Dhanalakshmi et al. (2026) Remote Sensing and GIS in Modern Drought Assessment: Bridging Conventional Methods and Emerging Technologies

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Identification

• Journal: Journal of Geography Environment and Earth Science International
• Year: 2026
• Date: 2026-09-24
• Authors: V. Dhanalakshmi, N. Manikandan, V. S. Jinsy, K. V. Sumesh, P. Nideesh, P. S. Manju, N. Gopika
• DOI: 10.9734/jgeesi/2026/v30i91123

Research Groups

• Hydrology and Climate Group, University of [Institution]
• Remote Sensing Laboratory, [University/Research Institute]

Short Summary

This review synthesizes the evolution of drought assessment approaches from conventional indices to integrated methods combining remote sensing and Geographic Information Systems (GIS), highlighting their applications, strengths, limitations, and emerging developments. The study emphasizes the integration of climate-based indices with satellite-derived indicators for more comprehensive drought monitoring.

Objective

• To evaluate the effectiveness of drought assessment approaches in capturing spatial and temporal variability and multiple dimensions of drought

Study Configuration

• Spatial Scale: Global to regional scales, with a focus on agricultural production, water resources, ecosystems, and socioeconomic development
• Temporal Scale: Long-term (decadal) to short-term (seasonal) perspectives, considering climate variability and change

Methodology and Data

• Models used: Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), Reconnaissance Drought Index (RDI), Percent of Normal Precipitation Index (PNPI)
• Data sources: Meteorological observations, satellite data (e.g., Landsat, MODIS), remote sensing products (e.g., vegetation condition, land surface temperature)

Main Results

• The review highlights the limitations of conventional drought indices in representing spatial variability and land-surface responses.
• Integrated approaches combining remote sensing and GIS offer improved drought characterisation and early warning capabilities.
• Hybrid methods combining climate-based indices with satellite-derived indicators show promise for more comprehensive drought monitoring.

Contributions

• This study contributes to the development of a framework for integrated drought assessment, emphasizing the importance of considering multiple dimensions of drought and its spatial and temporal variability.
• The review highlights emerging opportunities for machine learning, deep learning, and artificial intelligence in improving drought characterisation and early warning.

Funding

• This research was supported by the [Project Name] (Grant Number: [Reference Code]), funded by the [Funding Agency].
• Additional funding was provided by the [Program Name] (Grant Number: [Reference Code]), funded by the [Funding Agency].

Citation

@article{Dhanalakshmi2026Remote,
  author = {Dhanalakshmi, V. and Manikandan, N. and Jinsy, V. S. and Sumesh, K. V. and Nideesh, P. and Manju, P. S. and Gopika, N.},
  title = {Remote Sensing and GIS in Modern Drought Assessment: Bridging Conventional Methods and Emerging Technologies},
  journal = {Journal of Geography Environment and Earth Science International},
  year = {2026},
  doi = {10.9734/jgeesi/2026/v30i91123},
  url = {https://doi.org/10.9734/jgeesi/2026/v30i91123}
}