DETERMINATION OF FACTORS RESPONSIBLE FOR THE CHANGE IN VEGETAL COVER IN KATSINA TOWN

The study examined the factors responsible for change in vegetation cover between 1999 and 2019. Decadal data for climatic variable (rainfall and temperature), Landsat satellite images and population data of 1999, 2009 and 2019 were used. Land use/Land cover Change Detection, linear time series and Spearman rank order correlation analysis were used. The results revealed that the extent change between (1999-2009) and (2009-2019) for built-up, vegetation and bare surface were; (+91.66, +276.41), (-4.06, -40.42) and (-27.44, 23.5) respectively. There were increasing trends in the built-up environment, population growth and rainfall at the rate of (19.3 km per-), (110116 persons per-) and (231.5mm per-) respectively. There were decrease trend of temperature and vegetation cover at the rate of (-1.15C per-) and (-19.3 km per-) respectively. Negative relationship exist between population growth (r = -0.938), built up (r = -0.987), rainfall (r = -0.982) and vegetation cover, while positive relationship exist between temperature (r = 0.965) and vegetation cover. The study conclude that temperature is the major factor influencing the loss in vegetation cover, rapid population growth and urban expansion were experienced during the study period. The study recommend five (5) trees should be planted per built-up structure in order to create more carbon sink and to improve vegetal resource which were affected by human activities and changing climatic variables.


INTRODUCTION
Urban vegetation are affected by both natural and anthropogenic factors. The natural factors include changes in the climatic variable such as rainfall, sunlight and temperature while the anthropogenic factors include increase in human population, industrialization and urbanization which were influenced by natural increase in population and migration. Combination of these factors simultaneously affect the health, quality and distribution of vegetation in the urban environment. Urban vegetation is affected by many factors, which include; climate, biophysical feature of soil, anthropogenic disturbances (Huang, Xu, Yang, and Shi, 2009). According to Idris et al (2019) human activities changes the natural state of the environment into different forms which include; Settlement, Urbanization, Industrialization. Growing population is unconnected to some environmental challenges (Maier, 2015) and negative relationship between increase in population and environmental degradation (Okechi, 2017). United Nation, (2007) projects that by the year 2050, over 70% of the human population will be living in urban environment. More than 54 % of the world's total population were living in cities, and an estimated 66 % of them will occupy urban centers by the year 2025 (UN 2014) after Shirazi, and Kazmi, (2016). The urban population growth in Nigeria has change from less than seven (7%) urban in the year 1931 to (42 %) in the year 1991 which is projected to reach (61.6 %) by the year 2025 (Onibokun and Faniran, 1995) after Gadiga and Galtima (2017).
Continuous decrease in vegetative/green cover in cities were due to rapid population growth and consequent urbanization which took over green areas and agriculture lands (Shirazi and Kazmi, 2016). The natural increase in birth rate and migration stimulate growth of population in urban centers because of better social amenities, infrastructures and availability of industries which attract increase in population (Kane, 2018). Due to growing population, more urban infrastructure need to be put in place to meet the growing population at the expense of the natural vegetation. Urbanization affect the ecological processes, local climate and human health in urban areas by changing the vegetation phenology (Ren, He, Huang, and Zhou 2018). Spatial distribution of the major vegetation types at the global scale is influenced by climate, and its effect varies at the regional scale (Brovkin, 2002).Temperature is an important factor affecting vegetation phenology. The variation of the same species is influence by uneven distribution of temperature (Huang et al., 2009). Moderate increase in temperature result to increase in vegetation density and carbon sequestration potential (Bachelet, Neilson, Lenihan, and Drapek, 2001).
The inter-dependency between vegetation and climate in subtropical deserts and semi deserts is a function of precipitation. The amount of precipitation received and surface albedo determines the vegetation cover and bare surfaces (Brovkin, 2002). The effects of climate change on vegetation is as a result of the changes in rainfall, temperature, microbial activities, nutrient cycles and changes in precipitation affects the moisture regimes (Ali, 2012).
Rapid population growth and changes in climatic variables are FUDMA Journal of Sciences (FJS) ISSN online: 2616-1370ISSN print: 2645-2944Vol. 4 No. 3, September, 2020, pp 636 -644 DOI: https://doi.org/10.33003/fjs-2020  The resulted impact include increase in temperature, decrease in rainfall, loss of floral, drought and sometimes heavy rainfall will cause flooding and stunted plants. The study aims at assessing the factors responsible for the change in vegetal cover in Katsina urban area.

Study Area
Katsina town is located between latitude 12˚08' N and 10˚19'N of the equator, and longitude 7˚32'E and 7˚51'E of Greenwich Meridian Figure 1. Katsina town is capital of Katsina state. The town has a total population of 222,644 National Population Commission, (NPC, 2006). The vegetation was largely modified because of many years of bush clearing/burning, cultivation and fuel wood extraction. The town is characterized by both hot and dry seasons. The temperature here average is 26 o C and the annual rainfall average is 600mm.The rainfall last for six (6) month which starts around May to October, and dry seasons usually occur November to April (Olofin, 2014). The economic activities of the people include: Trading, Farming, Welding, livestock Rearing, Carpentry, and Civil Servants. However, there are quite a number of economic activities such as blacksmith, laborers, food vendors, tie and dye and other technical activities that serve as economic base of the people. annual rainfall, temperature, population, build up and vegetation cover. In order to identify variation within the trends, both annual rainfall and temperature from (1984 -2014).

Yt = a+ bt+et …………………………………………………………(1)
Where Yt= the amount of rainfall a = intercept b= slope, which measures the rate of change of the variables with time t et= random error component The Spearman's rank order correlation coefficient (r) was used to determine the trend of the linear time series analysis either it is upward or downward. It is computed as: ……………………………………………… (2) Where (r) is positive, it indicate upward/increasing pattern and where (r) is negative, it indicates downward/ decreasing pattern of the time series. Spearman's correlation analysis was also used to determine the relationship that exist between change in vegetation cover which is (Dependent Variable) and factors influencing vegetation change which include; population, rainfall, temperature and built up areas as (Independent Variable).
Ground trothing exercise was first of all conducted to collect coordinate (x and y) data of the area using Handheld GPS in the study area. Two set of satellite images ( The two (2) methods NDIV and NDVI were used because NDVI is best for vegetation and bare surface studies while NDBI is best used for build-up studies. The outcome for both NDVI and NDBI were merge in to one image for each year and rescaled using geometric method. The results obtained were overlay to determine the extent of change for the variables under investigation for the study periods.
Landsat 7: NIR stands for band 4 and RED stands for band 3, while Landsat 8: NIR stands for band 5 and RED stands for band 4.
NDVI ranges from 0 to 1. SWIR: Shortwave Infrared which stands as band 5 on Landsat 7 while band 6 on Landsat 8. Maximum Likelihood algorithm were used to classify the images into three (3) classes (Built-up Areas, Vegetation, and Bare surfaces). Erdas Imagine 2014 and ArcMap 10.3 were used in carrying out the analysis. Finally field validation exercise was carried out.

RESULTS AND DISCUSSION Land Use /Land Cover Change Detection
The trend/changes of land use / land cover in Katsina town for the period of 20 years (1999-2019) is presented in (Table 1). The built up area have increase due to population growth. The vegetal cover which serves as resource to man have been cleared for different purposes such as industrial, residential, educational, recreational and administrative purposes. In the year 1999, the over lay results revealed that built-up environment, vegetal cover and bare surface occupies 111.2 km 2 , 126.41 km 2 and 142.10 km 2 with their respective percentages (29.3%), (33.3%) and (37.4%) respectively of the total classes (Table 1) and (Figure 2). This may be due to the fact that population pressure was not high then.  (2020) However, in 2019 there was a great decrease in vegetation covers to 81.93 km 2 (12.6%) and there was rapid growth in built up areas with 479.27 km 2 (73.5%) while the bare surface decrease to 91.16 km 2 (13.9%) (Figure 4). This occurred due to tremendous increase in population growth which is estimated to be 488,150 persons. These populations exert pressure on vegetal resources especially the construction of basic and social facilities such as road, power station, health centers, recreational centers, religious, commercial, educational, administrative centers in the study area.
Furthermore, the continuous exertion of population pressure on vegetal covers result to the loss of carbon sinkers which helps to in regulating of air cycle. These may create room for generating more greenhouse gases (carbon dioxide) that are on the increase in the atmosphere and leading to global warming which subsequently results to climate change due to alteration of the climate system by man. There is a decreasing pattern of decadal mean temperature at the rate of (-1.15 o C per -10 ) and the coefficient of variation was (97%) presented in (Figure 6). This result was in line with the findings of Bello, Adebayo and Bashir (2020) predicted a decadal decreasing trend of temperature in Billiri. There was a decadal increasing trend of rainfall at the rate of (231.5mm per-10 ). The coefficient of variation is (93.8%). This relate with the findings of (Abaje Achiebo and Matazu , 2018) observed increasing trend of rainfall in Kaduna metropolis, and also (Bello et al., 2020) report an increasing trend of rainfall in Gombe town. This implies that the increasing rainfall in Katsina metropolis is in line with the current trends of rainfall within the urban centers. There is decadal increase in the buildup environment is at the rate of (19.3 km 2 per-10 ) and the coefficient of variation is (98.7%) while the decadal pattern of vegetation cover shows a decreasing trend at the rate of (-19.3 km 2 per-10 ) and the coefficient of variation is (98.7%). If the present trend continues, vegetation cover will decrease by (-193 km 2 ) and the built-up environment will increase by (193 km 2 ) in the next decade.
Similar findings like (Maina, et al., 2017), (Nwaogu, et al., 2017) and (Okosun, 2018) report that built up areas were increasing while vegetal cover were decreasing. The vegetation cover in Katsina town is decreasing as result of increase in built up environment and climatic factors.

Relationships between Climatic Factors (Rainfall and Temperature), Anthropogenic Factors (Build up and Human Population) and Vegetation Cover
The decadal data for population growth, temperature, rainfall, vegetation cover and built-up environment for the study period were presented in (Table 2). This data were used for the correlation analysis.   Table 3 provides the correlation coefficient of decadal rainfall, temperature, built up area, population and vegetation for the study period.  (2020) The correlation analysis between change in vegetation cover and population reveal that there is a very high negative relationship of (r = -0.938) between them and the P-value is (0.226), this information imply that there is not significant relationship between them. This result does not agree with the result of (Tobar, 2012) report that increasing population density trends have a strong direct correlation with natural environments (bare surface and vegetation) and (Jiang et al., 2017) noted that increasing population have a significant negative correlation with vegetation cover.
A very high positive relationship exist between change in vegetation cover and mean annual temperature (r = 0.965), the P-value is (0.170), this means there is not significant relationship between them. There is a very high negative relationship between vegetation and annual rainfall totals is (r = -0.982), while the P-value is (0.121) which is not significant at 5%. The relationship that exist between buildup area and the vegetation cover is (r = -0.987) which is (very high negative) and the P-value is (0.101) meaning not significant at 5%. From the results of correlation analysis obtain, temperature is the major factor in influencing the change in vegetation cover. This result is in line with the findings of (Huang et al., 2009) noted that temperature affect the distribution of vegetation and Awuh et al., (2019) report that strong relationship exist between builtup and Temperature while Leilei, Jianrong and Yang, (2014) noted that vegetation has a greater correlation coefficient with rainfall than Temperature.

CONCLUSION
The study conclude that Katsina metropolis is experiencing rapid growth in human population and urban expansion per decade. Climatic variable (temperature) is the major factor influencing decline in vegetation cover. Increase in human population and human activities like urbanization have tendency to affect urban vegetation.

RECOMMENDATION
The study recommend that government should create shelterbelts/ forest reserved around the study area and enforce environmental laws regarding vegetation within the urban center. Trees should be planted around every buildup structure within the urban center in order to create more carbon sink and improve vegetal resource which was affected by human activities and changing climate.