1. Introduction
Deforestation and forest degradation are among the major global challenges contributing to biodiversity loss and climate change. At the same time, forests are relevant for human well-being, particularly in many countries of the Global South, where local communities are directly dependent on the benefits of forest ecosystems, including the provisioning of timber and non-timber products, as well as many regulating services, such as flood protection and climate regulation. Addressing deforestation is therefore not only relevant to Sustainable Development Goals (SDGs) 15 (Life on land) and 13 (Climate Action) but to the sustainability agenda overall. The drivers of deforestation and forest degradation can be diverse and variable in different local contexts [
1,
2]. However, one of the main drivers of deforestation in many parts of the world, in particular in forests with high biodiversity value in the Global South, is agricultural expansion [
2,
3]. In the context of agricultural expansion, commercial agriculture stands out as the main driver of deforestation in the Americas, while both subsistence and commercial agriculture are the main drivers of deforestation in Africa and tropical Asia [
2,
3].
Similar to other tropical countries, deforestation in Myanmar has been driven by agricultural expansion due to commercial commodity production (e.g., rubber and oil palm), as well as subsistence agriculture (i.e., shifting cultivation and small-scale agricultural encroachment by farmers) [
4,
5,
6]. According to the existing Myanmar Forest Law (2018), forests may only be used for non-timber collection, and the establishment of new settlements and farming are strictly prohibited in state forests [
7]. The Forest Department, under the Ministry of Natural Resources and Environmental Conservation (MoNREC), is responsible for enforcing and monitoring this law [
7], but poor governance, an unstable political situation, corruption, poverty and population growth have limited the effectiveness of this law, leading to continued high levels of deforestation due to agriculture, even in state-managed forests [
4,
6]. Furthermore, conflicting interests between the Ministry of Agriculture, Livestock and Irrigation (MoALI), which supports an increase in arable land, and the MoNREC, which aims to reduce deforestation and expand forest lands, undermine coherent intervention efforts. Once a forest land title is converted into an agricultural land title and subsequently managed under the MoALI, the land title change becomes practically irreversible, and the Forest Department loses the right to intervene, e.g., through reforestation. Therefore, agricultural expansion in state forests has been a serious threat to the forests of Myanmar, causing permanent deforestation.
While the Myanmar Forest Department is dedicating intensive efforts to expand state forests to meet the target of 30% of the country’s area as mentioned in the nationally determined contributions submitted to the UNFCCC, many conflicts between the land use rights of farmers and the interests of forest conservation have become apparent, leading to intensive debates in parliament between 2010 and 2013 [
8]. To resolve this conflict, the government issued a policy intervention in 2013 that includes instructions to survey encroached areas in state forests, degazette established paddy fields from forest to agriculture and reforest rainfed agricultural areas through agroforestry community forests [
9].
Despite the promotion of agroforestry community forests for reforestation on agricultural land, these efforts have fallen short of expectations, as highlighted by San et al. (2023) [
10], who conducted the only study reported to date on the effectiveness of the policy on agricultural encroachment of forests in Myanmar. The importance of monitoring and evaluating policy implementation for effective forest management has been highlighted in many previous studies [
11,
12]. However, given the limited availability of financial and human resources, monitoring agricultural encroachment in forests and evaluating the effect of forest policies pose significant challenges [
13,
14,
15]. To overcome the challenges associated with the need for substantial investment of manpower and money for effective monitoring, remote sensing has been proposed as a cost- and time-effective tool for sustainable forest management [
16]. Blackman (2013) also suggested remote sensing as a low-cost method to conduct ex post analysis of forest policies [
12].
However, its limitations lie in its ability to capture context-specific explanations and social issues crucial for refining policies and their implications [
17]. To address this shortcoming, Ishtiaque et al. suggested the integration of remote sensing techniques with social science methodologies as a promising approach to deal with social challenges in forest management [
18]. In order to evaluate the effectiveness of the policy intervention in changing the behavior of farmers, social data including the reasons for increasing or decreasing encroachment activities and farmers’ perceptions are therefore necessary to provide a deeper comprehension. The usefulness of the integrated approach in forestry research has also been demonstrated in previous studies [
19,
20].
Hence, in this study, we intend to analyze land cover change and agricultural encroachment dynamics before and after the policy intervention to evaluate its effectiveness at the landscape level. The study provides a holistic and thorough evaluation of the policy related to agricultural encroachment in the state forests of Myanmar at the landscape scale. We apply an integrated approach using a land cover change analysis based on remote sensing techniques together with social data analysis, including a survey of local farmers. The results of the study have the potential to contribute to the effective monitoring and management of agricultural encroachment in Myanmar, as well as other tropical countries facing similar challenges and constraints.
3. Results
3.1. Land Cover Classification and Accuracy Assessment
The land cover classification results for 2010, 2015 and 2020 can be seen in
Table 2 and
Appendix B.
Figure A1a–c. The accuracy assessment of classified land cover reveals high overall accuracy values of 95.0, 95.5 and 93.4 for 2010, 2015 and 2020, respectively. The average producer and user accuracy for each land cover class for each year and their standard error can be seen in
Table 2.
According to the land cover classification results, most of the study area was covered by forests, other wooded lands and agriculture land, while water bodies and other land cover occupied only a small proportion of the study area. The area of water bodies slightly increased between 2010 and 2015 due to the construction of a new dam (see
Figure A1a,b). Apart from that, water bodies did not show significant changes between 2015 and 2020. Other land cover classes, including settlements, roads and bare land, covered only a small area, ranging between 0.3% and 0.4% throughout the entire ten-year (2010–2020) study period. Therefore, only land cover changes among forests, other wooded lands and agriculture are highlighted in
Section 3.2.
3.2. Comparison of Land Cover Changes before and after the Policy Intervention
The total forest area in 2010 was 62.8%, and it declined continuously throughout the whole study period: down to 58.2% and 51.9% in 2015 and 2020, respectively (
Figure 3). Before the policy intervention, the annual rate of forest loss was −1.5% and, afterwards, increased to −2.28% per year. If we analyze the net forest loss by different land covers before the policy intervention, the major net forest loss was caused by a shift to agriculture rather than a shift to the other wooded lands. Contrarily, after the policy intervention, the amount of forest loss to other wooded lands was considerably higher than forest loss to agriculture (
Figure 4 and
Figure 5).
Before the policy intervention, other wooded lands decreased from 25.6% to 23.4% of the study area, with an annual rate of decrease of −1.78%. In contrast, after the policy intervention, other wooded lands increased considerably to 25.1% of the study area, with an annual increase rate of 1.46%. As previously mentioned, the major increase in other wooded lands areas was due to a large area of forest land cover loss to other wooded lands.
In 2010, the total agricultural area covered 9.5% of the study area and increased in 2015 and 2020 to 14.5% and 18.5%, respectively. During the first five years (2010 to 2015), the annual rate of agricultural expansion was 8.58%. After the implementation of the policy in 2015, this expansion continued but at a lower annual rate of 4.9% until 2020.
Overall, we found that the net forest loss to agriculture reduced after the introduction of the policy compared to the period before the policy (
Figure 4 and
Figure 5). We also found that a large area of other wooded lands was converted to agricultural land, resulting in a high net loss of other wooded lands to agriculture after the policy implementation. We found a comparable increase in agricultural land between the two study periods but with different dynamic land use change patterns (
Table A2 and
Table A3). The net conversion of forest to other wooded land, which includes heavily degraded forest, immature forest plantations and fallow forests, increased up to 282 km
2 after the policy implementation and was significantly higher than before (
Figure 4). An overview of the detailed land use changes between categories over the two time periods can be seen in
Figure 4 and
Figure 5 and
Table A2 and
Table A3.
Change detection analysis revealed that areas of forest other wooded lands gained from agriculture were partly from the areas cleared for Taung-ya forest plantation establishment, where farmers grow crops between newly planted trees for the first 2–3 years. Furthermore, the analysis detected areas of small-sized agricultural land that were reforested during both study periods.
Throughout the study periods, we found other wooded lands in buffer areas between forests and agriculture areas, and agricultural expansion occurred mainly in those areas according to change detection analysis. It seems that after establishing agricultural fields, encroaching farmers degraded the surrounding forests over time and changed the forests to other wooded lands. In both study periods, the expanded agricultural areas were mostly clustered in small, sparse patches (less than 15 ha) that are likely to be expanded by small-scale encroaching farmers. We also observed a large clearance (greater than 60 ha) of forests and other wooded lands for forest plantation establishment.
3.3. Questionnaire Survey Responses
3.3.1. Household Characteristics, Livelihoods and Farming Practices
The average age of the interviewed farmers was 50 years, and the average agricultural area per household was 4.5 ha, indicating small-scale and subsistence farming. On average, a household consisted of five persons, out of which three were family workers. The average annual income was USD 2465. The main crops grown in the study area were sesame, rice and groundnuts in the rainfed upland areas and rice in the valley areas, which are often near streams among the hills. Out of the surveyed households, around 92% had been farmers since their first settlement in the forest. The occupations of the other 8% of respondents included government plantation workers, government staff, daily workers and bamboo harvesters, later changing their occupation to farmers.
During the field survey, it was found that 95.2% of total households (n = 291) practiced permanent agriculture, including bush fallow systems in their claimed farmland, while 3.1% practiced both permanent and shifting cultivation. No households were found to practice only shifting cultivation. The remaining 2% of households were no longer farmers and relied on off-farm income sources. Among the households practicing permanent agriculture during the field survey, 14% were originally shifting cultivators, and 2% were Taungya plantation farmers who switched to permanent agriculture and settled in villages within state forests between 2005 and 2020 while the rest practiced permanent agriculture since their first settlement. Shifting cultivators changed their practices for various reasons, such as a lack of areas for shifting cultivation because of occupation by private companies to establish plantations (32%) or due to population growth (16%); decisions to settle in a village instead of moving around for personal reasons such as marriage, getting old or limited labor capacity (29%); instruction from the Forest Department’s to stop cutting down the forests (18%); and an informal demarcation of farmland in the surrounding areas (5%).
3.3.2. Previous Land Cover and Origin of Encroached Farms
The majority of farmers (45%) reported that they cleared already degraded forests to establish their agricultural fields. According to their general shared perception, a degraded forest is a forest that has been used for harvesting multiple times and consists of few and low-value tree species with a noticeably reduced density. Around 3% of farmers received land from the government as a special arrangement for old government plantation workers. Around 52% of the farmers either inherited or bought land from other farmers. Regardless of the illegal status of the encroached farms, the existence of an informal market for transfer land was observed. Around 25% of farmers expanded their agricultural land by cutting down the forest around their farms after buying or receiving the land as an inheritance.
3.3.3. Farm Size Dynamics and the Effect of the Policy Intervention
Among all households, for the majority of farmers (54%, n = 158), the farm size had not changed since their initial settlement. However, 40% (n = 116) of households expanded their agricultural area after settlement, while the other 6% (n = 17) had reduced their farm size in 2020 compared to their initial farm size.
Among the 40% of households that increased their farm size, 17% expanded their farms annually, while 23% expanded their farms only once in specific years (
Figure 6a). Most farmers responded that expansion occurred between 2005 and 2020. Some farmers (
n = 18) responded that they expanded a long time ago (before 2005) and could not remember the specific year. Therefore, they were categorized together as having expanded before 2005. The most frequent expansion years after 2005 were 2010 and 2015 (
Figure 6b).
Most farmers (91%, n = 265) responded that the policy intervention in 2013 did not affect their farm expansion behavior or farm size changes. A few farmers (5%, n = 14) said that they expanded their encroached agricultural land by clearing the nearby degraded forest to claim more areas as their land because of the policy intervention. The remaining 4%, (n = 12) mentioned that they started demarcating already encroached areas as their property after the policy intervention was initiated.
3.3.4. Factors Affecting Settlements and Agricultural Encroachment
We collected information related to the perception of interviewees on settlements and land use dynamics due to farmland encroachment in their surrounding areas between 2010 and 2020. As two farmers refused to respond, we were able to gather information about the perceptions of 289 farmers.
First, we asked farmers whether the policy intervention had the intended effect of decreasing the number of settlers and the encroachment area or if the policy intervention was instead working as an incentive for encroachment behavior and settlement. The majority (97%, n = 281) of farmers perceived that the policy did not reduce the amount of agricultural encroachment or the number of settlers in the study area. Only 3% (n = 8) indicated that some farmers had stopped farming in their surrounding areas as an effect of the policy intervention. The majority (93%, n = 270) of farmers said that the policy intervention, particularly the establishment of agroforestry community forests, did not incentivize or attract other farmers to move into the forests and did not cause more encroachment. The rest (around 7%, n = 19) of the interviewed farmers perceived a minor increase in new farmers in the area, who immigrated due to the policy intervention. In conclusion, the intervention was not seen as directly affecting encroachment.
Secondly, we asked the interviewees which other factors, apart from the policy intervention, might be affecting settlement and agricultural encroachment, starting with factors that increased the number of settlers and encroachment, followed by other factors that decreased settlement and encroachment. Among the total respondents, the majority (87%,
n = 253) responded that they were not aware of other factors, while 12% (
n = 36) named different factors causing increases in agricultural encroachment and the number of settlers between 2010 and 2020. These mainly included socioeconomic factors; like livelihood needs and poverty, the availability of marketable non-timber forest products and job opportunities; social factors entailing immigration due to marriage; and an increase due to improved accessibility because of road construction (
Figure 7).
On the question of which other factors might have led to a decrease in encroachment and settlers, 82% (
n = 236) of farmers replied that they were not aware of any, whereas 18% (
n = 53) named other reasons besides the policy intervention. These included the establishment of commercial forest plantations by private, governmental or unspecified actors. They explained that the establishment of these plantations often led to a situation where farmers had fewer opportunities to encroach on surrounding areas or even became landless. This practice of land grabbing led to farmers’ out migration or changes in livelihoods (
Figure 8).
3.3.5. Forest Department’s Monitoring and Law Enforcement of Agricultural Encroachment
We also found that the majority of farmers were not aware of any Forest Department law enforcement related to agricultural encroachment. The majority (around 90%) of interviewees responded that the Forest Department did not monitor their agricultural encroachment status after conducting the encroachment survey according to the policy intervention. Only 10% (n = 30) mentioned that the Forest Department followed up with them after recording their encroachment status and warned them not to increase the farmland area by encroaching into the forested land. However, even if they did, none of them experienced any legal action taken by the Forest Department.
5. Conclusions
In this study, we demonstrated the benefits of integrating remote sensing techniques and questionnaire surveys in monitoring agricultural encroachment in forests and assessing the outcome of the applied policy. Based on the remote sensing analysis, we were able to reveal the dynamics of land cover and land use change, especially in the context of agricultural encroachment. Using the interview results, we were able to explain the driving factors behind these dynamics and the outcomes of the policy intervention. We showed that using remote sensing data to monitor the status of agricultural expansion in forests is an effective strategy for Myanmar and other countries with limited human and financial resources, while a social survey provides policy makers with information crucial for policy modification. Furthermore, we provided an overview of the outcomes of the forest policy intervention covering a large area of forest landscape. We concluded that the policy intervention (2013), established and designed by the Forest Department to reduce agricultural encroachment, did not lead to a decrease in deforestation nor a decrease in encroachment. In order to decelerate smallholder agricultural encroachments in forests in Myanmar and other countries with similar issues, we suggest prioritizing the protection of degraded forests in the buffer areas between agriculture areas and forests to stop agricultural expansion. Farming rights should be strictly linked with the responsibility to protect nearby forests to prevent further encroachment. During the social survey, we observed forest plantation establishment as a factor limiting available encroachment areas in the study area. However, it should be noted that this also is likely to lead to land use conflicts with local communities or cause the migration of farmers into other areas, which might also be forests with an even higher ecological value. An explicit land use map that distinguishes between areas managed by the Forest Department and other governing bodies is highly advised. The implementation of a combination of remote sensing and community-based monitoring, coupled with meticulous participatory planning, could be a promising system to surmount the resource constraints in monitoring agricultural expansion within forested regions.