ArcGIS REST Services Directory Login
JSON

Layer: Arroz Fisica Area (ID: 17)

Name: Arroz Fisica Area

Display Field: Unidade

Type: Feature Layer

Geometry Type: esriGeometryPolygon

Description: Title: Arroz Fisica Area / Rice Physical Area Summary: Description: http://mapspam.info/spam-2000/ Date Created: Date Updated: Spatial Reference: GCS_WGS_1984 WKID: 4326 Authority: EPSG Angular Unit: Degree (0.0174532925199433) Prime Meridian: Greenwich (0.0) Datum: D_WGS_1984 Spheroid: WGS_1984Semimajor Axis: 6378137.0 Semiminor Axis: 6356752.314245179 Inverse Flattening: 298.257223563 Data Owner: Credits or Copyright: IFPRI International Food Policy Research Institute Access Constraints: Public ISO Topic: agricultura / agriculture Tags: agricultura, agricola fisica area, trigo, arroz, milho, cevada, painço, sorgo, batata, batata doce, mandioca, plantagoes bananas, soja, feijao, leguminosas, cana de agucar, beterraba sacarina, café, algodao, culturas de fibra, amendoim, culturas oleaginosas, environment, crop physical area, wheat, rice, maize, barley, millet, sorghum, potato, sweetpotato, yam, cassava, banana plantain, soybean, beans, pulses, sugarcane, sugarbeet, coffee, cotton, fibre crops, groundnut, oil crops, mozambique, farming, agriculture Contact Name: Contact Company: Contact Phone Number: Contact Email: Scale: Capture Method: Using a variety of inputs, SPAM uses a cross-entropy approach to make plausible estimates of crop distribution within disaggregated units.1.We start with the administrative (geopolitical) units for which we have been able to obtain production statistics. These may typically be national or sub-national administrative regions such as countries, states, districts, or counties. The smaller the administrative units, the better the results.2.We receive an already classified land-cover image, where crop land has been identified. 3.We integrate crop-specific suitability information based on local landscape, climate and soil conditions, which provides information on how MUCH cropland exists at the pixel level.4.Combining all these input data and some more parameters the model applies a cross entropy approach to obtain the final estimation of crop distribution.Language: Portuguese, English

Service Item Id: 04d95f7470934b40880e1dddcba615d7

Copyright Text: Credits or Copyright: IFPRI International Food Policy Research Institute

Default Visibility: false

MaxRecordCount: 1000

Supported Query Formats: JSON, geoJSON

Min Scale: 0

Max Scale: 0

Effective Min Scale: 1000000

Supports Advanced Queries: true

Supports Statistics: true

Has Labels: false

Can Modify Layer: true

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

Extent:
Drawing Info: Advanced Query Capabilities:
HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeAsHTMLText

Type ID Field: null

Fields:
Supported Operations:   Query   Query Attachments   Generate Renderer   Return Updates

  Iteminfo   Thumbnail   Metadata