Climatch

Land with a climate like Bankāpur

🇮🇳Bankāpur, Karnataka, India

The towns with the closest growing climate to Bankāpur are Davangere, India (99% match), Saundatti and Gokak. About 254,000 sq mi of land in 13 countries matches 80% or better, most of it in Karnataka, India, Piauí, Brazil and Maranhão, Brazil.The towns with the closest growing climate to Bankāpur are Davangere, India (99% match), Saundatti and Gokak. About 658,000 km² of land in 13 countries matches 80% or better, most of it in Karnataka, India, Piauí, Brazil and Maranhão, Brazil.

Your growing climate

Zone 12a · No frost · 0 chill hours · 35 in rainZone 12a · No frost · 0 chill hours · 900 mm rain

What grows in Bankāpur →

Regions with the most land like yours

  1. 1

    🇮🇳Karnataka, India

    52k sq mi133k km² matching 80% or better

    For example Honnāli (99), Davangere (99)

  2. 2

    🇧🇷Piauí, Brazil

    28k sq mi74k km² matching 80% or better

    For example Uruçuí (87), Bom Jesus (87)

  3. 3

    🇧🇷Maranhão, Brazil

    21k sq mi55k km² matching 80% or better

    For example São Raimundo das Mangabeiras (85), São João dos Patos (84)

  4. 4

    🇮🇳Maharashtra, India

    10k sq mi27k km² matching 80% or better

    For example Shiraguppi (97), Hupari (96)

  5. 5

    🇧🇷Goiás, Brazil

    9,300 sq mi24k km² matching 80% or better

    For example Campos Belos (82), Posse (80)

  6. 6

    🇲🇲Magway, Myanmar

    7,000 sq mi18k km² matching 80% or better

    For example Taungdwingyi (84), Myaydo (81)

  7. 7

    🇨🇫Ouham-Fafa, Central African Republic

    5,900 sq mi15k km² matching 80% or better

    For example Bouca (85), Batangafo (77)

  8. 8

    🇬🇳Kindia, Guinea

    5,600 sq mi14k km² matching 80% or better

    For example Télimélé (88), Kolenté (86)

  9. 9

    🇲🇲Mandalay Region, Myanmar

    5,000 sq mi13k km² matching 80% or better

    For example Yamethin (84), Pyawbwe (84)

  10. 10

    🇮🇳Andhra Pradesh, India

    4,900 sq mi13k km² matching 80% or better

    For example Hindupur (92), Somandepalle (91)

  11. 11

    🇬🇳Labé Region, Guinea

    4,400 sq mi11k km² matching 80% or better

    For example Donghol-Sigon (80), Tougué (77)

  12. 12

    🇬🇳Faranah, Guinea

    4,100 sq mi11k km² matching 80% or better

    For example Banko (83), Dabola (82)

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

    🇮🇳DavangereKarnataka, India

    Zone 12a · No frost · 0 chill hours · 26 in rainZone 12a · No frost · 0 chill hours · 668 mm rain

    Shares 15 of your 17 great-fit crops

    99%match
  2. 2

    🇮🇳SaundattiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 41 in rainZone 12a · No frost · 0 chill hours · 1,039 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: avocado

    99%match
  3. 3

    🇮🇳GokakKarnataka, India

    Zone 12a · No frost · 0 chill hours · 38 in rainZone 12a · No frost · 0 chill hours · 972 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: avocado

    99%match
  4. 4

    🇮🇳Rabkavi-BanhattiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 792 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  5. 5

    🇮🇳ShivamoggaKarnataka, India

    Zone 12a · No frost · 0 chill hours · 41 in rainZone 12a · No frost · 0 chill hours · 1,050 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: avocado

    98%match
  6. 6

    🇮🇳ChitradurgaKarnataka, India

    Zone 12a · No frost · 0 chill hours · 24 in rainZone 12a · No frost · 0 chill hours · 614 mm rain

    Shares 14 of your 17 great-fit crops

    98%match
  7. 7

    🇮🇳GajendragarhKarnataka, India

    Zone 12a · No frost · 0 chill hours · 34 in rainZone 12a · No frost · 0 chill hours · 863 mm rain

    Shares 17 of your 17 great-fit crops

    97%match
  8. 8

    🇮🇳KottūruKarnataka, India

    Zone 12a · No frost · 0 chill hours · 27 in rainZone 12a · No frost · 0 chill hours · 681 mm rain

    Shares 15 of your 17 great-fit crops

    96%match
  9. 9

    🇮🇳BirūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 26 in rainZone 12a · No frost · 0 chill hours · 669 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: canola (rapeseed)

    96%match
  10. 10

    🇮🇳KoppalKarnataka, India

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 778 mm rain

    Shares 16 of your 17 great-fit crops

    96%match
  11. 11

    🇮🇳TumkūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 786 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: avocado, canola (rapeseed), barley

    96%match
  12. 12

    🇮🇳KadūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 25 in rainZone 12a · No frost · 0 chill hours · 647 mm rain

    Shares 14 of your 17 great-fit crops · Also great there: canola (rapeseed)

    96%match
  13. 13

    🇮🇳Urun-IslāmpurMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 34 in rainZone 11b · No frost · 0 chill hours · 872 mm rain

    Shares 17 of your 17 great-fit crops

    95%match
  14. 14

    🇮🇳AlnāvarKarnataka, India

    Zone 12a · No frost · 0 chill hours · 60 in rainZone 12a · No frost · 0 chill hours · 1,516 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: avocado

    95%match
  15. 15

    🇮🇳BagalkotKarnataka, India

    Zone 12a · No frost · 0 chill hours · 28 in rainZone 12a · No frost · 0 chill hours · 714 mm rain

    Shares 15 of your 17 great-fit crops

    94%match
  16. 16

    🇮🇳HosapeteKarnataka, India

    Zone 12a · No frost · 0 chill hours · 30 in rainZone 12a · No frost · 0 chill hours · 766 mm rain

    Shares 16 of your 17 great-fit crops

    94%match
  17. 17

    🇮🇳SāngliMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 29 in rainZone 11b · No frost · 0 chill hours · 737 mm rain

    Shares 17 of your 17 great-fit crops

    94%match
  18. 18

    🇮🇳SīraKarnataka, India

    Zone 12a · No frost · 0 chill hours · 22 in rainZone 12a · No frost · 0 chill hours · 569 mm rain

    Shares 14 of your 17 great-fit crops

    94%match
  19. 19

    🇮🇳PachgaonMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 51 in rainZone 11b · No frost · 0 chill hours · 1,290 mm rain

    Shares 16 of your 17 great-fit crops

    93%match
  20. 20

    🇮🇳ClosepetKarnataka, India

    Zone 12a · No frost · 0 chill hours · 32 in rainZone 12a · No frost · 0 chill hours · 812 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: avocado, canola (rapeseed)

    93%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 Bankāpur: 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.