tiny_forest_potential
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The Parcel_Score, SUM_PFlag, SUM_PArea_SqFt, and MFlag were used to create a ranking of which parcels are most suitable to become a No Mow Zone. This ranking is achieved by not only sorting the calculated fields in descending order, but also with a specific order of sorting. First, the MFlag field is sorted in descending order, followed by the Parcel_Score, the SUM_PFlag and the SUM_PArea_SqFt fields. This order is important because it takes into consideration first, which parcels are actually mowed, then it looks at each mowed parcel’s suitability score followed by the parking lot data. The following code created this ranked feature class: </SPAN></P><P /><P STYLE="margin:0 0 0 96;"><SPAN><SPAN># set local variables</SPAN></SPAN></P><P STYLE="margin:0 0 0 96;"><SPAN><SPAN>in_dataset = "COA_parcels"</SPAN></SPAN></P><P STYLE="margin:0 0 0 96;"><SPAN>out_dataset = "Ranked_Parcels"</SPAN></P><P STYLE="margin:0 0 0 96;"><SPAN /></P><P STYLE="margin:0 0 0 96;"><SPAN>## Order features first by the presence of a mow zone (MFlag), #then by the suitability analysis result (Parcel_Score) and the parking lot analysis (SUM_PFlag and SUM_PAreaSqFT) </SPAN></P><P STYLE="margin:0 0 0 96;"><SPAN><SPAN>sort_fields = [["MFlag", "DESCENDING"],["Parcel_Score", "DESCENDING"],["SUM_PFlag", "DESCENDING"],["SUM_PArea_SqFt", "DESCENDING"]]</SPAN></SPAN></P><P STYLE="margin:0 0 0 96;"><SPAN /></P><P STYLE="margin:0 0 0 96;"><SPAN># execute the function</SPAN></P><P STYLE="margin:0 0 0 96;"><SPAN>arcpy.Sort_management(in_dataset, out_dataset, sort_fields)</SPAN></P><P><SPAN> This brought the most suitable parcels to the top of the table. </SPAN></P><P><SPAN>Definition of Fields in the attribute table:</SPAN></P><P><SPAN>Weighted_Sum: </SPAN><SPAN STYLE="font-size:16pt"> </SPAN><SPAN>In the suitability analysis, all coincident cells from each criteria created an index where each cell has one value. Zonal s</SPAN><SPAN>tatistics calculated a total sum for each parcel by adding the adding the index of all cells within each parcel together to create one value for each parcel to populate this field. </SPAN></P><P><SPAN>Streams_Sum: The suitability analysis created an index for each cell based on its distance from streams. The index of all cells within each parcel were added together to populate this field. </SPAN></P><P><SPAN>Parcel_Score: The parcel score is the sum of the Weighted_Sum and Streams_Sum fields. The expression to calculate the field is: </SPAN><SPAN><SPAN>round(!Weighted_Sum! + !Stream_Sum!)</SPAN></SPAN></P><P><SPAN>parcel_avg_eleva: The average elevation of the parcel.</SPAN></P><P><SPAN>Sum_PFlag: The number of parking lots adjacent to the parcel that have a higher average elevation than the parcel.</SPAN></P><P><SPAN>SUM_PArea_SqFt: The total area in square feet of all the parking lots adjacent to the parcel that have a higher average elevation than the parcel.</SPAN></P><P><SPAN>MFlag: '1' in this field indicates that this parcel intersects a feature in the pard_mow_zone feature class. a '0' indicates that this field does not intersect with a feature in the pard_mow_zone feature class. </SPAN></P><P><SPAN /></P><P><SPAN /></P></DIV></DIV></DIV>
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[{'name': 'PK__TINY_FOR__E458E6E796F1C06A', 'fields': 'OBJECTID_1', 'isAscending': True, 'isUnique': True, 'description': '', 'indexType': 'Attribute'}, {'name': 'user_946.TINY_FOREST_POTENTIAL_TINY_FOREST_POTENTIAL_Shape_sidx', 'fields': 'Shape', 'isAscending': True, 'isUnique': False, 'description': '', 'indexType': 'Spatial'}, {'name': 'Shape__Area_Index', 'fields': 'Shape__Area', 'isAscending': True, 'isUnique': False, 'description': '', 'indexType': 'Attribute'}, {'name': 'Shape__Length_Index', 'fields': 'Shape__Length', 'isAscending': True, 'isUnique': False, 'description': '', 'indexType': 'Attribute'}]
nan
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[]
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