Climatch

Land with a climate like Sangkapura

🇮🇩Sangkapura, East Java, Indonesia

The towns with the closest growing climate to Sangkapura are Indramayu, Indonesia (99% match), Tegal and Cirebon. About 878,000 sq mi of land in 28 countries matches 80% or better, most of it in Pará, Brazil, Bolívar, Venezuela and Mimaropa, Philippines.The towns with the closest growing climate to Sangkapura are Indramayu, Indonesia (99% match), Tegal and Cirebon. About 2.3 million km² of land in 28 countries matches 80% or better, most of it in Pará, Brazil, Bolívar, Venezuela and Mimaropa, Philippines.

Your growing climate

Zone 13b · No frost · 0 chill hours · 77 in rainZone 13b · No frost · 0 chill hours · 1,947 mm rain

What grows in Sangkapura →

Regions with the most land like yours

  1. 1

    🇧🇷Pará, Brazil

    75k sq mi193k km² matching 80% or better

    For example Breu Branco (87), Tucuruí (87)

  2. 2

    🇻🇪Bolívar, Venezuela

    29k sq mi75k km² matching 80% or better

    For example La Paragua (92), Ciudad Piar (89)

  3. 3

    🇵🇭Mimaropa, Philippines

    22k sq mi58k km² matching 80% or better

    For example Roxas (95), El Nido (93)

  4. 4

    🇮🇩East Java, Indonesia

    21k sq mi55k km² matching 80% or better

    For example Bangkalan (99), Gresik (99)

  5. 5

    🇧🇷Amazonas, Brazil

    19k sq mi49k km² matching 80% or better

    For example Nhamundá (84), Urucará (84)

  6. 6

    🇮🇩East Nusa Tenggara, Indonesia

    18k sq mi47k km² matching 80% or better

    For example Tambolaka (94), Labuan Bajo (94)

  7. 7

    🇮🇩Central Java, Indonesia

    15k sq mi38k km² matching 80% or better

    For example Tegal (99), Bulakamba (99)

  8. 8

    🇨🇴Vichada Department, Colombia

    11k sq mi29k km² matching 80% or better

    For example Cumaribo (84), Puerto Carreño (84)

  9. 9

    🇻🇪Monagas, Venezuela

    10k sq mi27k km² matching 80% or better

    For example Barrancas (89), Caripito (86)

  10. 10

    🇧🇷Maranhão, Brazil

    10k sq mi26k km² matching 80% or better

    For example Pindaré-Mirim (86), Penalva (86)

  11. 11

    🇻🇪Anzoátegui, Venezuela

    9,400 sq mi24k km² matching 80% or better

    For example Soledad (89), Puerto La Cruz (84)

  12. 12

    🇨🇴Antioquia, Colombia

    8,900 sq mi23k km² matching 80% or better

    For example San Pedro de Urabá (92), San Juan de Urabá (92)

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

    🇮🇩IndramayuWest Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 67 in rainZone 13b · No frost · 0 chill hours · 1,691 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  2. 2

    🇮🇩TegalCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 76 in rainZone 13a · No frost · 0 chill hours · 1,943 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  3. 3

    🇮🇩CirebonWest Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 89 in rainZone 13b · No frost · 0 chill hours · 2,267 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  4. 4

    🇮🇩BangkalanEast Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 69 in rainZone 13a · No frost · 0 chill hours · 1,740 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  5. 5

    🇮🇩PamanukanWest Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 63 in rainZone 13b · No frost · 0 chill hours · 1,602 mm rain

    Shares 15 of your 18 great-fit crops

    99%match
  6. 6

    🇮🇩SumenepEast Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 62 in rainZone 13b · No frost · 0 chill hours · 1,569 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  7. 7

    🇮🇩PatiCentral Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 84 in rainZone 13b · No frost · 0 chill hours · 2,126 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  8. 8

    🇮🇩JeparaCentral Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 105 in rainZone 13b · No frost · 0 chill hours · 2,665 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  9. 9

    🇮🇩KarawangWest Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 70 in rainZone 13b · No frost · 0 chill hours · 1,789 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  10. 10

    🇮🇩BojonegoroEast Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 72 in rainZone 13a · No frost · 0 chill hours · 1,826 mm rain

    Shares 17 of your 18 great-fit crops

    98%match
  11. 11

    🇮🇩BloraCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 64 in rainZone 13a · No frost · 0 chill hours · 1,633 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  12. 12

    🇮🇩YogyakartaIndonesia

    Zone 13a · No frost · 0 chill hours · 85 in rainZone 13a · No frost · 0 chill hours · 2,165 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  13. 13

    🇮🇩MakassarSouth Sulawesi, Indonesia

    Zone 13b · No frost · 0 chill hours · 109 in rainZone 13b · No frost · 0 chill hours · 2,763 mm rain

    Shares 15 of your 18 great-fit crops

    98%match
  14. 14

    🇮🇩PamekasanEast Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 64 in rainZone 13a · No frost · 0 chill hours · 1,620 mm rain

    Shares 17 of your 18 great-fit crops

    98%match
  15. 15

    🇻🇳Cà Mau↻Seasons flipped. Ca Mau, Vietnam

    Zone 13b · No frost · 0 chill hours · 91 in rainZone 13b · No frost · 0 chill hours · 2,300 mm rain

    Shares 17 of your 18 great-fit crops

    97%match
  16. 16

    🇮🇩SemarangCentral Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 86 in rainZone 13b · No frost · 0 chill hours · 2,188 mm rain

    Shares 17 of your 18 great-fit crops

    97%match
  17. 17

    🇮🇩TeluknagaWest Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 71 in rainZone 13b · No frost · 0 chill hours · 1,795 mm rain

    Shares 18 of your 18 great-fit crops

    97%match
  18. 18

    🇮🇩KediriEast Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 73 in rainZone 13a · No frost · 0 chill hours · 1,856 mm rain

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

    97%match
  19. 19

    🇻🇳Cái Đôi Vàm↻Seasons flipped. Ca Mau, Vietnam

    Zone 13b · No frost · 0 chill hours · 89 in rainZone 13b · No frost · 0 chill hours · 2,270 mm rain

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

    97%match
  20. 20

    🇮🇩LumajangEast Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 74 in rainZone 13a · No frost · 0 chill hours · 1,884 mm rain

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

    96%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 Sangkapura: 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.