EGU23-9795, updated on 26 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Agricultural remote sensing boosting advances in pasture monitoring: Case of Tarqui river basin

Paul Calle-Bermeo1, Andrea Urgilez-Clavijo2,3, and David Rivas-Tabares4,5
Paul Calle-Bermeo et al.
  • 1Departamento de Posgrados, Universidad del Azuay, Cuenca, Ecuador (
  • 2IERSE, Instituto de Estudios de Régimen Seccional del Ecuador, Universidad del Azuay, 010204 Cuenca, Ecuador (
  • 3Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, Madrid, Spain (
  • 4Departamento de Recursos Hídricos y Ciencias Ambientales, Universidad de Cuenca, Cuenca, Ecuador (
  • 5Universidad Politécnica de Madrid, CEIGRAM, Madrid, Spain (

Agricultural remote sensing provides valuable information on various characteristics of vegetation states and processes that cannot be simultaneously surveyed over large areas of the territory or with high frequency. Grasslands are recognized worldwide as strategic vegetation in ecosystems and especially in southern Ecuador in South America, due to their extension and importance in the configuration of the social fabric. This area presents an interesting area for studying grassland dynamics since there is a complex mosaic of natural, semi-natural and managed grasslands in which ranchers, indigenous and farmers share a bounding and fragmented landscape. This work aims to validate the use of specific remote sensing tools for monitoring grassland dynamics and in the improvement in identifying the general management rules under fragmented landscape features. To do this, indices and metrics of historical series of satellite images are used, this facilitates the development of biomass production evaluation procedures with greater spatiotemporal precision. The vegetation indices coupled with advanced window timing record sensitivity points allow correlating a set of interested plots reducing the uncertainty in similar biogeographic conditions such as soil properties, slope and vegetation management. The preliminary results show that a reduced number of sensitive monitoring points is suitable for stakeholders in monitoring local and regional areas for estimates of grassland impacts in terms of high/low production, drought, and excess rains. Thus, this work supports the advancement towards optimizations in monitoring vegetation dynamics.  Besides, it develops a common methodological framework that can be used as a reference for the monitoring of pastures in mountainous fragmented landscapes and is useful for parameterising/calibrating vegetation and hydrological models.

The authors acknowledge the support of Master in Climate Change, Agriculture and Sustainable Rural Development (MACCARD), co-funded by the Erasmus + Programme of the European Union. The authors also acknowledge support from European Union NextGenerationEU and RD 289/2021 and the support of Project No. PGC2018-093854-B-I00 of the Ministerio de Ciencia, Innovación y Universidades de España.


  • David Rivas-Tabares, Ana M. Tarquis, Ángel de Miguel, Anne Gobin, Bárbara Willaarts. Enhancing LULC scenarios impact assessment in hydrological dynamics using participatory mapping protocols in semiarid regions. Sci. Total Environ., 803, 149906, 2022.
  • Rivas-Tabares, A. de Miguel, B. Willarts and A.M. Tarquis. Self-organising map of soil properties in the context of hydrological modeling. Applied Mathematical Modelling, 88,175-189, 2020.
  • Rivas-Tabares, D. A., Saa-Requejo, A., Martín-Sotoca, J. J., & Tarquis, A. M. (2021). Multiscaling NDVI Series Analysis of Rainfed Cereal in Central Spain. Remote Sensing13(4), 568.
  • Urgilez‐Clavijo, A., de la Riva, J., Rivas‐Tabares, D. A., & Tarquis, A. M. (2021). Linking deforestation patterns to soil types: A multifractal approach. European Journal of Soil Science72(2), 635-655.

How to cite: Calle-Bermeo, P., Urgilez-Clavijo, A., and Rivas-Tabares, D.: Agricultural remote sensing boosting advances in pasture monitoring: Case of Tarqui river basin, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9795,, 2023.