A rough way to do this, for example:
The radius of the circle is 1000 square meters. inches - sqrt (1000 / pi) = 17.8 ... This circle should then fit into the 35x35 matrix. If you make “indexes” for this matrix, where the center pixel is (0,0), you can easily check if the pixel falls into the circle or not by substituting x ^ 2 + y ^ 2 = r ^ 2 in the equation of the circle. Or you can use an alternative equation for a circle centered at (a, b). If it evaluates to TRUE, it does, if not, outside the circle.
As a pseudocode / example, in Python I would make an optimized version:
import numpy, math
target_area = 1000.0
r = (target_area / math.pi) ** 0.5
m = numpy.zeros((2*r+2,2*r+2))
a, b = r, r
for row in range(0, m.shape[0]):
for col in range(0, m.shape[1]):
if (col-a)**2 + (row-b)**2 <= r**2:
m[row,col] = 1
numpy.sum(m)
Here is the result when the target area is 100,000 pixels (actual circle generated 99988.0):

, , , , .