Delineation of Cocoa Agroforests Using Multi-spectral optical image of RapidEye
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The main aim of the study was to discriminate cocoa agroforest from transition forest cover using a multi-spectral optical image of RapidEye, which was recorded in January 2015. The data consist pre-processed image stack of the Top of Atmosphere (ToA) reflectances for the five (5) spectral bands: Blue, Green, Red, RedEdge and Near-infrared image bands.Field inventory was conducted from 2015 to 2017 to map cocoa agroforests and other vegetation and non-vegetation land cover. in the forest-savannah transition landscape in Bokito, Centre Cameroon. The dataset consists of geospatial data (shapefiles) of the land cover and land use in the study landscape' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Agroforestry","Mapping","Perennials","Random Forest Algorithm","RapidEye Multi-spectral image","Vegetation indices"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The main aim of the study was to discriminate cocoa agroforest from transition forest cover using a multi-spectral optical image of RapidEye, which was recorded in January 2015. The data consist pre-processed image stack of the Top of Atmosphere (ToA) reflectances for the five (5) spectral bands: Blue, Green, Red, RedEdge and Near-infrared image bands.Field inventory was conducted from 2015 to 2017 to map cocoa agroforests and other vegetation and non-vegetation land cover. in the forest-savannah transition landscape in Bokito, Centre Cameroon. The dataset consists of geospatial data (shapefiles) of the land cover and land use in the study landscape' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The main aim of the study was to discriminate cocoa agroforest from transition forest cover using a multi-spectral optical image of RapidEye, which was recorded in January 2015. The data consist pre-processed image stack of the Top of Atmosphere (ToA) reflectances for the five (5) spectral bands: Blue, Green, Red, RedEdge and Near-infrared image bands.Field inventory was conducted from 2015 to 2017 to map cocoa agroforests and other vegetation and non-vegetation land cover. in the forest-savannah transition landscape in Bokito, Centre Cameroon. The dataset consists of geospatial data (shapefiles) of the land cover and land use in the study landscape
Agroforestry; Mapping; Perennials; Random Forest Algorithm; RapidEye Multi-spectral image; Vegetation indices