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Open Data Cube for Natural Resources Mapping in Mexico

9 pagesPublished: November 4, 2019


In recent years, the efforts to enhance the analysis of Earth’s surface with satellite imagery have forced the scientific community to develop different techniques and methodologies. The Open Data Cube aims to provide tools to execute multi-temporal analysis and get accurate products, excluding low-quality pixels in small or large areas of study with an accuracy subject to the resolution of the data used for the analysis. This means that we can make use of the full potential of Earth observation data available from satellite data providers, in this document we take a closer look at Landsat Imagery and its applications. The beginning of the implementation of the Open Data Cube platform began in 2018, positioning itself as a valuable source of spatial data for Natural Resources projects in INEGI and seeks to support the decision-making process based on territorial analyzes with great certainty. The use of this technological solution represents a great leap between the traditional visual interpretation of raster data and the automated processing of data in time series.

Keyphrases: Landsat ARD, Multi-temporal classification, Open Data Cube, satellite imagery, space-time analysis

In: Oscar S. Siordia, José Luis Silván Cárdenas, Alejandro Molina-Villegas, Gandhi Hernandez, Pablo Lopez-Ramirez, Rodrigo Tapia-McClung, Karime González Zuccolotto and Mario Chirinos Colunga (editors). Proceedings of the 1st International Conference on Geospatial Information Sciences, vol 13, pages 70--78

BibTeX entry
  author    = {Jos\textbackslash{}'e Luis Ornelas De Anda and Juan Carlos Camacho P\textbackslash{}'erez and Hugo Alfredo S\textbackslash{}'anchez Miranda},
  title     = {Open Data Cube for Natural Resources Mapping in Mexico},
  booktitle = {Proceedings of the 1st International Conference on Geospatial Information Sciences},
  editor    = {Oscar S. Siordia and Jos\textbackslash{}'e Luis Silv\textbackslash{}'an C\textbackslash{}'ardenas and Alejandro Molina-Villegas and Gandhi Hernandez and Pablo Lopez-Ramirez and Rodrigo Tapia-McClung and Karime Gonz\textbackslash{}'alez Zuccolotto and Mario Chirinos Colunga},
  series    = {Kalpa Publications in Computing},
  volume    = {13},
  pages     = {70--78},
  year      = {2019},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2515-1762},
  url       = {},
  doi       = {10.29007/d19p}}
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