- By CME Group
- Topics: Agriculture
- Who is Indigo Ag
- What type of data does Indigo Ag provide?
- What is NDVI?
- What is CHI?
- How do I order the data?
- What is the file format of the Indigo Ag data?
- What is the average daily file size?
- How many files are available per day?
- What is the delivery frequency of the data?
- What time is delivery of the data each day?
- Are files compressed?
- Can you provide me a sample file for the CHI dataset?
- Can you provide me a sample file for the NDVI dataset?
- How far back, historically, is data available?
- What is the geo_level field?
- What do the geo_level values mean?
- What is the geo_id field?
- How can I identify a unique geography?
- Why are there occasionally a different number of records for one date versus another?
- Where can I obtain a reference guide for the different Geo Levels?
- Who do I contact if I have any issues with the data or CME DateMine?
- Data Structure
- API Documentation
- More about Indigo Ag
Indigo Ag is a Boston-based agricultural technology company, founded in 2014. Indigo develops microbial and digital technologies that improve grower profitability, environmental sustainability, and consumer health. These technologies underpin its pioneering business model, which spans agriculture’s full value chain.
Indigo Ag provides satellite-based metrics related to agriculture and plant health.
NDVI (Normalized Difference Vegetation Index) is a satellite-derived measurement for quantifying the presence or absence of live green vegetation. NDVI is perhaps the most widely known satellite-derived vegetation index, and this measurement is subsequently used by many in the agriculture space to estimate general health of a crop. However, not all NDVI measurements are created equal. At Indigo Ag, a unique, science-driven approach is used when calculating NDVI that elevates metrics from a simple vegetation index to a truly refined, agriculture-focused, crop-specific science-grade estimation insight. You can learn more about the Indigo Ag approach to NDVI in the Indigo Ag Crop Indices whitepaper.
CHI, otherwise known as the Indigo Ag Crop Health Index, is a proprietary, satellite-derived agricultural signal which estimates the overall health of a particular crop. The design process for CHI was informed by well-established metrics like NDVI and EVI (Enhanced Vegetation Index) that capitalize on the physical properties of photosynthesizing plants. However, Indigo Ag’s focus on agriculture versus generalized vegetation allows a tailored approach to the way the spectral information is combined in the index. CHI uses a ratio of spectral bands that seek to best capture changes in crop health which may be linked to end-of-season outcomes, resulting in CHI showing a promising dynamic range in response to yield. To learn more about all aspects of CHI, please refer to the Indigo Ag Crop Indices whitepaper.
You can order the data through CME DataMine, CME Group’s self-service cloud solution for historical and partner datasets.
The files are delivered in .CSV.
The average daily file ranges from 5KB-10KB in size.
Each country/crop/metric combination corresponds to an individual file.
For example, if you are subscribed to "Brazil, CHI, corn", you will receive a single file. If you are subscribed to "Brazil, CHI" for both corn and soy, then you will receive two files: one for corn and another for soy. If a user subscribes to all Indigo Ag datasets they will receive 12 files a day.
The files are delivered once per day.
All files are delivered to CME Group by 9:00 a.m. Eastern Time (ET).
Yes, the files are compressed.
Yes, click here to download a sample file.
Yes, click here to download a sample file.
The files go back six years (since July 2011) for the Brazil and Argentina regions and 15 years (since January 2003) for the United States.
The geo_level field is used to indicate the level of geographic granularity being reported for the given metric/date/crop. By geographic granularity, it is referring to measurements like National, State or County.
Since these geographic divisions are named differently across countries, this has been abstracted into a single value.
Level_1 is National, level_2 is State/Province.
The geo_id field is a numeric identifier for a given geography.
For example, in the United States, the state of Iowa has a geo_id value of 19.
These numeric identifiers make it easier to analyze the data and combine it with other datasets. The values are country-specific.
For example, while 19 is the geo_id value for Iowa in the United States, 19 is also the geo_id value for Rio de Janeiro in Brazil.
A unique geography can be identified by combining the values from three fields: country_iso, geo_level and geo_id. Combining these three fields will give a unique geography across all Indigo Ag datasets.
For example, USA, level_2, 19 will give the unique geography for the state of Iowa in the U.S.
Since the data relies on satellites, there are occasionally days during which cloud cover or other factors prohibit data collection for a specific geography. There are many systems in place to mitigate this scenario, but there will still be occasions for which the data collection for a specific geography on a given date might not meet our thresholds for processing. For this reason, there may occasionally be specific geographies omitted for certain dates.
For a reference guide for the different Geo Levels please click here.
For inquiries related to CME DataMine contact the Global Command Center (GCC), Sundays 2 p.m. – Fridays 4:30 p.m.
U.S.: +1 800 438 8616
Europe: +44 20 7623 4747
Asia: +65 6532 5010
| Field Name | CSV Column | Example Value | Supported Values | Description |
|---|---|---|---|---|
| Geo Level | A | level_1 | level_1, level_2 | Location- either National (level_1) or State level (level_2) |
| Country ISO | B | BRA | ARG, BRA, USA | Country of crop being measured |
| Geo ID | C | 19 | [00 through 54] | Geographic Identifier |
| Geo Display Name | D | BRAZIL | [Any name of a state/province within the U.S., Argentina, or Brazil. Or the name of the country itself] | Common name for Geography |
| Metric Date | E | 2018-03-09 | [Any valid date] | Crop that is being measured |
| Crop | F | corn | corn, soy | Crop that is being measured |
| Metric | G | .623009 | [Any valid metric value, traditionally from -0.020000 through 0.920000] | Metric Value (NDVI or CHI) |
You can query a list of entitled files using this api call, with optional criteria to limit the number of results returned.
| Name | Description | Required | Type |
|---|---|---|---|
| dataset | Dataset the user is querying. In this case, it should always equal “telluslabs” | Yes | String |
| exchangecode | The country’s files that the user is wanting to list. | No | String |
| yyyymmdd | Report date. Accepted format is yyyymmdd. Example: 20180312 | No | String |
| limit | Amount of results per request. A paging information will return with offset information. | No | int |
| offset | Pagination mechanism Use the offset returned by previous query for previous or next page. | No | int |
| firstfid | Alternative pagination mechanism Use the firstfid returned in the paging section to query previous page | No | String |
| lastfid | Use the lastfid returned in the paging section to query next page | No | String |
curl --user {{UNO_API_KEY}}:{{UNO_API_PASSWORD}} 'https://{{URL}}/cme/api/v1/list?{{criteria1}}={{val1}}&{{criteria2}}={{val2}}&{{criteriaN}}={{valN}}'
curl --user API_JOHNSMITH:12345
'https://datamine.cmegroup.com/cme/api/v1/list?dataset=telluslabs&exchangecode=USA
| Name | Description | Type |
|---|---|---|
| dataset | Dataset of the file | String |
| exchangecode | Country of the file | String |
| url | Fully qualified download URL | String |
| expiration | Expiration date of file access | String |
| productcode | Will always be a * | String |
| yyyymmdd | TellusLabs report date | String |
| checksum | MD5 Checksum for data | String |
| size | File size in KB | int |
| fid | Unique identifier for file | String |
| orderid | Order number | String |
{
"files": [
{
"dataset": "TELLUSLABS",
"yyyymmdd": "20180318",
"url": "https://datamineuat.cmegroup.com/cme/api/v1/download?fid=20180318-TELLUSLABS_USA_corn_CHI_0",
"fid": "20180318-TELLUSLABS_USA_corn_CHI_0",
"orderid": "3950",
"exchangecode": "USA",
"productcode": "*",
"checksum": "9a8764d5a1967b6642bbad395cddb2b4",
"size": 2477,
"expiration": "2018-04-18",
"s3url": "cme-antivirus/uat/clean/ophirh/20180318/TELLUSLABS_USA_corn_CHI_20180318.csv"
},
{
"dataset": "TELLUSLABS",
"yyyymmdd": "20180318",
"url": "https://datamineuat.cmegroup.com/cme/api/v1/download?fid=20180318-TELLUSLABS_USA_corn_CHI_0",
"fid": "20180318-TELLUSLABS_USA_corn_CHI_0",
"orderid": "3950",
"exchangecode": "USA",
"productcode": "*",
"checksum": "9a8764d5a1967b6642bbad395cddb2b4",
"size": 2477,
"expiration": "2018-04-18",
"s3url": "cme-antivirus/uat/clean/ophirh/20180318/TELLUSLABS_USA_corn_CHI_20180318.csv"
}
],
"paging": {
"previous": "",
"next": "https://datamineuat.cmegroup.com/cme/api/v1/list?dataset=telluslabs&exchangecode=usa&limit=2&lastFid=20180318-TELLUSLABS_USA_corn_CHI_0&page=1"
}
}
You can download a file that you have access to using this api call.
| Name | Description | Required | Type |
|---|---|---|---|
| fid | File Id, available from the list api, case insensitive. The fid format is: yyyymmdd-TELLUSLABS_[country]_[crop]_[analytic]_0 Example: 20180308-TELLUSLABS_USA_corn_CHI_0 | Yes | String |
curl -J -O --user {{UNO_API_KEY}}:{{UNO_API_PASSWORD}} 'https://{{URL}}/cme/api/v1/download?fid={{val}}'
curl -J -O --user API_JOHNSMITH:12345
'https://datamine.cmegroup.com/cme/api/v1/download?fid=20180308-TELLUSLABS_USA_corn_CHI_0'
You can use “-o” option to name your own file:
curl --user API_JOHNSMITH:12345
'https://datamine.cmegroup.com/cme/api/v1/download?fid=20180308-TELLUSLABS_USA_corn_CHI_0' -o my_eod_file.gz
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