商业与商务

CBD, regional centres, and industrial zones

如何使用商业地图

要点

  • 地图数据通过 URA、HDB 和 OneMap API 进行刷新 - 将鼠标悬停在任何标记上即可获取实时值。
  • 使用过滤器面板按地区、卧室类型、价格范围或保有权缩小结果范围。
  • 单击任何标记或多边形可深入查看基础属性或区域详细信息。

它的作用

The Business Map visualises ACRA-registered businesses across Singapore with clustered markers, a heatmap mode, and a district-level choropleth showing business density. Data is sourced from ACRA (Accounting and Corporate Regulatory Authority) business registration records, covering all active registered entities with a Singapore address. The map supports 11 industry sector filters — including F&B, Retail, Financial Services, Technology, Healthcare, Education, Construction, Logistics, Professional Services, Manufacturing, and Other. In markers mode, businesses are clustered by proximity and colour-coded by sector; clicking a cluster expands it to individual markers. In heatmap mode, the kernel-density layer shows concentration intensity without individual markers. The choropleth mode colours each district by total business count or density per square kilometre.

You can find this map on ShiokNest under the Maps tab in the Commercial section. Use the sidebar filter panel to select one or more industry sectors, toggle between markers / heatmap / choropleth display modes, and filter by business status (active / closed / all). The map pairs naturally with the Industry Trends page for time-series data on how business registration in each sector has evolved from 1970 to the present.

为什么它很重要

Residential property value is partly a function of the commercial ecosystem surrounding it. A neighbourhood with a high density of stable F&B, retail, and professional services businesses has stronger foot traffic, better amenity provision, and more employment within walking or cycling distance — all factors that support rental demand and occupancy rates. The Business Map lets you verify this commercial ecosystem before committing to a purchase or investment, rather than relying on an agent's description of a neighbourhood as "vibrant" or "up-and-coming."

The most actionable use of this map is the sector-filter heatmap. Filter for F&B businesses only and switch to heatmap mode: the resulting concentration map shows you exactly where Singapore's restaurant and cafe density peaks — not just the known hotspots like Orchard and Clarke Quay, but also the secondary nodes in D15 (Katong), D12 (Toa Payoh Central), and D20 (Bishan North) that sustain strong rental demand from younger professionals and families. A 2-bedroom investor unit located within a genuine F&B and retail cluster commands a broader tenant audience than an equivalent unit in a residential-only neighbourhood with minimal walkable retail.

For buyers evaluating commercial property or office space, the Technology and Financial Services sector filters reveal the concentration of fintech, tech, and professional-services firms by district. D3 (Alexandra / one-north), D14 (Paya Lebar), and D9/D10 (Orchard fringe) show the highest concentrations. Cross-referencing these clusters with the commercial rental index (available on the Commercial analytics page) lets investors assess whether a target commercial property is in a sector-demand-aligned location or in a district with softer commercial occupancy.

The choropleth mode is valuable for a district-level overview before drilling down to markers. Switching to "density per km²" normalises the business count for district area — so large-area planning zones like D17 (Loyang/Changi) do not appear dominant purely by total business count when the per-km² density is actually low. This normalised view more accurately reflects the commercial vibrancy that residents experience at street level. Use this alongside the Commute Time Map and Heatmap Layers for a complete neighbourhood quality assessment.

它是如何运作的

  • 平移并缩放到您感兴趣的新加坡地区。
  • 使用过滤器面板按地区、卧室类型或价格范围缩小结果范围。
  • 将鼠标悬停在任何标记或多边形上,即可获得具有精确值的工具提示。
  • 单击标记可打开基础属性或区域详细信息页面。

示例

D15 F&B cluster: validating the "Katong is vibrant" claim

输入
Sector filter
F&B only
Display mode
Heatmap
Status filter
Active businesses only
Geographic zoom
D15 — East Coast / Katong area
结果
F&B density vs Singapore median
2.4× above district median
Hotspot streets
East Coast Road, Joo Chiat Road, Siglap
Comparison
D15 F&B density close to D9 (Orchard fringe) level
Implication
Strong tenant demand driver — F&B foot traffic supports residential occupancy

如何阅读此内容: The heatmap confirms D15's F&B concentration is genuinely comparable to D9 at the street level — not just aspirational marketing. For an investor evaluating a 2-bedroom condo in D15, this data supports a thesis that the F&B and lifestyle ecosystem sustains tenant demand from professionals who prioritise walkable dining options. The map also reveals that the F&B cluster is concentrated along East Coast Road and Joo Chiat — meaning a condo within 400m of these streets benefits more than one 1km away in the same district. This spatial granularity is impossible to see from district-level statistics.

Technology sector filter: mapping Singapore's tech cluster vs residential pricing

输入
Sector filter
Technology businesses only
Display mode
Choropleth (density per km²)
Status filter
Active only
结果
Highest tech density
D3 (one-north / Biopolis / Mapletree), D9, D14 (Paya Lebar)
Emerging cluster
D18 (Tampines Regional Centre)
Low density residential
D27 (Sembawang) — very low tech business density
Implication
Proximity to tech employer clusters supports expat/professional rental demand

如何阅读此内容: The technology density choropleth confirms that D3 (one-north) is the strongest tech employer cluster in Singapore — with significant density also in D9 and the emerging Paya Lebar QB hub. Residential properties in D3 (Queenstown, Alexandra) and D14 (Geylang fringe / Paya Lebar) are within direct commute range of these clusters, supporting sustained rental demand from tech workers. Investors evaluating D3 condos can use this data to validate the "tech worker tenant pool" thesis with ACRA registration data rather than relying on anecdote.

提示和陷阱

专家提示

  • 在深入各个地区之前,首先要缩小范围以发现宏观模式。
  • 将此地图与租金收益率地图进行比较,以找到高需求、低价的异常值。
  • 使用图例来理解颜色编码——相同的颜色在不同的地图上可能意味着不同的东西。

常见陷阱

  • 仅通过标题颜色来判断一个地区——整个新加坡的潜在样本量差异很大。
  • 当中位数和均值同时显示时,将两者混淆——均值因奢侈品异常值而产生偏差。
  • 忘记新推出的价格是打折的——转售价格是公平价值的更好基准。

常见问题解答

地图数据从哪里来?
数据来源于 URA(城市重建局)、HDB、OneMap 和新加坡政府官方 API,每月更新一次。
地图多久更新一次?
随着 URA 和 HDB 发布新数据,基于交易的地图每月更新一次。规划层(总体规划、GLS)按公告更新。
我可以按地区或卧室类型过滤吗?
是的 - 使用地图上的过滤器面板。过滤器状态保留在 URL 中,以便您可以共享特定视图的深层链接。