3.1 Topological Parameters
3.1.1 Elevation
In this study, elevation and slope were regarded as significant topological parameters for rice cultivation. Based on SRTM data, the elevation of the coastal Indian region ranged from − 5 to 2500 m above the MSL. Regarding rice cultivation, elevation was reclassified into four major categories which were < 100 m, 100–500 m, 500–1000 m, and > 1000 m. Rice is traditionally cultivated in lowlands where water stagnation is favoured, making elevations below 100 m preferable for its growth 30,31. The elevation with < 100 m class covered about 73.08% (24029805.11 ha) of the total study area. The regions with 100–500 m elevation accounted for 22.46% (7386142.61 ha) which may be used for rice cultivation. The remaining regions with elevations 500–1000 and > 1000 m covered about 3.5 and 0.3% of the study area respectively, which are not suitable for producing rice. Higher weights were allotted to the areas with < 100 m elevation (Fig. 3a and Table 5).
For the production of coconut, the elevation was classified into 4 classes based on its suitable conditions namely, < 100, 100–600, 600–900, and > 900 m. Coconut can flourish well up to an elevation of 600 m above MSL. It can also be grown in areas with an elevation greater than 600 m, provided the temperature is favourable for its growth 32. The areas with elevation < 100 m occupied 73.08% (24029805.11 ha) of the total study area. The sites with 100–600, 600–900, and > 900 m elevations inhabit 24.46% (8044155.11 ha), 1.72% (564998.86 ha), and 0.74% (244411.36 ha) area, respectively. The higher weights were assigned to the areas with < 100 m elevation (Fig. 4a and Table 6).
3.1.2 Slope
SRTM data was used to calculate the slope map. A lower slope indicates flatter surfaces while a higher slope represents a sharp and steep slope. The slope of coastal India ranged from 0 to 207.62%. For the cultivation of rice, it was classified into five classes namely < 1, 1–3, 3–10, 10–15 and > 15% out of which the maximum area comes under level to nearly level slope (< 1%) with 45.05% (14813367.84 ha) area. The level to nearly level class was assigned with higher weightage as it allows standing water which is favorable for better growth and development of rice. Further, the very gently sloping (1–3%) class covered 27.08% (8903905.34 ha) area. The remaining classes with gently sloping (3–10%), moderately sloping (10–15%) and moderately steep (> 15%) covered about 14.11 (4640617.84 ha), 4.23 (1391961.59 ha) and 9.53% (3133517.84 ha) areas, respectively (Fig. 3b and Table 5).
The slope of the coastal region was classified into five major classes based on the requirement of a coconut, viz. < 4, 4–8, 8–15, 15–30, and > 30%. The areas under each of these classes were 76.49% (24815907.12 ha), 8.05% (2773563.37 ha), 6.15% (2160382.12 ha), 6.02% (2007737.05 ha), 3.29% (1125780.80 ha) of the total study region, respectively. For coconut cultivation, higher weights were allotted to the class with < 4% slope which was appropriate for its growth, since coconut prefers low-lying areas and higher slopes can affect the plant growth through erosion of fertile soil layer with surface runoff (Fig. 4b and Table 6).
3.2 Pedological Parameters
3.2.1 Soil depth
In the present study, soil depth for rice was categorized into seven classes ranging from extremely shallow (< 10 cm) to very deep (> 125 cm) soil depths. The maximum area of the study region is very deep (> 125 cm) covering about 23.99% (7889766.32 ha) followed by deep (100–125 cm) soil depths, and 26.37% (8670316.32 ha) areas, respectively. The remaining classes namely moderately deep (75–100 cm), moderately shallow (50–75 cm), shallow (25–50 cm), very shallow (10–25 cm), and extremely shallow (< 10 cm) soil depths covered 11.25% (3698547.57 ha), 6.15% (2021210.07 ha), 12.84% (4220660.07 ha), 10.55% (3470272.57 ha) and 8.86% (2912597.57 ha) of the total area, respectively. The higher weights were assigned to very deep soils followed by deep soil depths since higher depths will permit better root growth. Better root growth will help to extract higher soil moisture and nutrients leading to better crop growth and ultimately higher yield (Fig. 3c and Table 5).
Soil depth data for coconut growing conditions was reclassified into 4 classes, namely, < 50, 50–75, 75–100, and > 100 cm. 50.36% (16560082.63 ha), 11.25% (3698547.57 ha), 6.15% (2021210.07 ha), and 32.25% (10603530.20 ha) of the area belonged to each of these classes respectively. Soil depth > 100 cm was considered to be most suitable for coconut and was assigned the highest weights among others (Fig. 4c and Table 6).
3.2.2 Soil drainage
Different soil characteristics such as texture, structure and porosity of soil affect the soil drainage parameter. In the current study, soil drainage for rice was classified into six classes namely imperfect, very poor, poor, moderately well-drained, well-drained and excessive. The areas in each of these classes were 50.36% (16560082.63 ha), 11.25% (3698547.57 ha), 6.15% (2021210.07 ha), and 32.25% (10603530.20 ha), respectively. The maximum weightage was assigned to imperfect drainage because rice requires standing water for its growth and development. Imperfectly drained soil will allow standing water for a longer period (Fig. 3d and Table 5).
Soil drainage for coconut production was reclassified into 5 major classes namely, well-drained, moderately well-drained, imperfect, excessive, and poorly drained. These classes represented 40.16% (13206446.12 ha), 12.98% (4268464.87 ha), 16.69 (5488608.62 ha), 14.48% (4760864.87 ha), and 15.69% (5158985.99 ha) of the total study area, respectively. Coconut prefers well-drained soils for their optimal growth and development, hence this type of drainage system was allotted the highest weight followed by other sub-classes (Fig. 4d and Table 6).
3.2.3 Soil texture
Soil texture is one of the important factors responsible for crop production. The circulation and availability of air and water in the soil, root growth, water and nutrient intake, are mostly influenced by soil texture. For rice suitability, soil texture was classified into five classes viz. clay (consisting of clay, silty clay, clay loam, silty clay loam, sandy clay), loam (consisting of sandy clay loam, silt loam, loam, silt), loamy sand, sandy loam and sand where clayey soil texture was assigned with the highest weights. Because clayey soil includes more tiny particles, it can hold more water and nutrients than any other soil type, giving optimal growing conditions for rice crops. The maximum areas of the study region were under clayey soils (21911785.34 ha) followed by loam (10812841.59), sandy loam (158529.09), loamy sand (147.84 ha) and sand (66.59 ha) (Fig. 3e and Table 5).
For coconut, soil texture present in the study region was reclassified into three classes namely, 1) loam (comprising of clay loam, loam, sandy clay loam, sandy clay, silty clay loam, silty loam); 2) sandy loam (SL), silty clay (SiC), silt (Si); 3) sand (S), clay (C), and loamy sand (LS). The classes are composed of 88.31% (29038342.24 ha), 10.22% (3359098.49 ha), and 1.48% (485929.74 ha) of the total area. Loam soil type predominated in the study region and was assigned the highest weight due to its suitability for coconut cultivation (Fig. 4e and Table 6).
3.2.4 Soil pH
Soil pH is a critical factor influencing crop growth. Several chemical and biological processes inside the soil are regulated and controlled by soil pH. The increase in soil pH leads to a decrease in shoot weight and panicle number in rice, resulting in a significant decline in rice yield (Huang et al., 2017). Based on the suitable pH range for rice, it was categorized into five classes namely strongly acidic (< 4.5), moderately acidic (4.5–5.5), slightly acidic (5.5–6.5), neutral (6.5–7.5) and slightly alkaline (7.5–8.5). Among these classes, the coastal region predominantly consisted of neutral pH covering about 52.95% (17411514.87 ha). Slightly acidic soils were mainly observed in the eastern and western parts of the study region with 27.54% (9055183.62 ha) of the total area. Slightly alkaline, moderately acidic and strongly acidic soils were observed more in the western parts than eastern parts of the study region. The areas covered by these classes consisted of 2.40% (788696.12 ha), 5.40% (1776889.87 ha) and 11.71% (3851085.99 ha), of the total area respectively. The slightly acidic soil was given greater importance due to its pH level falling within the optimal range of 5.5 to 6.5 for rice cultivation. Neutral and moderately acidic soils, which are also suitable for rice development, were assigned lower weights (Fig. 3f and Table 5).
The optimal pH range for coconut plantations is typically between 5.0 and 6.5. Based on this requirement, the pH values were categorized into six major classes viz., < 4.0, 4.0-4.5, 4.5-5.0, 5.0-6.5, 6.5–7.5 and 7.5–8.5 34. Areas with pH less than 4.0 covered 11.39% (3,744,077.37 ha), pH 4.0-4.5 covered 0.33% (107,008.62 ha), pH 4.5-5.0 covered 0.35% (114,146.12 ha), the optimal pH range of 5.0-6.5 covered 32.59% (10,717,927.37 ha), pH 6.5–7.5 covered 52.95% (17,411,514.87 ha), and pH 7.5–8.5 covered 2.40% (788,696.12 ha). The highest weights were assigned to the pH values ranging between 5.0 and 6.5 for coconut suitability. Following this, 6.5–7.5 and 4.5-5.0, and 7.5–8.5 and 4.0-4.5 were assigned similar weights. Lastly, pH values below 4.0 received the lowest weight with respect to coconut suitability (Fig. 4f and Table 6).
3.2.5 SOC
The higher SOC content in the soil improves the growth of rice by supplying the required amount of nutrients. It is also essential for a variety of soil activities and ecological characteristics. The SOC in anaerobic waterlogged conditions decomposes more slowly than the upland soils 35. The SOC content for both rice and coconut was categorized into five groups: <0.25%, 0.25–0.50%, 0.50–0.75%, 0.75-1.00% and > 1.00%. The majority of the study region had a SOC > 1.00%, covering 75.25% (24744391.59 ha) of the total area. This was followed by 0.75-1.00, < 0.25, 0.50–0.75 and 0.25–0.50 classes with 11.18%, 9.37%, 3.70%, 0.50% and of the total area, respectively (Fig. 3g, 4g and Table 5, 6). Greater weights were assigned to higher SOC content as higher SOC levels indicate better soil quality.
3.3 Climatic parameters
3.3.1 Annual rainfall
Rainfall is a crucial factor for rice cultivation due to its high water requirements compared to other crops. Along the coastal region, the mean annual rainfall varies from 350.09 to 5043.19 mm. The optimal rainfall range for rice cultivation was categorized into four classes: <750 mm, covering 31.31% (10,294,986.36 ha) of the area; 750–900 mm, covering 7.36% (2,419,373.86 ha); 900–1100 mm, covering 14.18% (4,662,567.61 ha); and greater than 1100 mm, covering 47.16% (15,506,442.61 ha). Greater weightage was given to annual rainfall > 1100 mm, aligning with the optimal range of 1110–1250 mm for rice cultivation (Fig. 3h and Table 5).
The ideal range of mean annual rainfall necessary for a coconut plant's effective growth and productivity is between 1500 and 2500 mm. Rainfall for coconuts was classified into four categories: >1500, 1000–1500, 500–1000, and < 500 mm. The area calculated corresponding to each category was 30.70% (10094961.36 ha), 25.03% (8230573.86 ha), 31.42% (10333555.11 ha), 12.85% (4224280.11 ha) out of the total study area, respectively. The subclass with a higher amount of rainfall, that is > 1500 mm, received the most weightage, followed by subsequent classes (Fig. 4h and Table 6).
3.3.2 Temperature
Temperature is another critical factor influencing the growth of rice. It requires a greater temperature range (30–34°C) to sustain. For rice production, the temperature of the coastal region was determined considering the length of its growth period (June, July, August and September). The temperature during the rice growing season in the study region ranged from 13.30 to 31.72°C. It was categorized into five classes: <15, 15–20, 20–25, 25–30 and > 30°C amongst which temperature with > 30°C was assigned the highest weight. The area covered across these classes were 0.29% (94376.59 ha), 0.38% (124176.59 ha), 4.38% (1439082.84 ha), 65.39% (21502207.84 ha) and 29.57% (9723526.59 ha), respectively (Fig. 3i and Table 5).
The mean annual temperature was used for coconut suitability analysis which varied between 23.76 and 28.90°C in the study region. Suitable areas for coconut growth and development significantly depend on the surrounding temperature where the plant is grown. Given its tropical nature, it requires heat throughout the year with high humidity in extreme summer periods. Consequently, the coastal region of India is highly suitable for coconut cultivation. Temperature in coastal India was classified into two sub-classes: <26 and 27–29°C. A higher weight was attributed to temperatures ranging from 27 to 29°C. Each of these groups covers an area of 85.86% (28232447.73 ha) and 14.14% (4650922.73 ha), respectively (Fig. 4i and Table 6).
This LULC map containing eight classes: water, trees, flooded vegetation, crops, built area, bare ground, snow/ice and rangeland, was used for extracting the suitable areas for rice and coconut cultivation (Fig. 3j).
3.4 Crop suitability analysis for rice and coconut using AHP
Based on the AHP analysis conducted for rice crop, rainfall had the highest weightage (0.29) followed by, soil drainage (0.25), soil texture (0.16), and soil depth (0.11). Both slope and elevation were assigned equal weights (0.06) due to the interdependence of slope and elevation. Weights assigned to SOC (0.0437), temperature (0.03) and soil pH (0.02) were less than 0.05. Further, CR for rice was computed as the ratio of CI (0.1140) to the random index value for nine parameters (RI = 1.46). The CR value of 0.0781 was below the threshold of 0.1 and hence accepted for rice suitability analysis (Table 3).
For the coconut suitability analysis, the slope of the study area received the highest weight of 0.31, followed by elevation (0.22), soil drainage (0.15), soil texture (0.11), soil depth (0.08), temperature (0.06), rainfall (0.04), SOC (0.03), and pH (0.02) as per AHP. The calculated CI for coconut was observed as 0.1034 and the total number of parameters corresponding to this matrix was nine (n = 9). Based on these two values, the CR value was computed, which was found to be 0.0708. Since the CR was less than 0.1, it was accepted (Table 4).
Table 3
Pairwise comparison matrix of rice suitability using AHP
| | Rainfall | Temperature | Soil drainage | Soil depth | Soil texture | Slope | Elevation | SOC | Soil pH | Weights |
| Rainfall | 1.00 | 8.00 | 1.00 | 5.00 | 3.00 | 6.00 | 6.00 | 7.00 | 9.00 | 0.29 |
| Temperature | 0.13 | 1.00 | 0.13 | 0.20 | 0.17 | 0.33 | 0.33 | 0.50 | 2.00 | 0.03 |
| Soil drainage | 1.00 | 8.00 | 1.00 | 3.00 | 2.00 | 5.00 | 5.00 | 7.00 | 9.00 | 0.25 |
| Soil depth | 0.20 | 5.00 | 0.33 | 1.00 | 0.50 | 3.00 | 3.00 | 4.00 | 7.00 | 0.11 |
| Soil texture | 0.33 | 6.00 | 0.50 | 2.00 | 1.00 | 4.00 | 4.00 | 5.00 | 7.00 | 0.16 |
| Slope | 0.17 | 3.00 | 0.20 | 0.33 | 0.25 | 1.00 | 1.00 | 2.00 | 5.00 | 0.06 |
| Elevation | 0.17 | 3.00 | 0.20 | 0.33 | 0.25 | 1.00 | 1.00 | 2.00 | 5.00 | 0.06 |
| SOC | 0.14 | 2.00 | 0.14 | 0.25 | 0.20 | 0.50 | 0.50 | 1.00 | 3.00 | 0.04 |
| Soil pH | 0.11 | 0.50 | 0.11 | 0.14 | 0.14 | 0.20 | 0.20 | 0.33 | 1.00 | 0.02 |
Consistency index (CI) = \(\:({\lambda\:}_{max}-n\:)/(n-1)\) = 0.1140
Number of parameters (n) = 9
Maximum Eigenvalue \(\:{(\lambda\:}_{\text{m}\text{a}\text{x}})=\:9.9122\)
Random index (RI) = 1.46
Consistency ratio (CR) = CI/RI = 0.0781
Table 4
Pairwise comparison matrix of coconut suitability using AHP
| | Elevation | Slope | Soil depth | Soil texture | Soil drainage | Rainfall | Temperature | Soil pH | SOC | Weight |
| Elevation | 1.00 | 0.50 | 0.20 | 0.33 | 0.25 | 0.14 | 0.17 | 2.00 | 3.00 | 0.04 |
| Slope | 2.00 | 1.00 | 0.25 | 0.50 | 0.33 | 0.17 | 0.20 | 3.00 | 5.00 | 0.06 |
| Soil depth | 5.00 | 4.00 | 1.00 | 3.00 | 2.00 | 0.33 | 0.50 | 6.00 | 7.00 | 0.15 |
| Soil texture | 3.00 | 2.00 | 0.33 | 1.00 | 0.50 | 0.20 | 0.25 | 4.00 | 5.00 | 0.08 |
| Soil drainage | 4.00 | 3.00 | 0.50 | 2.00 | 1.00 | 0.25 | 0.33 | 5.00 | 7.00 | 0.11 |
| Rainfall | 7.00 | 6.00 | 3.00 | 5.00 | 4.00 | 1.00 | 2.00 | 8.00 | 9.00 | 0.31 |
| Temperature | 6.00 | 5.00 | 2.00 | 4.00 | 3.00 | 0.50 | 1.00 | 7.00 | 8.00 | 0.22 |
| Soil pH | 0.50 | 0.33 | 0.17 | 0.25 | 0.20 | 0.13 | 0.14 | 1.00 | 2.00 | 0.03 |
| SOC | 0.33 | 0.20 | 0.14 | 0.20 | 0.14 | 0.11 | 0.13 | 0.50 | 1.00 | 0.02 |
Consistency index (CI) = \(\:({\lambda\:}_{max}-n\:)/(n-1)\) = 0.1034
Number of parameters (n) = 9
Maximum Eigenvalue \(\:{(\lambda\:}_{\text{m}\text{a}\text{x}})=\:9.8274\)
Random index (RI) = 1.46
Consistency ratio (CR) = CI/RI = 0.0708
Similarly, using the AHP approach, each sub-class for all nine parameters of rice and coconut was assigned rankings and weights. The higher weightage was allotted to the best suitable sub-class and lesser weights were given to subsequent sub-classes and CR value was calculated (Supplementary Table 1 and Table 2).
Table 5
Rice parameter sub-classes, the area under each sub-class and weights.
| Parameter | Class | Area (ha) | Area (%) | Weights |
| Elevation (m) | < 100 | 24029805.11 | 73.08 | 0.58 |
| | 100–500 | 7386142.61 | 22.46 | 0.26 |
| | 500–1000 | 1253311.36 | 3.81 | 0.12 |
| | > 1000 | 214111.36 | 0.65 | 0.05 |
| Slope (%) | Level to nearly level (< 1) | 14813367.84 | 45.05 | 0.51 |
| | Very gentle slope (1–3) | 8903905.34 | 27.08 | 0.24 |
| | Gentle slope (3–10) | 4640617.84 | 14.11 | 0.14 |
| | Moderate slope (10–15) | 1391961.59 | 4.23 | 0.06 |
| | Moderate steep (> 15) | 3133517.84 | 9.53 | 0.04 |
| Depth (cm) | Very Deep (> 125) | 7889766.32 | 23.99 | 0.28 |
| | Deep (100–125) | 8670316.32 | 26.37 | 0.28 |
| | Mod. deep (75–100) | 3698547.57 | 11.25 | 0.20 |
| | Mod. shallow (50–75) | 2021210.07 | 6.15 | 0.12 |
| | Shallow (25–50) | 4220660.07 | 12.84 | 0.06 |
| | Very shallow (10–15) | 3470272.57 | 10.55 | 0.03 |
| | Extremely shallow (< 10) | 2912597.57 | 8.86 | 0.02 |
| Texture | Clayey | 21911785.34 | 66.63 | 0.52 |
| | Loam | 10812841.59 | 32.88 | 0.22 |
| | Sandy loam | 158529.09 | 0.48 | 0.11 |
| | Loamy sand | 147.84 | 0.00 | 0.10 |
| | Sand | 66.59 | 0.00 | 0.04 |
| Drainage | Imperfect | 5488608.62 | 16.69 | 0.39 |
| | Very poor | 2298271.12 | 6.99 | 0.28 |
| | Poor | 2860714.87 | 8.70 | 0.18 |
| | Moderately well drained | 4268464.87 | 12.98 | 0.08 |
| | Well drained | 13206446.12 | 40.16 | 0.05 |
| | Excessive | 4760864.87 | 14.48 | 0.03 |
| SOC (%) | Very high (> 1.00) | 24744391.59 | 75.25 | 0.43 |
| | High (0.75-1.00) | 3677329.09 | 11.18 | 0.31 |
| | Medium (0.50–0.75) | 1216172.84 | 3.70 | 0.14 |
| | Low (0.25–0.50) | 165397.84 | 0.50 | 0.07 |
| | Very low (< 0.25) | 3080079.09 | 9.37 | 0.04 |
| pH | Strongly acidic (< 4.5) | 3851085.99 | 11.71 | 0.09 |
| | Moderately acidic (4.5–5.5) | 1776889.87 | 5.40 | 0.20 |
| | Slightly acidic (5.5–6.5) | 9055183.62 | 27.54 | 0.46 |
| | Neutral (6.5–7.5) | 17411514.87 | 52.95 | 0.20 |
| | Slightly alkaline (7.5–8.5) | 788696.12 | 2.40 | 0.04 |
| Rainfall (mm) | > 1100 | 15506442.61 | 47.16 | 0.54 |
| | 900–1100 | 4662567.61 | 14.18 | 0.29 |
| | 750–900 | 2419373.86 | 7.36 | 0.11 |
| | < 750 | 10294986.36 | 31.31 | 0.06 |
| Temperature (°C) | > 30 | 9723526.59 | 29.57 | 0.48 |
| | 25–30 | 21502207.84 | 65.39 | 0.27 |
| | 20–25 | 1439082.84 | 4.38 | 0.15 |
| | 15–20 | 124176.59 | 0.38 | 0.06 |
| | < 15 | 94376.59 | 0.29 | 0.04 |
Table 6
Coconut parameter sub-classes, area under each sub-class and weights.
| Parameter | Class | Area (ha) | Area (%) | Weights |
| Elevation (m) | < 100 | 24029805.11 | 73.08 | 0.58 |
| | 100–600 | 8044155.11 | 24.46 | 0.26 |
| | 600–900 | 564998.86 | 1.72 | 0.12 |
| | > 900 | 244411.36 | 0.74 | 0.05 |
| Slope (%) | < 4 | 24815907.12 | 76.49 | 0.51 |
| | 4–8 | 2773563.37 | 8.05 | 0.24 |
| | 8–15 | 2160382.12 | 6.15 | 0.14 |
| | 15–30 | 2007737.05 | 6.02 | 0.06 |
| | > 30 | 1125780.80 | 3.29 | 0.04 |
| Depth (cm) | > 100 | 16560082.63 | 50.36 | 0.52 |
| | 75–100 | 3698547.57 | 11.25 | 0.30 |
| | 50–75 | 2021210.07 | 6.15 | 0.12 |
| | < 50 | 10603530.20 | 32.25 | 0.06 |
| Texture | Loam | 29038342.24 | 88.31 | 0.67 |
| | SL, SiC, Si | 3359098.49 | 10.22 | 0.24 |
| | S, C, LS | 485929.74 | 1.48 | 0.09 |
| Drainage | Well drained | 13206446.12 | 40.16 | 0.49 |
| | Moderately well drained | 4268464.87 | 12.98 | 0.24 |
| | Imperfect | 5488608.62 | 16.69 | 0.12 |
| | Excessive | 4760864.87 | 14.48 | 0.10 |
| | Poorly drained | 5158985.99 | 15.69 | 0.04 |
| SOC (%) | > 1.00 | 24744391.59 | 75.25 | 0.43 |
| | 0.75-1.00 | 3677329.09 | 11.18 | 0.31 |
| | 0.50–0.75 | 1216172.84 | 3.70 | 0.14 |
| | 0.25–0.50 | 165397.84 | 0.50 | 0.07 |
| | < 0.25 | 3080079.09 | 9.37 | 0.04 |
| pH | < 4.0 | 3744077.37 | 11.39 | 0.05 |
| | 4.0-4.5 | 107008.62 | 0.33 | 0.11 |
| | 4.5-5.0 | 114146.12 | 0.35 | 0.27 |
| | 5.0-6.5 | 10717927.37 | 32.59 | 0.57 |
| | 6.5–7.5 | 17411514.87 | 52.95 | 0.27 |
| | 7.5–8.5 | 788696.12 | 2.40 | 0.11 |
| Rainfall (mm) | > 1500 | 10094961.36 | 30.70 | 0.54 |
| | 1000–1500 | 8230573.86 | 25.03 | 0.29 |
| | 500–1000 | 10333555.11 | 31.42 | 0.11 |
| | < 500 | 4224280.11 | 12.85 | 0.06 |
| Temperature (°C) | 27–29 | 28232447.73 | 85.86 | 0.75 |
| | < 26 | 4650922.73 | 14.14 | 0.25 |
The crop suitability map was produced based on the 9 factors affecting the rice and coconut growth using the weighted overlay analysis method by considering the AHP calculated weights. The crop suitability index for rice ranged from 0.072 to 0.466 while for coconut, it ranged from 0.145 to 0.545 with higher values indicating better suitability. The derived crop suitability maps were reclassified into four major suitability classes using equal intervals namely highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and not suitable areas (N). Area suitable for rice crop under each of these classes was 16.10% (5293386.4 ha), 44.06% (14489161.4 ha), 24.11% (7927948.9 ha), and 15.73% (5172873.9 ha), respectively (Fig. 5 (a) and Table 10). The corresponding areas suitable for coconut was 5.60% (1840948.865 ha), 25.25% (8304430.115 ha), 50.40% (16574723.86 ha), and 18.74% (6163267.615 ha), respectively (Fig. 5 (b) and Table 11).
Taking into consideration the land available for agriculture, the LULC map was reclassified into two classes i.e. cropland area (flooded vegetation, crops, bare ground, rangeland) and non-cropland area (water, trees, built area, and snow/ice) which was used to generate crop mask. The observed areas corresponding to these cropland and non-cropland regions were 65.05% (21390891.48 ha) and 34.95% (11492478.98 ha), respectively (Supplementary Table 3).
The crop mask was used to extract rice and coconut suitable areas. Within the study region, 13.68% (4498035.4 ha) area was found highly suitable for rice cultivation, while 19.26% (6333154.1 ha) was moderately suitable, 18.35% (6034816.6 ha) was marginally suitable and 13.76% (4524885.4 ha) was not suitable (Fig. 6 (a) and Table 7). Concurrently with rice, areas suitable for coconut were 11.00% (3617660.4 ha), 27.40% (9010122.9 ha), 18.34% (6031010.4 ha) and 8.31% (2732097.9 ha) of the total study region (Fig. 6 (b) and Table. 8). Around 34.95% (11492479.0 ha) area of coastal India is permanently not suitable for crop cultivation as it includes the non-cropland (water, trees, built area, and snow/ice) areas.
The findings revealed that highly suitable areas for rice were mostly distributed on the eastern coast of India with 78.71% (3540383.325 ha) area than the western coast with 21.29% (957652.075 ha) (Fig. 6 (a)). A limited number of districts in Gujarat, Maharashtra, Goa, Karnataka, and Kerala exhibited sparsely distributed highly suitable areas for rice cultivation. It was discovered that coastal areas in eastern India were better suited for coconuts than those in western India. Moderately suitable sites for rice account for about 19.26% (6333154.1 ha) of the total area, with 36.31% (2299327.05 ha) and 63.69% (4033827.05 ha) of that area falling under India's western and eastern coasts, respectively. Moderately suitable regions for coconut were majorly occupied by the eastern coast except for some districts of Odisha. On the west coast, moderately suitable coconut sites were mostly present in districts of Maharashtra and Gujarat, with very few areas in the remaining districts.
For rice, marginally suitable areas account for around 18.35% (6034816.6 ha) of the total study region. The eastern and western coastal regions account for about 32.12% (1938177.05 ha) and 67.88% (4096639.55 ha) of the total marginally suitable areas, respectively. The majority of the areas that were moderately suitable along the western coast of India were found in the districts of Gujarat and Uttar Kannada district of Karnataka. A greater quantity of marginally suitable areas was found on the west coast out of which Gujarat districts had the majority of marginally suitable sites. Along the eastern coast of Prakasam, SPSN districts of Odisha and some districts of Tamil Nadu had marginally suitable sites.
The non-suitable areas were determined by geomorphological features such as high slopes and elevations, the presence of bare rocks, drainage requirements, unfavorable temperature, and rainfall. After crop mask, the non-suitable area for rice crops calculated was ~ 13.76% (4524885.4 ha) of the total study area. Approximately 19.75% (893664.575 ha) of the unsuitable area is located on the eastern coast of India, while the remaining 80.25% (3631220.825 ha) is located on the western coast. On the east coast, some districts of Andhra Pradesh and Tamil Nadu showed non-suitable areas for rice cultivation. The majority of the non-suitable areas in the western coastal region were located in the districts of Gujarat except Valsad, Surat and Navsari. In the west coast, all districts of Gujarat except Valsad and Navsari were found to be unsuitable for coconut production, whilst in the east coast, districts in Andhra Pradesh and Tamil Nadu comprised the majority of the unsuitable areas.
Table 7
Area suitable for rice cultivation in coastal region before and after masking of non-cropland area.
| Class | Before masking | 1 | After masking |
| Area (ha) | Area (%) | | Area (ha) | Area (%) |
| Highly suitable | 5293386.4 | 16.10 | | 4498035.4 | 13.68 |
| Moderately suitable | 14489161.4 | 44.06 | | 6333154.1 | 19.26 |
| Marginally suitable | 7927948.9 | 24.11 | | 6034816.6 | 18.35 |
| Not suitable | 5172873.9 | 15.73 | | 4524885.4 | 13.76 |
| Non-cropland area | - | - | | 11492479.0 | 34.95 |
| Total | 32883370.5 | 100 | | 32883370.5 | 100 |
Table 8
Area suitable for coconut cultivation in coastal region before and after masking of non-cropland area.
| Class | Before masking | | After masking |
| Area (ha) | Area (%) | | Area (ha) | Area (%) |
| Highly suitable | 6163267.6 | 18.74 | | 3617660.4 | 11.00 |
| Moderately suitable | 16574723.9 | 50.40 | | 9010122.9 | 27.40 |
| Marginally suitable | 8304430.1 | 25.25 | | 6031010.4 | 18.34 |
| Not suitable | 1840948.9 | 5.60 | | 2732097.9 | 8.31 |
| Non-cropland | - | - | | 11492479.0 | 34.95 |
| Total area | 32883370.5 | 100 | | 32883370.5 | 100 |