General Changes of Variables and Jacobians

Measure local area scaling and map a simple parameter region to a harder physical region.

Builds on Polar Coordinates in Double Integrals

The bigger question: How do we accumulate over an area?

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A derivative matrix scales small areas

For a differentiable map (x,y)=T(u,v)(x,y)=T(u,v), the Jacobian determinant is

J=det⁡∂(x,y)∂(u,v)=xuyv−xvyu.J=\det\frac{\partial(x,y)}{\partial(u,v)}=x_uy_v-x_vy_u.

Small parameter rectangles become approximate parallelograms with area scale ∣J∣|J|. Under a suitable one-to-one smooth change of variables with nonzero Jacobian in the interior,

∬Rf(x,y)dA=∬Sf(T(u,v))∣J(u,v)∣dudv.\iint_R f(x,y)dA=\iint_S f(T(u,v))|J(u,v)|du dv.

Standard extensions allow some boundary degeneracies. If a map covers the same area repeatedly, the ordinary one-to-one formula must be adjusted; an absolute determinant does not correct multiplicity.

Visual guide

VISUAL GUIDEA square maps to a parallelogram of twice the area
Under x = u + v, y = u − v, the unit parameter square becomes the shaded diamond. The Jacobian determinant is −2: magnitude 2 scales area, while the negative sign records orientation reversal.-0.5-1.50.25-0.75101.750.752.51.5xy
Under x = u + v, y = u − v, the unit parameter square becomes the shaded diamond. The Jacobian determinant is −2: magnitude 2 scales area, while the negative sign records orientation reversal.

Worked example: turn a parallelogram into a square

Let x=u+vx=u+v, y=u−vy=u-v with 0≤u,v≤10\le u,v\le1. The unit square maps to vertices (0,0),(1,1),(2,0),(1,−1)(0,0),(1,1),(2,0),(1,-1). The Jacobian is −2-2, so geometric area is ∫01∫012dudv=2\int_0^1\int_0^12du dv=2.

To integrate x+yx+y, substitute x+y=2ux+y=2u. The result is ∫01∫01(2u)2dvdu=2\int_0^1\int_0^1(2u)2dvdu=2. The negative determinant records orientation reversal; the area integral uses magnitude.

PAUSE & THINKA quick check, not a grade

Try it yourself.

Choose an answer and explain your reasoning to yourself. Use a hint if you get stuck.

With x=2u and y=3v, what is the absolute Jacobian determinant?

Hint 1 · Find a starting point

The derivative matrix is diagonal.

Hint 2 · Take the next step

Multiply the independent stretches 2 and 3.

Show the reasoning

Answer: 6

Areas scale by |2×3|=6, so dA=6 du dv.

Before moving on: what would make one of the other answers wrong? Saying why is part of understanding.

Worked example: an ellipse

Map the unit disk by x=aux=au, y=bvy=bv with a,b>0a,b>0. The image is x2/a2+y2/b2≤1x^2/a^2+y^2/b^2\le1 and ∣J∣=ab|J|=ab. Its area is therefore abπab\pi.

Combining this scaling with polar coordinates gives x=arcos⁡θx=ar\cos\theta, y=brsin⁡θy=br\sin\theta and total Jacobian abrabr. Jacobians multiply under composition, matching the chain rule for derivative matrices. This is often simpler than computing a large determinant from scratch.

If the available formula gives the inverse transformation, its determinant is reciprocal at corresponding regular points. Be explicit about which direction is being differentiated before inserting a factor into an integral.

Practice

  1. Find the Jacobian for x=2u,y=3vx=2u,y=3v.
  2. Find the area of the ellipse x2/4+y2/9≤1x^2/4+y^2/9\le1.
  3. Why does a determinant of zero prevent a regular local area conversion?
Show worked solutions
  1. J=6J=6.
  2. Semiaxes are 2,32,3, so the area is 6π6\pi.
  3. The derivative collapses at least one direction, so it is not locally invertible by the usual inverse-function theorem.

Further study

MIT OpenCourseWare: Multivariable Calculus provides a full university course with additional lectures and exercises.

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