You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 regional_sales
【Schema】
# Table: Customers
[
(CustomerID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Customer Names:TEXT, Examples: [Avon Corp, WakeFern , Elorac, Corp])
]
# Table: Sales Team
[
(SalesTeamID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Sales Team:TEXT, Examples: [Adam Hernandez, Keith Griffin, Jerry Green]),
(Region:TEXT, Examples: [Northeast, West, South])
]
# Table: Sales Orders
[
(OrderNumber:TEXT, Primary Key, Examples: [SO - 0001000, SO - 0001001, SO - 0001002]),
(Sales Channel:TEXT, Examples: [In-Store, Online, Distributor]),
(WarehouseCode:TEXT, Examples: [WARE-UHY1004, WARE-NMK1003, WARE-PUJ1005]),
(ProcuredDate:TEXT, Examples: [12/31/17, 4/10/18, 7/19/18]),
(OrderDate:TEXT, Examples: [5/31/18, 6/1/18, 6/2/18]),
(ShipDate:TEXT, Examples: [6/14/18, 6/22/18, 6/21/18]),
(DeliveryDate:TEXT, Examples: [6/19/18, 7/2/18, 7/1/18]),
(CurrencyCode:TEXT, Examples: [USD]),
(_SalesTeamID:INTEGER, Examples: [6, 14, 21]),
(_CustomerID:INTEGER, Examples: [15, 20, 16]),
(_StoreID:INTEGER, Examples: [259, 196, 213]),
(_ProductID:INTEGER, Examples: [12, 27, 16]),
(Order Quantity:INTEGER, Examples: [5, 3, 1]),
(Discount Applied:REAL, Examples: [0.075, 0.05, 0.1]),
(Unit Price:TEXT, Examples: [1,963.10, 3,939.60, 1,775.50]),
(Unit Cost:TEXT, Examples: [1,001.18, 3,348.66, 781.22])
]
# Table: Products
[
(ProductID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Product Name:TEXT, Examples: [Cookware, Photo Frames, Table Lamps])
]
# Table: Regions
[
(StateCode:TEXT, Primary Key, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Region:TEXT, Examples: [South, West, Northeast])
]
# Table: Store Locations
[
(StoreID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(City Name:TEXT, Examples: [Birmingham, Huntsville, Mobile]),
(County:TEXT, Examples: [Shelby County/Jefferson County]),
(StateCode:TEXT, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Type:TEXT, Examples: [City, Town, CDP]),
(Latitude:REAL, Examples: [33.52744, 34.69901, 30.69436]),
(Longitude:REAL, Examples: [-86.79905, -86.67298, -88.04305]),
(AreaCode:INTEGER, Examples: [205, 256, 251]),
(Population:INTEGER, Examples: [212461, 190582, 194288]),
(Household Income:INTEGER, Examples: [89972, 78554, 76170]),
(Median Income:INTEGER, Examples: [31061, 48775, 38776]),
(Land Area:INTEGER, Examples: [378353942, 552604579, 361044263]),
(Water Area:INTEGER, Examples: [6591013, 3452021, 105325210]),
(Time Zone:TEXT, Examples: [America/Chicago, America/Phoenix, America/Los Angeles])
]
【Foreign keys】
Sales Orders._ProductID=Products.ProductID
Sales Orders._StoreID=Store Locations.StoreID
Sales Orders._CustomerID=Customers.CustomerID
Sales Orders._SalesTeamID=Sales Team.SalesTeamID
Store Locations.StateCode=Regions.StateCode

    【Question】
    What sales channels are used the most in the 3 places with the highest median income? highest median income refers to Max(Median Income)

    【Evidence】
    highest median income refers to Max(Median Income)

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT `Sales Channel` FROM ( SELECT T1.`Sales Channel` FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID ORDER BY T2.`Median Income` DESC LIMIT 3 ) GROUP BY `Sales Channel` ORDER BY COUNT(`Sales Channel`) DESC LIMIT 1