Google Earth Engine App

Swiss monthly vegetation condition

Each month is compared with the same month in the other years since 2017. This removes normal seasonal change and shows only how the vegetation differs from its usual level. Green means better than usual, red means stress. The map covers all of Switzerland, farmland and forest alike. It is built from Sentinel-2 satellite images, using four vegetation indices that track greenness, chlorophyll, stress and canopy water.

Interpretation

> +2 very healthy, far above the norm
+1 to +2 healthier than usual
−1 to +1 typical condition
−2 to −1 moderately stressed
< −2 severely stressed

Note: a relative measure, not a health or drought score. Values far from zero mark conditions unusual for that place and month, in either direction. Low values may reflect drought, heat, pests, disease, storms or forest management, so read them alongside local knowledge.

Data source

Satellite

swissEO S2-SR v200 (swisstopo), Sentinel-2 Level-2A Surface Reflectance.

Sentinel-2 Level-2A Surface Reflectance (COPERNICUS/S2_SR_HARMONIZED).

Spatial resolution

10 m.

20 m.

Temporal resolution

Monthly median composites (June–August, 2017–present).

Masking

swisstopo cloud mask (clouds, thin clouds, cloud shadow), terrain shadow (illumination angle > 70°) and snow (NDSI > 0 or SCL snow).

QA60, Scene Classification Layer (SCL), Cloud Score+ (cs_cdf ≥ 0.70) and scenes with ≤20% cloud cover.

swissEO stacks more masks (e.g. terrain shadow, snow), so it looks more fragmented. The gaps are not from the forest mask.

swissEO

Copernicus

Vegetation indices

NDVI

$$\frac{\text{B8}-\text{B4}}{\text{B8}+\text{B4}} = \frac{\text{NIR}-\text{Red}}{\text{NIR}+\text{Red}}$$

How to read

Normalized Difference Vegetation Index

Values close to +1 indicate dense, healthy vegetation, values around 0 indicate sparse vegetation or bare soil, and values < 0 typically represent water, snow or clouds.

GNDVI

$$\frac{\text{B8}-\text{B3}}{\text{B8}+\text{B3}} = \frac{\text{NIR}-\text{Green}}{\text{NIR}+\text{Green}}$$

How to read

Green Normalized Difference Vegetation Index

Higher values indicate greater chlorophyll content and photosynthetic activity, while lower values indicate sparse or stressed vegetation.

NDRE

$$\frac{\text{B8A}-\text{B5}}{\text{B8A}+\text{B5}} = \frac{\text{NIR}-\text{RedEdge}}{\text{NIR}+\text{RedEdge}}$$

How to read

Normalized Difference Red Edge Index

Higher values indicate healthy, chlorophyll-rich vegetation, while lower values may indicate vegetation stress or senescence.

NDWI

$$\frac{\text{B8}-\text{B11}}{\text{B8}+\text{B11}} = \frac{\text{NIR}-\text{SWIR}}{\text{NIR}+\text{SWIR}}$$

How to read

Normalized Difference Water Index

Higher values indicate greater canopy water content, while lower values indicate drier vegetation or water stress.

Standardization

Standardized index

$$z_i = \frac{x_i - \mu_i}{\sigma_i}$$

Notation

where $x_i$ is the vegetation index value for the selected year; $\mu_i$ is the historical monthly mean calculated from all other available years for the same calendar month, leaving the selected year out so it is not compared with itself (a leave-one-out method); $\sigma_i$ is the corresponding historical monthly standard deviation.

Vegetation Condition

$$V.\text{condition} = \frac{z_{NDVI}+z_{GNDVI}+z_{NDRE}+z_{NDWI}}{n} = \frac{\sum_{i=1}^{n} z_i}{n}$$

Notation

where $n$ is the number of valid vegetation indices available for each pixel ($1 \le n \le 4$). If one or more vegetation indices are unavailable, the Vegetation Condition is calculated using only the available standardized indices.

Both versions (swissEO and Copernicus) use this same method; only the input imagery differs.

-2-1012

StressedHealthy

Compared with the same month in 2017–2026 (z-score, in σ): 0 = usual, below −2 = severely stressed.

Month

Index

Swipe

Map year

Opacity 100%

Mean inside the 50 m area of interest, one line per month.