Dr. Abraham Cardenas - Tristan
Autonomus University of San Luis Potosi
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Academic Career Length
16Years (2011-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 October 2020 in International Journal of Disaster Risk Reduction
Journal Article
ALAnqi Lin
Anqi Lin
HWHao Wu
Hao Wu
GLGuanghua Liang
Guanghua Liang
Abraham Cardenas - TristanXWXia Wu
Xia Wu
DLDan Li
Dan Li
+1
12 October 2020 in International Journal of Geographical Information Science
Journal Article
HWHao Wu
Hao WuALAnqi Lin
Anqi Lin
KCKeith Clarke
Keith Clarke
Wenzhong ShiAbraham Cardenas - TristanZTZhenfa Tu
Zhenfa Tu
The majority of spatial data provided as Volunteered Geographic Information (VGI) are roads and other linear map features. Such data have been widely used in routing and navigation, road network update, emergency response, urban planning and more. Due to the lack of cartographic standards and issues with volunteer credibility, the quality of VGI linear features remains a concern and could seriously hinder the broad application of VGI data. This research proposes a comprehensive quality assessment framework for VGI linear features which adopts factor analysis to integrate two novel quality metrics with six other commonly used metrics, and further examines the spatial autocorrelation and semantic correlation of VGI linear feature quality. The OpenStreetMap road network of Allegheny County, Pennsylvania (USA) was selected as an example to test the proposed framework. Our results suggest that the proposed metrics, Box-counting dimension difference and Link accuracy are feasible for detecting quality issues and are important supplements to the common quality metrics. The findings also show that significant spatial autocorrelation exists in spatial completeness, positional accuracy, and logical consistency. Road type such as Tertiary, Residential, Service and Link has been proven to be a typical indicator of the different quality elements for VGI linear features.
10 September 2019 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Journal Article
HWHao Wu
Hao WuXZXiang Zhang
Xiang ZhangWenzhong ShiSSShaoxian Song
Shaoxian SongAbraham Cardenas - TristanKLKui Li
Kui LiThe accuracy and robustness of plane segmentation using a region-growing algorithm remains an important and challenging topic for terrestrial laser scanning point clouds. The plane segmentation of a region-growing algorithm depends heavily on the seed point, as there are currently no universally valid criteria. This article proposes a multiscale tensor voting method (MSTVM) to determine the appropriate seed point for the region-growing algorithm. A comprehensive plane strength indicator calculated by the semivariogram model has been established to assess whether a certain point is suitably considered as a seed point or not. A point cloud containing 17, 881 points in a 400-m2 area was selected to validate the proposed algorithm. The results suggest that the scale range calculated by the semivariogram model can effectively mitigate the scale effect of the tensor voting method (TVM). The comprehensive plane strength of our proposed algorithm in seed point determination is shown to be more salient than the principal component analysis and the TVM. The findings further reveal that the utility of the MSTVM-based region-growing algorithm can achieve more accurate plane segmentation results and perform with better robustness in noisy point clouds. This allows our proposed method to be more widely applied to complex real situations.
Journal Article
María Navarro-Hernández
Roberto TomásJLJuan M Lopez-Sanchez
Juan M Lopez-SanchezAbraham Cardenas - TristanJMJordi J. Mallorqui
Jordi J. MallorquiThe San Luis Potosi metropolitan area has suffered considerable damage from land subsidence over the past decades, which has become visible since 1990. This paper seeks to evaluate the effects of groundwater withdrawal on land subsidence in the San Luis Potosi Valley and the development of surface faults due to the differential compaction of sediments. For this purpose, we applied the Coherent Pixels Technique (CPT), a Persistent Scatterer Interferometry (PSI) technique, using 112 Sentinel-1 acquisitions from October 2014 to November 2019 to estimate the deformation rate. The results revealed that the deformation areas in the municipality of Soledad de Graciano Sánchez mostly exhibit subsidence values between −1.5 and −3.5 cm/year; whereas in San Luis Potosi these values are between −1.8 and −4.2 cm/year. The PSI results were validated by five Global Navigation Satellite System (GNSS) benchmarks available, providing a data correlation between the results obtained with both techniques of 0.986. This validation suggests that interferometric derived deformations agree well with results obtained from GNSS data. The strong relationship between trace fault, land subsidence,e and groundwater extraction suggests that groundwater withdrawal is resulting in subsidence induced faulting, which follows the pattern of structural faults buried by sediments.
1 March 2021 in IOP Conference Series: Earth and Environmental Science
Conference Paper
AOA G C Ovalle
A G C Ovalle
Abraham Cardenas - TristanJAJ A Amador-Nieto
J A Amador-Nieto
RPR F Putri
R F PutriRZR A Zahra
R A Zahra
Changes in Land Use/Land Cover (LULC) generate several impacts which affect the energy balance of the Earth and, consequently, modifying the climate of a region. Accordingly, one of the most important indicators of this modification is the Land Surface Temperature (LST). The present work aims to analyze the relationship between LULC and LST, determining the influence of LULC on LST using Geographical Information Systems (GIS) and Remote Sensing (RS) techniques. The selected study area was the San Luis Potosí Basin, México (SLPB). A temporal analysis has been developed for 2007 and 2020. Satellite images from Landsat 5 TM and 8 OLI/TIRS has been used to calculate LST through a single-channel algorithm for winter and spring. LULC has been determined from a supervised classification with neural network algorithm. Finally, change rates for LULC and LST were assessed. The results indicate that an LST increase of 11 °C from 2007 to 2020 has been detected in the region. Also, results showed that covers with spare vegetation or without vegetation have the highest temperatures (29°C to 32°C). In comparison, the covers with dense vegetation and water showed the lowest temperatures (23°C to 25°C). This type of research allows addressing the LULC effects on LST, as well as prove its importance in improving land use planning systems.
1 May 2014 in Pattern Recognition Letters
Journal Article
GSGuillermo Sanchez-Diaz
Guillermo Sanchez-Diaz
GDGerman Diaz-Sanchez
German Diaz-Sanchez
MMMiguel Mora-Gonzalez
Miguel Mora-GonzalezIPIvan Piza-Davila
Ivan Piza-Davila
CACarlos Arturo Aguirre-Salado
Carlos Arturo Aguirre-SaladoAbraham Cardenas - Tristan +2
About Me
Specialist in Geospatial Sciences and Technologies, also known as Geomatics Sciences & Geoinformatics. These disciplines allow me to implement applications and analysis for various studies in the field of the evolution and growth of cities, their municipalities, their urbanization, knowledge and management of demographic problems, spatial planning and territorial ordering, the environmental protection and the use of natural resources.
Within my current projects I am analyzing trends for the management of sustainable cities (Smart Cities) regarding urban mobility, water management and distribution, integrated water management, water law and governance, atmospheric pollution, climatic variation, management of land ownership and the risks of subsidence phenomenon in urban areas.
Likewise, I analyze and develop federal expert opinions (topography, territorial boundaries, invasions and rights of way, determination of federal water zones, topographic-hydrological studies, and judicial expert opinions on geolocation and reconstruction of criminal acts). In the same way, I incursion in the studies of environmental impacts, urban and road impacts and the impacts of land use change.
For such research topics I apply the following Geospatial Sciences and Technologies: Satellite Positioning Systems (GPS-GNSS), Geographic Information Systems (GIS), Remote Sensing, Spatial Databases, Geostatistics, Spatial Analysis, Interferometry, Cartography, Photogrammetry, Topography, Geodesy, Geophy