marymuthee/elgeyo_marakwet_landslide

# Landslide Visualization in Elgeyo Marakwet, Kenya (2025) ## Sentinel-2 and MSAVI Change Detection Using Google Earth Engine ## 1. Introduction This repository documents a Google Earth Engine (GEE) workflow developed to visualize the November 2025 landslide in Chesongoch, Elgeyo Marakwet County, Kenya. The analysis uses pre- and post-event Sentinel-2 imagery and the Modified Soil Adjusted Vegetation Index (MSAVI) to assess vegetation disturbance and surface changes associated with the event. The workflow is intended as a compact example of how freely available satellite data and cloud-based processing can support rapid landslide impact assessment in data-scarce environments. ## 2. Study Area and Event Context In early November 2025, intense rainfall triggered a large landslide in the Chesongoch area of Elgeyo Marakwet, Kenya. The event resulted in loss of life and damage to housing and infrastructure. Direct field assessment in such terrain is often difficult and delayed, making satellite Earth observation a useful complementary source of information. The Area of Interest (AOI) is defined as a polygon in the GEE Code Editor representing the landslide-affected region around Chesongoch. ## 3. Data and Pre-Processing The analysis uses Sentinel-2 Harmonized Level-1C imagery available in Google Earth Engine under the collection: `COPERNICUS/S2_HARMONIZED` Two time windows are used: - Pre-event: 15 October 2025 – 31 October 2025 - Post-event: 4 November 2025 – 10 November 2025 For each period, the following preprocessing steps are applied within GEE: 1. Filter the Sentinel-2 collection to images intersecting the AOI. 2. Filter by the respective date range (pre-event or post-event). 3. Filter by cloud contamination using the `CLOUDY_PIXEL_PERCENTAGE` metadata (threshold: less than 30%). 4. Clip images to the AOI. 5. Sort by cloudiness and compute a median composite for each period. These steps provide cloud-reduced, spatially consistent pre- and post-eve …