BUG: Index.astype does not localize to UTC first like Series.astype with datetime64[ns, tz] dtypes
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```
In [4]: pd.__version__
Out[4]: '1.1.0.dev0+1202.g1de2cf1ac'

In [5]: pd.Series([pd.Timestamp('2020-01-01 15:00')]).astype('datetime64[ns, EST]')
Out[5]:
0   2020-01-01 10:00:00-05:00
dtype: datetime64[ns, EST]

In [6]: pd.Index([pd.Timestamp('2020-01-01 15:00')]).astype('datetime64[ns, EST]')
Out[6]: DatetimeIndex(['2020-01-01 15:00:00-05:00'], dtype='datetime64[ns, EST]', freq=None)
```

#### Problem description

`Out[5]` is the expected output as documented in https://pandas.pydata.org/docs/user_guide/timeseries.html#time-zone-series-operations. `Out[6]` should align therefore with `Out[5]`

#### Expected Output

```
In [6]: pd.Index([pd.Timestamp('2020-01-01 15:00')]).astype('datetime64[ns, EST]')
Out[6]: DatetimeIndex(['2020-01-01 10:00:00-05:00'], dtype='datetime64[ns, EST]', freq=None)
```
