Crop Monitoring Using Smartphone Based Near-Surface Remote Sensing: Ground Pictures of Wheat and Auxiliary Data from Northern India
<|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:'This is a processed dataset of approximately 20,000 near-surface remote sensing images acquired using inexpensive smartphones within the context of a picture-based insurance (PBI) initiative of 1,685 smallholder farmers ﬁelds in northwest India. Monitoring crop growth and disturbances is critical in strengthening farmers’ ability to manage production risks. The data presented monitors winter wheat growth and includes meta-data, either manually or automatically derived, to quantify 5 crop greenness, phenology and damage events as well as management practices. Our dataset offers granular visual ﬁeld data, with processed images and detailed meta-data that provide information on the timing of key developmental phases of winter wheat and crop growth disturbances which are not registered by common satellite remote sensing vegetation indices o' . 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" : ["ASIA","crowd sourcing","INDIA","insurance","picture-based crop insurance","remote sensing","SOUTH ASIA","technology","winter wheat"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This is a processed dataset of approximately 20,000 near-surface remote sensing images acquired using inexpensive smartphones within the context of a picture-based insurance (PBI) initiative of 1,685 smallholder farmers ﬁelds in northwest India. Monitoring crop growth and disturbances is critical in strengthening farmers’ ability to manage production risks. The data presented monitors winter wheat growth and includes meta-data, either manually or automatically derived, to quantify 5 crop greenness, phenology and damage events as well as management practices. Our dataset offers granular visual ﬁeld data, with processed images and detailed meta-data that provide information on the timing of key developmental phases of winter wheat and crop growth disturbances which are not registered by common satellite remote sensing vegetation indices o' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This is a processed dataset of approximately 20,000 near-surface remote sensing images acquired using inexpensive smartphones within the context of a picture-based insurance (PBI) initiative of 1,685 smallholder farmers ﬁelds in northwest India. Monitoring crop growth and disturbances is critical in strengthening farmers’ ability to manage production risks. The data presented monitors winter wheat growth and includes meta-data, either manually or automatically derived, to quantify 5 crop greenness, phenology and damage events as well as management practices. Our dataset offers granular visual ﬁeld data, with processed images and detailed meta-data that provide information on the timing of key developmental phases of winter wheat and crop growth disturbances which are not registered by common satellite remote sensing vegetation indices o
ASIA; crowd sourcing; INDIA; insurance; picture-based crop insurance; remote sensing; SOUTH ASIA; technology; winter wheat