1 Introduction

Forest deterioration is one of the world’s most serious environmental problem [1, 2]. Agriculture is putting more strain on forest resources to feed the world’s rapidly growing population [3, 4]. The spread of cultivated land into forest land, timber and charcoal production, and wood harvesting are the main causes of deforestation in developing countries [5]. Ethiopia, like other developing countries, experienced a rapid decline of forest cover due to agricultural encroachments, overgrazing, and settlements [6, 7]. For instance, forest cover of the country declined from 35% in early twentieth century to 2.4% in 1992[8]. Recently, the government of Ethiopia is reporting the increasing trend of forest by implementing afforestation and re-afforestation programme. The declining of forest resources increased the removal of top soil through erosion which may results in agricultural yield reduction and exposed the agrarian communities to food insecurity.

Forests play a critical role in managing climate change by absorbing carbon dioxide and alleviating global climate change [4]. In spite of forest role in climate change mitigation, Ethiopia lost roughly 141,000 hectares of forest (1.1%) per year between 1995 and 2010 [9].

Mapping of land use/land cover (LULC) is helpful to assess the extent and rate of change over a given period of time [4, 5]. Monitoring of LULC change is critical important to understand what has been lost so far to design appropriate land use planning and management. For instance, forest cover change detection provides vital information for effective forest management [10]. Several studies have been conducted on LULC change analysis in different parts of the country [11,12,13,14]. The evolution of geospatial technology allows the users to collect spatial data and use it for analysis, modeling, simulation, and geo-visualization. This technology is very crucial to provide a baseline information for decision and policy makers. Geospatial technologies can acquire data, store, analyze and visualize spatial data in maps, graphs or tables. However, little is known about the status of LULC change in the southwestern parts of Ethiopia in general and the Geba watershed in particular. Thus, this research will provide a baseline information for LULC change monitoring in the study area. The high demand for more agricultural land led to forest encouragement and utilization of hilly areas that significantly affects the micro-climate and accelerate soil erosion which in turn to declines of agricultural yield [15]. Thus, it is good to analyze LULC change over the southwestern parts, which will be used as a baseline information for further studies and policy makers. The rest of the paper is organized as follows. Section 2 presents materials and methods; Sect. 3 present results and discussion and Sect. 4 concludes the paper with sort of recommendation.

2 Methods and materials

2.1 Description of the study area

Geba watershed is located in upper Baro river basin, which is located between 7° 53′ 30″ to 8° 44′ 30″ N and 35° 19′ 30″ to 36° 14′ 30″ E. Administratively, Geba watershed is found in Ilu Aba Bor Zone of Oromia National Regional State, in southwestern part of Ethiopia. The elevation of the study area ranges between 2582.5 m and 798.9 m above the mean sea level (Fig. 1). Geba watershed cover an area of 4805.3 km2.

Fig. 1
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Location of the study area: Geba watershed-Geba River Sub-basin

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Based on Food and Agriculture Organization (FAO) soil data, there are seven types of soil in the Geba watershed which includes calcic xerosols, dystric gleysols, dystric nitisols, eutric cambisols, leptosols, orthic acrisols, and orthic solonchaks. Among all soil types dystric nitisols is the most dominant soil types, which covers about 2380.1 km2 followed by dystric gleysols (1185.6 km2) and eutric cambisols (1015.7 km2).

Broad leaf montane forest, wood land, cultivated land and water bodies are the major land use types in the study area. Rapid population growth, deforestation driven by agricultural expansion, forest exploitation for firewood, house construction and furniture’s are the major problems that affects the LULC change in southwestern parts of Ethiopia [16]. The climate of the study area is largely characterized by tropical highland humid zones and received unimodal rainfall brought by wind from Indian and Atlantic Ocean with maximum rainfall during summer season (June to August) [17, 18].

The rain-fed agriculture is the major form of crop cultivation in the study area. Teff, maize, sorghum, barley, millet, sesame, groundnut, coffee, hose bean, and pea are the major known crops cultivated in the study area. Similarly, fruit and vegetables such as mango, papaya, citrus, onion, potato, garlic, and carrot cabbage are some of the major cash incomes for the rural household in the study area.

2.2 Data sources

2.2.1 Remote sensing data acquisition and processing

Landsat images from 1990, 2003, and 2020 were utilized to analyze the spatiotemporal LULC change in the Geba watershed. ERDAS Imagine 2015 software is used to process the Landsat images. The study area LULC types were classified over three years (1990, 2003, and 2020) using a supervised classification method with a maximum likelihood algorithm [19, 20] to accomplish spatiotemporal LULC changes. For LULC classification, Landsat TM 1990, Landsat ETM + 2003, and Landsat OLI/TIRS 2020 were utilized (Table 1; Fig. 2). We use the Landsat images in the month of January to avoid the impact of cloud cover on image quality. Moreover, we perform image pre-processing techniques.

Table 1 Remote sensing data used in the study
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Fig. 2
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Methodological flowchart for the determination of LULC change

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The year 1990 is considered the starting point for LULC analysis due to its historical moment in the Ethiopian government structure. It was the last year of the Darge regime in the country. The year 2003 was chosen because of the mass resettlement programme by the Ethiopian government in response to drought. Finally, the year 2020 was chosen to assess changes in forest cover over the last three decades. In the present study, 20 training areas were taken from dense forest, open forest, agricultural land, and water body, while 30 were taken from settlement land cover class.

2.2.2 Land use land cover analysis

We classified the LULC of the study area into five major classes such as dense forest, open forest, agricultural land, settlement, and water body based on their dominance (Table 2).

Table 2 Descriptions of LULC classes used in the study area
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2.3 Classification accuracy assessment

The overall accuracy index [21] is calculated by dividing all properly identified pixels by the total number of pixels in the matrix (Eq. 1). The kappa coefficient measures the degree of agreement between two maps when all elements of the error matrix are taken into account (Eq. 2).

$${\text{Overall\,accuracy}}\,=\,\frac{\text{Sum}\,\text{of}\,\text{the}\,\text{diagonal}\,\text{elements}}{\text{Total}\,\text{number}\,\text{of}\,\text{accuracy}\, \text{sites}\,\left(\text{pixels}\right)}\,\times\,100$$
(1)
$$\text{K}\text{a}\text{p}\text{p}\text{a} =\frac{\text{O}\text{b}\text{s}-\text{e}\text{x}\text{p}}{1-\text{e}\text{x}\text{p}}$$
(2)

where: Obs is it represents accuracy reported in error matrix (overall accuracy) and Exp is it represents correct classification.

2.4 Spatio-temporal land use land cover change detection

The amount of changed area and extent of change should be examined to identify the magnitudes of change in terms of forest cover change [22]. Furthermore, the percent of change and rate of change were computed (Eq. 3) to show the magnitude of the changes between two periods [4, 23,24,25].

$$Rate\,of\,change \left(\frac{km2}{year}\right)=\frac{A2-A1}{Z}$$
(3)

where A2 is an area of LULC (km2) in time 2, A1 is an area of LULC (km2) in time 1; Z is Time Interval between A2 and A1 in years.

The technique of post-classification was used to detect LULC change [26]. The LULC change matrix was created to show the overall LULC change between 1990 and 2020.

3 Results and discussions

3.1 Analysis of land use land cover change (1990 to 2020)

Landsat imagery of thematic mapper 1990, enhanced thematic mapper plus 2003, and operational land imager 2020 were utilized to analyze the spatiotemporal LULC changes. The study area LULC is classified into five categories: agricultural lands, dense forest, open forest, settlement, and water body. The dense forest cover in the study area is substantial declined during the study period. Due to the increase of agricultural land, the area of dense and sparse forests has reduced. From 1990 to 2020, agricultural land and settlement land cover classes increased, while dense forest, open forest, and water bodies decreased. The LULC conversion, such as dense forest, open forest, and water bodies being converted to agricultural land and settlements, at Geba watershed [15]. Because of rapid population growth, people are forced to convert dense and open forest to agricultural land.

The forest cover has diminished in most parts of Ethiopia due to human activities [27]. Numerous research have confirmed the declining of forest cover in Ethiopia [11,12,13,14, 28, 4] claimed that in the Komto forest protected area. Human activities reduced the forest cover of the Geba watershed, owing to agricultural expansion into forest land, the manufacturing of charcoal, the collection of firewood, and the spread of human habitation into the forest, which resulted in the construction of shelter from forest products. Other LULC types, such as agricultural land and settlements, have increased in the study area, while dense and open forest have decreased (Fig. 3).

Fig. 3
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LULC map of 1990, 2003, and 2020

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The dense forest dominated the Geba watershed in 1990, covering 2129.2 km2 (44.3%), while agricultural land, open forest, water bodies, and settlement covered 1786.6 km2 (37.2%), 841 km2 (17.5%), 41.8 km2 (0.9%) and 6.5 km2 (0.1%), respectively. This result is similar with [4] findings in the Komto forest protected area, which show a loss in forest cover over the last three decades. The areas of agricultural land and settlement had expanded by 6.6 km2 (41.8%) and 16.1 km2 (0.3%) by the year 2003, respectively. The coverage of dense forest, open forest and water bodies was reduced by 41.9%, 750.5 km2 (15.6%) and 20.5 km2 (0.4%), respectively. This result is consistent with [3]. Similarly, in 2020, the area of dense forest and open forest was reduced by 1127.8 km2 (23.5%) and 457.2 km2 (9.5%), respectively, while the covering of agricultural land and settlement was increased by 3163.2 km2 (65.8%) and 37.3 km2 (0.8%). We discovered that agricultural land is highly increased at the expense of dense forest and open forest, as well as other LULC, over the last three decades in the study area, based LULC change assessment (Table 3).

Table 3 LULC areas in 1990, 2003 and 2020
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With kappa values of 0.86, 0.82, and 0.85, the total classification accuracies for the study periods of 1990, 2003, and 2020 were 86.3%, 84.8%, and 87.6%, respectively. A kappa score of larger than (>) 0.80 (80%) indicates a significant agreement, while a value of between 0.60 (60%) and 0.80 (80%) indicates a substantial agreement [29].

3.2 Rate of land use land cover change

From 1990 to 2020, the density of dense forest, open forest, and water bodies dropped at rates of 33.4 km2/year, 12.8km2/year, and 0.7 km2/year, respectively. Since the economy of the study area is depend on agriculture, there is overexploitation of dense and open forests for agricultural production to feed the rapid population growth. Thus, the rapid population growth is one of the main driving forces for the declining of forest resources that negatively affect the forest ecosystems. Over the last 30 years, agricultural land and settlement have grown at rates of 45.9 km2/year and 1km2/year, respectively (Fig. 4). According to our findings, forest cover in the Geba watershed has been quickly declining, which is consistent with earlier research [4, 13, 14, 30]. Similar to forest resources, waterbodies are also experienced a declining trend. In the last 30 years, almost 50% of water bodies has lost due to environmental modification and unwise use of water bodies. The use of irrigation technologies also contributes for the declining of water bodies in developing countries. The declining of rainfall due to loss of vegetation and the increasing of temperature which lead to evapotranspiration may contributes for the loss of water bodies over the study period. The declining of water resources may affect the agricultural yield and set back economic development of a nation [31, 32].

Fig. 4
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Forest cover map of 1990, 2003 and 2020

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The dense forest and open forest are declined by 1001.4 km2 and 383.8 km2 from 1990 to 2020, respectively. The rapid loss of foresee ecosystems requires sound polices to sustain the existence of forest in agriculturally based economy. On the other hand, agricultural land and settlement land cover classes are increased by 1376.7 km2 and 30.8 km2, respectively over study period (Fig. 5). The agricultural and settlement land cover classes are increasing on the expense of forest resources. This observed change indicates a reduction in forest cover and an increase in agricultural land and settlement land cover classes. Our result is consistent with previous study by [4] who reported that both dense and open forest declined Komto protected forest priority areas in east Wollega zone in Ethiopia. The declining of forest resources may lead to climate change that negatively affect the water quality and availability. The declining of forest resources can raise the surrounding temperature. The increasing of temperature could result in excess evapotranspiration, which may affect water availability and agricultural production in the region [33]. Water availability are the most significant constraining factors for agricultural production due to water scarcity [34].

Fig. 5
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Trends of LULC in the study area

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In the Geba watershed, the primary LULC is shown (Fig. 6). From 1990 to 2020, 647 km2 of dense forest and 750.4 km2 of open forest are converted to agricultural land, respectively. The loss of vegetation has a negative impact on environmental conservation. The declining of forest resources by agricultural expansion aggravates the problems of soil erosion in developing countries [35]. The declining of forest cover accelerated soil erosion, which cases food insecurity in developing countries requires policy interventions. From 1990 to 2020, 2855.2 km2 remained unchanged in all LULC categories. The results are presented in detail in (Table 4).

Table 4 LULC conversion from 1990 to 2020
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4 Conclusions

Geospatial technologies are used to examine LULC change in the present study. The LULC classes of the study area are classified using three years of Landsat imagery. Our results found that there is a rapid conversion of LULC change particularly the forest cover substantial declined over the study period, which might alter the microclimate and affect community livelihoods. The study’s findings suggest that forest cover area has decreased significantly over the last three decades. Results of this study show that a total of 1001.4 km2 and 383.8 km2 of dense forest and open forest are lost, respectively during the study period. In contrast, agricultural land and settlement land cover increased by 1376.7 km2 and 30.8 km2, respectively between 1990 and 2020. Agricultural expansions, timber production, charcoal production, firewood collection, and built-up area expansion are the main driving factors of LULC change. The deterioration of forest cover change, increasing of agricultural land and settlement land cover may increase the land surface temperatures and climate change which requires stakeholders’ intervention to minimize the potential impacts. Finally, policy intervention specifically, reforestation, afforestation, and community awareness are required to protect and wise use of natural resources (Fig. 6).

Fig. 6
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LULC conversion from 1990 to 2020

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