Quantifying temporal niche abundance through environmental predictability and seasonality: A novel framework for biodiversity assessment by Lei Huang, Futing Zhao, Shuwen Guo, Li Liu, Rongguang Zhang

“…Focusing on the southern foothills of Qilian Mountains, we employed Colwell’s indices and wavelet analysis to analyze seasonality and predictability patterns of temperature and precipitation. The temporal niche abundance derived from each environmental parameter was then synthesized to reveal spatial patterns of environmental suitability and stress for biodiversity from a niche perspective. …”
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A comprehensive framework for multi-modal hate speech detection in social media using deep learning by R. Prabhu, V. Seethalakshmi

“…CNNs extract key spatial features in visual tasks, while LSTMs process video sequences to capture evolving visual patterns. …”
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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

“…Therefore, it is essential to analyze the characteristics and spatial patterns of street property crimes in the built environment to make cities safe. …”
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La Réunion : une « terre de projets » dans les impasses du développement ? by Thierry Simon

“…Crises to conflicts, recurring forms, as in their spatial patterns, Reunion remains locked in an impasse multiple, economic and societal. …”
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Examining the Variability in Planetary Boundary Layer Height over Thailand: Correlations with ENSO and Aerosol Optical Depth by Sirapong Sooktawee, Khwanruthai Renuhom, Siriwan Kaewket, Aduldech Patpai, Pramet Kaewmesri, Thongchai Kanabkaew, Pichnaree Lalitaporn

“…EOF analysis reveals three interesting principal components (DecPC2, JanPC3, and FebPC2) that account for 11.3–23.5% of the total PBLH variance and that exhibit spatial correlation patterns resembling ENSO-induced patterns. …”
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Examining the Variability in Planetary Boundary Layer Height over Thailand: Correlations with ENSO and Aerosol Optical Depth by Sirapong Sooktawee, Khwanruthai Renuhom, Siriwan Kaewket, Aduldech Patpai, Pramet Kaewmesri, Thongchai Kanabkaew, Pichnaree Lalitaporn

“…EOF analysis reveals three interesting principal components (DecPC2, JanPC3, and FebPC2) that account for 11.3–23.5% of the total PBLH variance and that exhibit spatial correlation patterns resembling ENSO-induced patterns. …”
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Analysis of Points of Interest in Hsinchu Old City Blocks Using Space Syntax by Shaofu Li

“…Modern cities’ grid patterns and straight roads connect various scenic spots. …”
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Daily Mobility in Metropolitan Areas by Marcela Soto Caro

“…A range of research methods has been used to examine the student’s daily mobility patterns in this study. In order, these methods include: (1) Documentary and other secondary data which has been used to understand changes to existing metropolitan structure over three decades; to understand urban spatial conditions related to urban mobility, higher education and urban development, and explain the spatial distribution of Traditional Universities within the VMA; (2) Empirical methods including face-to-face structured interviews with higher education students and an extensive internet survey have been use to enrich the data gathered in the first phase, finally (3) data drawn from the initial survey work, together with data gathered from the in-depth interviews have been combined with mapping other secondary data to confirm and extend existing sources. …”
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Assessment of the Spatiotemporal Evolution Characteristics and Driving Factors of Ecological Vulnerability in the Hubei Section of the Yangtze River Economic Belt by Shuai Wu, Guanzhong Zeng, Jie Sun, Xiaohuang Liu, Xuanhui Li, Qinghua Zeng, Shijie Gu

“…The Theil index decreased and then rose, the degree of spatial agglomeration was floating in a “V” shape, and the spatial pattern of vulnerability was essentially the same in the hot- and cold-spot areas. …”
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Spatiotemporal Variation and Driving Mechanisms of Carbon Budgets in Territorial Space for Typical Lake-Intensive Regions in China: A Case Study of the Dongting Lake Region by Suwen Xiong, Zhenni Xu, Fan Yang, Chuntian Gu

“…Construction land was the most significant carbon emission source in territorial space. Spatially, carbon budgets exhibit a radial pattern, with high values concentrated in plains near water bodies, gradually decreasing inland. …”
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A Study on Carbon Fixation Capacity and Its Influencing Factors Based on InVEST Model at Wuhu City by Xia Quansheng, Hong Xin, Gui Xiang, Shen Gaoping, Deng Liang, Yao Zhenhai, Peng Peng, Chu Yunzhi, Xu Sheng, Xu Wei

“…[Objective] The spatial and temporal distribution pattern of carbon storage at Wuhu City, Anhui Province from 2011 to 2021 were analyzed, and the influence of ecological environmental factors, topographic factors, meteorological factors, and land use degree on carbon sequestration capacity were determined in order to provide a reference for land resource management and green agricultural development at Wuhu City. …”
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Wave Generation by a Finite Baffle Array in Application to Beam-Forming Analysis by Yuriy TASINKEVYCH

“…Some illustrative numerical examples presenting the far-field radiation pattern and wave-beam steering are given.…”
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Wave Activity in Jupiter's North Equatorial Belt From Near‐Infrared Reflectivity Observations by Rohini S. Giles, Glenn S. Orton, Andrew W. Stephens, Michael H. Wong, Patrick G. J. Irwin, James A. Sinclair, Fachreddin Tabataba‐Vakili

“…Abstract High spatial resolution images of Jupiter at 1.58–2.28 μm are used to track and characterize a wave pattern observed in 2017 at a planetocentric latitude of 14°N. …”
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Unlocking the potential of ChatGPT in detecting the XCO2 hotspot captured by orbiting carbon observatory-3 satellite by Young-Seok Hwang, Stephan Schlueter, Biswajeet Pradhan, Jung-Sup Um

“…ChatGPT exhibited performance comparable to ArcGIS in both z-score statistics and spatial distribution patterns of XCO2 hot and cold spots. …”
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Evolutionary analysis of landscape ecological risk in Baili Rhododendron National Forest Park. by Yin Yu, Wengang Cui, Suihua Liu, Ting Yu, Yang Song

“…The results show that (1) the landscape pattern changed visibly from 2000 to 2020, the comprehensive land-use dynamics increased from 8.53% to 9.66%, and the land use dynamics are greatest and change most dramatically on construction sites; (2) the landscape ecological risk level of the study area as a whole showed a declining trend, and 96.82% of the ecological risk plot index decreased, and the risk distribution was dominated by lower risk, medium risk and higher risk areas; (3) landscape ecological risk was spatially positively correlated across all time periods, and the spatial aggregation was gradually weakened, with the distribution of LH and HL areas dispersed and the distribution of HH and LL areas concentrated. …”
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The Impact of Road Functions on Road Congestions Based on POI Clustering: An Empirical Analysis in Xi’an, China by Hui Zhu, Kaiqi Zhang, Changjun Wang, Lujin Jia, Siyu Song

“…Urban land use patterns have a significant correlation with urban traffic congestion. …”
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Urban change detection with airborne LiDAR for hostilities’ impact estimation: a case study of Kharkiv by Sergiy V. Kostrikov, Denys S. Serohin

“…Statistical characteristics of computed urban changes reveal distinct spatial patterns, enabling differentiation between the routine urban development observed in Tallinn, Estonia, and the war-affected Kharkiv. …”
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Quantifying Visual Navigation in Campus Open Spaces Using a Computer Vision Model by Nabil Mohareb, Abdelaziz Ashraf

“…Additionally, the analysis is enhanced by integrating geographic information systems (GISs) for spatial analysis, allowing us to identify navigation and visual engagement patterns. …”
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Spatio-temporal characteristics and analysis of influencing factors of inclusive green growth in China’s oil and gas resource industry by Xiangyu Sun, Yanqiu Wang

“…Key observations include: (1) IGGOG exhibited a general upward trajectory, albeit with periodic fluctuations. (2) IGGOG’s spatial distribution adopts a “periphery-center” pattern, with pronounced spatial disparities. (3) Significant positive spatial autocorrelation in IGGOG is predominantly evident in high-high (HH) and low-low (LL) clusters. (4) Factors such as industrial agglomeration, industrial structures upgrading, urbanization rates, digital economy, and openness positively correlate with IGGOG, whereas green burdens adversely affect it. …”
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Co-occurrence and abundance of pollinators and pests in horticultural systems in Africa using an integrated Earth observation-based approach by Grace Rebecca Aduvukha, Elfatih M. Abdel-Rahman, Bester Tawona Mudereri, Arthur W. Sichangi, Godfrey Ouma Makokha, H. Michael G. Lattorff, Samira A. Mohamed, Tobias Landmann, Henri E. Z. Tonnang, Thomas Dubois

“…Thus, this study focused on investigating the influence of cropping patterns on the spatial distribution of pollinators (Apis mellifera, Hymenoptera other than A. mellifera, and Syrphidae), flower visitors (Calliphoridae), and pests, i.e. fruit fly (Bactrocera dorsalis) and false codling moth (Thaumatotibia leucotreta) of the avocado, a pollinator-dependent crop. …”
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