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GIS In Relation to Crop Insurance

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GIS In Relation to Crop Insurance. Mark Coffman Spring 2011. Definition of Crop Insurance. - PowerPoint PPT Presentation
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GIS In Relation to Crop Insurance Mark Coffman Spring 2011
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Page 1: GIS In Relation to Crop Insurance

GIS In Relation to Crop Insurance

Mark CoffmanSpring 2011

Page 2: GIS In Relation to Crop Insurance

A contract of indemnity by which one party promises to compensate another for the financial loss incurred by the destruction of agricultural products from the forces of nature, such as rain, hail, frost, or insect infestation.

Definition of Crop Insurance

Page 3: GIS In Relation to Crop Insurance

In 1938, Congress passed the Federal Crop Insurance Act establishing the first Federal crop insurance program

Before this, private insurers had difficulty providing affordable insurance products to producers

The costs of the Federal Crop Insurance Act were high and participation was low

History of Crop Insurance

Page 4: GIS In Relation to Crop Insurance

In 1980, Congress passed legislation that would lower costs and raise participation rates by forming partnerships between private insurers and the government

In May 2000, Congress passed legislation forming the Agricultural Risk Protection Act (ARPA)

This made it easier for producers to access different insurance policies

History of Crop Insurance

Page 5: GIS In Relation to Crop Insurance

2010 Oklahoma Indemnity Map

Page 6: GIS In Relation to Crop Insurance

2010 Oklahoma Crop Profile

Page 7: GIS In Relation to Crop Insurance

Excellent risk management for producers Provides loan security for lenders Provides a concrete source for bottom line

protection

Why Producers Use Crop Insurance

Page 8: GIS In Relation to Crop Insurance

Crop Revenue Coverage (CRC) Revenue Assistance (RA)

◦ Revenue insurance protecting against low yields, low prices, or combinations of these.

◦ Indemnities are paid when actual gross revenue falls below a revenue guarantee

CRC and RA Insurance

Page 9: GIS In Relation to Crop Insurance

Actual Production History (APH) insurance is the longest running crop insurance

Cheapest form of crop insurance Only covers producers from loss of bushels Price fluctuations are not accounted for with

APH insurance The yield average is based on the history of

that particular farm

APH Crop Insurance

Page 10: GIS In Relation to Crop Insurance

Insurance◦ Farm Average: 40 bu◦ 75% coverage level◦ 40 * 75% = 30 bu/ac yield guarantee

Actual Yield◦ 15 bu/ac◦ 100 acres◦ $5.00 price election◦ 30 – 15 = 15 bu/ac◦ Indemnity payment

15 bu/ac * 100 acres * $5/bu = $7,500

APH Plans

Page 11: GIS In Relation to Crop Insurance

Fire Insects (only if control practices were used) Plant diseases Wildlife Earthquake Volcanic eruption Failure of irrigation Revenue loss due to price Prevented planting (due to insurable cause of

loss)

Losses

Page 12: GIS In Relation to Crop Insurance

GIS systems can create geospatial snapshots of cropland

Land cover data layers provided by enhanced GIS systems help many people such as:◦ Crop insurance companies◦ Crop growers associations◦ Seed/fertilizer companies

GIS

Page 13: GIS In Relation to Crop Insurance

The USDA and the RMA administer the Federal crop insurance program

GIS helps this program by providing maps and products which are then incorporated with crop insurance policy data

GIS

Page 14: GIS In Relation to Crop Insurance

The original GIS tool was created by ArcGIS 8

There are 4 main data layers that were used for analysis:◦ Soil Rating for Plant Growth◦ Slope◦ Elevation ◦ Flooding Zones

The soil rating for plant growth is created by using nearly 25 parameters of soil quality in the Soil Survey Geographic Database. Some of these parameters include soil climate, depth of root zone, and fertility

Prototype GIS

Page 15: GIS In Relation to Crop Insurance

GIS can help RMA with maps of participation rates, causes of loss, loss ratios, etc.

Map areas that are more likely to experience loss based on physical factors

Analyze crop conditions based on satellite sensing and predict crop failure/loss in advance

GIS


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