SORA and the Specific category

Example 1 A suburban survey area next to a village

The flight geography is 400 × 300 m, with a maximum height of 60 m, a speed of 15 m/s, a 3 s pilot reaction time and an assumed stopping distance of 15 m. Population data is on a 100 m grid: rice fields to the west at 20 people/km², general area at 300 people/km², and a village to the east at 1,200 people/km² (hypothetical data).

import numpy as np

fg_w, fg_h = 400.0, 300.0     # flight geography (m)
height = 60.0                 # maximum height AGL (m)
speed, react = 15.0, 3.0      # speed m/s and pilot reaction time s
contingency = speed * react + 15.0   # distance during reaction + stopping distance (assumed)
buffer = height               # initial ground risk buffer by the 1-to-1 principle

def area(margin):
    return (fg_w + 2 * margin) * (fg_h + 2 * margin) / 1e6   # km²

print(f"contingency volume width {contingency:.0f} m, ground risk buffer {buffer:.0f} m")
print(f"flight geography {area(0):.3f} km², operational volume {area(contingency):.3f} km², "
      f"with buffer {area(contingency + buffer):.3f} km²")

# population density (people/km²) on a 100 m grid around the area (hypothetical)
x = np.arange(-200, 700, 100) + 50
y = np.arange(-200, 600, 100) + 50
X, Y = np.meshgrid(x, y)
dens = np.where(X >= 450, 1200, 300)         # village to the east
dens = np.where(X < 0, 20, dens)             # rice fields to the west
m = contingency + buffer
cover = (X > -m) & (X < fg_w + m) & (Y > -m) & (Y < fg_h + m)
fg = (X > 0) & (X < fg_w) & (Y > 0) & (Y < fg_h)
print(f"max density in flight geography {dens[fg].max()} /km², "
      f"in footprint with buffer {dens[cover].max()} /km²")

contingency volume width 60 m, ground risk buffer 60 m
flight geography 0.120 km², operational volume 0.218 km², with buffer 0.346 km²
max density in flight geography 300 /km², in footprint with buffer 1200 /km²

The area used for ground risk assessment is almost three times the flight geography, and although the route never enters the village, the buffer reaches the village cells. The maximum density to use is therefore 1,200, not 300 people/km². The contingency-width formula in this example is simplified for teaching; real work must include navigation error, wind and the aircraft’s actual stopping performance.

Example 2 Add a parachute, or shrink the flight area?

The drone is up to 1 m in size and flies no faster than 25 m/s, with residual ARC-b assumed in all cases. Compare three options: no mitigation; M2 at medium robustness with full evidence; and moving the eastern edge of the flight area 100 m west so the footprint no longer reaches the village (training case).

ROWS = [5, 50, 500, 5000, 50000]            # upper bounds of density rows (people/km²), SORA 2.5 Table 2
IGRC_1M = [2, 3, 4, 5, 6]                    # column 1 m / 25 m/s
MIN_1M = 1                                   # controlled ground area row
SAIL = {2: "I II IV VI", 3: "II II IV VI", 4: "III III IV VI",
        5: "IV IV IV VI", 6: "V V V VI", 7: "VI VI VI VI"}   # Table 7, ARC a b c d

def igrc(density):
    for top, g in zip(ROWS, IGRC_1M):
        if density < top:
            return g
    return 7

def sail(grc, arc):
    return SAIL[max(grc, 2)].split()["abcd".index(arc)]

cases = {
    "village east, no mitigation": (1200, 0, "b"),
    "village east, M2 medium (-1)": (1200, -1, "b"),
    "flight area cut by 100 m": (300, 0, "b"),
}
for name, (d, mit, arc) in cases.items():
    g0 = igrc(d)
    g = max(g0 + mit, MIN_1M)
    print(f"{name:30s} density {d:>5}  iGRC {g0}  final GRC {g}  ARC-{arc}  SAIL {sail(g, arc)}")

village east, no mitigation    density  1200  iGRC 5  final GRC 5  ARC-b  SAIL IV
village east, M2 medium (-1)   density  1200  iGRC 5  final GRC 4  ARC-b  SAIL III
flight area cut by 100 m       density   300  iGRC 4  final GRC 4  ARC-b  SAIL III

Both a parachute proven at medium robustness and shrinking the flight area reduce SAIL from IV to III, but at different costs: the parachute needs test evidence under Annex B, while shrinking the area may need an extra flight to cover the remainder. This example is for practice only; real work needs real population data, a real ARC assessment and acceptance by the authority.