Matthieu Noucher¹ , Françoise Gourmelon², Christophe Claramunt³

Revue Internationale de Géomatique, Vol.29, No.1, pp. 9-30, 2019, DOI:10.3166/rig.2019.00074

Abstract Extensive uses of geographic information generate a data deluge on many Web infrastructures. Monitoring and analyzing the content of these platforms is still a research challenge because these can be considered as very dynamic informational and algorithmic black boxes. The concept of “geographical information observatory” appears as an appropriate mean to monitor, analyze and then provide a better understanding of the evolution of the volume and flows of the spatial data available on a specific web infrastructure. Nevertheless, its implementation raises several methodological questions discussed in this paper, starting from the experimentation of a diachronic data observation of French Spatial… More >

Anh Tu Hoang¹ , Philippe Apparicio¹, Thi-Thanh-Hien Pham²

Revue Internationale de Géomatique, Vol.29, No.2, pp. 135-158, 2019, DOI:10.3166/rig.2019.00071

Abstract The objective of this article is to assess environmental equity regarding the accessibility of parks for four population groups (children, older people, low-education individuals, and highly-educated persons) in Ho Chi Minh City (HCMC). To achieve this, two accessibility measures calculated according to network distance in GIS: the distance to the nearest park (immediate proximity) and the enhanced two-step floating catchment area method (availability based on supply and demand). Several regression models were then constructed, with the accessibility measures as dependent variables and the percentages of the four groups as independent variables. The results show that the accessibility of parks in… More >

Clément Chagnaud^1,3, Philippe Garat², Paule-Annick Davoine^1,3, Guylaine Brun-Trigaud⁴

Revue Internationale de Géomatique, Vol.30, No.1, pp. 67-83, 2020, DOI:10.3166/rig.2020.00107

Abstract We propose a multidimensional statistical analysis procedure using projection and classification methods, in order to identify coherent clusters into a set of surficial entities called dispersion areas. The methodology includes a geographical factor to build the representation space for the projection of the data. By applying this method on geolinguistic data, we are able to identify and explain new spatial patterns among a set of dispersion areas of linguistic features.

RÉSUMÉ
Nous proposons une procédure d’analyse statistique multidimensionnelle couplant des méthodes de projection et de classification pour identifier des ensembles cohérents au sein d’un corpus d’entités géographiques surfaciques que l’on… More >

Luc Merchez¹ , Hélène Mathian² , Julie Le Gall³

Revue Internationale de Géomatique, Vol.30, No.1, pp. 85-104, 2020, DOI:10.3166/rig.2020.00103

Abstract The issue of food and characterization of food environments has been the subject of many studies and methodological developments to report and account for accessibility differentials. In the United States most studies are interested in this question with regard to health issues and have led to identify “food deserts”. As part of a project for which the main goal is to explore the transferability of this notion to other spaces, with a broader perspective on spatial justice, we propose a generic framework to shed light on this highly spatial question, generally addressed by qualitative (surveys, interviews) or quantitative methods (GIS-based… More >

Rami Sameer Ahmad Al Kloub^*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2801-2820, 2022, DOI:10.32604/cmc.2022.027847

Abstract Mainland China has a poor distribution of meteorological stations. Existing models’ estimation accuracy for creating high-resolution surfaces of meteorological data is restricted for air temperature, and low for relative humidity and wind speed (few studies reported). This study compared the typical generalized additive model (GAM) and autoencoder-based residual neural network (hereafter, residual network for short) in terms of predicting three meteorological parameters, namely air temperature, relative humidity, and wind speed, using data from 824 monitoring stations across China’s mainland in 2015. The performance of the two models was assessed using a 10-fold cross-validation procedure. The air temperature models employ basic… More >

Rami Sameer Ahmad Al Kloub^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5151-5165, 2022, DOI:10.32604/cmc.2022.024309

Abstract Flood disasters can be reliably monitored using remote sensing photos with great spatiotemporal resolution. However, satellite revisit periods and extreme weather limit the use of high spatial resolution images. As a result, this research provides a method for combining Landsat and MODIS pictures to produce high spatiotemporal imagery for flood disaster monitoring. Using the spatial and temporal adaptive reflectance fusion model (STARFM), the spatial and temporal reflectance unmixing model (STRUM), and three prominent algorithms of flexible spatiotemporal data fusion (FSDAF), Landsat fusion images are created by fusing MODIS and Landsat images. Then, to extract flood information, utilize a support vector… More >