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Vegetation Changes in Some Areas in Taif Province and Their Relationship with Some Climatic Factors

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Vegetation Changes in Some Areas in Taif Province and Their Relationship with Some Climatic Factors EurAsian Journal of BioSciences Eurasia J Biosci 14, 7181-7186 (2020) Vegetation changes in some areas in Taif province and their relationship with some climatic factors Abdul Arhamn Saeed Al- Hajar 1, Amal Ahmed Mohammed Al-Ghamdi 1*, Mona Abdulaziz Labeed Al-Malki 1, Haifa Mohammed Al-Nofaie 2, Rahma I Alshamrani 1, Fayza Ahmed Saleh Al-Zahrani 2 1 Department of Botany, Faculty of Biological Science, King Abdulaziz University, P.O. Box 35009, Jeddah 21488, Jeddah, Saudi Arabia 2 Department of Geographic Information Systems, Faculty of Social Science, Jeddah University, Jeddah, Saudi Arabia *Corresponding author: [email protected] Abstract Background: Different factors affect vegetation changes in all areas. Pointing out the climate factors is an important issue when considering vegetation. Methods: In Taif province, we studied the vegetation changes in Al-Hada and Al-Shafa areas in the period from 2000 to 2018. The correlation between vegetation and climate factors in the previously mentioned areas has been studied in spring. Results: Using NDVI images, we found that the highest coverage was in 2013 with 11.23% in Al- Hada area, while the lowest coverage was in 2018 with 3.48% in Al-Shafa area. The information about the climate factors was obtained from NOAH model data from NASA Global Land Data Assimilation System with spatial resolution (1.0º and 0.25º). We found that temperature and rain precipitation had the greatest impact. Conclusion: The results indicated that this method had the potential to be a useful guide to identify the impact of these two factors on the vegetation in this area. Keywords: Al-Hada, Al-Shafa, climate factors, NDVI, vegetation, temperature, precipitation Al- Hajar AAS, Al-Ghamdi AAM, Al-Malki MAL, Al-Nofaie HM, I Alshamrani R, Al-Zahrani FAS (2020) Vegetation changes in some areas in Taif province and their relationship with some climatic factors. Eurasia J Biosci 14: 7181-7186. © 2020 Al- Hajar et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License. INTRODUCTION NDVI = (NIR-RED)/(NIR+RED). NIR and RED point to the red and near-infrared electromagnetic spectra which Vegetation means the growth of plants in any area. are reflected from the object on the Earth’s surface (Nie The study of vegetation changes and processes is et al., 2012). The NDVI and GIS data help us understand known as the vegetation dynamics. The study of the changes of vegetation dynamics and the effects of vegetation can be explained and understood within the the climatic factors on these changes (Hou et al., 2011). ecological framework. Each factor in the ecosystem may Moreover, shedding light on these correlations assists in affect the plants coverage. Whatever is the type of the understanding the mechanism ecosystem and its ecosystem, the vegetation is the obvious physical responses to climate (Yang et al., 2012). Various representation of it, and this vegetation is the base of methods are used to unveil vegetation dynamics from classification of the ecosystem because it is the result of multi-temporal data including (i) statistical approaches, primary production and the organisms depending on it (ii) time series analysis, (iii) spectral-frequency for the food supply chain. The climatic factors play a techniques, and (iv) wavelet decomposition (Yang et al., major role in shaping the plants coverage in any area, 2012). whether it is desert or forest (Kent, 2011). The remote sensing studies in Saudi Arabia do not The vegetation maps have been utilized in order to cover all the country. Actually, they are less than we help us understand the patterns of vegetation which are need. However, Alwashe and Bokhari conducted a study directly used as data for managing natural resources with a main objective to monitor the vegetation coverage and supporting the environmental policymaking in Al-Madinah region using Landsat thematic mapper decisions through analyzing these patterns along with data (Alwashe & Bokhari, 1993). In 2017, a paper was spatial data in a GIS (Franklin, 2013). It will be difficult to monitor the changes that occur in the vegetation dynamics without remote sensing technologies (Hou et Received: September 2019 al., 2011). By using NDVI, we can study vegetation Accepted: March 2020 coverage and growth basically through the formula of Printed: December 2020 7181 EurAsian Journal of BioSciences 14: 7181-7186 (2020) Al- Hajar et al. Fig. 1. Location map shows the location for each area with borders within longitude and latitude. published by Hereher and Abdullah who discussed the 40°19’88″-40°18’29″ E with an elevation of 2200–2500 variations in rocky types in Aja complex using Landsat 8 m above sea level and an area of 5.15 Km². data (Hereher & Abdullah, 2017).(Li, J., Garshick, E., Al- Climate Data Hemoud, A., Huang, S., & Koutrakis, 2020) (Mohammed In the current study, we utilize the NASA Global Land & Algarni, 2020)(Alharthi et al., 2020)(Arshad, Eid, & Data Assimilation System (GLDAS-2). The Noah model Hasan, 2020) these are the articles that discussed NDVI contains 36 parameters and 1.0º resolution, with and vegetation in Saudi arabia. On the other hand, there monthly temporal dataset. We choose the parameters of are plenty of studies that investigate the vegetation rain precipitation rate, total precipitation rate, and coverage from a floristic perspective (El-Ghanim et al., temperature for the years of 2000, 2007, 2013, and 2010; Khalik et al., 2013; Osman et al., 2014; Al-Mutairi 2018, which are then represented on statistical graphics. et al., 2016; Al-Robai et al., 2017). NDVI Data The aim of the current research is to establish a In order to study the state of vegetation in Al-Hada decision support framework for a point source and Al-Shafa regions, the researcher relied on the relationship between vegetation and climate factors on satellite data of Landsat and analyzed the spectral Al-Hada and Al-Shafa areas which will also aid in response of the vegetation during the study period observing the vegetation diversity and plants through applying the Normalized Difference Vegetation communities’ structure and dynamics. Index (NDVI) for all the years under study. The NDVI was designed to exclude the impact of the soil on the MATERIALS AND METHODS group of energy reflections from the plant (Al-Ghamdi, Study Area 1996). The purpose of using this indicator is to extract Al-Shafa and Al-Hada are the study areas (Fig. 1), only the vegetation from the set of geographical which are located in Makkah region, Taif province. Al- phenomena in the two study areas, as it is more like a Hada lies between 21° 22’ 66″-21° 20’ 77″ N and selective process of the plant only. In order for the 40°17’74″-40°15’86″ E 20 Km northwest Taif city with an researcher to calculate the land occupied by the plant in elevation of 2000 m and an area of 18.36 Km². The the two study areas, this indicator is calculated by climate is temperate in summer and cold in winter; the dividing the energy reflection difference from the near rain season is in spring and winter. Al-Shafa is 25 Km infrared and infrared bands by the sum of the reflections southwest Taif city between 21°4’95″-21°3’64″ N and of the rays of the same two previous bands as follows: NDVI = (NIR - Red)/(NIR + Red). 7182 EurAsian Journal of BioSciences 14: 7181-7186 (2020) Al- Hajar et al. Table 1. Area of vegetation in Al-Hada and Al-Shafa regions during the years of 2000, 2007, 2013, and 2018 Total ratio of 2000 2007 2013 2018 Study area study Plant Plant Plant Plant Area ratio Area ratio Area ratio Area ratio area/Km² area/Km² area/Km² area/Km² area/Km² Al-Hada 18.36 1.33 7.2 1.6 9 2.1 11.4 1.8 10 Al-Shafa 5.15 0.5 10 0.2 4 0.5 10 0.2 4 Table 2. Rates of rain precipitation, temperature, and area of vegetation in Al-Hada area Years Rain precipitation mm/day Temperature rate/Cº Plant area/Km² 2000 0.6 21 1.3 2007 0.08 15 1.6 2013 1.55 21 2.1 2018 2.16 21 1.8 Table 3. Rates of rain precipitation, temperature, and area of vegetation in Al-Shafa area Years Rain precipitation mm/day Temperature rate/Cº Plant area/Km² 2000 0.6 22 0.5 2007 0.08 15 0.2 2013 1.55 21 0.5 2018 6.99 22 0.2 Mathematical Methods Analysis of the Relationship between The vegetation coverage changed between the Vegetation and Climatic Elements years of 2000 and 2018, and the percentage was used Climatic factors directly affect the state of the natural to compare between the results of the NDVI. By vegetation. The rain is the most obvious factor among all calculating the total vegetation area and comparing with other climatic factors in its direct impact on the natural rain precipitation and temperature, we identified the plant condition in terms of the amount of land it covers, pattern through which we can visualize the relationship given the stability of the impact of other soil-related between the climate factors and vegetation coverage. factors. The scarcity of rain and the fluctuation of its Converting Methods precipitation are observed in the limited vegetation The GLDAS data for precipitation was in Km m-2 s- spread on the surface of the soil. In addition, its 1, and in order to fully understand this data, we convert distribution may be concentrated on the flood areas of this to mm/day by using the following: the valleys and the areas of convex areas or parts that Kg m-2 day-1 = Kg m-2 s-1 ×86400 are lower than neighboring areas.
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