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Suitability Data
Suitability Data

Learn about the underlying data behind OY suitability maps.

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Written by Support
Updated over a year ago

Overyield’s Suitability Layer provide users with a better understanding of their land’s productive potential by way of various crop, soil, and climate heat-maps. The following article describes the underlying algorithms for these maps while citing each crop map’s data sources.


Basics

In generating Suitability maps for the continental US, Overyield cross-references a given crop’s environmental preferences with a selected parcel’s soil and climate characteristics, obtained through USGS and NRCS datasets.

These datasets indicate a parcel’s pH, depth to restrictive layer (i.e. bedrock), depth to the water table, flooding frequency, slope percentage, drainage class, hydric rating, and soil surface texture.


Calculations

For each soil and climate parameter, potential values realizable across the continental US are pre-defined, given as ranges. Take, for example, the table below, which lists potential slope values within our algorithm. These values run the gamut from 0-3% to 100-1000%.

Parameter

Low

High

Score

Score Notes

Slope

0

3

3

Ok

Slope

3

8

5

Prefers slight slope for drainage

Slope

8

25

3

Ok

Slope

25

50

0

Likely unsuitable

Slope

50

60

-100

Unsuitable for equipment

Slope

60

70

-100

Slope

70

80

-100

Slope

80

90

-100

Slope

90

100

-100

Slope

100

1000

-100

For each parameter, a crop’s suitability is then determined by assigning an acceptability score to individual ranges, depending on the crop’s preferences. In the given example, a crop preferring a slight slope achieved a score of 5 for the 3-8% range, in contrast to scores of 3, 0, and an arbitrary negative number — in this case -100 — for slopes that are less suitable or unsuitable for that crop.

A color classification system is then applied to these scores, with high suitability scores represented by deep green, and the low suitability scores represented by red.

Three additional classifications, represented by varying shades of grey, are unsuitable due to land use and/or environmental factors.

Data sources

Parcel Data

American Elderberry

Chinese Chestnut

American Hazelnut

Black Locust

Suitability Maps in Testing

The following maps are in progress, their approval pending validation:

Common Name

Latin Genus

Latin Species

Apple

Malus

domestica

Aronia

Aronia

melanocarpa

Bitternut Hickory

Carya

cordiformis

Blackcurrant

Ribes

Nigrum

European Elderberry

Sambucus

nigra

European Hazelnut

Corylus

avellana

Fodder Mulberry (same as Mulberry fruit)

Morus

alba

Honey Locust

Gleditsia

triacanthos

Hybrid Poplar

Populus

deltoides/ nigra

Paulownia

Paulownia

spp

Peach

Prunus

persica

Pecan

Carya

illinoinensis

Saskatoon

Amelanchier

alnifolia

Silver Maple

Acer

saccharinum

Sycamore

Platanus

spp

Willow (SX-61)

Salix

spp

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