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February 26, 2026Discover Hazards0 citationsOpen Access

An investigation of terrain recovery by analyzing the Puthumala landslide-impacted region in Kerala, India, utilizing both pre and post disaster NDVI and land surface temperature data

SRSandra RoseGPG. S. PradeepHVH. Vijith

Key Points

  • The aim is to analyze the spatial and temporal dynamics of the Puthumala landslide-impacted region using NDVI and LST data.
  • Utilized Landsat 8 OLI satellite images for NDVI and LST data.
  • Conducted analyses over pre-landslide (2017-2019) and post-landslide (2020-2024) periods.
  • Employed spatial statistics and linear regression analyses to assess changes.
  • Field investigations complemented satellite data to evaluate ecological recovery.
  • Significant decreases in NDVI and LST values were observed in the year following the landslide.
  • Gradual recovery of vegetation was noted in subsequent years.
  • An inverse relationship between NDVI and LST persisted, weakening initially after the landslide, then strengthening as recovery progressed.
  • Emergence of various plant types, including herbs, wetlands, and ferns, indicated successful ecological recovery.
  • Resurgence of butterfly species indicated a thriving habitat post-landslide.

Abstract

This research investigates the spatial and temporal dynamics of the Puthumala landslide region through the use of satellite imagery and geographic information systems (GIS). The study specifically analyzes vegetation characteristics and surface temperature before and after the landslide event, utilizing temporal datasets (pre-landslide periods of 2017–2019 and post-landslide periods of 2020–2024) of the normalized difference vegetation index (NDVI) and land surface temperature (LST) derived from Landsat 8 OLI's visible (Bands 4 and 5) and thermal (Band 10) imagery. To assess the changes in vegetation and surface temperature over both spatially and temporarily, a set of analytical techniques, such as spatial statistics, cross-sectional profiles, as well as correlation and linear regression analyses were utilised. The findings reveal significant changes in NDVI and LST values surrounding the landslide, with a notable decrease in these metrics during the year following the event. However, subsequent years indicate a gradual recovery of vegetation, highlighting ongoing land stabilization processes. Statistical analyses demonstrate a persistent inverse relationship between NDVI and LST, which weakened after the landslide but showed signs of strengthening as vegetation began to recover. The spatial and statistical evaluations suggest a progressive stabilization of the land, marked by the emergence of various plant types, including herbaceous plants, wetlands, and grasslands, alongside the establishment of lichens, mosses, and ferns. Field investigations further indicate that the resurgence of plant life has led to the reappearance of butterfly species, serving as indicators of a thriving habitat and successful ecological recovery post-landslide. In conclusion, the methodologies and datasets employed in this research are applicable to areas affected by landslides, facilitating the assessment of current conditions and informing decisions aligned with sustainable land use practices, encapsulated in the principle of "build back better” along with the Sustainable Development Goals (SDGs) SDG 11 (Sustainable cities and communities), SDG 13 (Climate Action), and SDG 15 (Life on Land).

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Cite This Study

Rose et al. (2026) studied this question.

synapsesocial.com/papers/699fe3af95ddcd3a253e7c10https://doi.org/10.1007/s44475-026-00016-5
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