Land Use/Land Cover Change (LUCC) analysis in relation to Wildlife distribution

Introduction

This project was a bachelor's thesis and it aimed at investigating the effects of urbanization on the wildlife habitat.

Vegetation within Nairobi National Park consists of open grasslands with scattered low trees and Ngong’ forest on the elevated terrain in the west.

It plays a host to a wide variety of wildlife including the endangered black rhinos, lions, leopards, cheetahs, hyenas, buffaloes (four of the ‘Big Five’).

Data processing

The main data used was the Landsat 7 and 8 satellite imagery (optical). Three images acquired in 2006, 2011, and 2016 were used.

The data processing and land cover analysis was carried out in ERDAS IMAGINE and mapped in arcGIS.

Normalized difference vegetation index (NDVI)

Normalized difference vegetation index (NDVI) which was important to assess the amount of vegetation cover over the area or interest, was obtained by use of ERDAS IMAGINE.

NDVI For all the years considered during the study i.e. 2006, 2011 and 2016 was carried out and the difference is obtained through comparison of high and low values on the legend. The results are as shown below

Series of normalized difference index images for 2006, 2011 and 2016 mapped in arcGIS.

Supervised classification

With the training data, I carried out supervised classification on ERDAS IMAGINE.

The land cover training data were used to determine the signatures before the classification.

The maximum likelihood algorithm was applied in the classification

Series of supervised classified images for 2006, 2011 and 2016 mapped in arcGIS.

By using supervised classification, it was shown that forest and grassland has reduced while urban area and shrubland has increased.

Unsupervised classification

The unsupervised classification unlike the supervised did not use the training sites. Instead, the pixels were grouped automatically according to the common pixels.

This classification though did not recognize the water class, so it was classified into six classes

Series of unsupervised classified images for 2006, 2011 and 2016 mapped in arcGIS.

By using supervised classification, it was shown that forest and grassland has reduced while urban area and shrubland has increased.

Accuracy Assessment

The classified images both from supervised and unsupervised needed to be assessed for accuracy before being used for decision-making.

Accuracy assessment under the classification tool in the supervised option in ERDAS was used. Random points were created in the classified image of interest.

75 points were added, and out of those points, the ones with unclassified (0) were queried out using the criteria option.

From the accuracy assessment and the analysis, the supervised classification had better results.

Series of accuracy assessment tables for 2006, 2011 and 2016

Wildlife Distribution

One of the factors that affect wildlife distribution is vegetation cover because of plant-animal relationship. Different animal species depend on vegetation cover for food and shelter. The animal species also need water for survival.

Urban development is a major form of human disturbance affecting the distribution of suitable habitat and species.

The wildlife distribution were mapped on ArcGIS using the data collected from KWS.

The animal species in different zones in the park has been represented in pie charts.

There is a relationship between the change in wildlife distribution in the park with the change in land cover in and around the park. For example, the coke’s hartebeest in zone N1 did reduce drastically due to the reduction in the grassland in that zone.

Series of wildlife distribution respresentation for 2011 and 2016 mapped in arcGIS.

It’s evident that Nairobi National Park and its surrounding is going through changes and for both classifications shrubland is increasing and animals are changing their location

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