Soft GND filter – gentle light balance for landscapes

If the sky is too bright and the foreground is in shadow, you need a graduated neutral density filter. The Soft Neutral Density filter is ideal when the horizon is not clearly defined—for example, in mountain landscapes, lakes with trees, or city panoramas. It provides a natural brightness balance and preserves the detail in the sky and clouds without darkening the foreground.

What is a soft GND filter?

A Soft GND (Graduated Neutral Density) filter has a soft, flowing gradient from dark (top) to clear (bottom). Unlike a Hard GND, the density gradient is much smoother—ideal when the dividing line between sky and landscape is irregular.

Typical application examples for Soft GND

  • 🏞️ Hilly landscapes with soft horizons
  • 🌲 Forests, meadows, lakes with light in the background
  • 🌇 Cityscapes at sunset
  • 🌄 Mountains with diffuse light

How is the soft GND filter used?

  1. Set up the tripod and determine the image section
  2. Equip the filter holder with the Soft GND
  3. Align the filter gradient to the horizon
  4. Check LiveView or histogram – fine-tune if necessary

Which strength makes sense?

Your advantages with the LC-PRO 100 filter system

  • 🧲 Combinable with magnetic CPL – for contrast and color saturation
  • 📐 Finely adjustable in the holder – precise gradient position
  • 🧤 Operation even in wind, cold or with gloves

Soft GND vs. other GND types – The comparison

Filter type Course Suitable for
Soft GND Gentle, flowing Uneven horizon lines
Hard GND Hard, abrupt Flat landscapes, sea
Reverse GND Dark in the middle Sun directly on the horizon
Center GND Density in the middle Special case: Central light source

Conclusion: Natural light with a soft gradient

The Soft GND filter is your tool when you need realistic brightness balance without harsh transitions. Especially in landscape photography during the golden hours, it provides more depth, better colors, and atmospheric results.

Discover Soft GND now → or get the starter set with holder