IJERD – International Journal of Environmental and Rural Development (2020) 11-1

Research articleerd

Impact of Forest Cover Change in Phnom Kulen National
Park on Downstream Local Livelihoods along Siem Reap
River, Cambodia
OUM SOMALY*Royal University of Agriculture, Phnom Penh, Cambodia
Email: oumsomaly@gmail.com / osomaly@rua.edu.kh

NOPHEA SASAKI
Asian Institute of Technology, Bangkok, Thailand

SOK KIMCHHIN
Royal University of Agriculture, Phnom Penh, Cambodia

TAKUJI W. TSUSAKA
Asian Institute of Technology, Bangkok, Thailand

SANGAM SHRESTHA
Asian Institute of Technology, Bangkok, Thailand

NEANG MALYNERoyal University of Agriculture, Phnom Penh, Cambodia
Received 31 January 2020

Accepted 10 April 2020(*Corresponding Author)

Abstract National parks play important roles in the conservation of biodiversity,
environmental protection, and provision of resources for local livelihoods. This research aims
at examining the effect of forest cover change in Phnom Kulen National Park (PKNP) onwater quality and downstream local livelihoods along the Siem Reap river. Forest coverchange in the park was collected from the United States Geological Survey from 2000 to2016 through the Multi-Temporal Satellite Imagery (MTSI). The study used livelihood
approach to interview with 120 households and four key-informants to elicit local perceptions
on effect of forest lost on their livelihoods. The research found the forest cover in PKNP
decreased by 22% from 2000 to 2016. The loss of forest cover has affected downstream local
people whose daily livelihoods depend on Siem Reap River. Scores on local perceptions werelow. Livelihood capital were performed low; only 0.48 score on natural capital, 0.44 score
on human, and 0.24 score on financial capital, in which correspondent perceived theirlivelihood did depend significantly on those capitals. However, we found that the physicaland social capitals were not significantly affected by the forest cover change because forest
clearing created stable access to infrastructure and social network. As forest cover declined
impacted on the declined of crop production, fish availability, water quality and access toclean water. As local needs to adopt new skills for living, human and financial capitals werelow. The study confirmed the forest cover change at national park had a serious impact on
the downstream local livelihoods.
Keywords Phnom Kulen National Park, forest cover change, sustainable livelihoods
approach, upstream-downstream issue, perception analysis

INTRODUCTION
Forest provides direct and indirect of good and services to human well-beings by ecosystem functions(Robert et al., 2002). Moreover, it was totally essential for water storage because when the naturalforest was damaged, rainfall would be declined, reduced infiltration of water, increased run-off, andⒸ ISERD

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reduced water quality (Robert et al., 2002). Existence of watershed areas in protected forests andnational parks played the vital functions for water purification and water resources for both upstream
and downstream livelihoods. National park was one of the great tools for forest and biodiversity
conservation. The PKNP was one of famous sacred tourist zones with immense spiritual, cultural,historical value. Moreover, it was the main source of water provision for downstream people almost
the whole year. However, weak law enforcement and higher market demands on timber and otherforest products caused serious forest lost in Protected Areas (Sanchez-azofeifa et al., 2002).
Approximately 70% of downstream local people were semi-subsistence farmers and fishers who
heavily depended on river-based livelihood activities (Hayes et al., 2013). Lastly, present Siem Reap
river had faced water shortage, soil fertility problems, and water pollution (UNDP, 2014).
OBJECTIVES
In overall, the study aimed at investigating the perception of local people on impact of forest coverchange in PKNP on Siem Reap river and their livelihood. The specific objectives are i). analyzing
the trend of the forest cover change in PKNP between 2000 and 2016; and ii). assessing the livelihood
capital of downstream people affected by upstream forest cover change. The limitation of the study
did not access to measure economic comparation between before and after the forest cover change
due to uncertainly of household’s livelihood diversity.
METHODOLOGY
Study Area
Figure 1 showed PKNP, targeted area, located at Siem Reap province, Cambodia (Hayes et al., 2013).
Over centuries, the PKNP provided not only main source of water for the city use throughout fullyear, but also for underground water, which support Angkor Wat temple basement and its scenery(Gaughan, Binford, & Southworth, 2009). Recently, the water from the park contributed importantly
daily consumption and agriculture of provincial population. However, there were concerned on thedeforestation, led to cause on both water quality and quantity from the park.

Fig. 1 Phnom Kulen National Park boundaries and administration
Forest Cover Change Detection in PKNP between 2000 to 2016
This study utilized Landsat Satellite Imagery (LSI) from 2000 to 2016. Multi-temporal satellite data
were downloaded from the United Stare Geographical Satellite including Landsat 5, Landsat 7 ETM+,and Landsat 8 OLI with a 30 meters resolution. ArcGIS software (ArcGIS 10.6) was utilized for
digital image processing, classification, and analysis as well as forest cover change maps generation.
Two types of land use and land cover (LULC) were classified including forest, and non-forest areas.
In addition, these satellite imageries were selected with less than 10 % of cloud. The band
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combination of mosaic and masking were used to analysis and merge the images and clip theboundary. Indeed, Regions of Interest (ROI) was used for supervising classification for forest change
detection. Band Combination false color of Landsat was used to take ROI which is forest or nonforest. Therefore, Band 4, 3, 2 was used for Landsat 5 from 2001 to 2011, and Band 7, 4, 2 was usedfor Landsat 7 ETM+ from 2000 to 2013 and Landsat 8 OLI from 2014 to 2016.
Accuracy Assessment
Accuracy assessment was conducted for all classification to prove the accuracy of each classified
image. Moreover, it used to compare the classification from one to another, assumed to be accurate
i.e. aerial photo (Parece et al., 2011). An error matrix was accomplished for this task. To assess theaccuracy of classification, there were four main steps: 1) create random point on image classified in
ArcGIS (100 sample), 2) convert layer to KML to assess the point in Google Earth, 3) insert the point
in Google Earth and compared the classification task and Google Earth, and 4) created the error
matrix table and calculate with the formula.
Cohen’s kappa co-efficient was an essential component of accuracy assessment, it provided theaccurate result how well our classification performed.
k̂=observed accuracy - chance agreement
1 - chance agreement

where, The KHAT value ranges from 0 to 1,0 indicates the classification is not any better than arandom assignment of pixels, 1 indicates that the classification is 100% improvement from random
assignment.
k̂=N∑ri=1 Xii - ∑ri=1 (Xi+2N- ∑ri=1 (Xi+X+i )X+i )where, r number of rows in the error matrix, Xii number of observations in row i and column i (thediagonal cells), Xi+ total observations of row i, X+i total observations of column I, N total ofobservations in the matrix (Parece et al., 2011).
This study calculated the error matrix formulations of two years: 2010 and 2016 to verify theaccuracy of forest cover change analysis. After calculating the error matrix of supervisedclassification in 2010, the overall accuracy of image classification is 96% and the Kappa was 91%.
In 2016, the overall accuracy of the image classification was 91% in 2010 and 82% in 2016.
Assessment of Livelihood of Downstream Local People Affected by Upstream Forest CoverChange
120 households were selected with purposive sampling for the questionnaire survey. Four keyinformants from forestry administration office, department of environment, department ofmeteorological and few rangers in Siem Reap province were interviewed for the confirmation of both
qualitive and quantitative survey.
Adapted from Qian et al. (2017), livelihood approach has five capitals including; Physicalcapital which had indicators: household fixed assets (Land, Machinery, etc.); Natural capital had
indicators: forest coverage (changing), necessary for forest protection (important of forest), forest
protection activities in National Park, and biodiversity (quantity of water, quality of water, crop
fishing in natural place); Human capital had indicators: skill and knowledge (improvement), healthstatus (illness or not); Financial capital has indictors: household income (income of agricultural
production, forest and NTFPs), and Social capital had indictors: community membership(participant), social network (relationship), and family decisions. The total scores of local livelihood
assets were calculated by:Ⓒ ISERD

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𝐶𝑃𝑐 + 𝐶𝑁𝑐 + 𝐶𝐻𝑐 + 𝐶𝐹𝑐 + 𝐶𝑆𝑐
5where; LA Livelihood Assets, 𝑪𝑷𝒄 Physical capital, 𝑪𝑵𝒄 Natural capital, 𝑪𝑯𝒄 Human capital, 𝑪𝑭𝒄
Financial capital, 𝑪𝑺𝒄 Social capital.
LA =RESULTS AND DISCUSSION
Trend of Forest Cover in Phnom Kulen National ParkIn Fig. shown in 2000, PKNP covered by 31000 ha of forest area. Between 2009 and 20163, forest
was dramatically declined about 2800ha. The forest in PKNP had lost huge amount at the same trendof forest cover in whole (ODC, 2016). According to the interview with rangers reported the main
reasons of population growth (both people who migrated in and population growth naturally insidethe village), people expanded land for settlement, agricultural activities. Moreover, it was because of
inadequate knowledge of local people regarding forest conservation and forest management, illegal
logging. The perpetrators cut trees and killed the wildlife for selling at nighttime, which was difficult
for rangers to take action. In addition, limitation of logistic and incentive of ranger affected on lesspatrolling activities.

hectare

45000

30000

15000

02000

2005

2010

2015

Fig. 2 Land surface of forest cover change in Phnom Kulen National Park from 2000 to 2016Between 2009 and 2013 is the period of creating the policy on economic land concession (ELC)by the government in the National Strategic Development Plan (NSDP). The purpose of creating theELC policy was to develop the industrial agricultural sector, sustain economic growth and reducepoverty (ODC, 2015). By contrast, our study found there was impact on the forest cover change in
Siem Reap province. Based on the NGOs reported ELC was a hot very topic for land conflict
including land grabs, evictions and exploitation of natural resources (ODC, 2016).
In a line, the result of forest cover from the LSI from 2000 and 2016 shown in Fig. , forest lost
about 22%, equal to 6780 ha and the rate of deforestation was 1.3%, account to big amount of forest
lost that had to be consideration of the Cambodian government and development agencies. Recently,
over 4,600 people had settled in PKNP, caused to forest land conversion to residential, crop cultivation
mainly rice and cashew nut and the area was mainly used for rice (A&D Foundation, 2018).
The analysis found that 65% of local people perceived that forest cover in the upstream of PKNP
had decreased, while 35% reported not. The score of forest coverage was 0.35, suggesting a3

In 2008, forest cover increased because of the cloud problem which made some error in calculation. In 2012
and 2013, the imagery of land 7 was selected to use because it is the clearest one but there has many gaps on
the image so the research applied Shoreline Extraction (Landsat 7 ETM+) to fix it.
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significant decline. Our analysis of satellite imagery found that sharp decline in Banteay Srei district,where local people depended mostly on timber and non-timber production for daily livelihoods.
The result shown in Table 1, the percentage of local people perceived the forest at upstream wasdeclined, water quantity in the region decline is 76.7% especially. Moreover, there are 23.3% ofcorrespondents reported water was not declined due to the forest cover change at upstream. The scoreof this water quantity was 0.23, which means deforestation impacted the decline of water quantity at
downstream area.

Fig. 3 Comparison of forest cover change in Phnom Kulen National in 2000 and 2016
Table 1 Percentage of correspondent on livelihood capitalStatement

No (%)

Do you know that forest in the upstream national park hasdecreased?
Do you think that since forest from upstream declined, water
quantity in your region has also declined?

35
23.3

Do you think since forest from the upstream decreased, water
quality in your region also decrease?
Do you think since forest from the upstream decreased, your crop
production also declined?
Do you think since forest from the upstream declined, the amountof fish in the river also decreases?

28.3
40.8
25.0Respondents (n=120)
Yes (%)
Score= 35*1+65*065= 35 % = 0.35
= 23.3*1+76.7*076.7= 23.3 % = 0.23
= 28.3*1+71.7*0
71.7= 28.3 % = 0.28
= 40.8*1+59.2*059.2= 40.8 % = 0.41
75.0

= 25.0*1+75.0*0= 25 % = 0.25

Scaling:
0.00 – 0.25
0.26 – 0.50
0.51 – 0.75
0.76 – 1.00

Largely decreased
Decreased
Increased
Largely Increased

Total score

0.30

Another result shown 71.7% of downstream people perceived the decreased forest at upstream
impacted on water quality. The score of water quality was 0.28. Correspondents reported last sevenyears ago before 2013, water in river and lake could be used for drinking, taking shower, and usingfor daily. In addition, 59.2% of the downstream people perceived the decreased forest at upstream
impacted on a decrease of crops productions due to water shortage, badly in dry season.
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There were 75% of the downstream people perceive the decreased forest at upstream, impacted
on the decline of natural fish stock in the river. The decline of fishery significantly affected on income
and food insecurity of the local livelihood.
Livelihood Assets of Downstream Local People in Relation to Siem Reap River Affected byUpstream Forest Cover Change
Although forest cover change occurred in upstream but physical capital was required to use for dailylife. Natural capital was reported decreasing in biodiversity with 0.48 score. Local people perceived
there was decreased in upstream forest cover led to decrease the water quality, water quantity,
impacted on yield decreasing of crops and fish production. People in Banteay Srei, Tbaeng Lech, Ta
Pen, and Samraong villages raised the same aspect on decline of water quality and quantity impacted
on reduction of crop production and fishery.
As shown in Fig. 4, the result indicated, physical capital was not impacted regarding the forest
cover change in upstream with score 0.61. Similar change of physical capital because people required
to use for their daily live.

Fig. 4 Downstream local perception in termof change of livelihood capitalFig. 5 Downstream local perception on current
situation of the livelihood capital

In Fig. 5, the result illustrated that the current situation shown score of financial capital was very
with score 0.24, local people mostly depend on agriculture. The mean score human capital and social
capital in term of current level was medium mean score 0.44 and 0.41 because people did not haveany serious case of their health and both of man and woman had decided together for decision making.
CONCLUSION
The research found forest cover in PKNP was declined 22% from 2000 to 2016 due to illegal logging,inadequate knowledge regarding forest conservation, population growth, increase in cashew nut, andrice fields. A strong link between natural capital and forest cover have found. As local people needto change to new skills in order to survive after decline of forest cover. Low scores on human capital
was observed, indicating the need for interventions of the local or national authority to assist localpeople. Similarly, for the current situation of their financial capital had low income and highexpenditure.
Therefore, this study provided very important evident base of the forest cover change thought
the satellite imagery maps from 2000 to 2016 and result of perceptions of local people about theimpacts of the forest cover change in PKNM, which contributed direct and indirect impacts to naturalcapital, human capital and influenced on the current situation of financial capital.
ACKNOWLEDGEMENTSFirst author thanks the Kurita Water and Environmental Foundation for providing a full scholarshipto pursue master’s degree at Asian Institute of Technology, Thailand, and full fund of this research.
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