Idenitity between TD(0) algorithm and Policy Evaluation in Dynamic Programming when alpha is equal to 1 TD(0) algorithm is defined as the iterative update of the following:

$$ V(s) \leftarrow V(s) + \alpha({r + \gamma V(s')} - V(s) ) $$

Now, if we assume alpha to be equal to 1, we get the traditional Policy Evaluation formula in Dynamic programming. Is it correct?
No - Dynamic programming estimates the value of the next state by first looking at all possible next states. Temporal difference 0 estimates the value of the next state by only looking at a single next state.