119

Evaluation of Recent Forest Cover Change in Savannakhet Province,
Lao PDR, Using AVNIR-2 and MODIS Satellite Images
Bumpei TOJO1*, Akihiko KOTERA2, Koji NAKAI2, Takanori NAGANO2,
Shigeo KOBAYASHI3 and Kazuhiko MOJI1
1

Research Institute for Humanity and Nature
457-4 Kamigamo Motoyama, Kita-ku, Kyoto 603-8047, Japan
2
Graduate School of Agricultural Science, Kobe University
1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan
3
Graduate School of Asian and African Area Studies, Kyoto University
46 Shimoadachi-cho, Yoshida, Sakyo-ku, Kyoto 606-8501, Japan*e-mail: bumpeitj08@chikyu.ac.jp

Abstract
In this study we analyzed the rate of change of forest coverage in Savannakhet Province, in central south
Lao PDR (People’s Democrotic Republic), and the causes of this change. In considering reasons for thetransition of forest coverage, we took into account human activities such as large-scale development,
expansion of agricultural land and shifting cultivation as well as effects of changes in rainfall. To survey
changes in land coverage, including forests, we used AVNIR-2 images with high spatial resolution and
MODIS images with high time resolution. To supplement the insufficient network of rainfall gauges in the
study area, data from the APHRODITE Project were used for analysis. As a result of this analysis, weestimated that the total forest coverage decreased by nearly 40,000 ha in Savannakhet Province, in the ten
years between 2000 and 2009. Deforestation occurred both in the open forest in the plains (dry dipterocarp
forest) and in isolated masses of dense forest (mixed deciduous forest) as the result of expansion ofagricultural areas, mainly in the western part of the province. We could find no long-term trend in rainfall, but
recently there has been a tendency of rainfall to decline where deforestation has occurred.
Key words: APHRODITE, deforestation, land cover and land use change, NDVI, object-based classification,satellite remote sensing

1. Introduction
In Southeast Asia, the forested area of the Lao PDR issecond largest after that of Cambodia, accounting for
50% to 60% of the country’s total area. This is a muchlarger number compared to that of neighboring countries
such as Thailand, Vietnam and Myanmar where forests
cover 20% to 40% of the land. However, the forests of the
Lao PDR are said to be in decline. In the severest
estimate, the forest coverage in the Lao PDR in 1997 is
said to have fallen to as low as 39% (Chanthirath, 1998).
Some of the reasons for this deforestation are said to be
shifting cultivation, expansion of grazing and agricultural
fields, and inappropriate commercial logging (Pheng,
1995; Chanthirath, 1998; Vajpeyi, 2001; MAF, 2005a). In
the Lao PDR, a large part of the nation’s foreign currency
acquisition relies on the export of forest resources (54%in 1991) and the lives of many people also depend on theuse of forests (Chanthirath, 1998). As such, forest
preservation is a crucial issue not only for the Lao PDR,
Global Environmental Research
15/2011: 119-129
printed in Japanbut also for the preservation of forests and biodiversity of
all of continental Southeast Asia.
In the Lao PDR, an accurate understanding of forest
cover change is essential in order to establish an accurate
forest preservation scheme. However, in developing
countries including the Lao PDR, the statistics used tounderstand changes in forest cover are often inaccurate(Fairhead, 1998). The use of remote sensing (satellite
images) and Geographic Information System (GIS)
technology is required to promote research into largescale and quantitative analysis of forest coverage change
and its causes. As the target area for this study, we
selected Savannakhet Province in central south Lao PDR,
known for its large area and the highest forest coverage inthe Lao PDR, and estimated the rate of forest coverchange and its causes in the period between 2000 and2009.
To verify changes in forest coverage, we used
the object-based supervised classification results ofAdvanced Visible and Near Infrared Radiometer type 2©2011 AIRIES

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(AVNIR-2) images and the Normalized Difference
Vegetation Index (NDVI) time-series analysis results of
the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) images. AVNIR-2 images have aspatial resolution of 10 m/pixel, excellent for a detailed
investigation of land coverage. However, as the satellite
takes 46 days to return to the area, AVNIR-2 images are
disadvantageous in tropical areas with long rainy seasonsfor capturing cloudless images over large areas every
year to observe changes in forest coverage. The satellite
was not in operation until 2006 so it cannot be used toverify the forest coverage before 2006. MODIS images,on the other hand, have a spatial resolution of 250
m/pixel, generating a variety of mixed pixels. In areas
with successions of tiny land coverage, it is difficult tocompare the classification results with the actual land
coverage. However, as the MODIS images can beobtained every eight days from the targeted area, they
have the advantage of minimizing the effects ofcloudiness, while being able to track changes in land
coverage with a high time resolution. In this study, we
combined the classification results of AVNIR-2 images
and unsupervised classification of MODIS images withlow spatial resolution.
We also analyzed rainfall trends in the province todetermine if they might have caused or triggered thechanges in forest coverage. Since rain gauge stations
were sparsely distributed and not all data were accessible,
we used an established precipitation data product of the
Asian Precipitation Highly Resolved Observational Data
Integration towards the Evaluation of Water Resources(APHRODITE) project (Yatagai et al., 2009).

2. Study Area
The study site was Savannakhet Province in central
south Lao PDR (Fig. 1A). Savannakhet is one of thelargest provinces in the Lao PDR and has 70% to 80% of
its area covered by forests. The total area of forests
within the province was the largest in Lao PDR as of1981 (Pheng, 1995). These large forests are seen in themountainous area and around the rivers as they approach
the Mekong River, significantly contributing to themaintenance of ecological services in the peripheral area,
including the climate regulation, water quality regulation
and biodiversity. The average annual rainfall is approximately 1,500 mm, 80% of which occurs in the fivemonth rainy season between May and September.
According to the classification by the Ministry ofAgriculture and Forestry (MAF), the forest coverage of
the Lao PDR is primarily categorized into three types:
Current Forests; Potential Forest Areas; and Other
Wooded Areas. Current Forests are further categorized
by the type of tree species as dry evergreen forests(DEF); mixed deciduous forests (MDF); and dry dipterocarp forests (DDF). Potential Forest Areas include
bamboo and unstocked forest, comprising less than 20%
tree crowns due to human intervention such as logging
and slash-and-burn farming. Other Wooded Areas include a variety of forests such as savannah, heath andscrub forest.
The total area of all these forest types between 1992
and 2002 was 86.9% (1,855,853 ha) of Savannakhet
Province (MAF, 2005b). The National Geographic
Department created a digital map (NGDD map) for all
kinds of land use and land coverage up to 1998 (Fig. 1B).
The ratio of forests in Savannakhet Province calculatedusing this map is 84.1% (1,795,948 ha), almost equal to
the figure shown by the MAF.
Looking at the NGDD map (Fig. 1B), the province’s
forest type distribution is divided by a border around105.7°east longitude, into the western half (the Thailandside) dominated by dry dipterocarp forest and the eastern
half (the Vietnam side) dominated by MDF, unstocked

Fig. 1 Location and forest distribution of Savannakhet Province.
A) Location of Savannakhet Province, Lao PDR.
B) Forest distribution by digital map of the Lao PDR. (1987-1998) and rain gauge station
locations in Savannakhet (1967-2005), Lahanam (1994-2005), and Xepon (1988-2002).

Recent Forest Cover Change in Savannakhet Province Laos

121

forest and shifting cultivation (Ray). The distribution offorest types clearly reflects the geographic condition of
the province. DDF consists of open forest stands which
are established on the plains. MDF, on the other hand, isestablished on hill slopes, thus it occurs in the easternpart of the province. It is also seen as isolated patches
across the small hills generated by the rivers in the plainsof the western part of the province. A large part of theunstocked forest in the mountainous area is said to beunder the influence of human intervention, such asslash-and-burn farming and large-scale logging (MAF,
2005b). DEF is scarcely seen, occurring in limited areas
such as deep in the mountains of the eastern part of theprovince.

3. Materials and Methods
3.1 Detection of forest distribution using high spatial
resolution satellite imagery
Using AVNIR-2 satellite images and the NGDD map,
we quantified the actual distribution of all types of forests.
A total of ten AVNIR-2 images were used, mosaickedfor each time batch (three from 9/13/2006, two from3/1/2008, two from 2/15/2009, two from 2/20/2009 and
one from 03/07/2010) without histogram matching. Eachof five mosaicked images was subdivided into segmentations called “objects” using eCognition8TM Software(Trimble Germany GmbH, 2011).
An “object” is defined as a group of pixels of spectral
homogeneity. Compared to a single pixel, the object has
additional values like texture and morphology. The
object-oriented approach enables exploration of the fullvalue of satellite images and extraction of GIS-readyinformation from images (Benz et al., 2004). The segmentation procedure starts with one pixel and repeatedly
merges other pixels into a larger unit as long as an upper
threshold of homogeneity is not exceeded locally. All
these processes run automatically on the eCognition. The
user can control the segmentation results by setting the
Scale Parameter (SP). The smaller the SP, the smaller theobject becomes, making it possible to extract more
micro- evenness (Fig. 2 A).
We tested all numbers of SP from 100 to 10, andselected SP=10 for this study. If the SP is too small (e.g.,8) it causes sudden interruption of the segmentation
procedure by program error. After the segmentation
procedure, some objects are selected from the whole
image as training samples by visual interpretation. In thisstudy we adopted three classification categories (water,
bare land, and wooded areas) and applied a supervised
method of maximum likelihood analysis using the object
mean value of each band (band 1: 0.42-0.50μm, band 2:
0.52-0.60μm, band 3: 0.61-0.69μm, band 4: 0.760.89μm) for classification.
The classification result “wooded areas” was exported as vector data (Fig. 2B), which were intersectedwith NGDD map vector data (Fig. 2C) on ArcGISTM
software to generate the wooded area map with forest
type (DEF, MDF, DDF, unstocked, ray, swamp, others)

Fig. 2 Example of object-based (object-oriented approach) classification of an AVNIR-2 image.
A) Influence of SP setting on object sizes.
B) “Wooded area” converted to vector data.
C) Vector data of the National Geographic Department
digital map.

information (Fig. 3). In this manner, spatial resolution of
the final product (shown in Fig. 3) became much higher
than that of Fig. 1.
3.2 Detection of land cover changes using time-series
satellite imageries
The Terra MODIS surface reflectance data
(MOD09Q1: 8-day composite, spatial resolution: 250 m)covering the area of Savannakhet Province (tile h28v07)
from April 2000 to March 2010 were used for thetime-series vegetation analysis in this study. The data
were obtained via the Warehouse Inventory Search Tool
(WIST) website <https://wist.echo.nasa.gov/~wist/api/
imswelcome>. As for vegetation signatures, NDVI was

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Fig. 3 Actual distribution of wooded areas by forest type, Savannakhet Province, generated from intersecting
mosaicked AVNIR-2 satellite imageries and the National Geographic Department’s digital map.
This classification was based on an object-base classification of ALOS/AVNIR-2 satellite imageries, using
ten satellite images obtained from 2006/9/13 (3 images), 2008/3/1 (2), 2009/2/15 (2), 2009/2/20 (2) and2010/03/07 (1). Information on the seven forest types (Dry Evergreen, Mixed Deciduous, Dry Diptercarp,
Unstocked, Ray, Swamp, Others) was added to the generated Wooded Area layer (Fig. 2B) by intersecting itwith the National Geographic Department’s digital map (Fig. 1B).

derived from band 1 (620-670 nm) and band 2 (841876 nm) reflectance data.
In order to reduce the cloud noise effect and to extract
characteristics of the vegetation dynamics, the Harmonic
Analysis of Time Series (HANTS) algorithm (Roerink
et al., 2000) was performed on time-series NDVI data.
The advantage of the HANTS algorithm is that the output
can be obtained as a smoothed time-series data. The algorithm captures only the most significant frequencies expected to be present in the time profiles determined by
Fast Fourier Transform (FFT) analysis, and applies aleast squares curve fitting procedure based on harmoniccomponents. In this study, number of frequencies (NOF),
suppression flag (SF) and fit error tolerance (FET) wereset as 2, low, 26 and 18, respectively, as control parameters of the algorithm. Since the majority of the vegetation
categories in Savannakhet Province have seasonal
growth cycles between rainy and dry seasons, in thisstudy, the annual vegetation dynamics was analyzed overa period of twelve months between April and the subsequent March.
To detect land cover changes, an unsupervised classification was performed on the cloud-free time-series

images. Unsupervised classification identifies clusters by
their time-series pattern similarities and allows the feature space to segment into similar pattern clusters(Cheema & Bastiaanssen, 2010). The K-means clustering
method was used in this study. To avoid variation ofclustering criteria among different years, the algorithm
was performed on a single mosaic image which wassynthesized by merging images of all years. The image
was classified into twelve classes as an initial trial, andthen refined into seven classes and labeled corresponding
to the forest distribution used in Fig. 3, by applying expert knowledge of the phenological patterns of trees andcrops in this area. The classification results in 2000 and2009 were then compared and changes between the two
images were detected.
3.3 Precipitation data
To analyze the effect of rainfall on changes in land
cover, we used a daily gridded precipitation dataset
created by collecting dense network rain-gauge observation data across Asia through the activities of
APHRODITE project (Yatagai et al., 2009). The dataset
we used contains reanalyzed data of daily rainfall in the

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Annual precipitation (mm)Recent Forest Cover Change in Savannakhet Province Laos

Fig. 4 Comparison of rain gauge data with the data of the nearest grid from APHRODITE for three locations, Savannakhet,
Lahanam and Xepon in Savannakhet Province, Lao PDR..
RMSE: root mean square error between APHRODITE and the rain gauge data.
The crossbars indicate the period of the forest cover survey from which forest cover statistics were derived in this study.
Source: Rain gauge stations at Savannakhet (16.55°N, 104.75°E, 1967-2005), Lahanam (16.27°N, 105.27°E, 1994-2005) and Xepon(16.69°N, 106.22°E, 1988-2002), and APHRODITE grid data (1951-2007) at Savannakhet (17.00°N, 104.75°E), Lahanam (16.25°N,
105.25°E) and Xepon (16.75°N, 106.25°E).

period between 1951 and 2007 in the monsoon Asia areaby daily 0.25 degree grids (APHRO_MA_025deg_
V1003R1_1951-2007), from which we extracted the dataof Savannakhet (16.00-17.00°N, 104.75-107.00°E).
To verify the accuracy of the dataset, we generated
monthly rainfall values from the dataset and comparedthem to rain gauge data observed at three stations in
Savannakhet, Lahanam, and Xepon (shown in Fig. 1)
published by the Department of Agriculture and Forestry,
Meteorology and Hydrology Section, Savannakhet
Province. APHRODITE’s grid precipitation dataset
tended to be larger than observed values (Fig. 4) and theroot-mean- square error (RMSE) between the dataset andobserved values were 53 mm, 71 mm and 72 mm for
Savannakhet, Lahanam, and Xepon, respectively. Because
APHRODITE’s grid precipitation was generated withcorrection of orographic effects, the grid data containing
mountains on the leeward side could be higher than therain gauge data, particularly for gauges placed in theplains area (Xie et al., 2007).
Using APHRODITE’s annual precipitation data,
we examined long-term (1951-2007) and medium-term
rainfall changes between periods when government
statistics were formulated (1989-1998) and when
AVNIR-2 and MODIS images were captured (19982007). For the trend analysis we used the linear
regression method, investigating the statistical signifi-

cance of the differences by the t-test.
Monthly precipitation data were compared with theseasonal vegetation dynamics in the case study area
where forest cover changes were detected by remotesensing analysis. Since the precipitation data after year
2007 have not yet been published, comparison withvegetation data was possible only between the years of2000 and 2007.

4. Results and Discussion
4.1 Forest cover distribution
Table 1 shows the area of each type of forest in
Savannakhet Province, calculated by GIS. We used
NGDD map data for 1987-1998 in the upper section. For
2006-2010 in the lower section, we calculated the size of
the wooded area extracted from AVNIR-2 images intersected with the NGDD map (Fig. 3).
The total forest area in 2006-2010 was 1,494,361 ha,equivalent to 70.0% of the total area of Savannakhet
Province. The difference between this estimate and theforest area by the government’s statistics (1987-1998)
was 312,009 ha (14.6% of the total area of the province).
For most of the forest types the differences remained lessthan a few percent of the province’s area but the difference of DDF alone was very large: 275,770 ha or 13% of
the total area .

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The difference in calculated area does not directly reflect the extent of deforestation between 1987 and 2010.
In particular, the large decrease in DDF may be attributed
to a difference in the spatial resolution of classification.
DDF is scattered in the plains and these forests create
complex mosaics with agricultural land and other land
coverage. It is probable that the NGDD map and forest
statistics by the Ministry of Agriculture and Forestry do
not sufficiently reflect the area of land coverage by small
agricultural lands and other land coverage that exist
within the area defined as DDF.
In Table 1, 108,328 ha is classified as “others.” This“others” refers to the area classified as wooded areas
according to the satellite image analysis, yet classified as

non-forests by the NGDD map. Because of this unconformity, they were excluded from the calculation of thetotal forest area. ”Others” also includes wooded areas
within cities, villages and agricultural fields, so not all ofthem are necessarily forests. However its extent, 108,328
ha, is equivalent to more than three times the area of the
DEF of the whole province, and almost equivalent to theareas of shifting cultivation and savannas. Therefore theamount of wooded area that should have been counted asforests (primarily in DDF) is not negligible. This analysis
alone did not clarify the extent of deforestation between
the two periods but rather revealed the poorness of spatial
resolution of the forest statistics in the past.

Table 1 Summary of area by forest type, calculated from GIS base map data for the Mekong River Basin and classification results of
ALOS/AVNIR-2 satellite images for Savannakhet Province, Lao PDR.
Year

a. DryEvergreen（DEF）

b. Mixed
Deciduous（MDF）

c. DryDipterocarp（DDF）

d. Bamboo,
Unstocked
Foreste. Ray,Savannah,
Scrub,
Grassland

f. Swamp

g. OthersA.

31,223 ha

394,962 ha

639,761ha

612,885 ha

117,114 ha

10,425 ha--- ha

1.5%

18.5%

30.0%

28.7%

5.5%

0.5%

---%

84.5%
1,494,361 ha(1987-1998)
B.
(2006-2010)
B-A

Total
1,806,370 ha

31,023 ha

369,244 ha

363,991 ha

526,546 ha

90,265 ha

4,964 ha108,328 ha

1.5%

17.3%

17.0%

24.7%

4.2%

0.2%

5.1%

70.0%

- 210 ha- 25, 718 ha-275,770 ha- 86,339 ha- 26,849 ha- 5,461 ha+108,328 ha- 312,009 ha- 0.0%- 1.2%- 13.0%- 4.0%- 1.3%- 0.3%+ 5.1%- 14.6%

A. GIS base map data for the Mekong River Basin（Land use data from NOFIP (FIPC) 1987-1998）(Fig 1B).
B. Classification results of AVNIR-2 satellite images (2006-2010) (Fig 3).

Fig. 5 Seven Land cover classes of Savannakhet Province, Lao PDR, in (A) 2000 and (B)2009 generated from unsupervised classification of MODIS time-series data.
This classification was based on annual phenology patterns from Apr. 2000 to Mar.
2001 (2000) and from Apr. 2009 to Mar. 2010 (2009).
*
**
***

Dry evergreen forest.
Mixed deciduous forest.
Unstocked forest is not closed forest because its tree cover is less than 20% in thedefinition of statistics, but actually, there are many areas of Unstocked forest in which
vegetation has recovered to the level of Class 1.
**** Dry Dipterocarp Forest.
*****Values in parentheses are the average ratio of the wooded area in the whole province.

Recent Forest Cover Change in Savannakhet Province Laos

4.2 Detection of deforestation by time-series imagery
Figs. 5A and B show the distribution of seven classesof land cover derived from unsupervised classification of
MODIS data. Fig. 6A shows the average phenologicalpatterns of the seven classes. Each class is a mixture ofmultiple land cover types since the spatial resolution ofeach pixel is coarse (250 m). To clarify the compositionof each class and to quantify the degree of deforestation,
the images in Fig. 3 and Fig. 5 were intersected on the
GIS and the ratio of wooded areas in each class was
obtained (Fig. 6 B).
In Figs. 6A and B, classes 1 and 2 exhibit a relatively
high NDVI throughout the year and the ratio of wooded
areas is high in each class (0.96 and 0.81). Class 1 consists of closed DEF and MDF forests, with relatively low
human intervention, while class 2 has a higher proportionof MDF with high human intervention (unstocked forest)
and ray, or poor vegetation like open forest (mainly DDF
situated in the plains). Contrarily, classes 5 and 6 haverelatively low and varying NDVI and their ratios ofwooded areas are 0.28 and 0.17, respectively. They canbe considered as mainly agricultural (paddy) areas.
Classes 3 and 4 can be considered areas where patches ofwooded areas and agricultural areas are mixed. The ratioof wooded areas in classes 3 and 4 are 0.56 and 0.42,
respectively. The wooded areas in these classes are

125

mainly DDF. Classes 3 and 4 seem to represent the transitional states where large DDFs are being replaced by
newly cultivated areas.
Table 2 is a matrix table summarizing the transition ofeach class from 2000 to 2009. From this table the total
loss of forests throughout Savannakhet Province wasestimated to be 41,578 ha. It is a very small number
compared to the estimated forest loss in Table 1(-312,009 ha). Large deforestations of -32,686 ha occurred in DEF and MDF (class 1) showing similarity to
the value in Table 1 (-25,928 ha). The degree of deforestation in DDF (classes 3 to 5 and partly class 2), in theplains of the province, was calculated to be -10,875 ha.
The calculated value for DDF in Table 1 (-275,770 ha)
was much larger than this value and it is likely to be an
overestimation arising from the poorness of spatial
resolution of past statistics.
4.3 Effects of rainfall on land cover changes
In Savannakhet Province, no long-term trend wasfound in annual rainfall in the past 57 years between 1951
and 2007 (P > 0.05). Annual rainfall fluctuated from year
to year, with coefficients of variation (CV) in around
Savannakhet (16.75° N, 104.75°E), Lahanam (16.50° N,
105.25°E) and Xepon (16.75° N, 106.00°E) being 13.5,
16.7 and 19.5%, respectively.

Fig. 6 Characteristics of vegetation classified to seven classes in Savannakhet Province.
A) Average pattern of seasonal NDVI change in seven classes.
B) Ratio of wooded areas in seven classes in 15 districts of Savannvakhet Province .
The ratio of wooded areas is derived from the wooded areas shown in Fig. 3 corresponding witheach classified area shown in Fig. 5.
*
Dry evergreen forest.
** Mixed deciduous forest.
*** Unstocked forest is not closed forest because its tree cover is less than 20% in the definition of
statistics, but actually, there are many areas of Unstocked forest in which vegetation has
recovered to the level of Class 1.
**** Dry dipterocarp forest.
*****Values in parentheses are the average ratio of the wooded area in the whole province.

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Table 2 Transition of land cover classes between 2000 and 2009 in Savannakhet Province, Lao PDR, as a result of analysis of MODIS
time-series NDVI data.
2000

Class 1
Class 2

2009

Class 3
Class 4
Class 5Class 6Class 7
Class areain 2000
Wooded area in2000 (ha)Wooded areachange in
2000-2009 (ha)Class 1

Class 2

Class 3

Class 4

Class 5Class 6Class 7496,807

91,836

820

0

0

0

0

119,681466,334

40,078

407

6

0

6

4,870

79,480420,416

45,494

6,125

1,032

647

876

3,397

80,62944,345

9,538

3,146

1,724

569

1,534

43,76539,23037,16015,066

1,422

379

502

6,755

7,759

14,86029,435

4,680

329

257

552

441

279

1,729

14,865623,510(29.1%)
598,570(28.0%)

643,339(30.1%)
521,105(24.4%)

593,015(27.7%)
332,089(15.5%)

137,675(6.4%)
57,824(2.7%)

67,967(3.2%)
19,031(0.9%)

50,408(2.4%)
8,569(0.4%)

23,344(1.4%)
1,868(0.1%)-32,686(-1.5%)-13,631(-0.6%)-19,573(-0.9%)+2,511(+0.1%)+19,818(+0.9%)+2,373(+0.1%)-391(-0.0%)Class area *Wooded area
2009 (ha)2009 (ha)589,462
565,884**(27.6%)(26.5%)
626,511507,474(29.3%)(23.7%)
558,064
312,516(26.1%)(14.6%)
143,655
60,335(6.7%)(2.8%)
138,746
38,849(6.5%)(1.8%)
64,37010,943
(3.0%)(0.5%)
18,524
1,476(0.9%)(0.1%)
2,139,259
1,497,476(100.0%)(70.0%)
1,539,055(71.9%)-41,578(-1.9%)

Values indicate the area (ha) in each class in 2000 classified into the image in 2009. For example, 119,681 ha of class 1 area in 2000 changed to class 2 in2009. Values with under bars indicate areas with no class change between 2000 and 2009.
* Wooded areas in each class are derived from the class area with the ratio of the wooded area shown in Fig. 4 (Class 1: 0.96, Class 2: 0.81, Class 3: 0.56,
Class 4:0.42, Class 5: 0.28, Class 6, 0.08, Class 7: 0.08).
** Values in parentheses are the percentage ratio of the area to the province area.

has been well studied (e.g., Kanae et al., 2001; Pielke
et al., 2007). Kanae (2001) reported that significant decreases in rainfall occurred as a result of deforestation on
the Indochina Peninsula, particularly in Thailand, which
is situated next to Laos. In the case of Savannakhet
Province, a similar phenomena may be going on and theestablishment of a denser rainfall observation network
would be necessary to verify it.

Fig. 7 Comparison of the mean annual rainfall of 1998-2007
to that of 1989-1998 in Savannakhet Province, Lao
PDR, using the APHRODITE dataset.

The areal average rainfall in the province between the
1990s when the government statistics were formulated,
and the 2000s when AVNIR-2 and MODIS images were
captured, also showed no significant change (P > 0.05).
The spatial distribution of rainfall in this period, however,shows a decline in the central and western areas (Fig. 7).
This spatial distribution seems to coincide with the
distribution of DDF, which was converted to cultivatedland as explained in the previous section. Recently, therole of landscape change in altering convective rainfall

4.4 Forest cover changes due to human activity
Human intervention in natural vegetation, such asreclamation of agricultural land and commercial logging,have been reported as the primary reason for deforestation (Pheng, 1995; Chanthirath, 1998; Vajpeyi, 2001;
MAF, 2005a). In this section, examples of such cases areshown by analysis of MODIS time-series vegetation dataover the ten years between 2000 and 2009.
The change from Fig. 8A to Fig. 8B illustrates a typical case where a closed forest was cut down and became
agricultural land (from class 1 to class 5). The annual
average of NDVI remained high until 2005 but rapidly
declined after 2006 (Fig. 8C). The annual rainfall of 2006
was less than that of 2005, but given the relationshipbetween NDVI and rainfall up to 2006, it is difficult toconclude that the rainfall of 2006 caused the change in
vegetation growth (Fig. 8C). From an analysis of seasonal changes in NDVI in Fig. 8D, logging of the forest
seems to have started in December 2006. In 2007, NDVI
remained low, similar to that of bare ground and it seems
there was no active land use. The patterns of NDVI in2008 and 2009 show signs of cultivation in this area.

Recent Forest Cover Change in Savannakhet Province Laos

127

Fig. 8 Examples of cases of conversion of forest to agricultural land.
A) Land cover status around the tracking point indicated by center circle (105.064°E, 16.521°N) in 2000.
B) Land cover status around the tracking point indicated by center circle (106.374°E, 16.617°N) in 2009.
C) Annual change in NDVI and precipitation. Annual rain data were acquired from AHRODITE (105.0°E, 16.5°N).
D) Seasonal change in NDVI.
*
**
***

Dry evergreen forest.
Mixed deciduous forest.
Unstocked forest is not closed forest because its tree cover is less than 20% in the definition of statistics, but actually, there aremany areas of unstocked forest in which vegetation has recovered to the level of Class 1.
**** Dry Dipterocarp Forest.
*****Values in parentheses are the average ratio of the wooded areas in the whole province.

The change from Fig. 9A to Fig. 9B is a case of slashand-burn farming, which was confirmed by our fieldsurvey, too. In this site the slash-and-burn farming was
conducted in 2005 and thus the NDVI in 2005 shows a
distinctive pattern (Fig. 9 D). In 2006 and onward thepatterns are similar to those before slashing.
Judging from Figs. 9C and D, the vegetation of slashand-burn farming fields recovers on average to class 2
forest within two to four years of lying fallow, and it
seems that a decade is enough to regenerate a once
cultivated area into secondary forest again. In Table 2,
there are 91,836 ha of class 2 area which have transformed to class 1. This number implies that at most about
15% of class 1 areas (estimated at 589,462 ha in 2009) inthis province are under a cycle of slash-and-burn farmingwith a ten-year fallow period.

5. Conclusion
The analysis using MODIS time-series data showedthat in Savannakhet Province, in the ten years between
2000 and 2009, forest coverage including DEF, MDF,
DDF and unstocked forest declined nearly as much as
40,000 ha. From the comparison of spatial distribution
between the years 2000 and 2009 (Fig. 5), it became
apparent that most of this deforestation occurred as theresult of expansion of agricultural areas in the westernpart of the province in both DDF and isolated masses of
MDF. By combining AVNIR-2 and MODIS satellite
image classification results we estimated that MDF and
DDF coverage decreased by 30,000 ha and 10,000 ha,
respectively. There was no long-term trend found in
rainfall in the province though in recent years a slightdecline in rainfall in the western part of the province was

128

B. TOJO et al.

Fig. 9 Traces of slash-and-burn cultivation in a closed forest.
A) Land cover status around the tracking point indicated by center circle (106.374° E, 16.617° N) in 2000.
B) Land cover status around the tracking point indicated by center circle (106.374° E, 16.617° N) in 2009.
C) Annual change in NDVI and precipitation. Annual rain data were acquired from AHRODITE (106.25° E,
16.5° N).
D) Seasonal change in NDVI.
*
**
***

Dry evergreen forest.
Mixed deciduous forest.
Unstocked forest is not closed forest because its tree cover is less than 20% in the definition of statistics, but actually,
there are many areas of Unstocked forest in which vegetation has recovered to the level of Class 1.
**** Dry dipterocarp Forest.
*****Values in parentheses are the average ratio of the wooded areas in the whole province.

observed. The amount of the decline was not likely to
influence changes in forest coverage and land use oversuch a short time period.

Acknowledgements
This article was funded by the Project for “Environmental Changes and Infectious Disease in Tropical Asia”
of the Research Institute for Humanity and Nature, withsupport from the Core Research for Evolutional Scienceand Technology (CREST) program, “Long-term Vision
for the Sustainable Use of Freshwater Resources,” of theJapan Science and Technology Agency (JST). The actual
distribution of wooded areas by forest type, Savannakhet
Province (Fig. 3), employed a part of the results acquired
for the entire Lao PDR by the above project. In ourfield survey, we cooperated with Prof. Dr. BOUPHA

Boungnong, Director of the National Institute of Public
Health (NIOPH); Dr. PONGVONGSA Tiengkham,
Director of the Station of Malariology, Parasitology andEntomology; and Dr. Thatheva SAPHANGTHONG,
Director of the Information Center of the Ministry ofAgriculture and Forestry, among others.
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129

Bumpei TOJO
Bumpei TOJO is a project researcher at the
Research Institute for Humanity and Nature(RIHN). In this project, he is engaged in interdisciplinary study concerning environmental
change and infectious diseases in tropical Asia,
mainly in the Lao PDR and Bangladesh. He
received his Doctorate in Area Studies from the
Graduate School of Area Studies, Kyoto
University. His doctoral thesis was entitled “Conflict between Forest
Conservation Policies and the Rights of Local Residents in Madhupur
National Park, Bangladesh.” He has been focusing on deforestation andforest use of local residents in Southeast Asia using R/S, GPS, GIS
monitoring and field interviews.

Akihiko KOTERA
Akihiko KOTERA is a post-doctoral fellow of the
CREST project at the Graduate School of
Agricultural Science, Kobe University (http://
www.edu.kobe-u.ac.jp/ans-rpww/index-j.htm).
He has a Doctorate in Agriculture from the
Department of Environmental Science andTechnology, Graduate School of Agriculture,
Kyoto University. He is interested in studies ofsustainable water use in agricultural production at
both local and global scales. He is also currently engaged in developing a
World Atlas of Irrigation Agriculture.

Koji NAKAI
Koji NAKAI is a graduate student at the Graduate
School of Agricultural Science, Kobe University(http://www.edu.kobe-u.ac.jp/ans-rpww/index-j.
htm). He is a project member of “Environmental
Change and Infectious Diseases in Tropical Asia”
at the Research Institute for Humanity andNature. He is currently engaged in developing ahair analysis method to monitor mineral balanceand heavy metal exposure in humans.

Takanori NAGANO
Takanori NAGANO has been an Associate
Professor at the Graduate School of Agricultural
Science, Kobe University since 2008. He received his Doctorate in Agriculture from the
Graduate School of Kyoto University in 2002. Heworked as a post-doctoral fellow at the ResearchInstitute for Humanity and Nature (2001-2004),
as a postdoctoral fellow at JSPS (2004-2007) andas a technical assistant staff member (2007-2008). His research fields are
soil hydrology, irrigation and drainage and rural planning. His current
research focus is on sustainability analyses of large irrigation schemes.

Shigeo KOBAYASHI
Shigeo KOBAYASHI has been a Professor at theGraduate School of Asian and African Area
Studies, Kyoto University since 2004. He worked
at the Soil Division of the Forestry & Forest
Products Research Institute until 1987. In 1988 hemoved to the Forestry and Forest Products
Research Institute, where he served as Head ofLaboratory at the Department of Forest Site
Environment.

Kazuhiko MOJI
Kazuhiko MOJI has worked for RIHN since 2007.
He received his MA (1978) and Ph.D. (1987) in
Health Sciences at the University of Tokyo. He
was a Research Associate at the Department of
Human Ecology at the University of Tokyo(1983-1987). In 1987 he moved to Nagasaki
University, where he served as Associate
Professor in the Department of Public Health(1987-1999) and Professor at the School of Allied Medical Sciences(1999-2001), Faculty of Health Sciences (2001-2002), and the ResearchCentre for Tropical Infectious Diseases at the Institute of Tropical Medicine(2002-2007).

(Received 31 May 2011, Accepted 7 October)