Combined GIS and Africa RISING Baseline Evaluation Survey (ARBES) Farm Household Data for FarmMatch, Tanzania
<|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:'GIS grid cells differ in biophysical conditions (soil, rainfall, etc.) and socio-economic circumstances (e.g. distance to market, population density). Moreover, within these cells we have households sampled within the Africa RISING Baseline Evaluation Survey (ARBES) database collected by IFPRI. For each household, we analyze in particular the main, easy to collect farm and household features (size, objectives, livestock, crop number, % off-farm income, etc.) and relate these to the farm practices and project-proposed technologies and techniques. The matching algorithm combines the GIS-derived data on biophysical conditions and socio-economic context circumstances with the farm features, to estimate the probability of use of the various technologies and techniques. The data scored are as follows: Elevation, Digital Elevation Model,' . 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" : ["AFRICA","AFRICA SOUTH OF SAHARA","agricultural systems","EAST AFRICA","geographical information systems","TANZANIA","technology"]} <|eot_id|>
 Here is the Description of a dataset. Description:'GIS grid cells differ in biophysical conditions (soil, rainfall, etc.) and socio-economic circumstances (e.g. distance to market, population density). Moreover, within these cells we have households sampled within the Africa RISING Baseline Evaluation Survey (ARBES) database collected by IFPRI. For each household, we analyze in particular the main, easy to collect farm and household features (size, objectives, livestock, crop number, % off-farm income, etc.) and relate these to the farm practices and project-proposed technologies and techniques. The matching algorithm combines the GIS-derived data on biophysical conditions and socio-economic context circumstances with the farm features, to estimate the probability of use of the various technologies and techniques. The data scored are as follows: Elevation, Digital Elevation Model,' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
GIS grid cells differ in biophysical conditions (soil, rainfall, etc.) and socio-economic circumstances (e.g. distance to market, population density). Moreover, within these cells we have households sampled within the Africa RISING Baseline Evaluation Survey (ARBES) database collected by IFPRI. For each household, we analyze in particular the main, easy to collect farm and household features (size, objectives, livestock, crop number, % off-farm income, etc.) and relate these to the farm practices and project-proposed technologies and techniques. The matching algorithm combines the GIS-derived data on biophysical conditions and socio-economic context circumstances with the farm features, to estimate the probability of use of the various technologies and techniques. The data scored are as follows: Elevation, Digital Elevation Model,
AFRICA; AFRICA SOUTH OF SAHARA; agricultural systems; EAST AFRICA; geographical information systems; TANZANIA; technology