ricg72 opened a new issue, #1273:
URL: https://github.com/apache/sedona/issues/1273

   ## Expected behavior
   drawing 10 x 10 polygon expect 100 pixels
   ```
   
+---------------------------------------+--------+-----+------------+--------------+
   |geo                                    
|size(px)|Is4_4|st_area(geo)|st_length(geo)|
   
+---------------------------------------+--------+-----+------------+--------------+
   |POLYGON ((1 1, 11 1, 11 11, 1 11, 1 1))|100     |true |100.0       |40.0    
      |
   
+---------------------------------------+--------+-----+------------+--------------+
   ```
   
   ## Actual behavior
   drawing 10 x 10 polygon only getting 40, on the boundary
   
   output - size(px) is wrong
   ```
   
+---------------------------------------+--------+-----+------------+--------------+
   |geo                                    
|size(px)|Is4_4|st_area(geo)|st_length(geo)|
   
+---------------------------------------+--------+-----+------------+--------------+
   |POLYGON ((1 1, 11 1, 11 11, 1 11, 1 1))|36      |true |100.0       |40.0    
      |
   
+---------------------------------------+--------+-----+------------+--------------+
   ```
   
   
   ## Steps to reproduce the problem
   ```
   case class A(g : String)
   val a0 = 1.0
   val a1 = 11.0
   val d = Seq( A(s"POLYGON (($a0 $a0, $a1 $a0, $a1 $a1, $a0 $a1, $a0 $a0))"))
   import spark.implicits._
   val df = d.toDS().toDF()
   val df2 = df
     .withColumn("geo",   expr("ST_GeomFromWKT(g)"))
     .withColumn("Is4_4", expr("ST_Contains(geo, ST_Point(4,4))")) // should be 
in
     .withColumn("px",    expr("ST_Pixelize(geo, 10,10, 
ST_PolygonFromEnvelope(0,0,12,12))")) // make sure (a0,a0) to (a1,a1)
     
   println( s"Number of pixels: ${df2.select( explode(col("px")) ).count()} - 
would expect ${(a1-a0) * (a1-a0)} ")
   
   df2.select( col("geo"), size(col("px")), col("Is4_4"), expr("ST_Area(geo)"), 
expr("ST_Length(geo)")).show(false)
   
   df2  .select( explode(col("px")) )  .show(false)
   ```
   ## Settings
   
   Sedona version = 1.5.0
   Apache Spark version = 3.3.0
   Apache Flink version = ?
   API type = Scala,
   Scala version = 2.12
   JRE version = 1.8
   Python version = ?
   Environment = Databricks
   


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