Climatch

Land with a climate like Lahad Datu

🇲🇾Lahad Datu, Sabah, Malaysia

The towns with the closest growing climate to Lahad Datu are Sandakan, Malaysia (99% match), Sitangkai and Bongao. About 1.9 million sq mi of land in 48 countries matches 80% or better, most of it in Sarawak, Malaysia, Amazonas, Brazil and Sabah, Malaysia.The towns with the closest growing climate to Lahad Datu are Sandakan, Malaysia (99% match), Sitangkai and Bongao. About 5.0 million km² of land in 48 countries matches 80% or better, most of it in Sarawak, Malaysia, Amazonas, Brazil and Sabah, Malaysia.

Your growing climate

Zone 13b · No frost · 0 chill hours · 79 in rainZone 13b · No frost · 0 chill hours · 1,996 mm rain

What grows in Lahad Datu →

Regions with the most land like yours

  1. 1

    🇲🇾Sarawak, Malaysia

    46k sq mi120k km² matching 80% or better

    For example Miri (97), Beluru (97)

  2. 2

    🇧🇷Amazonas, Brazil

    41k sq mi107k km² matching 80% or better

    For example Santa Isabel do Rio Negro (92), Barcelos (90)

  3. 3

    🇲🇾Sabah, Malaysia

    30k sq mi77k km² matching 80% or better

    For example Sandakan (99), Tawau (99)

  4. 4

    🇮🇩Central Kalimantan, Indonesia

    27k sq mi71k km² matching 80% or better

    For example Pangkalanbuun (92), Sampit (87)

  5. 5

    🇮🇩West Kalimantan, Indonesia

    25k sq mi64k km² matching 80% or better

    For example Sungai Raya (97), Pemangkat (96)

  6. 6

    🇮🇩North Sumatra, Indonesia

    23k sq mi59k km² matching 80% or better

    For example Bandar (95), Tanjungbalai (95)

  7. 7

    🇵🇭Bicol Region, Philippines

    17k sq mi45k km² matching 80% or better

    For example Esperanza (95), Masbate (95)

  8. 8

    🇵🇭Eastern Visayas, Philippines

    15k sq mi39k km² matching 80% or better

    For example Inopacan (96), Ormoc (94)

  9. 9

    🇵🇭Autonomous Region in Muslim Mindanao, Philippines

    15k sq mi38k km² matching 80% or better

    For example Sitangkai (99), Bongao (99)

  10. 10

    🇲🇾Johor, Malaysia

    13k sq mi35k km² matching 80% or better

    For example Pengerang (96), Kampung Selang (96)

  11. 11

    🇧🇷Bahia, Brazil

    9,900 sq mi26k km² matching 80% or better

    For example Ilhéus (88), Jaguaripe (87)

  12. 12

    🇨🇩Équateur, Democratic Republic of the Congo

    9,600 sq mi25k km² matching 80% or better

    For example Mbandaka (85), Bolenge (84)

Regions are states and provinces, counting land within 75 km of a town. At most three per country, so the list covers the world.

Closest towns

  1. 1

    🇲🇾SandakanSabah, Malaysia

    Zone 13b · No frost · 0 chill hours · 98 in rainZone 13b · No frost · 0 chill hours · 2,489 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  2. 2

    🇵🇭SitangkaiAutonomous Region in Muslim Mindanao, Philippines

    Zone 13b · No frost · 0 chill hours · 65 in rainZone 13b · No frost · 0 chill hours · 1,654 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  3. 3

    🇵🇭BongaoAutonomous Region in Muslim Mindanao, Philippines

    Zone 13b · No frost · 0 chill hours · 62 in rainZone 13b · No frost · 0 chill hours · 1,577 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  4. 4

    🇵🇭MatiDavao Region, Philippines

    Zone 13b · No frost · 0 chill hours · 76 in rainZone 13b · No frost · 0 chill hours · 1,939 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  5. 5

    🇲🇾TawauSabah, Malaysia

    Zone 13b · No frost · 0 chill hours · 85 in rainZone 13b · No frost · 0 chill hours · 2,156 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  6. 6

    🇵🇭MalitaDavao Region, Philippines

    Zone 13b · No frost · 0 chill hours · 69 in rainZone 13b · No frost · 0 chill hours · 1,751 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  7. 7

    🇵🇭MapunMimaropa, Philippines

    Zone 13b · No frost · 0 chill hours · 83 in rainZone 13b · No frost · 0 chill hours · 2,104 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  8. 8

    🇲🇾KudatSabah, Malaysia

    Zone 13b · No frost · 0 chill hours · 91 in rainZone 13b · No frost · 0 chill hours · 2,305 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  9. 9

    🇵🇭LuponDavao Region, Philippines

    Zone 13b · No frost · 0 chill hours · 82 in rainZone 13b · No frost · 0 chill hours · 2,071 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  10. 10

    🇵🇭GingoogNorthern Mindanao, Philippines

    Zone 13b · No frost · 0 chill hours · 107 in rainZone 13b · No frost · 0 chill hours · 2,709 mm rain

    Shares 16 of your 18 great-fit crops

    99%match
  11. 11

    🇮🇩TernateNorth Maluku, Indonesia

    Zone 13b · No frost · 0 chill hours · 89 in rainZone 13b · No frost · 0 chill hours · 2,252 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  12. 12

    🇮🇩DarubaNorth Maluku, Indonesia

    Zone 13b · No frost · 0 chill hours · 81 in rainZone 13b · No frost · 0 chill hours · 2,055 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  13. 13

    🇮🇩TobeloNorth Maluku, Indonesia

    Zone 13b · No frost · 0 chill hours · 82 in rainZone 13b · No frost · 0 chill hours · 2,084 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  14. 14

    🇮🇩Toli-ToliCentral Sulawesi, Indonesia

    Zone 13b · No frost · 0 chill hours · 82 in rainZone 13b · No frost · 0 chill hours · 2,095 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  15. 15

    🇵🇭ManayDavao Region, Philippines

    Zone 13b · No frost · 0 chill hours · 104 in rainZone 13b · No frost · 0 chill hours · 2,635 mm rain

    Shares 17 of your 18 great-fit crops

    98%match
  16. 16

    🇮🇩Waisai↻Seasons flipped. Southwest Papua, Indonesia

    Zone 13b · No frost · 0 chill hours · 105 in rainZone 13b · No frost · 0 chill hours · 2,663 mm rain

    Shares 17 of your 18 great-fit crops

    98%match
  17. 17

    🇮🇩Kawasi↻Seasons flipped. North Maluku, Indonesia

    Zone 13b · No frost · 0 chill hours · 66 in rainZone 13b · No frost · 0 chill hours · 1,667 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    98%match
  18. 18

    🇮🇩TahunaNorth Sulawesi, Indonesia

    Zone 13a · No frost · 0 chill hours · 106 in rainZone 13a · No frost · 0 chill hours · 2,693 mm rain

    Shares 17 of your 18 great-fit crops

    98%match
  19. 19

    🇵🇭DigosDavao Region, Philippines

    Zone 13b · No frost · 0 chill hours · 69 in rainZone 13b · No frost · 0 chill hours · 1,755 mm rain

    Shares 17 of your 18 great-fit crops

    98%match
  20. 20

    🇵🇭DavaoDavao Region, Philippines

    Zone 13b · No frost · 0 chill hours · 82 in rainZone 13b · No frost · 0 chill hours · 2,088 mm rain

    Shares 17 of your 18 great-fit crops

    97%match

Any town over 15,000 people, skipping those within 75 km of you. ↻ = seasons flipped across the equator.

How matching works

We compare all twelve months of average highs and lows, rain, humidity and sunshine, the same way as Climatch's places-like search, but weighted for growing: winter lows count most, since frost, chill and hardiness decide which perennials survive, then summer highs and rain. Humidity counts least.

Scores show how unusual a match this close is: 80 or better is closer than all but about 2% of random pairs of places. Across the equator seasons are lined up (↻), so a southern farm's January is compared with a northern July. Climate is only part of it: check soil, water and day length (it matters for photoperiod crops) before buying land.

Looking for land?

We're building detailed reports on land like Lahad Datu: frost risk year by year, water, and how each match's climate is shifting by 2050.

We'll only use your email for the report and related updates.

Climate data: TerraClimate 1991–2020 monthly averages (Abatzoglou, J.T. et al., 2018, Scientific Data 5:170191). Humidity is derived from TerraClimate vapor pressure; “sunshine” is solar radiation.

Places: GeoNames (CC BY 4.0). Map: © OpenStreetMap contributors, tiles by OpenFreeMap.

Grower tools: crop ranges from FAO ECOCROP and university extension guides (cited per crop). Daily weather, frost dates and chill are estimated from the monthly averages; chill portions use the Dynamic Model (Fishman, Erez & Couvillon, 1987), hardiness zones follow the USDA definition.