L’action sur les territoires face au défi d’une temporalité ouverte. L’improvisation comme modèle pour l’action aménagiste ? by Lisa Levy

Get full text

Eco-Spatial Modeling of Two Giant Flying Squirrels (Sciuridae: <i>Petaurista</i>): Navigating Climate Resilience and Conservation Roadmap in the Eastern Himalaya and Indo-Burma Bio... by Imon Abedin, Manokaran Kamalakannan, Tanoy Mukherjee, Hilloljyoti Singha, Dhriti Banerjee, Hyun-Woo Kim, Shantanu Kundu

Get full text

Predicting species distributions in the open ocean with convolutional neural networks by Morand, Gaétan, Joly, Alexis, Rouyer, Tristan, Lorieul, Titouan, Barde, Julien

“…These findings show the adequacy of deep learning for species distribution modelling in the open ocean. Additionally, this purely correlative model was then analysed with explicability tools to understand which variables had an influence on the model’s predictions. …”
Get full text

Relationships between abundances of breeding ducks and attributes of Canadian prairie wetlands by Blake Bartzen, Kevin W. Dufour, Mark T. Bidwell, Michael D. Watmough, Robert G. Clark

“…In regions where duck densities were high, there were more ducks per pond; conversely, there were fewer ducks per pond in regions where pond densities were high, indicating that mechanisms influencing local habitat use were, in part, mediated by processes occurring at larger spatial scales. Although models explained small amounts of variation of duck abundance on a per pond basis, these models explained more variation when results were aggregated to the level of survey segment, indicating reasonable performance of models for estimating duck abundance over specific areas with known pond areas. …”
Get full text

Spatial correlations and risk transmission of virtual water flow at city scale: A case study of the Yellow River Basin by Jingjing Yang, Zhong Ma, Weijing Ma, Xingxing Niu, Ting Mao

Get full text

Prediction of the change in suitable growth area of Sabina tibetica on the Qinghai-Tibetan plateau using MaxEnt model by Xiaoxiong Li, Dongsheng Yang, Jingjie Wang, Gang Pan

“…We employed the MaxEnt model with 10 bioclimatic and topographic variables to predict its distribution shifts under RCP4.5 and RCP8.5 scenarios for 2050 and 2070. …”
Get full text

A Convolutional Neural Network-Weighted Cellular Automaton Model for the Fast Prediction of Urban Pluvial Flooding Processes by Jiarui Yang, Kai Liu, Ming Wang, Gang Zhao, Wei Wu, Qingrui Yue

“…Abstract Deep learning models demonstrate impressive performance in rapidly predicting urban floods, but there are still limitations in enhancing physical connectivity and interpretability. …”
Get full text

Enhancing landslide-scale rainfall threshold predictive modeling for rainfall-induced red-bed soft rock landslide occurrence using a stock-taking approach by Qi Li, Zidan Liu, Ziyu Tao

“…Using a Bayesian modeling framework for predicting the probability occurrence of landslides triggered by a rainfall event above the defined rainfall threshold, we found that high intensity rainfall events play a more important role in triggering R-SRLs than their long duration.…”
Get full text

Using Earth observation to support the predictive accuracy of species distribution models in ecological restoration: a case study of Poland beavers (Castor fiber) by H. A. Cheriyanda Raveendra, L. Picco, F. Pirotti, F. Pirotti

Get full text

Generation driven understanding of localized 3D scenes with 3D diffusion model by Hao Sun, Junping Qin, Zheng Liu, Xinglong Jia, Kai Yan, Lei Wang, Zhiqiang Liu, Shaofei Gong

“…In addition to accurately predicting the distribution of the noise tensor, the framework significantly enhances the understanding of localized scenes by effectively integrating spatial context information. …”
Get full text

Soil Erosion Prediction Using Morgan-Morgan-Finney Model in a GIS Environment in Northern Ethiopia Catchment by Gebreyesus Brhane Tesfahunegn, Lulseged Tamene, Paul L. G. Vlek

“…Even though scientific information on spatial distribution of hydrophysical parameters is critical for understanding erosion processes and designing suitable technologies, little is known in Geographical Information System (GIS) application in developing spatial hydrophysical data inputs and their application in Morgan-Morgan-Finney (MMF) erosion model. …”
Get full text

Flexible movement kernel estimation in habitat selection analyses with generalized additive models by Rafael Arce Guillen, Jennifer Pohle, Florian Jeltsch, Manuel Roeleke, Björn Reineking, Natasha Klappstein, Ulrike Schlägel

“…In addition, including a bivariate tensor product in the model leads to a better uncertainty estimation of the model parameters and lower mean‐squared error of the model predictions. …”
Get full text

STFGCN: Spatio-Temporal Fusion Graph Convolutional Networks for Subway Traffic Prediction by Xiaoxi Zhang, Zhanwei Tian, Yan Shi, Qingwen Guan, Yan Lu, Yujie Pan

“…Experimental results on the Hangzhou Metro&#x2019;s inbound and outbound passenger flow datasets demonstrate that the STFGCN model exhibits significant superiority over baseline models and shows excellent performance in metro passenger flow prediction. …”
Get full text

Estimation and prediction of water conservation in the upper reaches of the Hanjiang River Basin based on InVEST-PLUS model by Pengtao Niu, Zhan Wang, Jing Wang, Yi Cao, Peihao Peng

“…With the gradual prominence of global water shortage and other problems, evaluating and predicting the impact of land use change on regional water conservation function is of great reference significance for carrying out national spatial planning and environmental protection, and realizing land intelligent management. …”
Get full text

A Novel Short‐Term Prediction Model for Regional Equatorial Plasma Bubble Irregularities in East and Southeast Asia by Xiukuan Zhao, Guozhu Li, Haiyong Xie, Lianhuan Hu, Wenjie Sun, Yi Li, Guofeng Dai, Jianfei Liu, Yu Li, Baiqi Ning, Michi Nishioka, Septi Perwitasari, Prasert Kenpankho

“…For 60‐min prediction, the STEP model can still achieve reasonable accuracy with an RMSE of 0.110 TECU/min and an R2 of 0.482, showing significant improvement over traditional models. …”
Get full text

A cellular automata coupled multi-objective optimization framework for blue-green infrastructure spatial allocation by Qinghe Hou, Hanwen Xu, Mingkun Xie, Pingjia Luo, Yuning Cheng

“…In contrast to existing methods that primarily rely on semi-distributed models such as SWMM, the proposed framework advances spatial precision by explicitly modelling hydrological processes at the grid level and allowing for fine-grained spatial allocation of BGI elements. …”
Get full text

Predicting Urban Vitality at Regional Scales: A Deep Learning Approach to Modelling Population Density and Pedestrian Flows by Feifeng Jiang, Jun Ma

“…Applied to New York City, UVPN leverages diverse urban morphological features such as streetscape attributes and land use patterns to predict continuous vitality distributions. The model outperforms existing architectures, achieving reductions of 34.03% and 38.66% in mean squared error for population density and pedestrian flow predictions, respectively. …”
Get full text

Predicting the needs of people living with a disability using the two-level logit-skewed exponential power model by Abayomi Ajayi, Olaniyi Olayiwola, Fadeke Apantaku, Idowu Osinuga, Oluwaseun Wale-Orojo

“…Cartograms were used to determine the spatial distribution for the proportion of doctor’s visit and cost using the predicted values. …”
Get full text

Spatial targeting of Screening + Eave tubes (SET), a house-based malaria control intervention, in Côte d'Ivoire: A geostatistical modelling study. by Tiago Canelas, Edward Thomsen, Daniel McDermott, Eleanore Sternberg, Matthew B Thomas, Eve Worrall

Get full text

The Sloping Mire Soil-Landscape of Southern Ecuador: Influence of Predictor Resolution and Model Tuning on Random Forest Predictions by Mareike Ließ, Martin Hitziger, Bernd Huwe

“…The recursive partitioning algorithm Random Forest was used to predict the spatial water stagnation pattern and the thickness of the organic layer from terrain attributes. …”
Get full text