The correct answer is B.
On the first hand, collecting information about the population of Colombus during the last 100 years, means gathering time-series data. Only one variable is tracked, and just one value is stored per year, hence in total the dataset will contain 100 values. Such type of data is used to assess the changes that have taken place along a period of time. Therefore the temporal dimension of the data is specially important on this research.
On the other hand, data about the different crops in Ohio nowadays would compose a cross-sectional dataset. This type of dataset contains one value of each of the variables included. All values correspond to the same point in time (same year, day month). Therefore, it will have the name number of values and variables, and there will be as many variables as type of crops in Ohio. In this case, the temporal dimension is unimportant as all the information collected pertains to the same time period.