Google Earth Engine ——数据全解析专辑（Canada AAFC Annual Crop Inventory）

此星光明

发布于 2024-02-02 08:50:53

980

发布于 2024-02-02 08:50:53

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).

从 2009 年开始，加拿大农业和农业食品部 (AAFC) 科技部 (STB) 的地球观测团队开始了生成一年生作物类型数字地图的过程。 2009 年和 2010 年以草原省份为重点，使用基于光学（Landsat-5、AWiFS、DMC）和雷达（Radarsat-2）的卫星图像应用了基于决策树 (DT) 的方法。从 2011 年的生长季节开始，这项活动已扩展到其他省份，以支持国家作物清单。迄今为止，这种方法可以始终如一地提供在最终空间分辨率为 30m（2009 年和 2010 年为 56m）时满足至少 85% 总体目标精度的作物清单。

Resolution

30 meters

Bands Table

Name	Description	Min	Max
landcover	Main crop-specific land cover classification.	1	255

Class Table: landcover

Value	Color Value	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	Quinoa
142	#999900	Sorghum
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

影像属性：

Name	Type	Description
landcover_class_names	List of Strings	Array of cropland landcover classification names.
landcover_class_palette	List of Strings	Array of hex code color strings used for the classification palette.
landcover_class_values	List of Ints	Value of the land cover classification.

引用：

Dataset Availability

2009-01-01T00:00:00 - 2019-01-01T00:00:00

Dataset Provider

Agriculture and Agri-Food Canada

Collection Snippet

ee.ImageCollection("AAFC/ACI")

Agriculture and Agri-Food Canada Annual Crop Inventory. {YEAR}

数据代码：

var dataset = ee.ImageCollection('AAFC/ACI');
var crop2016 = dataset
    .filter(ee.Filter.date('2016-01-01', '2016-12-31'))
    .first();
Map.setCenter(-103.8881, 53.0371, 10);
Map.addLayer(crop2016);