这是OpenLayers 2的实现函数。有一个顺时针多边形的条件是面积< 0，这是由这个参考确定的。

function IsClockwise(feature)
{
    if(feature.geometry == null)
        return -1;

    var vertices = feature.geometry.getVertices();
    var area = 0;

    for (var i = 0; i < (vertices.length); i++) {
        j = (i + 1) % vertices.length;

        area += vertices[i].x * vertices[j].y;
        area -= vertices[j].x * vertices[i].y;
        // console.log(area);
    }

    return (area < 0);
}

从其中一个顶点开始，计算每条边对应的角度。

第一个和最后一个将是零(所以跳过它们);对于其余部分，角度的正弦值将由归一化与(点[n]-点[0])和(点[n-1]-点[0])的单位长度的叉乘给出。

如果这些值的和是正的，那么你的多边形是逆时针方向绘制的。

求出这些点的质心。

假设有直线从这个点到你们的点。

求line0 line1的两条直线夹角

而不是直线1和直线2

...

...

如果这个角是单调递增的，而不是逆时针递增的，

如果是单调递减，则是顺时针递减

Else(它不是单调的)

你不能决定，所以这是不明智的

下面是一个基于@Beta答案的算法的简单c#实现。

让我们假设我们有一个Vector类型，它的X和Y属性为double类型。

public bool IsClockwise(IList<Vector> vertices)
{
    double sum = 0.0;
    for (int i = 0; i < vertices.Count; i++) {
        Vector v1 = vertices[i];
        Vector v2 = vertices[(i + 1) % vertices.Count];
        sum += (v2.X - v1.X) * (v2.Y + v1.Y);
    }
    return sum > 0.0;
}

%是执行模运算的模运算符或余数运算符，该运算符(根据维基百科)在一个数除以另一个数后求余数。

根据@MichelRouzic评论的优化版本:

double sum = 0.0;
Vector v1 = vertices[vertices.Count - 1]; // or vertices[^1] with
                                          // C# 8.0+ and .NET Core
for (int i = 0; i < vertices.Count; i++) {
    Vector v2 = vertices[i];
    sum += (v2.X - v1.X) * (v2.Y + v1.Y);
    v1 = v2;
}
return sum > 0.0;

这不仅节省了模运算%，还节省了数组索引。

测试(参见与@WDUK的讨论)

public static bool IsClockwise(IList<(double X, double Y)> vertices)
{
    double sum = 0.0;
    var v1 = vertices[^1];
    for (int i = 0; i < vertices.Count; i++) {
        var v2 = vertices[i];
        sum += (v2.X - v1.X) * (v2.Y + v1.Y);
        Console.WriteLine($"(({v2.X,2}) - ({v1.X,2})) * (({v2.Y,2}) + ({v1.Y,2})) = {(v2.X - v1.X) * (v2.Y + v1.Y)}");
        v1 = v2;
    }
    Console.WriteLine(sum);
    return sum > 0.0;
}

public static void Test()
{
    Console.WriteLine(IsClockwise(new[] { (-5.0, -5.0), (-5.0, 5.0), (5.0, 5.0), (5.0, -5.0) }));

    // infinity Symbol
    //Console.WriteLine(IsClockwise(new[] { (-5.0, -5.0), (-5.0, 5.0), (5.0, -5.0), (5.0, 5.0) }));
}

虽然这些答案是正确的，但它们在数学上的强度比必要的要大。假设地图坐标，其中最北的点是地图上的最高点。找到最北的点，如果两个点相等，它是最北的，然后是最东的(这是lhf在他的答案中使用的点)。在你的观点中，

点[0]= (5,0)

点[1]= (6,4)

点[2]= (4,5)

点[3]= (1,5)

点[4]= (1,0)

If we assume that P2 is the most north then east point either the previous or next point determine clockwise, CW, or CCW. Since the most north point is on the north face, if the P1 (previous) to P2 moves east the direction is CW. In this case, it moves west, so the direction is CCW as the accepted answer says. If the previous point has no horizontal movement, then the same system applies to the next point, P3. If P3 is west of P2, it is, then the movement is CCW. If the P2 to P3 movement is east, it's west in this case, the movement is CW. Assume that nte, P2 in your data, is the most north then east point and the prv is the previous point, P1 in your data, and nxt is the next point, P3 in your data, and [0] is horizontal or east/west where west is less than east, and [1] is vertical.

if (nte[0] >= prv[0] && nxt[0] >= nte[0]) return(CW);
if (nte[0] <= prv[0] && nxt[0] <= nte[0]) return(CCW);
// Okay, it's not easy-peasy, so now, do the math
if (nte[0] * nxt[1] - nte[1] * nxt[0] - prv[0] * (nxt[1] - crt[1]) + prv[1] * (nxt[0] - nte[0]) >= 0) return(CCW); // For quadrant 3 return(CW)
return(CW) // For quadrant 3 return (CCW)

Sean的答案的JavaScript实现:

function calcArea(poly) { if(!poly || poly.length < 3) return null; let end = poly.length - 1; let sum = poly[end][0]*poly[0][1] - poly[0][0]*poly[end][1]; for(let i=0; i<end; ++i) { const n=i+1; sum += poly[i][0]*poly[n][1] - poly[n][0]*poly[i][1]; } return sum; } function isClockwise(poly) { return calcArea(poly) > 0; } let poly = [[352,168],[305,208],[312,256],[366,287],[434,248],[416,186]]; console.log(isClockwise(poly)); let poly2 = [[618,186],[650,170],[701,179],[716,207],[708,247],[666,259],[637,246],[615,219]]; console.log(isClockwise(poly2));

我很确定这是对的。这似乎是有效的:-)

这些多边形看起来是这样的，如果你想知道的话: