This article covers the following index layers:
In addition to the red, green, and blue bands used to create the truecolor layers, we also pull other bands from our public imagery sources. These bands, or wavelengths, can provide additional insights into changing conditions on the ground. We provide four index layers in Lens, meaning that they are calculated from remote sensing data reflectance values and can be quantified. These relate to vegetation vigor and water presence on the landscape. These indices are available on a weekly time scale in the case of Sentinel-2 data, about every 16 days in the case of Landsat 8, and less frequently for NAIP data. Selecting an index layer from the Layer dropdown will display the corresponding captures in the Date dropdown.
Vegetation vigor is a measure of photosynthetic activity, or how much plant growth is occurring. It's derived from the Normalized Difference Vegetation Index (NDVI) using visible and near-infrared reflectance detected by satellite or aerial sensors. The vegetation layer ranges from 0 to 1, with low values indicating no vegetation present in white or yellow and high values showing areas with vigorous vegetation in dark green. This data provides a reliable way to evaluate vegetation health and changes over time.
Sentinel-2 Surface Water
Sentinel-2 Surface Water is derived from the Normalized Difference Water Index (NDWI) and shows which parts of a property have standing water present. Values range from -0.1 to 0.4, where low values show dry land and higher values in blue show areas with water, such as rivers or ponds.
Sentinel-1 Surface Water (Radar)
This Surface Water dataset is derived from ESA Sentinel-1, launched in 2014 and captured approximately every 12 days. Sentinel-1 uses C-band synthetic aperture radar to collect data in any conditions, regardless of weather or time of day. Surface Water is displayed on a spectrum from dry to water, or white to blue respectively, and can be viewed visually or as a time-series in Analyze Area. This dataset is ideal for assessing water conditions in areas with significant cloud cover or storms, and applications include monitoring changes in bodies of water or post-disaster assessments.
The Surface Moisture layer uses infrared and visible spectrum public satellite data to identify moist bare soil and very shallow water. Derived from the Normalized Difference Water Index (NDWI), this layer ranges from -0.6 to 0, where higher values indicate more moisture and saturated bare ground in darker blues, and lower values indicate variations in dry land. The moisture layer is best used in areas with bare ground or minimal vegetation when some context on ground conditions is known. Since the layer is heavily influenced by shadow, it is less ideal for areas with lots of topography. This layer provides more detail on areas that appear dry in the Surface Water layer, such as saturated land in wetland environments. Small and narrow streams or water bodies are also more easily picked up with this layer.
In regions where vegetation is blocking a top-down view of the soil or water surface, this Surface Moisture layer will display values indicating no water present. We, therefore, recommend using the Vegetation layer to assess moisture in vegetated areas, where darker greens indicate plants that are not experiencing water stress. Note that buildings and roads reflect light in a similar way to water, so we recommend that you refer to other layers to ensure that areas appearing blue in this layer are in fact moist, rather than developed. In some cases, shadows may also be present based on the angle the imagery was taken. We recommend taking a look at the Truecolor layer first to get oriented before utilizing this layer.
The snow layer uses the Normalized Difference Snow Index (NDSI) to highlight areas on a property where snow is present. NDSI is calculated from a satellite image’s green and short-wave infrared bands, using public satellite data inputs to derive a value between 0 and 1. Lower values indicate a lack of snow, while higher values denote areas with snow presence and are shown in white.
Available for Sentinel-2 and Landsat 8 sensings, the Normalized Burn Ratio can provide insight into the timing and severity in burned areas. This can be used by organizations assessing pre- and post-fire conditions or monitoring vegetation recovery following a fire. NBR is an index calculated using near-infrared (NIR) and shortwave infrared (SWIR) values derived from NASA/USGS Landsat 8 and ESA Sentinel-2.
Burned areas display high SWIR and low NIR reflectance, which is the opposite of healthy vegetation. Values in Lens range from -0.1 to 0.4, where lower values denote healthy vegetation and higher values correspond to more intense burns. Though NBR traditionally ranges from 0 to 1, this range was reduced in Lens to make it easier to distinguish burned areas. Because index values may vary based on the landscape, pre-fire vegetation, presence of smoke or clouds, it’s useful to view alongside truecolor, vegetation, and other datasets. For example, a desert landscape in the hot summer will show higher burn index values than a forested area, even without any fire event. Climate and phenological cycles are important to keep in mind when viewing this dataset, and it’s intended to support assessment in areas where known fires have occurred.
Using the Analyze Area tool with the Burn Index layer to gauge the timing of a wildfire.