flood risk. The relationship between flood risks, contemporary urbanization, and its economic dimensions has been evaluated to reduce risks and achieve sustainable cities.

Remote Sensing & GIS Integration Bases Evaluation of Ground Water Quality in Telangana State, India

About 85% of drinking water needs in rural and 40% drinking water needs in urban areas are met from groundwater resources in Telangana state. There is a huge demand of ground water for different uses like agriculture, drinking and industrial purposes as the command area is very low in the state and it is evidenced by the fact that around 70% irrigation is dependent on ground water sources as compared to other surface sources like Tanks/Canals/Reservoirs etc. Climate change has affected the hydrological cycle with uncertain and increased variability in rainfall followed by with high rainfall in a short span of time resulting more surface runoff which ultimately decreases there charge to groundwater. Decreased recharge to the groundwater and excess withdrawal of groundwater has accelerated the depletion of groundwater resources there by resulting in stress on groundwater regime in terms of quality as well as quantity. The groundwater quality evaluation of Telangana state is carried out by using legacy quality data (2012-14) collected from Rural Water Supply & Sanitation Department, Government of Telangana. Contamination spread of groundwater is one of the most important concerns that have received attention at regional, local and global levels because of their importance on public health and its further impact in ecosystems. The spatial distribution of chemical parameters like pH, Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA), Fluoride (F), Chloride (Cl), Iron (Fe), Nitrate (NO3) and Sulfate (SO4) are examined with respect to its contamination level. The spatial distribution and concentration of chemical elements is carried out by using spatial interpolation technique namely Inverse Distance Weightage (IDW) method from the point source data. The distribution maps reveal important information to understand the hot spot areas of the groundwater systems and for identification of potential areas for providing safe drinking water supply. Site specific water conservation and artificial recharge measures are needed to be taken up with scientific lines by using Remote Sensing & GIS techniques, for enhancing the groundwater storage and also improving its quality.

Flood Modeling: A Comprehensive Review on IDF Curves, HEC-HMS, HEC-RAS, and GIS Integration

Flood Modeling: A Comprehensive Review on IDF Curves, HEC-HMS, HEC-RAS, and GIS Integration

Optimizing Biodiversity Conservation in Sundaland through Advanced Geospatial Techniques and Remote Sensing Technologies

Sundaland ecosystems are under threat from human activity and climate change such as logging, agricultural practices, overexploitation of wildlife and climatic change that have led to frequent forest fires and a decline in indigenous plant and animal species. This study investigates the risks to Sundaland's biodiversity as well as the management possibilities using GIS, RS, and AI. The goal was to find out how artificial intelligence (AI) can be applied to effectively manage biodiversity and expand on the body of knowledge already available about the useful roles that GIS and RS play in the area. In this systematic method, seven databases were used to gather data from 110 research publications, of which 101 were screened for scope and subject variable. 80% (81articles) of the examined studies collected data using GIS and RS. It is found that. AI in biodiversity management is poised to grow, offering new opportunities to address the intricate challenges facing our planet's diverse ecosystems. In conclusion, for efficient monitoring, well-informed policy creation, and decision-making to guarantee the long-term preservation of Sundaland's biodiversity, integration of GIS, RS, and AI is essential.

Integration of GIS and remote sensing for evaluating forest canopy density index in Kunar Province, Afghanistan

Integration of GIS and remote sensing for evaluating forest canopy density index in Kunar Province, Afghanistan

Integration of GIS and Artificial Intelligence Algorithms in Rural Landscape Protection and Planning

Integration of GIS and Artificial Intelligence Algorithms in Rural Landscape Protection and Planning

Advancing soil erosion prediction in Wadi Sahel-Soummam watershed Algeria: A comparative analysis of deep neural networks (DNN) and convolutional neural networks (CNN) models integrated with GIS

This study employs adaptive deep learning (utilizing DNN and CNN approaches) to accurately predict soil erosion, a crucial aspect of sustainable soil resource management. The goal is to develop fuzzy logic models for erosion forecasting in a large watershed with limited in-puts, comparing them to predictions from the Revised Universal Soil Loss Equation (RUSLE). Integration of GIS enables analysis of satellite data, providing crucial details like land use, slope, rainfall distribution, and flow direction. This synergistic approach enhances erosion prediction capabilities and yields spatial erosion distributions. Producing precise erosion risk maps within GIS is crucial for prioritizing high-risk areas and implementing effective conservation methods in the Wadi Sahel watershed, Algeria. The assessment in the Oued Sahel-Soummam watershed involved overlaying five RUSLE factor maps using Arc GIS spatial analysis, resulting in an aver-age annual soil loss of 4.22 tons per hectare. The DNN and CNN models were integrated with GIS for detailed calculation of annual average soil loss (tons per hectare per year) and mapping erosion risk areas in Wadi Sahel-Soummam watershed. Using the CNN model, estimated annual soil loss in Sahel-Soummam wadi was about 4.00 tons per hectare per year, while the DNN model estimated around 4.13 tons per hectare per year. This study employed two deep learning models for erosion prediction, with the DNN model featuring six hidden layers performing no-tably better than the compared CNN model.

Exploring the Potential and Benefits of AHP and GIS Integration for Informed Decision-Making: A Literature Review

Exploring the Potential and Benefits of AHP and GIS Integration for Informed Decision-Making: A Literature Review

An Overview of GIS-RS Applications for Archaeological and Cultural Heritage under the DBAR-Heritage Mission

In recent decades, the application of GIS and RS in archaeological and cultural heritage (ACH) has witnessed a notable surge both in terms of quantity and scope. During the initial implementation period (2016–2021) of the Digital Belt and Road Heritage (DBAR-Heritage) working group, several instances of GIS-RS-based applications in support of cultural heritage conservation have merged. In this paper, in order to discuss the great potential of GIS and RS on the Silk Road, an overview of GIS- and RS-based applications in ACH is first presented. In a substantial portion of the published scientific literature, the identification and comprehension of archaeological sites, the monitoring and risk assessment of cultural heritage, and the management and visualization of cultural heritage data are highlighted. Following this, five illustrative case studies from the DBAR-Heritage working group are presented to exemplify how the integration of GIS and RS serves as key approaches in recognizing and appreciating cultural heritage. These selected case studies showcase the utilization of multi-source data for the identification of linear sites; detailed, refined monitoring and assessment of the Angkor Wat heritage; and the reconstruction of the Silk Road routes. These instances serve as the cornerstone for highlighting current trends in GIS and RS applications in ACH along the Silk Road. These methodologies efficiently integrate multi-source geospatial data and employ multidisciplinary approaches, ultimately furnishing sophisticated and intelligent tools for the exploration and management of archaeological and cultural heritage in the era of Big Earth Data. Subsequently, a comprehensive discussion on the merits and challenges of GIS and RS applications in ACH is presented, followed by an exploration of the current application trends. Finally, the prospects for the widespread application of GIS and RS in ACH along the Silk Road are outlined in accordance with the operational plan of DBAR-Heritage during its second implementation phase.

Accelerated eutrophication alters fish and aquatic health: a quantitative assessment by using integrative multimarker, hydrochemical, and GIS modelling method in an urban lake.

The ramifications of anthropogenic activities on the environment and the welfare of aquatic life in lakes worldwide are becoming increasingly alarming. There is a lack of research in the Indian Himalayas on fish biomarker responses to stressful aquatic conditions and the use of environmetric modelling in GIS. Our research evaluates the environmental health of urban lakes in multiple basins using multi-biomarker endpoints (13 features) in Schizothorax niger and hydrochemical characterization (9 features) of water. The study covers 31 grids, each at a distance of 1 km2. This study demonstrated a statistically significant (P = 0.001) increase in white blood cells (WBC), mean cell size (MCH), helminth infection, and health assessment index score (HAIS) score in fish from a highly eutrophic cluster or basin compared to a reference cluster, which is indicative of environmental stress in fish. Based on hydrochemical similarities, the lake water datasets were divided into three categories using hierarchical cluster analysis (HCA). In the PCA analysis, the first three principal components were responsible for 78.1% of the data's variance. The first principal component (PC1) accounted for 57.4% of the variance and had a strong positive loading from ammonia, total phosphate, pH, nitrates, and total alkalinity for water quality parameters. Additionally, PC1 had a favourable loading from WBC, helminth infection (%), and the health assessment index score (HAIS) for biological endpoints. These findings are in alignment with the results of the multivariate analysis. The trophic state index (TSI) showed a significant (P < 0.05) increase in Cluster 1, which includes the peripheral areas of Hazratbal and Gagribal side (> 70), compared to the reference cluster. The multiple regression model indicates that ammonia, phosphate, and nitrate significantly impact the general health of fish (R2 > 0.7). A novel methodology for monitoring water quality fluctuations across different basins and clusters is presented in this study. By integrating fish health biomarkers and GIS technology, we have developed a comprehensive approach to evaluate the overall well-being of aquatic habitat. This technique may prove beneficial in the management of urban lentic water bodies in the Kashmir Himalayas and other comparable water systems around the globe, while also supporting sustainable practices.

GIS INTEGRATION OF LAND COVER WITH NIGHT-TIME LIGHTS FOR SPATIOTEMPORAL EVALUATION OF URBAN EXPANSION

Abstract. Monitoring the urbanisation process requires accurate knowledge of the present and historical spatial extents of built-up area. Understanding the quantification of urban growth is a crucial component of urban and environmental planning. The current research is focussed on evaluating the spatiotemporal change evaluation of built-up area by using a combination Landsat 8 and NPP-VIIRS datasets with GIS integration. Firstly, spatial change analysis of the built-up area was done by employing the Land Use and Land Cover (LULC) classification methodology for the years 2014 and 2022. This was done using the Random Forest (RF) classifier within the Google Earth Engine (GEE) platform. Secondly, the change in built-up area was evaluated with respect to the NTL data. The night-time light (NTL) images detect artificial lights being radiated from cities at night. The NTL data was categorised into three classes and later used to categorise the built-up area into ‘core urban’, ‘peri-urban’ and ‘rural’. The proportion of 'core urban' pixels experienced substantial growth, increasing from 9.8% to 15.5% of the total pixels between 2014 and 2022. This represents a notable increase of 58.75%. Conversely, the 'peri-urban' pixels saw a smaller increase of 4.6%, while the 'rural' pixels witnessed a decline of 8.7%. The average built-up density of the 'core urban' area exhibited an increase from 0.385 in 2014 to 0.398 in 2022. These changes can be attributed to the progressive conversion of 'rural' pixels into 'peri-urban' areas, and subsequently, the transformation of 'peri-urban' areas into 'core urban' regions.

A new method for orthographic video map construction based on video and GIS

For the problem that the non-ground plane and dynamic object areas in surveillance videos have large deformation after geographic mapping, a new method for orthographic video map construction (OVMC) based on video and GIS is proposed. Firstly, the segmented video background (SegBG), dynamic object sub-image (SubObjPic) and its coordinates are extracted. Secondly, the homography matrix (H) is solved. An area (R) is set in a 2D map. based on H−1, the orthophoto map of the video background (OrviBG) is constructed. Finally, each SubObjPic are converted to geographic space and overlaid on OrviBG, then the ortho video map is generated. The results show that:(1) The accuracy of the semantic segmentation model for removing non-ground plane is 96.70%; (2) Compared with the traditional method, the amount of orthographic video is reduced by 22.9%; (3) The deformation of non-ground and dynamic object areas is eliminated. This method can promote the deep integration of surveillance video and GIS.

Enhancing Decision-Making for Sustainable Agriculture and Tourism Development through System Dynamics and GIS Integration: A Study of Jenawi District

As one of the districts that have an important role for Karanganyar Regency in agriculture and tourism, Jenawi District is a producer of 18 out of the 22 agricultural commodities in Karanganyar Regency, Indonesia. In addition, Jenawi District also has various natural tourism objects such as caves, valleys, waterfalls, springs, and other tourism objects. However, the potential of agriculture and tourism has not been able to improve community welfare because there is no policy to encourage the agricultural and tourism sectors in Jenawi District. Therefore, this study aims to formulate alternative policy models in the agriculture and tourism sectors in Jenawi District. This research uses quantitative research methods using primary and secondary data types, where the data collection techniques used are observation, interviews, FGDs, literature reviews, and GIS analysis. GIS analysis enabled spatial data integration and visualization, facilitating the identification of patterns, relationships, and potential areas for agriculture and tourism development. The analysis method used is a dynamic system method that uses the causal loop diagram analysis technique. The analysis results found that the dynamic system model in Jenawi District that has been designed is able to work properly with high accuracy levels. There are differences between with and without policies, especially in the incentives used, which have significant differences. With the implementation of policies in Jenawi District, there is a difference in income results in the agricultural sector reaching 20%-27%, and in the tourism sector reaching 80%.

Applications of BIM in Information Technology: A Review

Abstract: To promote intelligent development in the construction sector and enhance construction management efficiency, the concept of smart development has been integrated into the planning of smart cities. A crucial aspect of smart city projects is developing a 3D digital city model. The integration of GIS and BIM technology is vital for achieving this, supporting the creation and analysis of dynamic smart cities. Using AR technology, we can recreate real-world scenes in virtual reality to provide customers with a more "immersive" experience. This article explores the diverse applications of GIS-BIM integration technology, focusing on construction schedule management, site material handling, and worker safety. Additionally, it delves into the application trends of GIS-BIM integration technology, global wide area network, Internet of Things (IoT), virtual reality, and other emerging technologies in integrated building construction management, promoting intelligent and visually enhanced management through GIS-BIM technology. This paper addresses safety management considering the entire project life cycle, setting a benchmark to elevate safety standards comprehensively in construction projects

Aggregating an economic model and GIS to explore trade potentials of India-Caspian countries and a way forward for INSTC

The Caspian countries have a crucial role in new trade scenarios for India as it constantly steers towards its trade diversification and expansion. With the establishment and expansion of INSTC (International North South Transport Corridor), the importance of Caspian countries (Azerbaijan, Iran, Turkmenistan, Kazakhstan, and Russia) has increased. INSTC is also seen as a gateway to Central Asia. It is, therefore, of utmost significance to estimate the trade potential of the aforesaid with India adopting novel methods and techniques with giving due attention to the role of INSTC. The objective of the present study is to examine the role of INSTC in the light of geographical background and in promoting Indian trade. The study also attempts to analyze past trends of Indo-Caspian trade potential. A profound gravity model is developed to estimate India-Caspian countries' recent pattern of trade potential. Population, GDP, trade, and service area of the countries' ports are taken as influencing variables in modelling the trade potential and their statistical significance is estimated using ordinary least square method. The integration of GIS based network analysis and service area modelling is performed first time for estimating trade potential as it represents the port's connectivity to the hinterland. The findings of the gravity model postulate that recent years have been full of changes where Iran has lost its dominance, and Azerbaijan has risen to capture the top position from 2015 to 2020. Steady growth has been observed in Russia and sudden growth in Azerbaijan. The present study is a standalone in which the service area of ports has been used and has a positive relation with trade.

Determination of groundwater potential distribution in Kulfo-Hare watershed through integration of GIS, remote sensing, and AHP in Southern Ethiopia

Determination of groundwater potential distribution in Kulfo-Hare watershed through integration of GIS, remote sensing, and AHP in Southern Ethiopia

Suitability Assessment Constraints of Potential Aggregate Resources Using an Integrated GIS Approach

Suitability Assessment Constraints of Potential Aggregate Resources Using an Integrated GIS Approach

GIS Integration into Geography Curriculum in Türkiye: A Case Study Evaluation

GIS Integration into Geography Curriculum in Türkiye: A Case Study Evaluation