Murasheva et al. (2025) Information support for monitoring of agricultural lands based on the remote sensing and geoinformation technologies in Kon tum province of the Republic of Vietnam

Identification

• Journal: Zemleustrojstvo, kadastr i monitoring zemel' (Land management, cadastre and land monitoring)
• Year: 2025
• Date: 2025-09-12
• Authors: A A Murasheva, Pham Chi Kong
• DOI: 10.33920/sel-04-2509-09

Research Groups

• Department of Land Resources and Real Estate Management, State University of Land Management, Moscow, Russia

Short Summary

This paper develops a methodology for monitoring agricultural and environmental lands in Kon Tum province, Vietnam, using remote sensing and GIS technologies via Google Earth Engine, demonstrating its effectiveness for sustainable resource management.

Objective

• To develop a methodology for information support for monitoring agricultural and environmental resources in Kon Tum province, Vietnam, based on the Google Earth Engine (GEE) platform.

Study Configuration

• Spatial Scale: Kon Tum province, Vietnam (regional scale).
• Temporal Scale: Multi-temporal analysis, with algorithms for calculating indices across various time intervals to show spatio-temporal changes.

Methodology and Data

• Models used: Automated system for calculating and analyzing Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Land Surface Temperature (LST), and Temperature Vegetation Dryness Index (TDVI) within the Google Earth Engine (GEE) platform.
• Data sources: Remote sensing data, including multispectral satellite imagery, accessed and processed via Google Earth Engine.

Main Results

• An automated system for calculating and analyzing NDVI, NDMI, and LST indices was developed, enabling the assessment of vegetation status, soil moisture, and land surface temperature characteristics.
• A comprehensive system for monitoring droughts and land use changes, specifically for agricultural lands, was established.
• The developed methodology effectively addresses the scarcity of remote sensing data for the study region by providing algorithms for index calculation across various temporal intervals.
• The findings confirm the efficacy of using Google Earth Engine for sustainable management of agricultural and environmental resources in the region.

Contributions

• Presentation of a novel methodology for information support for agricultural land monitoring in Kon Tum province, Vietnam, leveraging remote sensing and GIS technologies.
• Development of an automated system within Google Earth Engine for calculating multiple key indices (NDVI, NDMI, LST, TDVI) to assess vegetation, soil moisture, and temperature, and to monitor droughts and land use changes.
• The methodology is designed to be adaptable and applicable to other regions, particularly those with limited remote sensing data, by offering flexible algorithms for various temporal intervals.

Funding

• Not specified in the provided text.

Citation

@article{Murasheva2025Information,
  author = {Murasheva, A A and Kong, Pham Chi},
  title = {Information support for monitoring of agricultural lands based on the remote sensing and geoinformation technologies in Kon tum province of the Republic of Vietnam},
  journal = {Zemleustrojstvo, kadastr i monitoring zemel' (Land management, cadastre and land monitoring)},
  year = {2025},
  doi = {10.33920/sel-04-2509-09},
  url = {https://doi.org/10.33920/sel-04-2509-09}
}