5. Research methods

Survey design was adopted in carrying out the study. [54] describes survey research as the one in which a group of people or item is studied by collecting and analyzing data from only a few people or items considered to be representative of the entire group. Population of the study: Anambra state is made up of 2270 smallholder maize farmers (Anambra State Agricultural GIS-Based Assessment of Smallholder Farmers' Perception of Climate Change Impacts and Their… http://dx.doi.org/10.5772/intechopen.79009 121

Figure 3. Map of Anambra state showing the four sampled study sites of Akwa North, Idemili, Orumba North and Oyi 1 local government areas (L.G.A.).

Development Programme, which formed the sample frame). The distribution is as follows; Anambra-520, Aguata-680, Awka-620, Onitsha-450. Sampling Techniques and sample size: A multi-stage sampling method was used in selecting the sample units for the study. Anambra state is made up of four agricultural zones, namely, Anambra, Aguata, Awka and Onitsha. One extension block was randomly selected from each of the four agricultural zones to avoid bias; Awka north, Orumba north, Oyi 1 and Idemili to give a total of four blocks. Secondly, two circles were randomly selected from each of the four blocks again to give equal coverage, the selected circles were Amansi and Awba ofe nmiri from Awka north, Ufuma and Ajali from Orumba north, Nteje and Umunya from Oyi 1 and Nkpor and Obosi from Idemili north, thereby giving a total of eight circles. In the fourth stage, two sub-circles were randomly selected from each of the circles, the selected sub-circles were Ore, Egbe agu, Umu eze and Enugu agu from Amansi and Awba ofe nmiri, Umu onyiba, Umu ogem, Umu abiama and Umu ereh from Ufuma and Ajali, Umuefi, Achalla, Umuebo and Amaezike from Nteje and Umunya, Akuzor, Nbuba, Ire and Umu ota from Nkpor and Obosi, thereby given a total of sixteen sub- circles. The last stage involved random selection of eight farmers contact from each sub-circles. In all, a total of 128 farmers (respondents) were chosen from a list comprising of 2270 small scale maize farmers provided by Anambra ADP which formed the sampling size.

empirical evidence as to what extent climate variability is perceived by the smallholders maize farmers in Anambra state. These scenarios create the pertinent need to researching the assessment of smallholders maize farmers' perception on climate variability and its emerging consequences

Figure 2. Climograph (left) and temperature graph (right and down) of Anambra state. Source https://en.climate-data.

Survey design was adopted in carrying out the study. [54] describes survey research as the one in which a group of people or item is studied by collecting and analyzing data from only a few people or items considered to be representative of the entire group. Population of the study: Anambra state is made up of 2270 smallholder maize farmers (Anambra State Agricultural

on their livelihoods in Anambra State of Nigeria.

5. Research methods

org/location/46675/#temperature-graph.

120 Corn - Production and Human Health in Changing Climate

Reliability of Instrument: Reliability of the questionnaire was tested using cromlech alpha method which is 0.82%.

#### 5.1. Method of data collection

Primary data were collected with well validated open and close ended questionnaire by the researcher. Questionnaire construction was based on the objectives of this study.

Where X1 = age (years), X2 = sex, X3 = house hold size (No), X4 = educational level (no of years), X5 = farming years (No), X6 = farming size (No), X7 = labor source (Manday), X8 =

GIS-Based Assessment of Smallholder Farmers' Perception of Climate Change Impacts and Their…

http://dx.doi.org/10.5772/intechopen.79009

123

membership organization (No), X9 = average income ( ₦ ), X10 = average yield (kg).

The various activities of the small scale maize farmers that contribute to climate variability are

Result in Table 1, reveals that the majority of the small scale maize farmers (88.28%) indicated that bush burning contribute to climate variability while (82.03%), (60.16%), (56.25%) and (50.78%) indicated that intensive agricultural land use, use of inorganic fertilizers, use of fossil fuels and deforestation as factors that contribute to climate variability. The implication of this finding is that many of the farming activities in the area contribute to climate change. This finding agrees with the study of Oladipo [41], who noted that most agricultural activities are

The result of mean responses of the level of awareness of climate variability by small scale

The result here, reveals that the smallholder maize farmers were significantly aware of the following climate variability in the study area: decreased rainfall days ( = 2.05; SD = 0.914), early onset of rainfall and early cessation ( = 2.08; SD = 0.929), late onset of rainfall and early cessation ( = 2.02; SD = 0.816), shorter than normal rainfall ( = 2.14; SD = 1.132), low

Farmers' activities Frequency\* (n = 128) Percentage (%)

Burning of bush 113 88.28 Intensive agricultural land use 105 82.03 Use of inorganic fertilizers 77 60.16 Use of fossil fuels (fuel, kerosene, etc.) 72 56.25 Deforestation 65 50.78 Use of herbicides 54 42.19 Use of pesticides 55 42.97 Improper disposal of farm wastes 46 35.94

Table 1. Percentage response of farmers according to the activities that contribute to climate variability.

6. Findings and interpretations

the major factors of climate variability.

maize farmers is shown in Table 2.

6.2. Level of awareness of climate variability

shown in Table 1.

\*Multiple response. Source: Field survey, 2017.

6.1. Activities that contribute to climate variability

## 5.2. GIS technique

The aim of the GIS technology applied in this present study is provide maps of climate variability, degree of climate change adaptation and level of acceptability among the samples sites. The input data were from outcome of the questionnaire approach and GPS coordinates.
