W 2009 r. zespół ds. obserwacji Ziemi z sekcji naukowo-technicznej (STB) w Agriculture and Agri-Food Canada (AAFC) rozpoczął proces tworzenia rocznych cyfrowych map typów upraw. W latach 2009–2010 w prowincjach Prairie zastosowano metodologię opartą na drzewie decyzyjnym (DT) z wykorzystaniem optycznych (Landsat-5, AWiFS, DMC) i radarowych (Radarsat-2) zdjęć satelitarnych. Od sezonu wegetacyjnego 2011 r. działania te zostały rozszerzone na inne prowincje w celu stworzenia krajowego spisu upraw.
Dzięki temu podejściu można uzyskać spójny spis upraw, który spełnia ogólny docelowy poziom dokładności wynoszący co najmniej 85% przy końcowej rozdzielczości przestrzennej 30 m (56 m w 2009 i 2010 r.).
Pasma
Rozmiar piksela 30 metrów
Pasma
Nazwa
Minimum
Maks.
Rozmiar piksela
Opis
landcover
1
255
metry
Główna klasyfikacja pokrycia terenu według upraw.
Tabela klas pokrycia terenu
Wartość
Kolor
Opis
10
#000000
Chmura
20
#3333ff
Woda
30
#996666
Exposed Land and Barren
34
#cc6699
Urban and Developed
35
#e1e1e1
Greenhouses
50
#ffff00
Shrubland
80
#993399
Bagna
85
#501b50
Peatland
110
#cccc00
Łąka
120
#cc6600
Rolnictwo (niezróżnicowane)
122
#ffcc33
Pastwiska i pasze
130
#7899f6
Zbyt mokra, aby można było ją obsiać
131
#ff9900
Fallow
132
#660000
Zboża
133
#dae31d
Jęczmień
134
#d6cc00
Inne ziarna
135
#d2db25
Proso
136
#d1d52b
Owsiane
137
#cace32
Rye
138
#c3c63a
Orkisz
139
#b9bc44
Triticale
140
#a7b34d
Pszenica
141
#b9c64e
Switchgrass
142
#999900
Sorghum
143
#e9e2b1
komosa ryżowa,
145
#92a55b
Pszenica ozima
146
#809769
Pszenica jara
147
#ffff99
Kukurydza
148
#98887c
Wyroby tytoniowe
149
#799b93
Żeń-szeń
150
#5ea263
Nasiona oleiste
151
#52ae77
Borage
152
#41bf7a
Camelina
153
#d6ff70
Rzepak
154
#8c8cff
siemię lniane,
155
#d6cc00
Musztardowy
156
#ff7f00
Safflower
157
#315491
Słonecznik
158
#cc9933
Soja
160
#896e43
Rośliny strączkowe
161
#996633
Inne rośliny strączkowe
162
#8f6c3d
Groszek
163
#b6a472
Ciecierzyca
167
#82654a
Fasola
168
#a39069
Fababeans
174
#b85900
Soczewica
175
#b74b15
Warzywa
176
#ff8a8a
pomidory,
177
#ffcccc
Ziemniaki
178
#6f55ca
Buraki cukrowe
179
#ffccff
Inne warzywa
180
#dc5424
Owoce
181
#d05a30
Jagody
182
#d20000
Jagoda
183
#cc0000
Cranberry
185
#dc3200
Inne jagody
188
#ff6666
Sady
189
#c5453b
Inne owoce
190
#7442bd
Winnice
191
#ffcccc
Hops
192
#b5fb05
Darń
193
#ccff05
Zioła
194
#07f98c
Żłobek
195
#00ffcc
Gryka
196
#cc33cc
Kanar
197
#8e7672
Konopie
198
#b1954f
Vetch
199
#749a66
Inne uprawy
200
#009900
Las (niezróżnicowany)
210
#006600
Iglaste
220
#00cc00
Broadleaf
230
#cc9900
Mixedwood
Właściwości obrazu
Właściwości obrazu
Nazwa
Typ
Opis
landcover_class_names
STRING_LIST
Tablica nazw klasyfikacji pokrycia terenu uprawnego.
landcover_class_palette
STRING_LIST
Tablica ciągów znaków z szesnastkowymi kodami kolorów używanych w palecie klasyfikacji.
W 2009 r. zespół ds. obserwacji Ziemi z sekcji naukowo-technicznej (STB) w Ministerstwie Rolnictwa i Żywności Kanady (AAFC) rozpoczął proces tworzenia rocznych cyfrowych map typów upraw. W latach 2009–2010 w przypadku prowincji Prairie zastosowano metodologię opartą na drzewie decyzyjnym (DT) z wykorzystaniem danych optycznych (Landsat-5, …
[null,null,[],[[["\u003cp\u003eThe Annual Crop Inventory (ACI) dataset provides annual crop type maps for Canada, starting from 2009 and updated yearly.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset utilizes a Decision Tree methodology and satellite imagery (optical and radar) to classify cropland with an accuracy target of at least 85%.\u003c/p\u003e\n"],["\u003cp\u003eIt offers a 30-meter resolution and includes a comprehensive land cover classification with values representing various crop types, land uses, and infrastructure.\u003c/p\u003e\n"],["\u003cp\u003eThe ACI dataset is provided by Agriculture and Agri-Food Canada and is openly accessible under the OGL-Canada-2.0 license.\u003c/p\u003e\n"],["\u003cp\u003eUsers can access and analyze the dataset using Google Earth Engine for research, education, and non-profit purposes.\u003c/p\u003e\n"]]],["Agriculture and Agri-Food Canada (AAFC) initiated annual crop type mapping in 2009, utilizing optical and radar satellite imagery. The dataset, available from 2009 to 2023, employs a Decision Tree methodology to classify land cover, including specific crops. With a 30-meter pixel size and annual cadence, this inventory achieves at least 85% overall accuracy. The classification includes 255 different crops or land types, with a landcover band representing them.\n"],null,["# Canada AAFC Annual Crop Inventory\n\nDataset Availability\n: 2009-01-01T00:00:00Z--2023-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [Agriculture and Agri-Food Canada](https://open.canada.ca/data/en/dataset/ba2645d5-4458-414d-b196-6303ac06c1c9)\n\nCadence\n: 1 Year\n\nTags\n:\n [agriculture](/earth-engine/datasets/tags/agriculture) [canada](/earth-engine/datasets/tags/canada) [crop](/earth-engine/datasets/tags/crop) [landcover](/earth-engine/datasets/tags/landcover) \naafc \n\n#### Description\n\nStarting in 2009, the Earth Observation Team of the Science and Technology\nBranch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process\nof generating annual crop type digital maps. Focusing on the Prairie\nProvinces in 2009 and 2010, a Decision Tree (DT) based methodology was\napplied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based\nsatellite images. Beginning with the 2011 growing season, this activity has\nbeen extended to other provinces in support of a national crop inventory.\nTo date this approach can consistently deliver a crop inventory that meets\nthe overall target accuracy of at least 85% at a final spatial resolution of\n30m (56m in 2009 and 2010).\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Min | Max | Pixel Size | Description |\n|-------------|-----|-----|------------|-----------------------------------------------|\n| `landcover` | 1 | 255 | meters | Main crop-specific land cover classification. |\n\n**landcover Class Table**\n\n| Value | Color | Description |\n|-------|---------|--------------------------------|\n| 10 | #000000 | Cloud |\n| 20 | #3333ff | Water |\n| 30 | #996666 | Exposed Land and Barren |\n| 34 | #cc6699 | Urban and Developed |\n| 35 | #e1e1e1 | Greenhouses |\n| 50 | #ffff00 | Shrubland |\n| 80 | #993399 | Wetland |\n| 85 | #501b50 | Peatland |\n| 110 | #cccc00 | Grassland |\n| 120 | #cc6600 | Agriculture (undifferentiated) |\n| 122 | #ffcc33 | Pasture and Forages |\n| 130 | #7899f6 | Too Wet to be Seeded |\n| 131 | #ff9900 | Fallow |\n| 132 | #660000 | Cereals |\n| 133 | #dae31d | Barley |\n| 134 | #d6cc00 | Other Grains |\n| 135 | #d2db25 | Millet |\n| 136 | #d1d52b | Oats |\n| 137 | #cace32 | Rye |\n| 138 | #c3c63a | Spelt |\n| 139 | #b9bc44 | Triticale |\n| 140 | #a7b34d | Wheat |\n| 141 | #b9c64e | Switchgrass |\n| 142 | #999900 | Sorghum |\n| 143 | #e9e2b1 | Quinoa |\n| 145 | #92a55b | Winter Wheat |\n| 146 | #809769 | Spring Wheat |\n| 147 | #ffff99 | Corn |\n| 148 | #98887c | Tobacco |\n| 149 | #799b93 | Ginseng |\n| 150 | #5ea263 | Oilseeds |\n| 151 | #52ae77 | Borage |\n| 152 | #41bf7a | Camelina |\n| 153 | #d6ff70 | Canola and Rapeseed |\n| 154 | #8c8cff | Flaxseed |\n| 155 | #d6cc00 | Mustard |\n| 156 | #ff7f00 | Safflower |\n| 157 | #315491 | Sunflower |\n| 158 | #cc9933 | Soybeans |\n| 160 | #896e43 | Pulses |\n| 161 | #996633 | Other Pulses |\n| 162 | #8f6c3d | Peas |\n| 163 | #b6a472 | Chickpeas |\n| 167 | #82654a | Beans |\n| 168 | #a39069 | Fababeans |\n| 174 | #b85900 | Lentils |\n| 175 | #b74b15 | Vegetables |\n| 176 | #ff8a8a | Tomatoes |\n| 177 | #ffcccc | Potatoes |\n| 178 | #6f55ca | Sugarbeets |\n| 179 | #ffccff | Other Vegetables |\n| 180 | #dc5424 | Fruits |\n| 181 | #d05a30 | Berries |\n| 182 | #d20000 | Blueberry |\n| 183 | #cc0000 | Cranberry |\n| 185 | #dc3200 | Other Berry |\n| 188 | #ff6666 | Orchards |\n| 189 | #c5453b | Other Fruits |\n| 190 | #7442bd | Vineyards |\n| 191 | #ffcccc | Hops |\n| 192 | #b5fb05 | Sod |\n| 193 | #ccff05 | Herbs |\n| 194 | #07f98c | Nursery |\n| 195 | #00ffcc | Buckwheat |\n| 196 | #cc33cc | Canaryseed |\n| 197 | #8e7672 | Hemp |\n| 198 | #b1954f | Vetch |\n| 199 | #749a66 | Other Crops |\n| 200 | #009900 | Forest (undifferentiated) |\n| 210 | #006600 | Coniferous |\n| 220 | #00cc00 | Broadleaf |\n| 230 | #cc9900 | Mixedwood |\n\n### Image Properties\n\n**Image Properties**\n\n| Name | Type | Description |\n|-------------------------|-------------|----------------------------------------------------------------------|\n| landcover_class_names | STRING_LIST | Array of cropland landcover classification names. |\n| landcover_class_palette | STRING_LIST | Array of hex code color strings used for the classification palette. |\n| landcover_class_values | INT_LIST | Value of the land cover classification. |\n\n### Terms of Use\n\n**Terms of Use**\n\n[OGL-Canada-2.0](https://spdx.org/licenses/OGL-Canada-2.0.html)\n\n### Citations\n\nCitations:\n\n- Agriculture and Agri-Food Canada Annual Crop Inventory. {YEAR}\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.ImageCollection('AAFC/ACI');\nvar crop2016 = dataset\n .filter(ee.Filter.date('2016-01-01', '2016-12-31'))\n .first();\nMap.setCenter(-103.8881, 53.0372, 10);\nMap.addLayer(crop2016, {}, '2016 Canada AAFC Annual Crop Inventory');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/AAFC/AAFC_ACI) \n[Canada AAFC Annual Crop Inventory](/earth-engine/datasets/catalog/AAFC_ACI) \nStarting 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, ... \nAAFC/ACI, agriculture,canada,crop,landcover \n2009-01-01T00:00:00Z/2023-01-01T00:00:00Z \n36.83 -135.17 62.25 -51.24 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://open.canada.ca/data/en/dataset/ba2645d5-4458-414d-b196-6303ac06c1c9)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/AAFC_ACI)"]]
