Spatial Analysis of the Effect of Land Cover Changes on the Socio-Economic Population in Parakansalak District, Sukabumi Regency

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Tropical Environments) Tropical Environments)

Volume 5 Number 2 Article 4

12-1-2021

SPATIAL ANALYSIS OF THE EFFECT OF LAND COVER CHANGES SPATIAL ANALYSIS OF THE EFFECT OF LAND COVER CHANGES ON THE SOCIO-ECONOMIC POPULATION IN PARAKANSALAK ON THE SOCIO-ECONOMIC POPULATION IN PARAKANSALAK DISTRICT, SUKABUMI REGENCY

DISTRICT, SUKABUMI REGENCY

Taqyudin Taqyudin

Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia Chairun Nisa Efendi

Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, chairun.nisa@ui.ac.id

Supriatna Supriatna

Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia Ratri Candra Restuti

Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia

Follow this and additional works at: https://scholarhub.ui.ac.id/jglitrop Part of the Geography Commons

Recommended Citation Recommended Citation

Taqyudin, Taqyudin; Efendi, Chairun Nisa; Supriatna, Supriatna; and Restuti, Ratri Candra (2021) "SPATIAL ANALYSIS OF THE EFFECT OF LAND COVER CHANGES ON THE SOCIO-ECONOMIC POPULATION IN PARAKANSALAK DISTRICT, SUKABUMI REGENCY," Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments): Vol. 5: No. 2, Article 4.

Available at: https://scholarhub.ui.ac.id/jglitrop/vol5/iss2/4

This Research Article is brought to you for free and open access by UI Scholars Hub. It has been accepted for inclusion in Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments) by an authorized editor of UI Scholars Hub.

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Journal homepage: www.jglitrop.ui.ac.id http://dx.doi.org/10.7454/jglitrop.v5i2.162

Spatial Analysis of the Effect of Land Cover Changes on the Socio-Economic Population in Parakansalak District, Sukabumi Regency

Taqyudin¹, Chairun Nisa Efendi¹, Supriatna¹, Ratri Candra Restuti¹

1Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia

E-mail: chairun.nisa@ui.ac.id

Received: 02 July 2021; Accepted: 23 December 2021; Published: 30 December 2021

Abstract. Many land changes have occurred in Indonesia, especially in developing areas, so those rural areas can turn into urban areas. These changes can be felt directly by the community and have an impact on the social economy of the surrounding population. The importance of knowing the social and economic conditions of the community to know the conditions of regional development. Therefore, this study aims to determine changes in land cover in 2014-2020 and their effect on the social economy of the population in Parakansalak District. This research uses a descriptive quantitative method with spatial and statistical analysis in it. The techniques used in data collection were questionnaires, interviews, and observations, while the data processing techniques used the Google Earth Engine platform, ArcGIS software, Excel, and SPSS. The results of the study showed that changes in land cover partially affected the socio-economic status of 51%, with the most affected being jobs and incomes of residents in the Parakansalak District.

Employment is affected by 68% and income is affected by 71% of land cover changes. The land cover that changed the most was agricultural land in Bojonglongok Village and Parakansalak Village. Therefore, the occupations of the surrounding residents also changed, such as some residents becoming traders, landlords, ranchers, teachers, and so on, and eventually, it also affected their income.

Keywords: Land cover changes, socio-economic, effect, Google Earth Engine, Parakansalak District.

1. Introduction

In the current era where technological developments are growing rapidly along with the development of a region. The development of an area contributes to changes in other aspects, such as social, economic, and even the land itself. Land is the physical material of the earth's crust that supports all life because it includes parts of the systems in it (Wahyuni et al 2014). Since the first land has an important role that can help improve people's lives. Many changes in land cover have occurred in Indonesia, especially in areas that are under construction, so those rural areas can turn into urban areas.

Changes in land cover are conditions of land that are different from before and occur in space and time due to interactions between environmental and human dynamics that have been recorded on land in the community (Briassoulis, 2020). One of the areas where land cover changes occurred was in North Bogor District due to population growth, land demand increased. Therefore, agricultural land is decreasing and built-up land is increasing due to development (Sulikawati et al., 2016).

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Coverage is a biophysical cover on the earth's surface that can be observed and is the result of regulation, activity, and human treatment carried out on certain types of land cover to carry out production, change, or maintenance activities in that area (National, B. S., 2014). Land cover changes can occur due to human activities. However, if the conversion of paddy fields occurs, it will have an impact on regional food security in the future. Furthermore, this transformation also has implications for the loss of multi-function rice fields, both in the socio-economic aspects of the community, such as job creation, poverty alleviation, and rural development (Fitri et al., 2022). However, there may still be positive impacts from changes in land cover.

It is important to know the social and economic conditions of the community to know whether the area is fully developed or not. Not only the government but also the people. In measuring the socio- economic conditions of the community, Soekanto's theory, 2009 (Jaya et al., 2020) states that the most important factors in assessing the socio-economic conditions of the community are employment, education, income, and wealth ownership. Based on previous socio-economic research (Kullo et al., 2021) quantitative methods are used to measure the socioeconomic population.

The area in Parakansalak District in 2014 was still filled with vegetation land, but over time there was development in the area. Only in some parts, there is built-up land, which is increasingly spreading, or there is new built-up land that replaces vegetated land. One method for monitoring land cover change data is the remote sensing method (Zurqani et al. 2019). Based on previous research (Fikri et al, 2021) the use of the Google Earth Engine platform can be a fast way to process land cover data. Therefore, in this study, we will discuss how land cover changes and its impact on the socio-economic population of Parakansalak District whose socio-economy is measured by the variables of livelihood, education, income, and land ownership as socio-economic measurements in society.

2. Materials and Methods 2.1. The Study Area

Parakansalak is one of the districts in Sukabumi Regency, West Java Province. This district is located at coordinates 106˚40'58" - 106˚43'51" E and 6˚44'25" - 6˚48'42" S with the position of the area at an altitude of 500 m - 750 m above sea level. In terms of regional layout, Parakansalak District is bordered to the north by Bogor Regency. Then in the south by the District of Bojonggenteng, east by the District of Cidahu, and west by the District of Kalapanunggal.Parakansalak District consists of 6 villages, namely Bojongasih Village, Bojonglongok Village, Lebaksari Village, Parakansalak Village, Sukakersa Village, and Sukatani Village.

There are roads in every village in Parakansalak District, but in the northern part of Parakansalak District there are not many roads that can be seen on the map in Figure 1. This is because the northern part of Parakansalak District is forests and oil palm plantations, so access roads it's hard to get there. In general, the topography of the Parakansalak District consists of plains, hills, and mountains, with a slope between 0-3% which can be said to be flat, then the land is relatively waving with 3-8%, land with a slope of 15-25% which means it is rather steep and > 40% indicates steep and mountainous land.

The Parakansalak area has different types of land, such as rice fields, plantations, and settlements.

However, based on BPS Parakansalak District (2020) the main potential in Parakansalak District is in the agricultural sector.

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Figure 1. Map of Research Locations in Parakansalak District (Source: Data Processing, 2022).

2.2. Data Collection

This study focuses on residents affected by land cover changes in Parakansalak District. The influencing factor is socio-economic which can be measured by profession, education, income, and land ownership of residents in the district. This can be seen in Figure 2 which shows the flow of thought from land cover taken from 2014 to 2020 and the socio-economic status of the population. For the land cover, a land cover classification system will be used based on the National Standardization Agency (National, B. S., 2014). The end of this research is how the relationship and influence between land cover and socio-economic population.

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Figure 2. A Research Framework

The workflow of this research begins with the preparation stage which can be seen in Figure 3, beginning with looking at the problems that occur in the environment. Then it is matched with some of the literature or previous research that has been done. If it is felt that the research can be carried out, it can be determined the title, the area to be studied, and what variables will be used for the research. By looking at the socio-economic side, it is necessary to collect data directly (primary) from residents around the sub-district. This research also collects secondary data using literature study and interpretation: various kinds of data are needed to support the research, such as collecting land cover data using satellite imagery via Google Earth Engine.

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Figure 3. A Research Workflow

Primary data collection was carried out directly in the field using questionnaires, interviews, and observations. The questionnaire is a data collection technique that is done by giving a set of questions or written questions to respondents to answer (Sugiyono, D., 2013). Furthermore, there is an interview technique, which is a method of collecting data by meeting two people to exchange information and ideas through question and answer, so that meaning can be constructed in a particular topic. Then according to Widoyoko (2014: 46) observation is a systematic observation and recording of the elements that appear in a symptom in the object of research.

2.3. Data Processing

After collecting secondary and primary data, then proceed with the processing of existing data. The data processing must be sourced from the existing data collection. Based on Table 1, there is a list of data, sources, and processing tools that will be used in this study. Land use in this study uses the Google Earth Engine platform from the initial process of collecting satellite image data to becoming a land use map. While the primary data in the form of data on livelihoods, education, income, and land ownership obtained from the questionnaire were processed using Excel and SPSS software.

Table 1. Table of Research Data

Data Data Type Data Source Processing Tools Data

Administrative Boundary

Secondary Geospatial Information Agency

ArcGIS

Profession Primary Questionnaire SPSS dan Excel

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Data Data Type Data Source Processing Tools Data

Income Primary Questionnaire SPSS dan Excel

Education Primary Questionnaire SPSS dan Excel

Land Ownership Primary Questionnaire SPSS dan Excel

Land Cover Secondary Landsat 8 Image Data Google Earth Engine

2.4. Data Analysis

In this study, quantitative analysis methods are used which are classified as structured using statistical tools or data that have all been collected, so that during data processing, if there are problems, the main solution is to change the formula or pay attention to the calculations that are correct or not and do not need to take samples again. The quantitative statistical analysis used in this research is simple linear regression analysis. A simple linear regression equation is an equation model that describes the relationship of one independent variable/predictor (X) with one dependent variable/response (Y), which is usually described by Equation 1 (Yuliara, I. M., 2016).

𝑌̂ = 𝛼 + 𝑏𝑋 (Equation 1.)

Where: 𝑌̂ is a variable response, 𝛼 is constant, b is regression constant (slope), and X is the independent variable (predictor).

In addition to the statistical analysis, spatial analysis is also used which adds the dimension of space (space). In this study, spatial analysis is useful for analyzing land cover changes in Parakansalak District with the overlay method. The type of overlay used is a union or merging of 2 maps without eliminating the data on the map. After a statistical and spatial analysis has been carried out, it will be analyzed by describing all existing results to obtain answers to research questions as they are without intending to make conclusions that apply to the public or generalizations.

3. Results and Discussion

3.1. Land Cover Changes in Parakansalak District 2014-2020

This study analyzes land cover through the Google Earth Engine platform using supervised classification. The accuracy test has been carried out on the map which can be seen in Table 2, the accuracy value in 2014 was 84% and in 2020 it was 79%. This level of accuracy already meets the standard because it is above 70% (Purwadhi, 2001). In the year 2014, forest classification had the largest test value. This may be because when digitizing forest classifications, multiple samples and more detail are used so that the sample points match the field data.

Table 2. Table of Confusion Matrix and Accuracy for Land cover in 2014 and 2020 through Google Earth Engine.

Classification Classification Results Year 2014 Classification Results Year 2020

Agriculture 77 0

Forest 1591 0

Open Shrubland 0 223

Urban Land 22 128

Built-up Land 7 57

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Classification Classification Results Year 2014 Classification Results Year 2020

Water 19 19

Total pixels 1716 427

Total samples 2029 535

Overall Accuracy 0,845736816 0,798130841

84,57% 79,81%

Source: Data Processing, 2022

Then, in 2020, the smallest test value is in the classification of agriculture and forest. This may be because the sample points of agriculture and forest do not match their classification so during testing the accuracy of many sample points does not match the field data. In addition to using the Google Earth Engine, direct validation has also been carried out in the field to match the map with the actual situation in Parakansalak District. Therefore, land cover maps can be used for analysis in this study.

The image data used to be processed into maps is the Landsat 8 TOA Reflectance Image in 2014 and 2020. The results of processing the image data through the Google Earth Engine can be seen in Figure 4 below. Based on the map results, it can be seen that there are changes in forest land, expanding urban land, and built-up land that began to appear in Parakansalak District in 2020. When there is a change in land cover, old land (e.g. agricultural land) can be reduced because it is used for new land (such as urban land), so agricultural land seems to decrease and urban land seems to increase. Even though the land does not increase or decrease, only rotation or land cover changes occur. More details can be seen in Table 3.

After seeing the addition or subtraction of the land, it can also be seen the location of the changed land location by doing an overlay analysis with the union technique. Based on Figure 4, it can be seen that the northern part of Parakansalak District has only slightly changed, so it can be said that the forest there is still maintained, preserved, and not converted. Then, it can also be seen that in almost every village there has been a change in land cover from 2014 to 2020, either from agricultural land to urban land or to built-up land.

Table 3. Table of Land Cover Change Area from 2014 to 2020

Land Cover

Area (Ha) Changes in Total

Land Area Year 2014 Year 2020

Agriculture 1388,51 1098,53 - 289,98

Forest 1104,02 1173,58 + 69,56

Open Shrubland 616,609 764,58 + 147,971

Urban Land 526,58 570,66 + 44,08

Built-up Land 10,45 57,27 + 46,82

Water 59,306 40,83 - 18,476

Source: Data Processing, 2022

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Figure 4. Land Cover Maps 2014 and 2020 (Source: Data Processing, 2022).

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If you look at Figure 5, in the southernmost part, there is a red color that indicates urban land. This explains that there has been a change in land cover from previously agricultural to urban land. The area is located in the village of Bojonglongok, so it is possible that the village is being developed to make it better than before. Then look at the center to the east, there is Parakansalak Village where there is also a change in the land cover into urban land and agriculture. The village in the east previously had a lot of open shrublands, but in 2020 it has changed with some urban land and some agricultural land. This change was proven by some information from respondents who said that previously the area was open shrubland and then many migrants built houses so that they became urban land.

Figure 5. Map of Land Cover Changes in Parakansalak District (Source: Data Processing, 2022).

3.2. Respondent's Demographics

Based on data obtained directly from the field through questionnaires and interviews, it was found that respondents were on average natives of Parakansalak District. With an age range ranging from 20 - 70 years for elderly people. The data collection of this research is also spread out so that the data on where elderly peoples live also varies from village to village. There are several professions of respondents, such as traders, teachers, and breeders. The respondents were found to live in Jalan Kampung Sirna, Kampung Sindang, Kampung Cikupa, Kampung Lemah Dubur, Kampung Nangeweh, Kampung Silingke, and many more.

3.3. The Effect of Land Cover Change on Education

Land cover changes in Parakansalak District need to be tested for linear regression with the education in the district. This educational data is obtained from respondents' information based on their knowledge. The results of the regression test in Table 4 show that the p-value (sig) was 0.45, which

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means it is greater than 5% alpha or 0.05. In addition, judging from the R Square the value is 0.058, which means that the change in land cover only contributes 5% to the education of the population.

Table 4. Results of the Strength Model and Educational Linear Regression Test

Model Summary Coefficients

Independent

Variable R R

Square

Adjusted R Square

Std.

Error of the Estimate

Unstandardized Coefficients

Standardized Coefficients

t Sig.

B Std.

Error Beta Land Cover

Change 0.240 0,058 -0,037 15,927 0,423 0,541 0,240 0,782 0,452 Source: Data Processing, 2022

Thus, it can be stated that education is not affected by changes in land cover in Parakansalak District. These results are contrary to previous research (Sarwendami, 2018) which says that the existence of a higher education area can have a positive impact on the economic condition of the community or the income felt by the community. Even though education in the district is not affected, according to one respondent, if there is a change in land that supports the increase in educational land, it can improve education in Parakansalak District. It was also said in previous research (Andari et al., 2018) that changes can also occur in the value of education where people have different views on sending their children to school after the shift from paddy fields to industrial land has a positive impact.

3.4. The Effect of Land Cover Change on Profession

The types of professions of the populations in Parakansalak District are different, but most of them are farmers. If we look at the data collected, there are also types of work for teachers, traders, breeders, and even those who don't even work, such as housewives. Based on the information from the respondents, it was found that the work data carried out by the linear regression test were as follows.

Table 5. Results of the Strength Model and Profession Linear Regression Test

Independent

Variable R R

Square

Adjusted R Square

Std.

t Sig.

B Std.

Change 0.829 0,688 0,657 9,167 1,462 0,311 0,829 4,694 0,001 Source: Data Processing, 2022

Judging from the results of the strength of the model in Table 5, the value of R Square is 0.688 or which means that the change in land cover accounts for 68% of the population's employment. Then, as seen from the regression test, the p-value (sig) is 0.001 which means it is smaller than 5% alpha or 0.05.

Therefore, it can be said that the profession of the population is affected by changes in land cover in Parakansalak District. This is related to previous research (Londar et al., 2016) which said that the increase in land use was followed by changes in community livelihood patterns. Then, these results are also in line with previous research (Sofyan et al., 2013) which says that the conversion of agricultural land has an effect on the livelihoods of local people, especially those who work in agriculture, turning into non-agricultural fields.

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Besides that, the information obtained related to this work is that several residents feel the negative impact of land changes. This is because in the past the land used to be rubber and tea many elderly people were employed to harvest the produce, but after the land was converted into oil palm the elderly people became unemployed because of their limited age to be able to work. However, some elderly people mention that they have had a positive impact from land changes because they feel that there is development, such as the increasing number of urban land and built-up lands, so that there are more job vacancies and opening up land, such as renting, will be more profitable at this time.

3.5. The Effect of Land Cover Change on Income

The income earned will certainly be related to the type of work done. The better the work done, the higher the probability of earning. This can also be proven by the results of the regression test between changes in closing and income. Based on the results of the SPSS in Table 6 below, it can be said that changes in land cover have an effect of 71% on the income of residents in the Parakansalak District.

This is also supported by the p-value (sig) which is 0.001 which means it is smaller than alpha 5%, so it can be concluded that the income of the population is influenced by changes in land cover.

Table 6. Results of the Strength Model and Income Linear Regression Test

Independent

Variable R R

Square

Adjusted R Square

Std.

t Sig.

B Std.

Apart from the results of the regression test, there is also information from respondents there who say that there is a change in income, as previously the income from working in rubber and oil palm production is slightly different where oil palm production is more profitable because of the faster harvest time. The respondent's jobs as a trader also feel the negative impacts, where when there is a change in the land she has to work to trade near the oil palm fields. However, the number of buyers is relatively small due to the infrequent number of people who pass the road.

3.6. The Effect of Land Cover Change on Land Ownership

Ownership of wealth or facilities is ownership of valuable items that have a high value in a household (Kurnianto, 2017). Land ownership in this study is private and can be used freely by the owner.

Although land ownership has a high value, if an individual owns the land and wants to change the type of land, it will not have much effect on the surrounding population. This can also be seen in the following linear regression test in Table 7.

Table 7. Results of Model Strength and Land Ownership Linear Regression Test

Independent

Variable R R

Square

Adjusted R Square

Std.

t Sig.

B Std.

Error Beta

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Land Cover

Based on the results of the regression test in Table 7, it can be seen that the p-value (sig) is 0.27, which means it is greater than 5% alpha, so it can be said that land ownership is not affected by changes in land cover. Although privately owned land is not affected by land changes, land owned by a state or company or a certain party can be affected by land changes. For example, there is a change in plantation land which is now owned by Korea and then leased, so that it cannot be used directly or purchased by the community. This is also related to the strength of the model on R Square which means that land cover changes have a 15% effect on land ownership.

3.7. The Effect of Land Cover Changes on the Socio-Economic of the Parakansalak District Population After previously analyzing the spatial changes in land cover and statistical analysis of each data on education, profession, income, and land ownership, the next step is to analyze the socioeconomic population in Parakansalak District. This socio-economic description is a description of the condition of the population in Parakansalak District based on education, profession, income, and land ownership.

Based on the results of the regression test through SPSS in Table 8, it can be seen that the p-value (sig) is 0.009, which means it is smaller than alpha 5%, so it can be said that changes in land cover have an influence on the socioeconomic population in Parakansalak District. Looking at the magnitude of its power, changes in land cover affect its socio-economic status by 51%. It was found that half of the 100% was related to socio-economic measurements that had been analyzed previously. The linear regression test is used again to find out how much influence it has on the socioeconomic population of the population.

Table 8. Results of the Strength of the Model and the Population Socio-Economic Linear Regression Test

Independent

Variable R R

Square

Adjusted R Square

Std.

t Sig.

B Std.

The change in land cover partially affects the socio-economic community, or more specifically only affects the profession and income of the population in Parakansalak District. This is also supported by information obtained from respondents who stated that there were land changes that occurred in Parakansalak District, such as in Bojongasih Village there was a change from rice fields to Korean state- owned industrial factories that produced beauty drugs. This job change also has the effect of an increasing number of job vacancies for young people who have just graduated from school, but fewer vacancies for adults due to the limited age in working in the factory. Therefore, unemployment for elderly people can also increase.

Some of the land covers that turned into settlements and built-up lands had an impact on residents.

Residents there feel as if the economy is spinning, although the negative impact is very clear, some

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residents think their economy is more profitable after a change in land cover. This is because the more urban land there is, the more buyers there will be for traders. Then, there is also one resident who supports the development, so he feels that the change in land cover can improve the economy. Residents who did get a decent job before and after the change, felt the positive impact of the change because their income was increasing.

In addition to the impact on the economy, land cover changes also have an impact on the social community. According to several residents in Parakansalak District, changes in land cover resulted in an increase in population density and more immigrants living in the district. With the increasing number of immigrants, they can make social changes, such as behavior in society. The manners of native people will be different from that of immigrants, so it can be one of the concerns for residents to be able to socialize with each other. If longer immigrants are more than the natives, the possibility of a loss of indigenous culture can also occur. Therefore, immigrants must participate in preserving the original culture in the area.

Another impact felt by residents due to land cover changes is that the environment also changes.

The meaning of the environment is that previously the temperature was cool because there were plantations, now it is hotter because it has turned into urban lands. Then, some residents regret the change to oil palm because of the lack of water needs, then many animals around them also die. If this environmental damage is not balanced with revitalization, it can continue to cause disasters that have never happened before.

4. Conclusion

Land cover in Parakansalak District experienced a difference between 2014 and 2020, namely forest land changed slightly, decreasing agricultural land, expanding urban land, and built-up land that began to appear in Parakansalak District in 2020. After a linear regression test, it was found that land cover changes had an effect on the social economy of the population in Parakansalak District by 51% and the rest was influenced by other things. This is because humans and the environment cannot be separated, and humans will try to adapt to their environment. Therefore, if the environment changes, humans will also change. This land cover change affects the income and profession of residents in the district, where the positive impact is that there are more job vacancies and the negative is that there are elderly people who are unemployed because of the age limit for these job vacancies. With the effect on work, the income earned also has an effect. Meanwhile, education and land ownership are not directly affected by changes in land cover because they have little impact.

In addition to the impact on the economy, land cover changes also have an impact on the social community, such as their behavior and culture. This is because the more immigrants, the population density will increase and the behavior and culture of the immigrants will be different from the original population. Then, other impacts, namely the environment can be damaged or can cause disaster if it is not balanced with the preservation and revitalization of the land change. In this study, the results showed that there were many changes in agricultural land, so that the work of the surrounding population also changed, such as being traders, rented owners, livestock, teachers, and others. Thus, it can be said that the socio-economic population in the district has not been fully evenly distributed because land cover changes only have an impact on certain parties or community groups.

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