Suitability mapping for rice cultivation in Benue State, Nigeria using satellite data

Figures & data

Figure 1. The study area of Benue State.

Table 1. Data sets and their suitability classification.

		Data Range
Parameter	Data source	S1	S2	S3	NS	Reference
Temp.(°C)	http://srtm.csi.cgiar.org/	20–30	30–34	34–35	<20 >35	Ayehu and Besufekad 2015
Prec.(mm)	http://dx.doi.org/10.3334/ORNLDAAC/1247	1000–2000	2000–3500	>3500		Samanta, Pal, and Pal 2011
PH	http://data.ceda.ac.uk/badc/cru/data/cru_ts/cru_ts_4.00/data/	5–7.44	7.4–7.8	5.1–5.6	<5.1 >7.8	Ayehu and Besufekad 2015
BD(g/cm^3)	http://data.ceda.ac.uk/badc/cru/data/cru_ts/cru_ts_4.00/data/	1.10–1.39	1.30–1.39	1.39–1.47	>1.47	USDA, 2014
CEC(cmolc/k)	https://soilgrids.org/#!/?layer = TAXNWRB_250m&vector = 1	17–23	10–16	5–10	<5	Olaleye et al. 2008
Land Cover	http://dx.doi.org/10.3334/ORNLDAAC/1247	- Rice field -Wetlands	-Mixed forests	-Bare land	-Urban -Built
Slope(%)	http://glcfapp.umiacs.umd.edu/index.shtml	0–4	4–8	8–20	>20	Ayehu and Besufekad 2015
SOC(g/kg)	http://dx.doi.org/10.3334/ORNLDAAC/1247	>50	30–50	0–30		Umweni and Ogunkunle 2014

Figure 2. Maps of (a) mean temperature (oC) of 1985– 2015, (b) mean precipitation (mm) of 1985-2015, (c) soil pH, (d) bulk density (g/cm3), (e) CEC (cmol/kg), (f) land cover, (g) slope (% rise), (h) SOC (g/kg).

Figure 3. Rasterized suitability criteria for rice cultivation over Benue State, constraint (a) mean temperature, (b) mean precipitation, (c) soil pH, (d) bulk density, (e) CEC, (f) land cover, (g) slope, (h) SOC.

Table 2. Scales for pair-wise AHP comparisons (Maddahi et al. 2014).

Scale of Importance	Description
1	Equal Importance
3	Moderate Importance
5	Strong Importance
7	Very Strong Importance
9	Extreme Importance
2,4,6,8	Intermediate Values
Reciprocals	Values for inverse comparison

Table 3. PCM of all the parameters relevant to rice crop land suitability for Benue State, Nigeria.

	Slope	CEC	Temp	P	PH	BD	LC	SOC	Weights%
Slope	1	3.000	0.333	0.333	3.000	0.333	0.333	0.333	6.5
CEC	0.333	1	0.143	0.200	1.000	0.333	0.333	0.333	3.4
Temp	3.000	7.000	1	3.000	7.000	5.000	3.000	3.000	32.4
P	3.000	5.000	0.333	1	5.000	3.000	3.000	3.000	21.4
PH	0.333	1.000	0.143	0.200	1	0.333	0.333	0.333	3.4
BD	3.000	3.000	0.200	0.333	3.000	1	0.333	0.333	8.1
LC	3.000	3.000	0.333	0.333	3.000	3.000	1	1.000	12.4
SOC	3.000	3.000	0.333	0.333	3.000	3.000	1.000	1	12.4

Table 4. Random index.

Order Matrix	RI
1	0.00
2	0.00
3	0.58
4	0.90
5	0.12
6	1.24
7	1.32
8	1.41
9	1.45
10	1.49

Figure 4. Comparison between CRU gridded and NIMET Observation data for (a) Precipitation and (b) Temperature, (c) Seasonal relationship between CRU and Observation.

Table 5. Summary of spatial regression results (change in pixels over study area).

Suitability class	Regression Model	Dry season trends (%)			Wet season trends (%)
		Negative	Zero	Positive	Negative	Zero	Positive
Highly Suitable	NDVI/Precipitation	100.0	0.0	0.0	55.7	1.0	43.3
	NDVI/Temperature	0.0	0.0	100.0	0.0	2.0	98.0
Suitable	NDVI/Precipitation	100.0	0.0	0.0	41.1	0.8	58.1
	NDVI/Temperature	0.0	0.0	100.0	0.0	0.5	99.5

Figure 5. Seasonal NDVI from 1985 to 2015.

Figure 6. Spatial regression trend between (a) growing season NDVI and precipitation (mm/NDVI unit), (b) dry season NDVI and precipitation (mm/NDVI unit), (c) growing season NDVI and temperature (oC/NDVI unit), and (d) dry season NDVI and temperature (oC/NDVI unit) from 1985 to 2015.

Figure 7. Land suitability analysis for paddy field cultivation based on multi-criterion method, (b) percentage composition of the suitability classes.

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