Pavement Deterioration Modeling of the International Roughness Index Based on Fuzzy Logic Approach by Abdualmtalab Ali, Abdalrhman Milad, Hussein ALMufargi, Nur Izzi Md Yusoff

“…This paper strives to construct a system rooted in fuzzy logic to appraise the requirements for maintenance and (IRI) evaluation within a network of pavement roads. This system utilizes data on pavement distress collected from the United States and Canada to achieve its objectives. …”
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Factors affecting woody plant species diversity of fragmented seasonally dry oak forests in the Mixteca Alta, Oaxaca, Mexico by María de los Remedios Aguilar-Santelises, Rafael F. del Castillo

“…The density ofstumps and roads were used as estimators of disturbance intensity. …”
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Inland wetlands mapping and vulnerability assessment using an integrated geographic information system and remote sensing techniques by C.E. Akumu, J. Henry, T. Gala, S. Dennis, C. Reddy, F. Tegegne, S. Haile, R.S. Archer

“…A weighted geospatial vulnerability analysis was developed using variables such as roads, land cover/ land use (developed and agricultural areas) and climate data (temperature) to predict potentially vulnerable inland wetland types. …”
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Study on Change of Landscape Pattern Characteristics of Comprehensive Land Improvement Based on Optimal Spatial Scale by Baoping Feng, Hui Yang, Yarong Ren, Shanshan Zheng, Genxiang Feng, Yuwei Huang

“…This scale can reflect the spatial variability of the landscape pattern in the study area and is the most suitable analysis range. (3) The fragmentation degree of paddy fields as landscape matrix decreased and the landscape dominance degree increased in the comprehensive land improvement; the degree of fragmentation of irrigated land and agricultural land for facilities increased, the aggregation of land for construction increased, the dominance degree of the pond surface decreased, and the overall landscape diversity of each mosaic decreased; the landscape heterogeneity of ditches, rural roads, forest and grassland corridors was weakened, and the ecosystem service function was weakened. (4) The trend of increased fragmentation, simplification of landscape types, and decreased diversity presented by the landscape pattern clearly indicates that the landscape pattern of the study area has been seriously damaged to some extent under the influence of human activities. …”
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Identifying Priority Areas for the Indian Leopard (Panthera pardus fusca) Within a Shared Landscape by Aparna Kolekar, Kimberley Hockings, Kristian Metcalfe, Sanjay Gubbi

“…Environment variables were chosen to reflect land use, climatic, topographic, and human disturbances that could affect habitat selection at a resolution of 0.1 km2. …”
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PENGARUH BANGKITAN PERJALANAN PEMUKIMAN BARU TERHADAP JARINGAN JALAN AKSES (Studi Kasus Perumahan Bukit Semarang Baru, Mijen Kota Semarang) by Agung Sutarto

“…From regression analysis found that variables that influence significantly on the number of trips is the number of families, the number of family members working and family income. …”
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HAZARD AND ACTIVITY OF LANDSLIDES ON THE TERRITORY OF THE CAUCASIAN MINERAL WATERS by V. V. Razumov, K. S. Viskhadzhieva, N. D. Bogdanova, A. V. Lysenko

“…Both factors are characterized by spatial and temporal variability, which determines the spatial and temporal variability of landslide manifestations. …”
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Cost Effectiveness of Chip Seal and Hot Mix Asphalt Pavements by Bojan Žlender, Cahit Gürer, Rok Varga, Primož Jelušič

“…An analytical model was employed to design unpaved roads and determine the required thickness of unbound layers. …”
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Decoding dynamic landslide hazard processes for a massive refugee camp in Bangladesh by Dewan Mohammad Enamul Haque, Ritu Roy, Sumya Tasnim, Shamima Ferdousi Sifa, Suniti Karunatillake, A.S.M. Maksud Kamal, Juan M. Lorenzo

“…Anthropogenic modifications, such as distance from roads, land-use/NDVI changes, and rainfall, are treated as dynamic factors, while other factors are considered static predisposing conditions. …”
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Harnessing geospatial tools to map the forest fire: Risk zonation in Pauri Garhwal, Uttarakhand by Oishi Bhattacharya, Suman Sinha, Varun Narayan Mishra, Maya Kumari, Fahdah Falah Ben Hasher, Jonmenjoy Barman, Mohamed Zhran

“…Climatic and biotic parameters, including land surface temperature (LST), normalized difference vegetation index (NDVI), normalized differencewater index (NDWI), and normalized difference moisture index (NDMI), were integrated with topographical variables such as slope, aspect, and elevation. Additionally, proximity to anthropogenic factors like roads and settlements was analyzed to enhance risk assessment accuracy. …”
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Leisure physical activity and barriers perceived by homosexual men in a mid-sized city in Southeast Brazil by José Humberto Alves, Fernanda Machain Silva Tannús, Karina de Almeida Brunheroti, Jeffer Eidi Sasaki, Camila Bosquiero Papini

“…The level of physical activity was not associated with demographic variables or perceived health. The most practiced types of physical activity were walking (46.8%) and resistance training (46.8%), while the most cited locations were private gyms (56.5%) and public roads (40.3%). …”
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Enhanced Rapid Mangrove Habitat Mapping Approach to Setting Protected Areas Using Satellite Indices and Deep Learning: A Case Study of the Solomon Islands by Hyeon Kwon Ahn, Soohyun Kwon, Cholho Song, Chul-Hee Lim

“…By incorporating spatial variables such as distance from roads and urban centers, along with mangrove area, this study proposes priority mangrove protection areas. …”
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Machine Learning for Decision Support and Automation in Games: A Study on Vehicle Optimal Path by Gonçalo Penelas, Luís Barbosa, Arsénio Reis, João Barroso, Tiago Pinto

“…A vehicle driving game is implemented, in which the goal is to reach a certain target within a small number of steps, while respecting the boundaries of the roads. Our study compares Proximal Policy Optimization (PPO) and Soft Actor–Critic (SAC) in terms of learning efficiency, decision-making accuracy, and adaptability. …”
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Using Street View Images to Examine the Impact of Built Environment on Street Property Crimes in the Old District of CA City, China by Xiliang Chen, Gang Li, Muhammad Sajid Mehmood, Annan Jin, Mengjia Du, Yutong Xue

“…There are two explanations for the positive and negative correlations of some environmental variables with a crime before dawn, daytime, and nighttime. …”
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Human-caused ignition pathways under climate change scenarios in Eastern Spain by Pere Gelabert, Adrián Jiménez-Ruano, Jaime Ribalaygua, Luís Torres, Marcos Rodrigues

“…Our approach combines historical ignition records of fires larger than 5 ha (849 ignitions during 1998–2016) in eastern Spain and geospatial information regarding ignition variables. The method leverages the Random Forest algorithm to train a spatially-explicit model of ignition probability, combining distance to wildland interfaces and roads, population density, fuel types, and daily estimates of dead fuel moisture content (DFMC). …”
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Hard and soft climate-smart investments in aquaculture in Bangladesh: Conditioning factors and decision space by T.S. Amjath-Babu, Peerzadi Rumana Hossain, Sanzida Akhter Anee, Essam Yassin Mohammed, Timothy J. Krupnik

“…Climate change and its’ associated weather variabilities and extremes are posing significant risks to aquaculture productivity, particularly in the coastal regions of Bangladesh. …”
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The Impact of Noise on Agricultural Tractor Operator in Relation to Certain Operational Parameters: An Analytical Hierarchy Process (AHP) Approach by Željko Barač, Ivan Plaščak, Dorijan Radočaj, Mladen Jurišić

“…By conducting a one-way ANOVA on the mean values of the dependent variables grouped by AHP, significant differences in noise were found. …”
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Adoption of sustainable agricultural intensification practices: assessing the role of institutional and socio-economic factors amongst smallholder farmers by Enos Katya Kule, David Agole, Alfred Obia, Daniel Micheal Okello, Walter Odongo

“…Institutional factors i.e., group membership, access to all-weather roads, credit, and extension information were the significant predictors of the adoption and the adoption intensity of SAIPs. …”
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Applying Machine Learning Algorithms for Spatial Modeling of Flood Susceptibility Prediction over São Paulo Sub-Region by Temitope Seun Oluwadare, Marina Pannunzio Ribeiro, Dongmei Chen, Masoud Babadi Ataabadi, Saba Hosseini Tabesh, Abiodun Esau Daomi

“…This study employs four ML algorithms—differential evolution (DE), naïve Bayes (NB), random forest (RF), and support vector machines (SVMs)—to develop flood susceptibility models using 16 predictor variables. Key categorical factors influencing flood susceptibility included topographical, anthropogenic, and hydrometeorological, particularly elevation, slope, NDVI, NDWI, and distance to roads. …”
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Adoption of sustainable agricultural intensification practices: assessing the role of institutional and socio economic factors amongst smallholder farmers. by Kule, Enos Katya, Agole, David, Obia, Alfred, Okello, Daniel Micheal, Odongo, Walter

“…Institutional factors i.e., group membership, access to all-weather roads, credit, and extension information were the significant predictors of the adoption and the adoption intensity of SAIPs. …”
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