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GCRI · 贸易与战略资源

物流与冷链

Logistics move goods from producers to users through containers, warehouses, trucks, rail and air freight; the cold chain does the same for food, vaccines and medicines that must stay within a temperature range. Both depend on energy, equipment and labour, and both fail quietly before shortages show. This page sets out how logistics and cold chains work and break, how capacity and integrity are measured, and what evidence serves the operators and agencies responsible.

01画布

工作如何开展。

系统 · 围绕本主题示意

走廊与咽喉要道监测器

Logistics and cold chain · Corridor A · Week 28

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咽喉要道中断GCRI · 贸易与战略资源

走廊

红色:已中断

枢纽 A枢纽 B海峡港口枢纽枢纽 E枢纽 F终端咽喉要道N

恢复时间与生存时间

按关键投入品

化肥海峡76短
燃料海峡46紧张
半导体港口枢纽158短
谷物走廊 A511已覆盖
Corridor and chokepoint monitor: the screen’s structure, terms and states for Logistics and cold chain.示例名称和示意数值;是设计方案,并非记录或实时系统。

图Corridor and chokepoint monitor: example names and illustrative values, not a record or a live system.

02问题

Logistics and cold chain: how the risk develops.

Transport time and disruption. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

机制

Capacity is tightly balanced

Containers, vessels, trucks and warehouse space are run near full use to keep costs low. When demand jumps or capacity is lost, delays and costs rise sharply.

机制

Cold chains need constant power

Refrigerated stores and transport depend on electricity and fuel. Outages and equipment failures expose products to temperatures that reduce quality or make them unsafe.

机制

Labour is a critical link

Drivers, port workers and warehouse staff are often in short supply. Illness, strikes and border rules can stop flows as surely as damaged infrastructure.

机制

Losses show up as shortages

Spoiled food, lost vaccine doses and expired medicines are counted late, if at all. The first visible sign is often a 短缺 at the point of use.

03地理

马六甲海峡的活动与危害。

Night lights, population density and crop greenness over the Strait of Malacca, from NASA GIBS. Each layer carries its own date.

交互式地图需要JavaScript;图层列表和来源见下文。

图层 3

本页的活动与危害

关于本图层
证据
观测
来源
VIIRS Black Marble(VNP46A2)(NASA LAADS DAAC)
提供方
NASA LAADS DAAC
许可协议
NASA 开放数据
年份版本
每日;卫星辐射亮度,已校正月光和大气影响
构建时的最新内容
2026-10-12
处理结果
约 500 米网格
不确定性
所示日期的卫星夜间辐射亮度;灯光是用电和停电的替代指标,并非对供应或获得电力情况的测量。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
估计值
来源
世界网格化人口 v4.11(NASA SEDAC(哥伦比亚大学 CIESIN))
提供方
NASA SEDAC(哥伦比亚大学 CIESIN)
许可协议
CC BY 4.0
年份版本
null;基于人口普查的估算,静态(2020)
处理结果
约 1 公里网格
不确定性
基于人口普查的 2020 年每平方公里人口估算,作为风险暴露背景展示;不是受任何危害影响的人数。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
观测(云层造成缺口)
来源
VIIRS 全球洪水产品(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星探测;云层造成缺口
构建时的最新内容
2026-10-14
处理结果
约 250 米网格
不确定性
卫星探测;云层造成缺口。卫星或模型栅格数据,按提供方发布的原样呈现。云层、条带缺口和反演误差会造成缺口和噪声;数值是指标,而非某地的测量值。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
观测
来源
VIIRS NOAA-20 校正反射率(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星图像
构建时的最新内容
2026-10-14
处理结果
约 250 米网格
不确定性
卫星图像。卫星或模型栅格数据,按提供方发布的原样呈现。云层、条带缺口和反演误差会造成缺口和噪声;数值是指标,而非某地的测量值。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
模型生成(GIBS 发布的最新年份)
来源
MODIS Terra 和 Aqua 土地覆盖(MCD12Q1)(NASA LP DAAC)
提供方
NASA LP DAAC
许可协议
NASA 开放数据
年份版本
每年;卫星分类;GIBS 发布的最新年份
构建时的最新内容
2024-01-01
处理结果
约 500 米网格
不确定性
所示年份的卫星土地覆盖类别,含农田;该分类存在已知误差,并非农场登记册。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
观测(云层造成缺口)
来源
MODIS Terra NDVI(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星指数;云层造成缺口
构建时的最新内容
2026-10-13
处理结果
约 250 米网格
不确定性
截至所示日期 8 天的卫星绿度指数;是作物和牧草状况的指标,不是产量估算,也不是粮食安全预警。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问

最新可用

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth

正在加载最新的NASA影像。

拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放;悬停可查看指针下的数值;重置可返回该区域。

活动与危害,以马六甲海峡为取景。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。

数据:NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap 贡献者 · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERT来源与许可

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
  • VIIRS Black Marble 夜间灯光,NASA 戈达德航天中心;由 NASA Level-1 与大气档案和分发系统(LAADS DAAC)分发;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). 采用 CC BY 4.0 许可。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS 近实时产品(洪水、地表温度、积雪覆盖、校正反射率),NASA LANCE;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • MODIS 陆地产品(植被指数、总初级生产力、土地覆盖),NASA LP DAAC 和 LANCE;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • ASTER GDEM 是 METI 和 NASA 的产品(ASTER Global Digital Elevation Model V003,NASA LP DAAC);影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。引用格式:NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA 开放数据
  • 使用 Natural Earth 制作。免费矢量和栅格地图数据,见 naturalearthdata.com。 公有领域
  • © OpenStreetMap 贡献者(ODbL),经由 NASA GIBS(海岸线、边界、道路和地名)。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 ODbL
  • Blue Marble,NASA Earth Observatory;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • 地球仪和平面地图上的背景信息:海岸线、边界、道路和地名来自 NASA GIBS 参考图层(OpenStreetMap 数据,ODbL,© OpenStreetMap contributors);Blue Marble 影像可作为可选底图;3D 地形和高程读数来自 ASTER GDEM 高程色彩指数(5 m 至 200 m 分级,为便于辨识而作了夸张处理)。边界按已发布的样式绘制,不代表对任何领土的立场。
  • 实时事件:NASA Earth Observatory Natural Event Tracker(EONET);事件仅供参考,并保留其原始来源链接。
  • 实时:NASA EONET。事件仅供参考,不是主管机构的预警。
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • 天气数据来自 Open-Meteo.com (https://open-meteo.com/), 依据 CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). 授权。
  • 可选图层(图层列表中有 7 个来源:实时、预报、观测和背景)开启时会在地图上和此处显示其提供方署名;预报是模型输出,派生指数是估计值。

图层与日期

  • 夜间灯光,每日:VIIRS Black Marble(VNP46A2),NASA LAADS DAAC · 2026年10月12日
  • 人口密度,2020 年:人口:哥伦比亚大学 CIESIN,世界网格化人口 v4.11(2018),NASA SEDAC, CC BY 4.0 · 静态
  • 洪水水体,3 日合成:VIIRS 全球洪水产品,NASA LANCE · 2026年10月14日
  • 真彩色:VIIRS NOAA-20 校正反射率,NASA LANCE · 2026年10月13日
  • 土地覆盖类型(IGBP),年度:MODIS Terra 和 Aqua 土地覆盖(MCD12Q1),NASA LP DAAC · 2024
  • 植被绿度(NDVI),滚动 8 天:MODIS Terra NDVI,NASA LANCE · 2026年10月13日

04跨领域

Logistics and cold chains keep food and medicine moving.

05模拟器

冲击在投入产出经济中的传播。

一个部门的产出损失通过技术系数传导至其供应商和客户,并按您设定的速率恢复;这些系数是教学数值,不是国民账户。这是带有明示示意数值的教学模型,不是预测。本页地图显示马六甲海峡;模型本身不与任何地点绑定。

控制措施

最先受冲击的部门(在列表中的位置)
0
冲击规模
其产出的 30%
冲击持续时间
30 days
恢复速率
每天 0.08
模拟天数
180 days

读数

运行期间损失的产出
0.52% of a year’s output
总量与直接量之比(乘数)
1.59 times
受影响最大的其他部门
贸易
其峰值不可运行性
4.1%
数字、方法与来源
部门峰值不可运行性(%)产出权重(%)
农业30.2811.7
能源0.279.8
制造业0.6823.5
交通与港口0.3824.3
贸易4.0818.4
服务2.3812.2

方法

  1. 投入产出分析 Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
  2. 不可运行性投入产出模型 Haimes and Jiang (2001), Journal of Infrastructure Systems 7
  3. 动态不可运行性与恢复 Lian and Haimes (2006), Systems Engineering 9
  4. 不确定性扇形图(参数蒙特卡罗) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  5. 单因素敏感性(龙卷风图) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

数据

The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:

  • 海港 Natural Earth
  • 海上咽喉要道 Nexus(按公布坐标标注的指定海峡和运河)
  • 铁路 Natural Earth
  • 主要道路 Natural Earth
冲击在投入产出经济中的传导。示意性教学模型:它依据控件设定的数值运行,而非实测数据。方法:Input-output analysis (Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press);Inoperability input-output model (Haimes and Jiang (2001), Journal of Infrastructure Systems 7);Dynamic inoperability and recovery (Lian and Haimes (2006), Systems Engineering 9)。
06指标

衡量什么,以及衡量得如何。

每个指标都注明其单位、频率、背后的来源类型以及数值将附带的证据标签。此处不显示数值:数值由计划依据其自身权限提供。

指标单位节奏来源类型标签
Container dwell time at port天每周Port and terminal data观测
Warehouse vacancypercent of space每季度Property market reports已报告
Refrigerated storage capacitycubic metres per thousand population每次评估Industry and government surveys估算
Temperature excursions in vaccine cold chain每期计数每月Temperature monitoring devices观测
Food loss in supply chainpercent of production lost before retail每次评估SDG indicator 12.3.1(a) Food Loss Index估算
Truck driver vacancies计数年度Labour market statistics已报告
07孪生与级联模拟器

Model logistics and cold chain as a system. Run the cascade.

Assembled from the Nexus Standards area profile 供应链与贸易风险: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

灾害

  • 溃坝
  • 河流洪水 (在下游引发)
  • 山洪 (在下游引发)
  • 大规模流离失所(在下游引发)
  • 大范围停电(在下游引发)
  • 供水短缺(在下游引发)

控制措施

  • NS-0 章程与原则
  • NS-3 风险记录 UNI(语法、旧编码对照、分配机构)
  • NS-9 情境 UNI(部署、实例、计划实例)
  • NS-10 政策和条款(机器可读的义务:定义、约束、评估和执行)
  • NS-11 验证与监测(证据、证明、零信任符合性观测)
  • NS-12 软件、模型和 AI/ML 制品(供应链、模型卡、数据集说明)
  • NRS-H60 危害类别:供应链与流动中断(NHS-1 sys.supply-chain)
  • NRS-X4 贸易、运输与供应链风险
  • NRS-H89 危害类别:交通网络中断(NHS-1 infra.mobility)
  • NRS-K38 领域包概况:供应链与贸易(DOMAIN-038)
  • NRS-H43 危害族:畜牧业和水产养殖动物疫病(NHS-1 health.animal-health)
  • NRS-M10 方法结构:市场、贸易与供应链

观测

  • IMF PortWatch port activity and chokepoint disruptions (listed for reference)
  • Global Supply Chain Pressure Index (listed for reference)
  • OECD Data Explorer(SDMX API)(仅列作参考)
  • World Bank Open Data 和 World Development Indicators API(仅列作参考)
  • Developing countries’ and least developed countries’ share of global exports
  • Passenger and freight volumes, by mode of transport

示例地理范围

  • The Strait of Malacca: 227 hexagonal cells
  • 今夜夜间灯光与停电(VIIRS 昼夜波段),NASA GIBS
  • 穿透云层的地表水,30 m(OPERA DSWx-S1 雷达),NASA GIBS
  • 过去半小时降雨率(IMERG),NASA GIBS
  • 地表土壤湿度(SMAP),NASA GIBS
08来源

证据来自何处。

具名公共数据集与机构记录,各自注明许可类别。依协议获得的来源仅按其条款使用,绝不再次发布。

来源它提供什么许可类别
FAO Food Loss and Waste databaseFood loss estimates by commodity and stageOpen, FAO terms
WHO and UNICEF Effective Vaccine Management assessmentsVaccine supply chain performance in countriesPublic summaries, terms per agency
IMF PortWatch and UNCTADstatPort activity and maritime statisticsPublic, terms to check
International Institute of Refrigeration publicationsCold chain capacity and practiceLicence per publication
National transport and logistics statisticsFreight volumes, capacity and labourPublic records, licence per government
09方法与证据

How logistics and cold chain is modelled, measured and tested.

模型、其假设、数据和不确定性,以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意,不是研究发现。

系统模型

The couplings between the systems in logistics and cold chain: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−+贸易产业社区经济R 增强B 平衡
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR 指导原则 · GO FAIR 和 FORCE11W3C PROV · 万维网联盟关于一致处理不确定性的指南 · IPCCCEOS 分析就绪数据 · 地球观测卫星委员会
10决定

由谁决定,以及证据服务于什么。

Trade and Strategic Resources prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

谁来决定问题本页面服务的证据
Ministries of health and immunisation programmesWhere cold chain capacity and monitoring must improveCapacity maps; temperature excursion data
Ministries of agriculture and tradeWhere storage and logistics investment reduces food lossFood loss and capacity evidence
Logistics operatorsWhere to add buffer capacity and backup powerBottleneck analyses; power dependency reviews

该主题产生的产出

  • Cold chain capacity maps against food and health needs
  • Logistics bottleneck analyses from port and freight data
  • Power dependency reviews for cold stores
  • Evidence notes for supply continuity planning
11核心问题

What experts ask about logistics.

  • How much spare capacity exists in ports, fleets, warehouses and labour?
  • How long can goods wait before they lose value or become unsafe?
  • What happens to cold storage and transport when power fails?
  • How dependent is the system on digital platforms and data exchange?
  • Where do last-mile gaps leave communities without reliable supply?
12机制与驱动因素

Why time and temperature matter.

Logistics networks are designed for efficiency, which often means high utilisation and little slack. When demand surges or capacity is lost, queues build quickly: ships wait at anchor, containers pile up and delivery times stretch. Recovery takes time because equipment and crews must be repositioned.

Perishable goods add a hard constraint. Fresh food, vaccines and many medicines must be kept within temperature ranges throughout the journey. A break in the cold chain, from a power outage, a delayed truck or a failed refrigeration unit, can spoil the product. Losses in the cold chain are a significant source of food waste in many regions.

Logistics is increasingly digital. Booking, customs, tracking and payment 系统 are interconnected, so a 网络事件 or system outage at a major operator can halt physical flows.

13方法与数据

方法及其局限。

  1. 01

    Operations research models

    Queueing, routing and inventory models using 优化与运筹学. They rely on assumptions about behaviour under stress.

  2. 02

    Transport engineering

    Assessment of terminal, road and rail capacity using transport engineering.

  3. 03

    Temperature monitoring data

    Sensor records from cold-chain shipments. Data are proprietary and not standardised.

  4. 04

    Disruption case studies

    Structured analysis of past events. Each event is different, which limits generalisation.

Real operating data are mostly held by private operators, so public analysis often relies on proxies and case studies.

14方法

如何研究,以及方法无法说明的内容。

15Where this page’s references

Where this page’s references lead.

阅读本页时所对照的机构和文件。状态和版本会变化;每个链接都指向发布机构。

16问题

问题与解答。

What is a cold chain?
A temperature-controlled supply chain that keeps products such as food, vaccines and medicines within a specified temperature range from production to use.
What is a temperature excursion?
A period when a product is exposed to temperatures outside its permitted range, which may reduce its quality or safety.
Why do logistics problems appear suddenly?
Because capacity is run close to full and buffers are thin, so small losses of capacity or rises in demand quickly cause delays and shortages.
Does the platform cover humanitarian logistics?
It covers the systems and constraints that humanitarian logistics shares with commercial logistics. Operations remain with humanitarian agencies.
Why is the cold chain singled out?
Because temperature-sensitive goods, especially food and medicines, have little tolerance for delay and depend on continuous power.
Can operators contribute data?
Yes, by enquiry and under clear terms. Commercial data are not published without permission.
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GCRI贸易与战略资源战略系统情景与压力测试
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