**7. Result and discussion**

Data collection is critical in geospatial analysis, typical data used for this study include Land Use map classified from Remote sensing data source; geo-coded data of the biomass sources, this is usually in the form of point data, obtained using GPS device. The acquired data points and the value was transferred into Arcmap environment of ArcGIS and processed into vector map for the site suitability analysis. The result of the various data analysis and modeling of suitable sites for the biogas plant by excluding unwanted areas identified in the constrain map and overlaying the thematic maps is fully discussed below.

#### **7.1 Land Use classification map**

Based on prior knowledge of land use of some geographical co-ordinates points, six classes were categorized. They are agriculture areas, barren/open land, dense forest, sand, urban land, and water body. The classified land use map is shown in **Figure 2**.

**155**

**Table 2.**

**Figure 3.**

*Scatter plot of image classification in ArcGIS.*

*Area occupation of various LULC classes.*

*Location Analysis and Application of GIS in Site Suitability Study for Biogas Plant*

Assessment of classification accuracy was carried out using the scatter plot analysis in statistical toolbar in ArcGIS 10. All the training data were highlighted to compare the scatter plot of the six classes to each other. The classes were examined to detect any form of overlap (these are classes having different pixel value). This shown in **Figure 3**, the statistics for the training data was also used to assess the accuracy of the classification. The statistic are usually organized for each training area. The covariance statistics evaluates the correlation between the values of different

The areas covered by each class of the LULC shows that urban land occupies

class is the sand class followed by water body, these feature classes occupies landmass

mined is 83%. The Table of LULC classification of Anambra State, area occupied in

**7.2 Biomass data of abattoir waste generating centers and map**

and percentage occupies by the various classes is shown in Table 4.1 (**Table 2**).

One of the basics for site analysis of biogas plant is the biomass potential density; **Figure 4** shows the abattoir biomass data indicating areas where the bio-wastes are generated across the study area. **Figure 4** shows the towns and villages in the State that has abattoir centers. From the Figure, there are no abattoir centres in the

**Class Area(km) Percentage (%)** WATER BODY 14000 1.00 SAND 13080 0.94 DENSE FOREST 257999 18.59 URBAN LAND 506896 36.52 AGRICULTURAL LAND 356430 25.68 BARREN/OPEN LAND 239400 17.25 TOTAL 1387805 100

of landmass of the overall LULC while the least

respectively. The overall classification accuracy deter-

*DOI: http://dx.doi.org/10.5772/intechopen.95508*

bands and were adequate for the study.

and 14000km2

36.52% which represent 506896km2

of 13080km2

km2

**Figure 2.** *Land cover and land use suitability map.*

#### *Location Analysis and Application of GIS in Site Suitability Study for Biogas Plant DOI: http://dx.doi.org/10.5772/intechopen.95508*

Assessment of classification accuracy was carried out using the scatter plot analysis in statistical toolbar in ArcGIS 10. All the training data were highlighted to compare the scatter plot of the six classes to each other. The classes were examined to detect any form of overlap (these are classes having different pixel value). This shown in **Figure 3**, the statistics for the training data was also used to assess the accuracy of the classification. The statistic are usually organized for each training area. The covariance statistics evaluates the correlation between the values of different bands and were adequate for the study.

The areas covered by each class of the LULC shows that urban land occupies 36.52% which represent 506896km2 of landmass of the overall LULC while the least class is the sand class followed by water body, these feature classes occupies landmass of 13080km2 and 14000km2 respectively. The overall classification accuracy determined is 83%. The Table of LULC classification of Anambra State, area occupied in km2 and percentage occupies by the various classes is shown in Table 4.1 (**Table 2**).
