![AAFC/ACI](https://developers.google.com/earth-engine/datasets/images/AAFC/AAFC_ACI_sample.png?authuser=19)
- Dataset Availability
- 2009-01-01T00:00:00Z–2023-01-01T00:00:00Z
- Dataset Provider
- Agriculture and Agri-Food Canada
- Earth Engine Snippet
-
ee.ImageCollection("AAFC/ACI")
- Tags
Description
Starting in 2009, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology was applied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based satellite images. Beginning with the 2011 growing season, this activity has been extended to other provinces in support of a national crop inventory. To date this approach can consistently deliver a crop inventory that meets the overall target accuracy of at least 85% at a final spatial resolution of 30m (56m in 2009 and 2010).
Bands
Resolution
30 meters
Bands
Name | Min | Max | Description |
---|---|---|---|
landcover |
1 | 255 | Main crop-specific land cover classification. |
landcover Class Table
Value | Color | Description |
---|---|---|
10 | #000000 | Cloud |
20 | #3333ff | Water |
30 | #996666 | Exposed Land and Barren |
34 | #cc6699 | Urban and Developed |
35 | #e1e1e1 | Greenhouses |
50 | #ffff00 | Shrubland |
80 | #993399 | Wetland |
85 | #501b50 | Peatland |
110 | #cccc00 | Grassland |
120 | #cc6600 | Agriculture (undifferentiated) |
122 | #ffcc33 | Pasture and Forages |
130 | #7899f6 | Too Wet to be Seeded |
131 | #ff9900 | Fallow |
132 | #660000 | Cereals |
133 | #dae31d | Barley |
134 | #d6cc00 | Other Grains |
135 | #d2db25 | Millet |
136 | #d1d52b | Oats |
137 | #cace32 | Rye |
138 | #c3c63a | Spelt |
139 | #b9bc44 | Triticale |
140 | #a7b34d | Wheat |
141 | #b9c64e | Switchgrass |
142 | #999900 | Sorghum |
143 | #e9e2b1 | Quinoa |
145 | #92a55b | Winter Wheat |
146 | #809769 | Spring Wheat |
147 | #ffff99 | Corn |
148 | #98887c | Tobacco |
149 | #799b93 | Ginseng |
150 | #5ea263 | Oilseeds |
151 | #52ae77 | Borage |
152 | #41bf7a | Camelina |
153 | #d6ff70 | Canola and Rapeseed |
154 | #8c8cff | Flaxseed |
155 | #d6cc00 | Mustard |
156 | #ff7f00 | Safflower |
157 | #315491 | Sunflower |
158 | #cc9933 | Soybeans |
160 | #896e43 | Pulses |
161 | #996633 | Other Pulses |
162 | #8f6c3d | Peas |
163 | #b6a472 | Chickpeas |
167 | #82654a | Beans |
168 | #a39069 | Fababeans |
174 | #b85900 | Lentils |
175 | #b74b15 | Vegetables |
176 | #ff8a8a | Tomatoes |
177 | #ffcccc | Potatoes |
178 | #6f55ca | Sugarbeets |
179 | #ffccff | Other Vegetables |
180 | #dc5424 | Fruits |
181 | #d05a30 | Berries |
182 | #d20000 | Blueberry |
183 | #cc0000 | Cranberry |
185 | #dc3200 | Other Berry |
188 | #ff6666 | Orchards |
189 | #c5453b | Other Fruits |
190 | #7442bd | Vineyards |
191 | #ffcccc | Hops |
192 | #b5fb05 | Sod |
193 | #ccff05 | Herbs |
194 | #07f98c | Nursery |
195 | #00ffcc | Buckwheat |
196 | #cc33cc | Canaryseed |
197 | #8e7672 | Hemp |
198 | #b1954f | Vetch |
199 | #749a66 | Other Crops |
200 | #009900 | Forest (undifferentiated) |
210 | #006600 | Coniferous |
220 | #00cc00 | Broadleaf |
230 | #cc9900 | Mixedwood |
Image Properties
Image Properties
Name | Type | Description |
---|---|---|
landcover_class_names | STRING_LIST | Array of cropland landcover classification names. |
landcover_class_palette | STRING_LIST | Array of hex code color strings used for the classification palette. |
landcover_class_values | INT_LIST | Value of the land cover classification. |
Terms of Use
Terms of Use
Citations
Agriculture and Agri-Food Canada Annual Crop Inventory. {YEAR}
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.ImageCollection('AAFC/ACI'); var crop2016 = dataset .filter(ee.Filter.date('2016-01-01', '2016-12-31')) .first(); Map.setCenter(-103.8881, 53.0372, 10); Map.addLayer(crop2016, {}, '2016 Canada AAFC Annual Crop Inventory');