Intuitive query language for online operating with huge and permanently expanding datasets of satellite images to derive all power of satellite images and deploy it to your applications.

Setup parameters of the query:

What data you need (satellite imagery, weather, IoT)

How to process it (RGB, NDVI, false colors; any other indexes, band combination, color scheme, etc.)

How you would like to get a result (map, scene, metadata, datafeed, etc.)


Receive an immediate result that you can:

Integrate to the application

Process it or do research


Get your API key to start


Queries for satellite images with VANE SQL v0.2

Tiles or polygons

Request an area of your interest by two ways that are tiles (XYZ) and polygons consisting of a number of geographical coordinates (lat/lon)

Bands

Choose bands to construct your scene in grayscale, RGB, NDVI, false colors; any combination of available bands is possible

Operation with an image

Choose Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), RGB or change detection operations with images

Customized color scheme

Configure a color palette of any image to get proper colors, e.g. for vegetation indexes

Color correction

Normalize brightness of an individual image for better color compatibility with other images to generate naturally looking maps

Time

Choose images on the specific date, for the particular period, pick up the best images for the last month or week, and many other options.

Queries

Query by a tile server (XYZ):

//sat.owm.io/sql/
{z}/{x}/{y}?
select={select}&
from={from}&
where={where}&
order={order}&
op={op}&
APPID={APIKEY}
Query by a polygon:

//sat.owm.io/sql?
select={select}&
from={from}&
where={where}&
order={order}&
op={op}&
APPID={APIKEY}&
polygon={polygon}

Parameters

{z}/{x}/{y} query by a tile server. Z is the zoom level, and X and Y identify the tile

{polygon} encoded GeoJSON string, contains pairs of coordinates describing all points of selected polygon.

{select} bands that you choose for processing. E.g., for RGB you set up b4,b3, and b2 bands (Landsat 8)

{from} name of the dataset. Currently, Landsat 8 satellite images are available.

{where} combination of filters to choose images more precisely.

{order} set up an order of images

{op} operation that you apply to images

{color} color processing

APIKEY API key of the user

Parameters in details

Parameter Details
{select}

Bands (Landsat8) that you use for processing

E.g. for RGB select=b4,b3,b2

for NDVI select=b5,b4

In the forthcoming version of the language, you can configure formulas like (b4-b3)/(b4+b3), NDVI(b4,b3) and many others.

{from}

Name of the dataset. Currently, Landsat 8 satellite images are available.

from=landsat8

In the next version of the language, we add Modis satellite images and Weather data.

{where}

Set up a filter by specific date or period.

day:2016-08-01

between(2016-06-23:2016-07-09)

day<2016-08-25

day>2016-08-01

now-100


Set up cloudiness filter to choose images with clouds less than some level, in %.

clouds<80

{order}

The result can include lots of images. To optimize it you can set up an order of choosing and combining of images.

You can choose amongst the following parameters like ‘first,' ‘last’ or ‘best.'

order=first

{color}

You can apply a variety of color processing to your images.

Basic correction of colors and brightness:

color=auto

color=none


Set up levels of brightness for RGB:

color=brightness(5000:16000)


Set up a color scheme for NDVI:

color=0:ffffe5ff;0.1:f7fcb9ff;0.2:d9f0a3ff;0.3:addd8eff;0.4:78c679ff;0.5:41ab5dff;0.6:238443ff;0.7:006837ff;1:004529ff

{op}

Operation of combining of chosen layers/bands

'rgb', 'ndvi', 'evi', and 'change' for change detection are available in the current version.

op=NDVI

{polygon}

Get your GeoJson array with coordinates describing your polygon, then encode it into string using any encoder you prefer, then pass the resulting string as a parameter polygon=%7B%22type%22%3A%22Feature%22%2C%22geometry%22%3A%7B%22type%22%3A%22Polygon%22%2C%22
coordinates%22%3A%5B%5B%5B-121.32%2C37.65%5D%2C%5B-121.32%2C37.72%5D%2C%5B-121.11%2C37.72%5D%2C%5B-121.11%2C37.65%5D%2C%5B-121.32%2C37.65%5D%5D%5D%7D%7D+

You can draw a polygon using the tool for visual query constructing owm.io/cases/create-polygon

Examples of queries

Basic map generated from the best images ever
Parameters
select=b4,b3,b2
order=best

Tile server template
//{s}.sat.owm.io/sql/{z}/{x}/{y}?select=b4,b3,b2&order=best

Example
//sat.owm.io/sql/9/143/218?select=b4,b3,b2&order=best&appid=..

viewer

RGB color from Sat, 09 Jul 2016
Parameters
select=b4,b3,b2
where=day:2016-07-09

Tile server template
//{s}.sat.owm.io/sql/{z}/{x}/{y}?select=b4,b3,b2&where=day:2016-07-09

Example
//sat.owm.io/sql/12/3560/2179?select=b4,b3,b2&where=day:2016-07-09&appid=..

viewer

False color from Sat, 09 Jul 2016
Parameters
select=b7,b5,b4
op=rgb
where=day:2016-07-09

Tile server template
//{s}.sat.owm.io/sql/{z}/{x}/{y}?select=b7,b5,b4&where=day:2016-07-09

Example
//sat.owm.io/sql/12/3560/2179?select=b7,b5,b4&where=day:2016-07-09&appid=..

viewer

Custom false color
Parameters
select=b10,b7,b5
op=rgb
where=day:2016-10-01
color=log

Tile server template
//{s}.sat.owm.io/sql/{z}/{x}/{y}?select=b10,b7,b3&where=day:2016-10-01&from=landsat8&color=log

Example
//b.sat.owm.io/sql/9/82/198?select=b10,b7,b3&where=day:2016-10-01&from=landsat8&color=log&appid=..

viewer

NDVI
Parameters
select=b5,b4
op=ndvi
where=day<2016-07-19
order=last

Tile server template
//{s}.sat.owm.io/sql/{z}/{x}/{y}?select=b5,b4&op=ndvi&where=day<2016-07-19&order=last

Example
//sat.owm.io/sql/12/883/1630?select=b5,b4&where=day<2016-07-19&from=landsat8&order=last&color=auto&op=ndvi&appid=..

viewer

Map generated from images available within a particular period
Between
2016-06-01 and 2016-06-31
Parameters
where=between(2016-06-01:2016-06-31)
order=best

Tile server template
//{s}.sat.owm.io/sql/{z}/{x}/{y}?select=b4,b3,b2&where=between(2016-06-01:2016-06-31)&order=best

Example
//sat.owm.io/sql/10/496/402?where=between(2016-06-01:2016-06-31)&appid=..

viewer

Map generated from the best images for the last 200 days
Parameters
where=now-200

Tile server template
//{s}.sat.owm.io/sql/{z}/{x}/{y}?select=b4,b3,b2&where=now-200

Example
//sat.owm.io/sql/10/496/402?select=b4,b3,b2&where=now-200&appid=..

viewer

RGB color by polygon from 14 Aug 2016 with set up levels of brightness
Parameters
where=day:2016-08-14
color=brightness(5000:16000)
polygon={GeoJSON Polygon}

Tile server template
//{s}.sat.owm.io/sql?where=day:2016-08-14&color=brightness(5000:16000)&polygon=...

Example
//sat.owm.io/sql?where=day:2016-08-14&color=brightness(5000:16000)&polygon=...


NDVI by polygon from 14 Aug 2016
Parameters
select=b5,b4
where=day:2016-08-14
op=ndvi
polygon={GeoJSON Polygon}

Tile server template
//{s}.sat.owm.io/sql?select=b5,b4&where=day:2016-08-14&op=ndvi&polygon=...

Example
//sat.owm.io/sql?select=b5,b4&where=day:2016-08-14&op=ndvi&polygon=...



Queries for metadata with VANE SQL v0.2

Query for image list

Query
Query for image list by coordinates Parameters
lat
lon

Example
sat.owm.io/api/3.0/search?lat=55&lon=37

Query for image list by a polygon Parameters
poly

Example
sat.owm.io/api/3.0/search?poly={"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[-121.32,37.65],[-121.32,37.72],[-121.11,37.72],[-121.11,37.65],[-121.32,37.65]]]}}

Query by a tile server Parameters
Z is the zoom level
X, Y — identify the tile

Example
sat.owm.io/api/3.0/search/12/3560/2179

Meta information

Query
Query by tile server Parameters
where
from
order

Example
sat.owm.io/meta/8/124/100?where=day<2016-10-01&from=landsat8&order=best

Scene information

Query
Query by a scene ID Parameters
ID
Example
api.sat.owm.io/api/2.5/scene?id=LC80120282015304LGN00

Data sources

Landsat 8

In the current version of VANE Language, we use images from Landsat8 satellite that covers the entire Earth every 16 days making hundreds of images with a unique name for each one like LC81410552016219LGN00 and pixel size of 30 meters, each image consists of 11 bands, the size of the uncompressed image is 2 GB.

  • Every day we receive around 400 new Landsat 8 images.
  • By default, we get B2, B3, B4, B5, B7, but it is possible to download any other bands.
  • Our database contents around 20,000 Landsat 8 images since 2013 available for immediate processing.

Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images consist of nine spectral bands with a spatial resolution of 30 meters for Bands 1 to 7 and 9. New band 1 (ultra-blue) is useful for coastal and aerosol studies. New band 9 is useful for cirrus cloud detection. The resolution for Band 8 (panchromatic) is 15 meters. Thermal bands 10 and 11 are useful in providing more accurate surface temperatures and are collected at 100 meters. Approximate scene size is 170 km north-south by 183 km east-west (106 mi by 114 mi).

Landsat 8
Operational
Land Imager
(OLI)
and
Thermal
Infrared
Sensor
(TIRS)

Launched
February 11, 2013
Bands Wavelength
(micrometers)
Resolution
(meters)
Band 1 - Coastal aerosol 0.43 - 0.45 30
Band 2 - Blue 0.45 - 0.51 30
Band 3 - Green 0.53 - 0.59 30
Band 4 - Red 0.64 - 0.67 30
Band 5 - Near Infrared (NIR) 0.85 - 0.88 30
Band 6 - SWIR 1 1.57 - 1.65 30
Band 7 - SWIR 2 2.11 - 2.29 30
Band 8 - Panchromatic 0.50 - 0.68 15
Band 9 - Cirrus 1.36 - 1.38 30
Band 10 - Thermal Infrared (TIRS) 1 10.60 - 11.19 100 * (30)
Band 11 - Thermal Infrared (TIRS) 2 11.50 - 12.51 100 * (30)

* TIRS bands are acquired at 100 meter resolution, but are resampled to 30 meter in delivered data product.

More about Landsat 8 landsat.usgs.gov/landsat8.php

More about band names landsat.usgs.gov/band_designations_landsat_satellites.php