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You need to quantify Laem Chabang congestion reliably, but you keep bumping into “live AIS wait time” dashboards that don’t match what your planners see on the ground. By the end of this post, you’ll pull IMF PortWatch–based congestion/activity for Laem Chabang (THLCH), understand the 6–7 day lag, and drop copy‑pasteable code into your system to monitor the 7‑day average versus the 90‑day baseline.

What the Laem Chabang congestion signal measures (and what it doesn’t)

The FreightPulse congestion/activity feed for THLCH is sourced from IMF PortWatch using UN Global Platform AIS data. It is not a live “vessel wait time” metric. Instead, it compares the average number of port calls over the most recent 7 days to a 90‑day historical baseline for the same port.

Illustration: Laem Chabang Congestion Today

Because of upstream processing, the data is typically lagged about 6–7 days even though it updates daily. Treat it as a short‑lag operational signal, not a real‑time anchorage/wait KPI. A lower recent average can reflect lower throughput or disruptions; a higher recent average can reflect elevated activity but is not a direct measurement of queue length or berth wait.

Quick start: Query THLCH congestion

Use the single‑port endpoint with your API key in the X-API-Key header. The response is a JSON envelope with the shape {"success": true, "data": {...}} and a results array for the port.

cURL:

curl -H "X-API-Key: YOUR_API_KEY" "https://freightpulsehq.com/api/v1/port-congestion?port=THLCH"

JSON:

{
    "success": true,
    "data": {
        "results": [
            {
                "port": "Laem Chabang",
                "locode": "TH LCH",
                "country": "Thailand",
                "activity": "moderate",
                "congestion": "moderate",
                "as_of": "2026-10-30",
                "metrics": {
                    "recent_avg_portcalls_per_day": 18,
                    "baseline_avg_portcalls_per_day": 19,
                    "ratio_vs_baseline": 0.95
                }
            }
        ],
        "global_summary": {
            "ports_high_activity": 0,
            "ports_moderate_activity": 1,
            "ports_low_activity": 0,
            "ports_high_congestion": 0,
            "ports_moderate": 1,
            "ports_low": 0
        },
        "meta": {
            "source": "IMF PortWatch (portwatch.imf.org) - UN Global Platform AIS data",
            "data_lag_days": "~6-7 (daily updates, not real-time)",
            "methodology": "activity is port-call volume, not congestion: last 7 days' avg calls vs a 90-day baseline for the same port. low means fewer calls than usual, which can be a closure or ships waiting offshore. It does not measure vessel wait or anchorage time. congestion is a deprecated alias of activity."
        }
    },
    "meta": {
        "request_id": "f09260bd-49de-40a0-bd56-6ecd18ee2e37"
    }
}

Field notes you’ll actually use:

Python example: Fetch and interpret Laem Chabang

This script calls the same endpoint, extracts the key fields, and prints a human‑readable summary. It handles the standard success envelope and a single result for THLCH.

import os
import requests

API_KEY = os.getenv("FREIGHTPULSE_API_KEY", "YOUR_API_KEY")
URL = "https://freightpulsehq.com/api/v1/port-congestion"
PORT = "THLCH"

headers = {"X-API-Key": API_KEY}
params = {"port": PORT} # the endpoint uses a 'port' query with the code THLCH

resp = requests.get(URL, headers=headers, params=params, timeout=20)
resp.raise_for_status()
payload = resp.json()

if not payload.get("success"):
raise RuntimeError("API returned success=false")

data = payload.get("data", {})
results = data.get("results", [])
if not results:
raise RuntimeError("No results for port THLCH")

r = results[0]
as_of = r.get("as_of")
activity = r.get("activity")
congestion = r.get("congestion") # alias of activity
metrics = r.get("metrics", {})
recent = metrics.get("recent_avg_portcalls_per_day")
baseline = metrics.get("baseline_avg_portcalls_per_day")
ratio = metrics.get("ratio_vs_baseline")

print(f"Port: {r.get('port')} ({r.get('locode')}) - {r.get('country')}")
print(f"As of (lagged): {as_of}")
print(f"Activity label: {activity} (alias: congestion={congestion})")
print(f"7-day avg port calls: {recent}")
print(f"90-day baseline: {baseline}")
print(f"Ratio vs baseline: {ratio}")

# Simple classification you can reuse for alerts
if ratio is not None:
if ratio < 0.8:
status = "low activity vs baseline"
elif ratio < 1.1:
status = "near baseline (moderate)"
else:
status = "elevated activity vs baseline"
print(f"Operational status: {status}")

Interpreting Laem Chabang’s signal for planning

Use ratio_vs_baseline for relative change. A ratio moderately below 1.0 indicates fewer recent calls than the port’s 90‑day baseline; above 1.0 indicates more. Because the metric is activity (port‑call volume), do not treat it as a direct proxy for berth wait time or anchorage queue. It is useful to detect deviations that often coincide with disruptions, closures, holidays, or surges.

The as_of date is the reference for the 7‑day window end and is typically several days behind today due to the upstream lag. If you display this to operations teams, label it clearly as “lagged by ~6–7 days” to prevent confusion with live AIS tiles.

Operational implementation notes

How to present the THLCH signal to end users

Origin catalog facts for this feed

FAQ

Is this “congestion” value a real measurement of wait time at Laem Chabang?

No. It is an activity label based on recent port‑call volume versus a 90‑day baseline from IMF PortWatch. It does not measure vessel wait time or anchorage duration.

How fresh is the THLCH data?

The dataset updates daily but is typically lagged by about 6–7 days due to upstream processing. Use the as_of date in the response to anchor your displays and alerts.

What’s the best single number to alert on?

Use metrics.ratio_vs_baseline. For example, trigger alerts when the ratio crosses thresholds relevant to your operations (e.g., below 0.8 or above 1.2) and confirm with the activity label.

Do I need an API key?

You can make up to 100 requests/day per IP without a key. For reliable production use and higher volume, register and use X-API-Key in the request header.

Can I query multiple ports at once?

This guide focuses on Laem Chabang (THLCH). If you expand to multiple ports, iterate over the set of port codes and combine the results array from each call. Check the Documentation for broader query patterns.

Set up your key and start pulling lagged PortWatch congestion/activity for Laem Chabang in minutes. Create your account here: Register.