Tennessee Freight Zones and Top Partners

What follows is the transcript of this chat as State Planner generated it. It is here to show how the answer above was arrived at: every query State Planner ran, what each one returned, and where the data came from.

transcript.md

↑ Contents

State Planner chat · https://stateplanner.com

State: Tennessee (TN)
Started: October 22, 2026, 12:31 AM UTC
Runtime: 1 min 36 sec
Status: completed

Prompt

What are Tennessee’s biggest freight trading partners and commodities, by tonnage and value, for truck, rail and water? Map Tennessee’s freight regions and each one’s top partners.

Model: Anthropic: Claude Haiku 5.5 (anthropic/claude-haiku-5.5, via openrouter)

Response

I'll start with the freight flow table's columns and caveats.

The four Tennessee zones and modes are clear. Next I'll check how imports and exports are coded, since their partner is a foreign region rather than a domestic zone.

Imports and exports carry a foreign partner (fr_orig / fr_dest), and domestic rows carry the other domestic zone. Next I'll rank statewide partners for truck, rail and water, by tonnage and by value.

The statewide partner list mixes in flows between Tennessee's own zones, which are not trading partners in the usual sense. I'll separate those out and rank external partners by zone, and rank commodities by mode.

I have the rankings I need. Now I'll map the four Tennessee zones with each zone's top five domestic partners, drawn as lines to partner centroids.

Tennessee's largest external freight partners in 2022 are neighbouring states (Indiana, Kentucky, Alabama, Mississippi, Georgia, Arkansas) and, by value, East Asia. Most tonnage, though, moves between Tennessee's own zones. Truck, rail and water together carried about 376 million short tons and $667 billion (2022 constant dollars).

Scope and definitions

Source: FAF6 (BTS Freight Analysis Framework), 2022 shipments with Tennessee at one end. Modes: truck (including customer pick-up), rail and water.
Tonnage is thousand short tons (kt). Value is million 2022 dollars ($M).
A "partner" is the other end of a shipment. For domestic shipments that is the other zone. For imports and exports it is the foreign region (Eastern Asia, Europe, Canada and so on).
These are shipment origins and destinations, not traffic on any highway.

Totals by mode

Mode	Tons (kt)	Value ($M)	Tons moving inside Tennessee
Truck	316,470	636,722	165,207 kt (52%)
Rail	51,105	26,884	9,745 kt (19%)
Water	8,455	3,689	31 kt

Top external partners, all three modes

Tennessee's own zones are left out of this list because they are not trading partners.

Largest external partners by tonnage

Partner	Tons (kt)	Value ($M)
Rest of Indiana	22,168	9,256
Rest of Kentucky	20,284	25,041
Rest of Alabama	9,424	13,225
Mississippi	9,098	21,607
Atlanta, GA	8,852	26,458
Rest of Missouri	6,862	3,852
Arkansas	6,844	21,553
Eastern Asia (foreign)	5,692	35,313
Las Vegas, NV	5,508	607
Rest of Georgia	5,320	9,441

Largest external partners by value

Partner	Value ($M)	Tons (kt)
Eastern Asia (foreign)	35,313	5,692
Atlanta, GA	26,458	8,852
Rest of Kentucky	25,041	20,284
Mississippi	21,607	9,098
Arkansas	21,553	6,844
Europe (foreign)	19,858	2,711
Canada	16,382	3,714
Mexico	16,040	2,794

Top commodities

Statewide, by tonnage: gravel 53,720 kt (14% of tons), nonmetallic minerals 31,353 kt (8%), natural gas and other fossil products 27,971 kt (7%), cereal grains 27,875 kt (7%), waste and scrap 18,103 kt (5%).

By mode, ranked by tonnage and by value:

Truck: gravel, nonmetallic minerals and natural gas lead by tonnage. By value, pharmaceuticals ($81.4B, 13% of truck value), motorized vehicles ($79.4B) and electronics ($59.7B) lead.
Rail: cereal grains lead by tonnage (19,772 kt, 39% of rail tons). By value, motorized vehicles ($6.0B, 22%), gasoline ($4.7B, 18%) and basic chemicals ($2.6B) lead.
Water: gravel leads by tonnage (5,440 kt, 64% of water tons). By value, motorized vehicles ($0.8B, 22%), other agricultural products ($0.4B) and textiles and leather ($0.4B) lead.

Top five external partners by tonnage, for each Tennessee zone

Memphis (TN part)

Mississippi: 4,467 kt, $12.5B
Rest of Missouri: 4,221 kt, $1.0B
Arkansas: 3,392 kt, $15.7B
Houston, TX: 1,396 kt, $2.3B
Rest of Kentucky: 612 kt, $0.9B (this is the fifth entry on the map; Eastern Asia ranks fifth in tonnage but has no point to draw)

Nashville

Rest of Kentucky: 7,218 kt, $12.0B
Las Vegas, NV: 5,466 kt, $0.2B
Rest of Alabama: 2,895 kt, $5.4B
Atlanta, GA: 2,701 kt, $7.8B
Birmingham, AL: 2,061 kt, $4.7B

Knoxville

Rest of Indiana: 19,512 kt (46% of the zone's external tonnage), $1.6B
Rest of Kentucky: 3,217 kt, $3.0B
Houston, TX: 1,609 kt, $2.3B
Atlanta, GA: 1,160 kt, $3.4B
Rest of North Carolina: 815 kt, $1.3B

Rest of Tennessee

Rest of Kentucky: 9,237 kt, $9.1B
Rest of Alabama: 5,673 kt, $5.1B
Atlanta, GA: 4,398 kt, $12.7B
Rest of Virginia: 3,631 kt, $3.5B
Mississippi: 3,187 kt, $5.6B

Map legend

Shaded polygons: the four FAF zones (Memphis, Nashville, Knoxville, rest of Tennessee). The popup gives each zone's external tons and value.
Coloured lines: each zone's top five domestic partners by tonnage, drawn from the zone centroid to the partner centroid. Red is from Memphis, orange from Nashville, teal from Knoxville, purple from the rest of Tennessee.
Yellow dots: partner regions, with the zones that list them among their top five.
Foreign partners (Eastern Asia, Europe, Canada and others) have no geometry in the data, so they appear in the tables only.

Caveats

These are 2022 FAF6 estimates. Tonnage is rounded and value is in 2022 constant dollars.
Zones are county groupings, not MPOs, Census urban areas or state highway districts.
Partner shares are shares of all truck, rail and water freight. They are not shares of each zone's own total.

Tennessee Freight Zones and Top Partners

Tennessee Freight Zones and Top Partners

Exploratory Queries

Query 1 — List Tennessee's four freight zones and their names.

   SELECT r.faf_id,
          r.short_name,
          r.name,
          r.region_type,
          (
             SELECT count(*)
               FROM tn_faf_od o
              WHERE o.dms_orig = r.faf_id
                 OR o.dms_dest = r.faf_id
          ) AS rows_touch
     FROM tn_faf_regions r
    WHERE r.state = 'TN'
 ORDER BY r.faf_id

faf_id	short_name	name	region_type	rows_touch
471	Memphis TN-MS-AR (TN Part)	Memphis-Forrest City, TN-MS-AR CFS Area (TN Part)	C	56464
472	Nashville TN	Nashville-Davidson-Murfreesboro, TN CFS Area	C	23248
473	Knoxville TN	Knoxville-Morristown-Sevierville, TN CFS Area	C	20142
479	Rest of TN	Remainder of Tennessee	R	22929

data/turn-1-query-1.csv

Query 2 — Check the totals by trade type and mode.

   SELECT trade_type,
          dms_mode,
          m.name,
          round(sum(tons)) AS kt,
          round(sum(value)) AS usd_m,
          count(*)
     FROM tn_faf_od o
LEFT JOIN tn_faf_modes m ON m.code = o.dms_mode
 GROUP BY 1,
          2,
          3
 ORDER BY 1,
          4 DESC

trade_type	dms_mode	name	kt	usd_m	count
1	1	Truck (include customer pick-up)	302211	542235	20629
1	6	Pipeline	122980	37101	140
1	2	Rail	46015	16167	423
1	5	Multiple modes & mail	44081	119011	16488
1	3	Water	7226	758	23
1	7	Other and unknown	3012	8527	1997
1	4	Air (include truck-air)	56	13598	1761
2	1	Truck (include customer pick-up)	8972	69141	8913
2	2	Rail	3192	7259	3078
2	5	Multiple modes & mail	1001	9087	2941
2	3	Water	781	2345	1701
2	4	Air (include truck-air)	306	45490	22842
2	6	Pipeline	102	22	6
2	7	Other and unknown	42	246	242
3	1	Truck (include customer pick-up)	5287	25346	8771
3	2	Rail	1898	3458	2924
3	5	Multiple modes & mail	463	1026	2394
3	3	Water	448	586	1334
3	4	Air (include truck-air)	322	57195	23525
3	7	Other and unknown	57	235	80

data/turn-1-query-2.csv

Query 3 — Look up the foreign region names and check the Tennessee zone rows.

   SELECT faf_id,
          name,
          region_type,
          centroid IS NOT NULL AS has_pt
     FROM tn_faf_regions
    WHERE state IS NULL
       OR faf_id IN ('471', '472', '473', '479')
 ORDER BY faf_id;

faf_id	name	region_type	has_pt
471	Memphis-Forrest City, TN-MS-AR CFS Area (TN Part)	C	true
472	Nashville-Davidson-Murfreesboro, TN CFS Area	C	true
473	Knoxville-Morristown-Sevierville, TN CFS Area	C	true
479	Remainder of Tennessee	R	true
801	Canada	F	false
802	Mexico	F	false
803	Rest of Americas	F	false
804	Europe	F	false
805	Africa	F	false
806	SW & Central Asia	F	false
807	Eastern Asia	F	false
808	SE Asia & Oceania	F	false

data/turn-1-query-3.csv

Query 4 — Check how domestic, import and export rows are split by Tennessee side for truck, rail and water.

   SELECT trade_type,
          CASE
                    WHEN dms_orig IN ('471', '472', '473', '479') THEN 'TN'
                    ELSE 'non-TN'
          END AS orig_side,
          CASE
                    WHEN dms_dest IN ('471', '472', '473', '479') THEN 'TN'
                    ELSE 'non-TN'
          END AS dest_side,
          fr_orig <> '' AS has_fr_orig,
          fr_dest <> '' AS has_fr_dest,
          count(*),
          round(sum(tons)) AS kt,
          round(sum(value)) AS usd_m
     FROM tn_faf_od
    WHERE dms_mode IN (1, 2, 3)
 GROUP BY 1,
          2,
          3,
          4,
          5
 ORDER BY 1,
          2,
          3,
          4,
          5

trade_type	orig_side	dest_side	has_fr_orig	has_fr_dest	count	kt	usd_m
1	non-TN	TN	false	false	10065	102022	191760
1	TN	non-TN	false	false	10419	78542	219824
1	TN	TN	false	false	591	174888	147577
2	non-TN	TN	true	false	11255	12838	58857
2	TN	non-TN	true	false	1301	22	1742
2	TN	TN	true	false	1136	86	18146
3	non-TN	TN	false	true	1069	9	1516
3	TN	non-TN	false	true	11072	7615	26078
3	TN	TN	false	true	888	8	1795

data/turn-1-query-4.csv

Query 5 — Rank statewide trading partners for truck, rail and water by tonnage.

     WITH f AS (
             SELECT o.trade_type,
                    o.dms_mode,
                    o.tons,
                    o.value,
                    CASE
                              WHEN o.trade_type = 1 THEN CASE
                                        WHEN o.dms_orig IN ('471', '472', '473', '479') THEN o.dms_dest
                                        ELSE o.dms_orig
                              END
                              WHEN o.trade_type = 2 THEN o.fr_orig
                              ELSE o.fr_dest
                    END AS partner_id
               FROM tn_faf_od o
              WHERE o.dms_mode IN (1, 2, 3)
          ),
          p AS (
             SELECT f.partner_id,
                    sum(f.tons) AS kt,
                    sum(f.value) AS usd_m,
                    sum(f.tons) FILTER (
                        WHERE trade_type = 1
                    ) AS kt_dom,
                    sum(f.tons) FILTER (
                        WHERE trade_type <> 1
                    ) AS kt_intl
               FROM f
           GROUP BY 1
          )
   SELECT p.partner_id,
          r.short_name,
          r.region_type,
          round(p.kt) AS kt,
          round(p.usd_m) AS usd_m,
          round(p.kt_dom) AS kt_domestic,
          round(coalesce(p.kt_intl, 0)) AS kt_foreign,
          round(100 * p.kt / sum(p.kt) OVER ()) AS pct_tons
     FROM p
LEFT JOIN tn_faf_regions r ON r.faf_id = p.partner_id
 ORDER BY p.kt DESC
    LIMIT 15

partner_id	short_name	region_type	kt	usd_m	kt_domestic	kt_foreign	pct_tons
472	Nashville TN	C	77785	51210	77785	0	21
479	Rest of TN	R	56716	40754	56716	0	15
189	Rest of IN	R	22168	9256	22168	0	6
473	Knoxville TN	C	21342	21377	21342	0	6
219	Rest of KY	R	20284	25041	20284	0	5
471	Memphis TN-MS-AR (TN Part)	C	19045	34237	19045	0	5
019	Rest of AL	R	9424	13225	9424	0	3
280	Mississippi	R	9098	21607	9098	0	2
131	Atlanta GA	C	8852	26458	8852	0	2
299	Rest of MO	R	6862	3852	6862	0	2
050	Arkansas	R	6844	21553	6844	0	2
807	Eastern Asia	F	5692	35313		5692	2
321	Las Vegas NV	C	5508	607	5508	0	1
139	Rest of GA	R	5320	9441	5320	0	1
519	Rest of VA	R	4531	6439	4531	0	1

data/turn-1-query-5.csv

Query 6 — Rank statewide trading partners for truck, rail and water by value.

     WITH f AS (
             SELECT o.trade_type,
                    o.dms_mode,
                    o.tons,
                    o.value,
                    CASE
                              WHEN o.trade_type = 1 THEN CASE
                                        WHEN o.dms_orig IN ('471', '472', '473', '479') THEN o.dms_dest
                                        ELSE o.dms_orig
                              END
                              WHEN o.trade_type = 2 THEN o.fr_orig
                              ELSE o.fr_dest
                    END AS partner_id
               FROM tn_faf_od o
              WHERE o.dms_mode IN (1, 2, 3)
          ),
          p AS (
             SELECT f.partner_id,
                    sum(f.tons) AS kt,
                    sum(f.value) AS usd_m
               FROM f
           GROUP BY 1
          )
   SELECT p.partner_id,
          r.short_name,
          r.region_type,
          round(p.kt) AS kt,
          round(p.usd_m) AS usd_m,
          round(100 * p.usd_m / sum(p.usd_m) OVER ()) AS pct_value
     FROM p
LEFT JOIN tn_faf_regions r ON r.faf_id = p.partner_id
 ORDER BY p.usd_m DESC
    LIMIT 15

partner_id	short_name	region_type	kt	usd_m	pct_value
472	Nashville TN	C	77785	51210	8
479	Rest of TN	R	56716	40754	6
807	Eastern Asia	F	5692	35313	5
471	Memphis TN-MS-AR (TN Part)	C	19045	34237	5
131	Atlanta GA	C	8852	26458	4
219	Rest of KY	R	20284	25041	4
280	Mississippi	R	9098	21607	3
050	Arkansas	R	6844	21553	3
473	Knoxville TN	C	21342	21377	3
804	Europe	F	2711	19858	3
801	Canada	F	3714	16382	2
802	Mexico	F	2794	16040	2
019	Rest of AL	R	9424	13225	2
808	SE Asia & Oceania	F	2648	11838	2
171	Chicago IL-IN-WI (IL Part)	C	2295	11815	2

data/turn-1-query-6.csv

Query 7 — Rank commodities for truck, rail and water by tonnage and value.

     WITH f AS (
             SELECT o.sctg2,
                    o.dms_mode,
                    o.tons,
                    o.value
               FROM tn_faf_od o
              WHERE o.dms_mode IN (1, 2, 3)
          )
   SELECT f.sctg2,
          s.title,
          round(sum(tons)) AS kt,
          round(sum(value)) AS usd_m,
          round(100 * sum(tons) / sum(sum(tons)) OVER ()) AS pct_tons,
          round(100 * sum(value) / sum(sum(value)) OVER ()) AS pct_value
     FROM f
LEFT JOIN tn_faf_sctg s ON s.sctg2 = f.sctg2
 GROUP BY 1,
          2
 ORDER BY sum(tons) DESC
    LIMIT 15

sctg2	title	kt	usd_m	pct_tons	pct_value
12	Gravel	53720	813	14	0
31	Nonmetal min. prods.	31353	11780	8	2
19	Natural gas and other fossil products	27971	8995	7	1
02	Cereal grains	27875	2963	7	0
41	Waste/scrap	18103	3230	5	0
11	Natural sands	16822	321	4	0
32	Base metals	16722	33174	4	5
26	Wood prods.	14139	13819	4	2
17	Gasoline	11968	10982	3	2
07	Other foodstuffs	11214	20400	3	3
43	Mixed freight	10872	46234	3	7
03	Other ag prods.	10458	8887	3	1
20	Basic chemicals	10018	12860	3	2
25	Logs	9945	803	3	0
24	Plastics/rubber	9381	34057	2	5

data/turn-1-query-7.csv

Query 8 — Rank each Tennessee zone's external partners for truck, rail and water.

     WITH legs AS (
             SELECT dms_orig AS zone,
                    CASE
                              WHEN trade_type = 1 THEN dms_dest
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END AS partner_id,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_orig IN ('471', '472', '473', '479')
          UNION ALL
             SELECT dms_dest,
                    CASE
                              WHEN trade_type = 1 THEN dms_orig
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_dest IN ('471', '472', '473', '479')
          ),
          p AS (
             SELECT zone,
                    partner_id,
                    sum(tons) AS kt,
                    sum(value) AS usd_m
               FROM legs
           GROUP BY 1,
                    2
          ),
          ranked AS (
             SELECT p.*,
                    r.short_name AS partner,
                    row_number() OVER (
                    PARTITION BY zone
                     ORDER BY kt DESC
                    ) AS rk_t,
                    row_number() OVER (
                    PARTITION BY zone
                     ORDER BY usd_m DESC
                    ) AS rk_v,
                    sum(kt) OVER (
                    PARTITION BY zone
                    ) AS zone_kt,
                    sum(usd_m) OVER (
                    PARTITION BY zone
                    ) AS zone_usd
               FROM p
          LEFT JOIN tn_faf_regions r ON r.faf_id = p.partner_id
              WHERE p.partner_id NOT IN ('471', '472', '473', '479')
          )
   SELECT zone,
          rk_t,
          partner,
          partner_id,
          round(kt) AS kt,
          round(usd_m) AS usd_m,
          round(100 * kt / zone_kt) AS pct_zone_tons,
          round(100 * usd_m / zone_usd) AS pct_zone_value,
          rk_v
     FROM ranked
    WHERE rk_t <= 6
       OR rk_v <= 6
 ORDER BY zone,
          rk_t

zone	rk_t	partner	partner_id	kt	usd_m	pct_zone_tons	pct_zone_value	rk_v
471	1	Mississippi	280	4467	12502	15	10	2
471	2	Rest of MO	299	4221	1045	14	1	22
471	3	Arkansas	050	3392	15650	12	13	1
471	4	Houston TX	486	1396	2345	5	2	15
471	5	Eastern Asia	807	704	6036	2	5	5
471	6	Rest of KY	219	612	928	2	1	27
471	14	Europe	804	405	8375	1	7	3
471	40	New York NY-NJ-CT-PA (NJ Part)	341	161	6812	1	6	4
471	62	Louisville KY-IN (KY Part)	212	72	3229	0	3	6
472	1	Rest of KY	219	7218	12037	14	7	2
472	2	Las Vegas NV	321	5466	205	10	0	100
472	3	Rest of AL	019	2895	5410	5	3	5
472	4	Atlanta GA	131	2701	7767	5	4	3
472	5	Birmingham AL	011	2061	4687	4	3	9
472	6	Eastern Asia	807	1799	20827	3	12	1
472	15	SE Asia & Oceania	808	846	4933	2	3	6
472	16	Europe	804	846	6617	2	4	4
473	1	Rest of IN	189	19512	1585	46	3	9
473	2	Rest of KY	219	3217	2959	8	5	3
473	3	Houston TX	486	1609	2304	4	4	7
473	4	Atlanta GA	131	1160	3381	3	6	2
473	5	Eastern Asia	807	1050	6311	2	10	1
473	6	Rest of NC	379	815	1292	2	2	11
473	8	Canada	801	628	2655	1	4	4
473	15	Europe	804	473	2461	1	4	6

25 out of 36 are listed here.

data/turn-1-query-8.csv

Query 9 — Rank commodities within truck, rail and water by tonnage and value.

     WITH f AS (
             SELECT o.dms_mode,
                    o.sctg2,
                    o.tons,
                    o.value
               FROM tn_faf_od o
              WHERE o.dms_mode IN (1, 2, 3)
          ),
          g AS (
             SELECT dms_mode,
                    sctg2,
                    sum(tons) kt,
                    sum(value) usd
               FROM f
           GROUP BY 1,
                    2
          ),
          r AS (
             SELECT g.*,
                    s.title,
                    row_number() OVER (
                    PARTITION BY dms_mode
                     ORDER BY kt DESC
                    ) rk_t,
                    row_number() OVER (
                    PARTITION BY dms_mode
                     ORDER BY usd DESC
                    ) rk_v,
                    sum(kt) OVER (
                    PARTITION BY dms_mode
                    ) mode_kt,
                    sum(usd) OVER (
                    PARTITION BY dms_mode
                    ) mode_usd
               FROM g
          LEFT JOIN tn_faf_sctg s ON s.sctg2 = g.sctg2
          )
   SELECT dms_mode,
          m.name AS mode,
          title,
          round(kt) kt,
          round(usd) usd_m,
          round(100 * kt / mode_kt) pct_mode_tons,
          round(100 * usd / mode_usd) pct_mode_value,
          rk_t,
          rk_v
     FROM r
LEFT JOIN tn_faf_modes m ON m.code = r.dms_mode
    WHERE rk_t <= 5
       OR rk_v <= 5
 ORDER BY dms_mode,
          rk_t

dms_mode	mode	title	kt	usd_m	pct_mode_tons	pct_mode_value	rk_t	rk_v
1	Truck (include customer pick-up)	Gravel	44751	740	14	0	1	35
1	Truck (include customer pick-up)	Nonmetal min. prods.	30768	11652	10	2	2	16
1	Truck (include customer pick-up)	Natural gas and other fossil products	25822	8083	8	1	3	20
1	Truck (include customer pick-up)	Waste/scrap	17514	2950	6	0	4	32
1	Truck (include customer pick-up)	Natural sands	16363	305	5	0	5	39
1	Truck (include customer pick-up)	Mixed freight	10866	46213	3	7	8	5
1	Truck (include customer pick-up)	Machinery	8205	49077	3	8	13	4
1	Truck (include customer pick-up)	Motorized vehicles	8188	79419	3	12	15	2
1	Truck (include customer pick-up)	Electronics	4904	59661	2	9	21	3
1	Truck (include customer pick-up)	Pharmaceuticals	2012	81355	1	13	31	1
2	Rail	Cereal grains	19772	804	39	3	1	8
2	Rail	Coal	5480	329	11	1	2	17
2	Rail	Gasoline	4657	4745	9	18	3	2
2	Rail	Gravel	3529	34	7	0	4	34
2	Rail	Basic chemicals	3034	2633	6	10	5	3
2	Rail	Base metals	1108	1736	2	6	8	5
2	Rail	Plastics/rubber	1056	1769	2	7	9	4
2	Rail	Motorized vehicles	635	5954	1	22	15	1
3	Water	Gravel	5440	39	64	1	1	22
3	Water	Other ag prods.	944	447	11	12	2	2
3	Water	Cereal grains	610	189	7	5	3	5
3	Water	Metallic ores	192	48	2	1	4	17
3	Water	Motorized vehicles	167	821	2	22	5	1
3	Water	Textiles/leather	82	399	1	11	9	3
3	Water	Machinery	64	299	1	8	12	4

data/turn-1-query-9.csv

Query 10 — Measure how much truck, rail and water freight stays inside Tennessee zone to zone.

   SELECT o.dms_mode,
          m.name,
          round(
          sum(o.tons) FILTER (
              WHERE o.dms_orig IN ('471', '472', '473', '479')
                AND o.dms_dest IN ('471', '472', '473', '479')
          )
          ) AS intra_tn_kt,
          round(sum(o.tons)) AS all_kt,
          round(
          sum(o.value) FILTER (
              WHERE o.dms_orig IN ('471', '472', '473', '479')
                AND o.dms_dest IN ('471', '472', '473', '479')
          )
          ) AS intra_tn_usd_m,
          round(sum(o.value)) AS all_usd_m
     FROM tn_faf_od o
LEFT JOIN tn_faf_modes m ON m.code = o.dms_mode
    WHERE o.dms_mode IN (1, 2, 3)
 GROUP BY 1,
          2
 ORDER BY 1

dms_mode	name	intra_tn_kt	all_kt	intra_tn_usd_m	all_usd_m
1	Truck (include customer pick-up)	165207	316470	161535	636722
2	Rail	9745	51105	5967	26884
3	Water	31	8455	16	3689

data/turn-1-query-10.csv

Map Layer Queries

Tennessee freight zones (FAF 2022)

     WITH legs AS (
             SELECT dms_orig AS zone,
                    CASE
                              WHEN trade_type = 1 THEN dms_dest
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END AS partner_id,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_orig IN ('471', '472', '473', '479')
          UNION ALL
             SELECT dms_dest,
                    CASE
                              WHEN trade_type = 1 THEN dms_orig
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_dest IN ('471', '472', '473', '479')
          ),
          ext AS (
             SELECT zone,
                    sum(tons) AS kt,
                    sum(value) AS usd
               FROM legs
              WHERE partner_id NOT IN ('471', '472', '473', '479')
           GROUP BY zone
          )
   SELECT r.geom,
          r.short_name AS "Freight zone",
          round(e.kt) AS "External tons, truck+rail+water(kt)",
          round(e.usd) AS "External value, truck+rail+water($M 2022)"
     FROM tn_faf_regions r
     JOIN ext e ON e.zone = r.faf_id
    WHERE r.state = 'TN'

Picture: maps/turn-1-tn-freight-zones-partners.png

Top 5 partner flows by tons (from each zone) — colored by "From zone": From Memphis (#d62828), From Nashville (#f77f00), From Knoxville (#2a9d8f), From rest of TN (#6a4c93)

     WITH legs AS (
             SELECT dms_orig AS zone,
                    CASE
                              WHEN trade_type = 1 THEN dms_dest
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END AS partner_id,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_orig IN ('471', '472', '473', '479')
          UNION ALL
             SELECT dms_dest,
                    CASE
                              WHEN trade_type = 1 THEN dms_orig
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_dest IN ('471', '472', '473', '479')
          ),
          p AS (
             SELECT zone,
                    partner_id,
                    sum(tons) AS kt,
                    sum(value) AS usd
               FROM legs
              WHERE partner_id NOT IN ('471', '472', '473', '479')
           GROUP BY 1,
                    2
          ),
          rk AS (
             SELECT p.*,
                    row_number() OVER (
                    PARTITION BY zone
                     ORDER BY kt DESC
                    ) AS rn
               FROM p
               JOIN tn_faf_regions pr ON pr.faf_id = p.partner_id
                AND pr.centroid IS NOT NULL
          )
   SELECT ST_MakeLine(z.centroid, pr.centroid) AS geom,
          z.short_name AS "From zone",
          pr.short_name AS "Partner region",
          round(rk.kt) AS "Tons, truck+rail+water(kt)",
          round(rk.usd) AS "Value($M 2022)",
          rk.rn AS "Rank by tons in zone"
     FROM rk
     JOIN tn_faf_regions z ON z.faf_id = rk.zone
     JOIN tn_faf_regions pr ON pr.faf_id = rk.partner_id
    WHERE rk.rn <= 5

Picture: maps/turn-1-tn-freight-zones-partners.png

Top 5 partner regions (domestic)

     WITH legs AS (
             SELECT dms_orig AS zone,
                    CASE
                              WHEN trade_type = 1 THEN dms_dest
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END AS partner_id,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_orig IN ('471', '472', '473', '479')
          UNION ALL
             SELECT dms_dest,
                    CASE
                              WHEN trade_type = 1 THEN dms_orig
                              WHEN trade_type = 2 THEN fr_orig
                              ELSE fr_dest
                    END,
                    tons,
                    value
               FROM tn_faf_od
              WHERE dms_mode IN (1, 2, 3)
                AND dms_dest IN ('471', '472', '473', '479')
          ),
          p AS (
             SELECT zone,
                    partner_id,
                    sum(tons) AS kt,
                    sum(value) AS usd
               FROM legs
              WHERE partner_id NOT IN ('471', '472', '473', '479')
           GROUP BY 1,
                    2
          ),
          rk AS (
             SELECT p.*,
                    row_number() OVER (
                    PARTITION BY zone
                     ORDER BY kt DESC
                    ) AS rn
               FROM p
               JOIN tn_faf_regions pr ON pr.faf_id = p.partner_id
                AND pr.centroid IS NOT NULL
          )
   SELECT pr.centroid AS geom,
          pr.short_name AS "Partner region",
          string_agg(DISTINCT z.short_name, '; ') AS "Top-5 partner for",
          round(sum(rk.kt)) AS "Tons across those zones(kt)"
     FROM rk
     JOIN tn_faf_regions z ON z.faf_id = rk.zone
     JOIN tn_faf_regions pr ON pr.faf_id = rk.partner_id
    WHERE rk.rn <= 5
 GROUP BY pr.faf_id,
          pr.short_name,
          pr.centroid

Picture: maps/turn-1-tn-freight-zones-partners.png

Used Data Sets

tn_faf_modes — last synced 2026-09-27 · 8 rows
tn_faf_od — last synced 2026-09-27 · 120,212 rows
tn_faf_regions — last synced 2026-09-27 · 142 rows
tn_faf_sctg — last synced 2026-09-27 · 42 rows

data/turn-1-query-1.csv

↑ Contents

faf_id	short_name	name	region_type	rows_touch
471	Memphis TN-MS-AR (TN Part)	Memphis-Forrest City, TN-MS-AR CFS Area (TN Part)	C	56464
472	Nashville TN	Nashville-Davidson-Murfreesboro, TN CFS Area	C	23248
473	Knoxville TN	Knoxville-Morristown-Sevierville, TN CFS Area	C	20142
479	Rest of TN	Remainder of Tennessee	R	22929

4 rows.

data/turn-1-query-2.csv

↑ Contents

trade_type	dms_mode	name	kt	usd_m	count
1	1	Truck (include customer pick-up)	302211	542235	20629
1	6	Pipeline	122980	37101	140
1	2	Rail	46015	16167	423
1	5	Multiple modes & mail	44081	119011	16488
1	3	Water	7226	758	23
1	7	Other and unknown	3012	8527	1997
1	4	Air (include truck-air)	56	13598	1761
2	1	Truck (include customer pick-up)	8972	69141	8913
2	2	Rail	3192	7259	3078
2	5	Multiple modes & mail	1001	9087	2941
2	3	Water	781	2345	1701
2	4	Air (include truck-air)	306	45490	22842
2	6	Pipeline	102	22	6
2	7	Other and unknown	42	246	242
3	1	Truck (include customer pick-up)	5287	25346	8771
3	2	Rail	1898	3458	2924
3	5	Multiple modes & mail	463	1026	2394
3	3	Water	448	586	1334
3	4	Air (include truck-air)	322	57195	23525
3	7	Other and unknown	57	235	80

20 rows.

data/turn-1-query-3.csv

↑ Contents

faf_id	name	region_type	has_pt
471	Memphis-Forrest City, TN-MS-AR CFS Area (TN Part)	C	true
472	Nashville-Davidson-Murfreesboro, TN CFS Area	C	true
473	Knoxville-Morristown-Sevierville, TN CFS Area	C	true
479	Remainder of Tennessee	R	true
801	Canada	F	false
802	Mexico	F	false
803	Rest of Americas	F	false
804	Europe	F	false
805	Africa	F	false
806	SW & Central Asia	F	false
807	Eastern Asia	F	false
808	SE Asia & Oceania	F	false

12 rows.

data/turn-1-query-4.csv

↑ Contents

trade_type	orig_side	dest_side	has_fr_orig	has_fr_dest	count	kt	usd_m
1	non-TN	TN	false	false	10065	102022	191760
1	TN	non-TN	false	false	10419	78542	219824
1	TN	TN	false	false	591	174888	147577
2	non-TN	TN	true	false	11255	12838	58857
2	TN	non-TN	true	false	1301	22	1742
2	TN	TN	true	false	1136	86	18146
3	non-TN	TN	false	true	1069	9	1516
3	TN	non-TN	false	true	11072	7615	26078
3	TN	TN	false	true	888	8	1795

9 rows.

data/turn-1-query-5.csv

↑ Contents

partner_id	short_name	region_type	kt	usd_m	kt_domestic	kt_foreign	pct_tons
472	Nashville TN	C	77785	51210	77785	0	21
479	Rest of TN	R	56716	40754	56716	0	15
189	Rest of IN	R	22168	9256	22168	0	6
473	Knoxville TN	C	21342	21377	21342	0	6
219	Rest of KY	R	20284	25041	20284	0	5
471	Memphis TN-MS-AR (TN Part)	C	19045	34237	19045	0	5
019	Rest of AL	R	9424	13225	9424	0	3
280	Mississippi	R	9098	21607	9098	0	2
131	Atlanta GA	C	8852	26458	8852	0	2
299	Rest of MO	R	6862	3852	6862	0	2
050	Arkansas	R	6844	21553	6844	0	2
807	Eastern Asia	F	5692	35313		5692	2
321	Las Vegas NV	C	5508	607	5508	0	1
139	Rest of GA	R	5320	9441	5320	0	1
519	Rest of VA	R	4531	6439	4531	0	1

15 rows.

data/turn-1-query-6.csv

↑ Contents

partner_id	short_name	region_type	kt	usd_m	pct_value
472	Nashville TN	C	77785	51210	8
479	Rest of TN	R	56716	40754	6
807	Eastern Asia	F	5692	35313	5
471	Memphis TN-MS-AR (TN Part)	C	19045	34237	5
131	Atlanta GA	C	8852	26458	4
219	Rest of KY	R	20284	25041	4
280	Mississippi	R	9098	21607	3
050	Arkansas	R	6844	21553	3
473	Knoxville TN	C	21342	21377	3
804	Europe	F	2711	19858	3
801	Canada	F	3714	16382	2
802	Mexico	F	2794	16040	2
019	Rest of AL	R	9424	13225	2
808	SE Asia & Oceania	F	2648	11838	2
171	Chicago IL-IN-WI (IL Part)	C	2295	11815	2

15 rows.

data/turn-1-query-7.csv

↑ Contents

sctg2	title	kt	usd_m	pct_tons	pct_value
12	Gravel	53720	813	14	0
31	Nonmetal min. prods.	31353	11780	8	2
19	Natural gas and other fossil products	27971	8995	7	1
02	Cereal grains	27875	2963	7	0
41	Waste/scrap	18103	3230	5	0
11	Natural sands	16822	321	4	0
32	Base metals	16722	33174	4	5
26	Wood prods.	14139	13819	4	2
17	Gasoline	11968	10982	3	2
07	Other foodstuffs	11214	20400	3	3
43	Mixed freight	10872	46234	3	7
03	Other ag prods.	10458	8887	3	1
20	Basic chemicals	10018	12860	3	2
25	Logs	9945	803	3	0
24	Plastics/rubber	9381	34057	2	5

15 rows.

data/turn-1-query-8.csv

↑ Contents

zone	rk_t	partner	partner_id	kt	usd_m	pct_zone_tons	pct_zone_value	rk_v
471	1	Mississippi	280	4467	12502	15	10	2
471	2	Rest of MO	299	4221	1045	14	1	22
471	3	Arkansas	050	3392	15650	12	13	1
471	4	Houston TX	486	1396	2345	5	2	15
471	5	Eastern Asia	807	704	6036	2	5	5
471	6	Rest of KY	219	612	928	2	1	27
471	14	Europe	804	405	8375	1	7	3
471	40	New York NY-NJ-CT-PA (NJ Part)	341	161	6812	1	6	4
471	62	Louisville KY-IN (KY Part)	212	72	3229	0	3	6
472	1	Rest of KY	219	7218	12037	14	7	2
472	2	Las Vegas NV	321	5466	205	10	0	100
472	3	Rest of AL	019	2895	5410	5	3	5
472	4	Atlanta GA	131	2701	7767	5	4	3
472	5	Birmingham AL	011	2061	4687	4	3	9
472	6	Eastern Asia	807	1799	20827	3	12	1
472	15	SE Asia & Oceania	808	846	4933	2	3	6
472	16	Europe	804	846	6617	2	4	4
473	1	Rest of IN	189	19512	1585	46	3	9
473	2	Rest of KY	219	3217	2959	8	5	3
473	3	Houston TX	486	1609	2304	4	4	7
473	4	Atlanta GA	131	1160	3381	3	6	2
473	5	Eastern Asia	807	1050	6311	2	10	1
473	6	Rest of NC	379	815	1292	2	2	11
473	8	Canada	801	628	2655	1	4	4
473	15	Europe	804	473	2461	1	4	6
473	16	Mexico	802	470	2576	1	4	5
479	1	Rest of KY	219	9237	9117	12	5	3
479	2	Rest of AL	019	5673	5140	7	3	8
479	3	Atlanta GA	131	4398	12663	6	7	2
479	4	Rest of VA	519	3631	3498	5	2	14
479	5	Mississippi	280	3187	5589	4	3	7
479	6	Rest of GA	139	3011	4696	4	3	9
479	7	Eastern Asia	807	2184	13354	3	7	1
479	15	Canada	801	1407	6094	2	3	5
479	20	Mexico	802	1059	5987	1	3	6
479	22	Europe	804	1000	7839	1	4	4

36 rows.

data/turn-1-query-9.csv

↑ Contents

dms_mode	mode	title	kt	usd_m	pct_mode_tons	pct_mode_value	rk_t	rk_v
1	Truck (include customer pick-up)	Gravel	44751	740	14	0	1	35
1	Truck (include customer pick-up)	Nonmetal min. prods.	30768	11652	10	2	2	16
1	Truck (include customer pick-up)	Natural gas and other fossil products	25822	8083	8	1	3	20
1	Truck (include customer pick-up)	Waste/scrap	17514	2950	6	0	4	32
1	Truck (include customer pick-up)	Natural sands	16363	305	5	0	5	39
1	Truck (include customer pick-up)	Mixed freight	10866	46213	3	7	8	5
1	Truck (include customer pick-up)	Machinery	8205	49077	3	8	13	4
1	Truck (include customer pick-up)	Motorized vehicles	8188	79419	3	12	15	2
1	Truck (include customer pick-up)	Electronics	4904	59661	2	9	21	3
1	Truck (include customer pick-up)	Pharmaceuticals	2012	81355	1	13	31	1
2	Rail	Cereal grains	19772	804	39	3	1	8
2	Rail	Coal	5480	329	11	1	2	17
2	Rail	Gasoline	4657	4745	9	18	3	2
2	Rail	Gravel	3529	34	7	0	4	34
2	Rail	Basic chemicals	3034	2633	6	10	5	3
2	Rail	Base metals	1108	1736	2	6	8	5
2	Rail	Plastics/rubber	1056	1769	2	7	9	4
2	Rail	Motorized vehicles	635	5954	1	22	15	1
3	Water	Gravel	5440	39	64	1	1	22
3	Water	Other ag prods.	944	447	11	12	2	2
3	Water	Cereal grains	610	189	7	5	3	5
3	Water	Metallic ores	192	48	2	1	4	17
3	Water	Motorized vehicles	167	821	2	22	5	1
3	Water	Textiles/leather	82	399	1	11	9	3
3	Water	Machinery	64	299	1	8	12	4

25 rows.

data/turn-1-query-10.csv

↑ Contents

dms_mode	name	intra_tn_kt	all_kt	intra_tn_usd_m	all_usd_m
1	Truck (include customer pick-up)	165207	316470	161535	636722
2	Rail	9745	51105	5967	26884
3	Water	31	8455	16	3689

3 rows.

maps/turn-1-tn-freight-zones-partners.png

↑ Contents

provenance/tn_faf_modes.md

↑ Contents

Provenance: `tn_faf_modes`

This file describes how the rows in PostgreSQL table tn_faf_modes were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: tn_faf_modes
Family: FAF
Display name: FAF Transportation Modes
Source URL: https://faf.ornl.gov/faf6/data/Download_Files/ZIP/FAF6.0.zip
Geometry (source / stored): none
Update cycle: Manual

Pipeline (FAF family)

BTS Freight Analysis Framework version 6 (FAF6, 2022 CFS geography): Tennessee-touching origin–destination flows, the code lists, and the zones with BTS's own polygons. The flows and the code lists are read at sync time from the FAF6.0 regional zip (flows and the metadata workbook), and the zones from that zip and the FAF6 zone shapefile; the county crosswalk, where the state has one, is built from the Census county list and the zone file (doc/FAF-SYNC.md).

faf_modes — mode codes 1–8.
faf_sctg — 2-digit SCTG titles.
faf_regions — 134 domestic CFS areas + 8 foreign regions. Tennessee's 4 zones have BTS polygons; other domestic zones have a centroid; foreign regions have names only.
faf_county_xwalk — 95 Tennessee counties → FAF zone. Join tn_census_counties on county_fips.
faf_od — 2022 tons (thousand short tons) and value (million 2022 $) by origin, destination, commodity, and mode. Kept when dms_orig or dms_dest is a Tennessee zone.

U.S. Government Works. Cite BTS FAF6 https://doi.org/10.21949/fhgm-g335

Field → column mapping

Source field	Column	Esri type	Description
Numeric Label	`code`	smallint	1–8
Description	`name`	varchar(40)	Mode name

Geometry

No geometry column.

provenance/tn_faf_od.md

↑ Contents

Provenance: `tn_faf_od`

This file describes how the rows in PostgreSQL table tn_faf_od were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: tn_faf_od
Family: FAF
Display name: FAF Origin-Destination Commodity Flows (Tennessee-touching)
Source URL: https://faf.ornl.gov/faf6/data/Download_Files/ZIP/FAF6.0.zip
Geometry (source / stored): none
Update cycle: Manual

Pipeline (FAF family)

faf_modes — mode codes 1–8.
faf_sctg — 2-digit SCTG titles.
faf_regions — 134 domestic CFS areas + 8 foreign regions. Tennessee's 4 zones have BTS polygons; other domestic zones have a centroid; foreign regions have names only.
faf_county_xwalk — 95 Tennessee counties → FAF zone. Join tn_census_counties on county_fips.
faf_od — 2022 tons (thousand short tons) and value (million 2022 $) by origin, destination, commodity, and mode. Kept when dms_orig or dms_dest is a Tennessee zone.

U.S. Government Works. Cite BTS FAF6 https://doi.org/10.21949/fhgm-g335

Field → column mapping

Source field	Column	Esri type	Description
(FAF6.0)	`year`	smallint	2022
fr_orig	`fr_orig`	varchar(3)	Foreign origin; `''` if not import
dms_orig	`dms_orig`	varchar(3)	Domestic origin / US entry region
dms_dest	`dms_dest`	varchar(3)	Domestic dest / US exit region
fr_dest	`fr_dest`	varchar(3)	Foreign dest; `''` if not export
fr_inmode	`fr_inmode`	smallint	Import inbound mode; `0` if none
dms_mode	`dms_mode`	smallint	Domestic mode
fr_outmode	`fr_outmode`	smallint	Export outbound mode; `0` if none
sctg2	`sctg2`	varchar(2)	2-digit SCTG
trade_type	`trade_type`	smallint	1 domestic, 2 import, 3 export
tons_2022	`tons`	double precision	Thousand short tons
value_2022	`value`	double precision	Million 2022 $

Geometry

No geometry column.

provenance/tn_faf_regions.md

↑ Contents

Provenance: `tn_faf_regions`

This file describes how the rows in PostgreSQL table tn_faf_regions were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: tn_faf_regions
Family: FAF
Display name: FAF6 Regions
Source URL: https://faf.ornl.gov/faf6/data/FAF6.zip
Geometry (source / stored): polygon, NAD83 / geometry(MultiPolygon, 4326) (Tennessee's zones) and centroid (every domestic zone)
Update cycle: Manual

Pipeline (FAF family)

faf_modes — mode codes 1–8.
faf_sctg — 2-digit SCTG titles.
faf_regions — 134 domestic CFS areas + 8 foreign regions. Tennessee's 4 zones have BTS polygons; other domestic zones have a centroid; foreign regions have names only.
faf_county_xwalk — 95 Tennessee counties → FAF zone. Join tn_census_counties on county_fips.
faf_od — 2022 tons (thousand short tons) and value (million 2022 $) by origin, destination, commodity, and mode. Kept when dms_orig or dms_dest is a Tennessee zone.

U.S. Government Works. Cite BTS FAF6 https://doi.org/10.21949/fhgm-g335

Field → column mapping

Source field	Column	Esri type	Description
FAF6 / Numeric Label	`faf_id`	varchar(3)	`'471'`, `'801'`, …
CFS22_ID	`cfs_area`	varchar(6)	`'368'`, `'99999'`; null if foreign
Long Description (workbook)	`name`	text	Long CFS / foreign name
Short Description (workbook)	`short_name`	text	Short label
FAF6 id prefix	`state_fips`	varchar(2)	`'47'`; null if foreign
FAF6 id prefix	`state`	varchar(2)	USPS code; null if foreign
CFS22_ID	`region_type`	varchar(1)	C, M, R, or F: a real CBSA is M, else a real CSA is C, else R
FAF6.shp rings, `ST_BuildArea`, 4269 → 4326	`geom`	geometry(MultiPolygon, 4326)	Tennessee's zones only
ST_PointOnSurface of the zone polygon	`centroid`	geometry(Point, 4326)	every domestic zone

Geometry

SRID 4326 (WGS84). GIST index on geom.
Empty / null geometries stored as SQL NULL.

provenance/tn_faf_sctg.md

↑ Contents

Provenance: `tn_faf_sctg`

This file describes how the rows in PostgreSQL table tn_faf_sctg were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: tn_faf_sctg
Family: FAF
Display name: FAF SCTG Commodity Titles
Source URL: https://faf.ornl.gov/faf6/data/Download_Files/ZIP/FAF6.0.zip
Geometry (source / stored): none
Update cycle: Manual

Pipeline (FAF family)

faf_modes — mode codes 1–8.
faf_sctg — 2-digit SCTG titles.
faf_regions — 134 domestic CFS areas + 8 foreign regions. Tennessee's 4 zones have BTS polygons; other domestic zones have a centroid; foreign regions have names only.
faf_county_xwalk — 95 Tennessee counties → FAF zone. Join tn_census_counties on county_fips.
faf_od — 2022 tons (thousand short tons) and value (million 2022 $) by origin, destination, commodity, and mode. Kept when dms_orig or dms_dest is a Tennessee zone.

U.S. Government Works. Cite BTS FAF6 https://doi.org/10.21949/fhgm-g335

Field → column mapping

Source field	Column	Esri type	Description
Numeric Label	`sctg2`	varchar(2)	`'01'`–`'41'`, `'43'`
Description	`title`	text	Short commodity title

Geometry

No geometry column.

Tennessee Freight Zones and Top Partners

Layers

Data sets used

Ask your own question about Tennessee

Transcript

State Planner chat · https://stateplanner.com

Prompt

Response

Exploratory Queries

Query 1 — List Tennessee's four freight zones and their names.

Query 2 — Check the totals by trade type and mode.

Query 3 — Look up the foreign region names and check the Tennessee zone rows.

Query 4 — Check how domestic, import and export rows are split by Tennessee side for truck, rail and water.

Query 5 — Rank statewide trading partners for truck, rail and water by tonnage.

Query 6 — Rank statewide trading partners for truck, rail and water by value.

Query 7 — Rank commodities for truck, rail and water by tonnage and value.

Query 8 — Rank each Tennessee zone's external partners for truck, rail and water.

Query 9 — Rank commodities within truck, rail and water by tonnage and value.

Query 10 — Measure how much truck, rail and water freight stays inside Tennessee zone to zone.

Map Layer Queries

Tennessee freight zones (FAF 2022)

Top 5 partner flows by tons (from each zone) — colored by "From zone": From Memphis (#d62828), From Nashville (#f77f00), From Knoxville (#2a9d8f), From rest of TN (#6a4c93)

Top 5 partner regions (domestic)

Used Data Sets

Provenance: tn_faf_modes

Identity

Pipeline (FAF family)

Field → column mapping

Geometry

Provenance: tn_faf_od

Identity

Pipeline (FAF family)

Field → column mapping

Geometry

Provenance: tn_faf_regions

Identity

Pipeline (FAF family)

Field → column mapping

Geometry

Provenance: tn_faf_sctg

Identity

Pipeline (FAF family)

Field → column mapping

Geometry

Provenance: `tn_faf_modes`

Provenance: `tn_faf_od`

Provenance: `tn_faf_regions`

Provenance: `tn_faf_sctg`