Application of GIS and geographically weighted regression to evaluate the spatial non-stationarity relationships between precipitation vs. Irrigated and rainfed maize and soybean yields

Transactions of the ASABE

Volumn 54, Issue 3, 2011, Pages 953-972

  Sharma, V ^a   Irmak, S ^a   Kabenge, I ^a  

^a UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Geographically weighted regression; GIS; Maize; Ordinary least square regression; Precipitation; Soybean; Spline

Indexed keywords

AGRICULTURAL PRODUCTIVITY; AGRICULTURAL SETTING; AVERAGE ANNUAL PRECIPITATION; AVERAGE YIELD; CROP YIELD; FOOD SECURITY; GENERAL TRENDS; GEOGRAPHICALLY WEIGHTED REGRESSION; GROWING SEASON; INTERPOLATED PRECIPITATION; IRRIGATED CROPS; LINEAR CORRELATION; LONG-TERM TREND; MAIZE; MAIZE YIELD; MANAGEMENT DECISIONS; MEAN ANNUAL PRECIPITATION; MEAN PRECIPITATION; NEBRASKA; ORDINARY LEAST SQUARE REGRESSION; ORDINARY LEAST SQUARES; POLICY DECISIONS; RAINFED; RAINFED CONDITION; RAINFED CROP; REGRESSION MODEL; RESOURCE ASSESSMENTS; SCIENTIFIC DISCIPLINE; SEASONAL PRECIPITATIONS; SOYBEAN; SPATIAL NON-STATIONARITY; SPLINE INTERPOLATION; STATISTICAL TECHNIQUES; STRONG CORRELATION; TEMPORAL TRENDS; TOTAL PRECIPITATION; VARYING COEFFICIENTS; WATER STRESS; YIELD RELATIONSHIP;

CROPS; DECISION MAKING; FOOD SUPPLY; INTERPOLATION; PRODUCTIVITY; REGRESSION ANALYSIS; SCALES (WEIGHING INSTRUMENTS); SPLINES; WATER RESOURCES;

GEOGRAPHIC INFORMATION SYSTEMS;

AGRICULTURAL MANAGEMENT; CROP PRODUCTION; CROP YIELD; FOOD SECURITY; GIS; IRRIGATION SYSTEM; MAIZE; POLICY MAKING; PRECIPITATION (CLIMATOLOGY); RAINFED AGRICULTURE; REGRESSION ANALYSIS; RESOURCE ASSESSMENT; SOYBEAN; SPATIOTEMPORAL ANALYSIS; YIELD RESPONSE;

NEBRASKA; UNITED STATES;

GLYCINE MAX; ZEA MAYS;

EID: 79959798819     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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