From: GHG mitigation in Agriculture, Forestry and Other Land Use (AFOLU) sector in Thailand
Indicators | Assumptions | Equation* | R^{2} |
---|---|---|---|
Agriculture | |||
Crop area (thousand hectares) | Time series analysis using 2005–2015 data | ||
Rice | Historical growth rate (0.07% p.a.) | – | – |
Cassava | Using linear function | y = 41.0x + 1049 | 0.76 |
Maize | Historical growth rate (0.41% p.a.) | – | – |
Vegetables | Using logarithmic function | y = − 75.6ln(x) + 860 | 0.90 |
Oil crops | Using linear function | y = 12.3x + 865 | 0.76 |
Sugarcane | Using linear function | y = 50.7x + 861 | 0.76 |
Other crops | Using logarithmic function | y = − 166ln(x) + 4562 | 0.64 |
Livestock (thousand heads) | Time series analysis using 2005–2015 data | ||
Cattle (dairy) | Historical growth rate (0.62% p.a.^{a}) | – | – |
Cattle_(other) | Constant during 2015–2050 | – | – |
Buffaloes | Constant during 2015–2050 | – | – |
Swines | Historical growth rate (1.9% p.a.^{a}) | – | – |
Goats | Liner regression | y = 16.8x + 318 | 0.71 |
Sheep | Historical growth rate (− 0.27% p.a.^{a}) | – | – |
Horses | Constant during 2015–2050 | – | – |
Duck | Liner regression | y = 950x + 21,582 | 0.45 |
Chicken | Liner regression | y = 18,699x + 191,094 | 0.79 |
Land use | |||
Forest | Government target to achieve 40% [6] | – | – |
Grassland | Constant with 2015 | – | – |
Agricultural | Constant with 2015 | – | – |
Settlement |
Settlement area per capita constant Population projection based on government [30] | – | – |