Study of land cover change in vietnam for the period 2001 2003 using modis 32 days composite

STUDY OF LAND COVER CHANGE IN VIETNAM FOR THE PERIOD 2001-2003 USING MODIS 32 DAYS COMPOSITE Nguyen Dinh Duong Institute of Geography, VAST 18 Hoang Quoc Viet Rd., Cau Giay, Hanoi, Viet

STUDY OF LAND COVER CHANGE IN VIETNAM FOR

THE PERIOD 2001-2003 USING MODIS 32 DAYS COMPOSITE

Nguyen Dinh Duong Institute of Geography, VAST

18 Hoang Quoc Viet Rd., Cau Giay, Hanoi, Vietnam Phone: 84-4-7562417, Fax: 84-4-8361192, Email: duong.nd@hn.vnn.vn

ABSTRACT

Land cover is important information source for many environmental study including conservation and agriculture development The change of the land cover of a specific area over a time period can provide us information on how sustainable the land has been used Land cover mapping based on high resolution satellite remote sensing data as Landsat TM, SPOT HRV etc has been widely used in practice However, due to low temporal resolution, these images do not provide sufficient information on seasonal change characteristics of land cover that could cause misclassification and difficulties in post classification refining The new sensors such as TERRA MODIS, ENVISAT MERIS and ADEOS-II GLI with high temporal (revisit time is from 2 to 4 days) and spectral resolution are ideal data source for land cover mapping in global and regional scale In this paper, the author presents result on land cover mapping of Vietnam based on MODIS 500m 32-day global composite developed

by the University of Maryland Land cover classification was carried out by the GASC algorithm which was developed by the author for multitemporal remote sensing data analysis Classification scheme is kept following IGBP standards As result, a land cover map of Vietnam for the year 2001, 2002 and 2003 were established The classification result was validated using ground GPS photo database The paper has pointed out usefulness of usage of high temporal and medium spatial resolution remote sensing data for natural resource inventory and environment monitoring in country-wide, regional and global scale The time seriers of land cover of Vietnam for the years 2001, 2002 and 2003 was used for change analysis Though it is relatively short time data series some trend of land cover change reflecting both positive and negative impact of development to the environment have been addressed in the paper

1 INTRODUCTION

MODIS (Moderate Resolution Imaging Spectroradiometer) is one of the sensors onboard Terra and Aqua satellite This instrument belongs to moderate spatial resolution sensor group that consists of sensors such as ADEOS-II GLI , ENVISAT MERIS This is a class of sensors which are capable of observation of Earth surface and atmosphere in moderate spatial resolution, high spectral resolution with short revisit time Data provided by these sensors are extremely useful for environmental monitoring and natural resource management in global, regional and country-wide scale At present the MODIS belongs to one of system which provides stable dataset for environment monitoring The time series of data collected globally from 2001 to 2003 can be used for change analysis globally and locally In this paper the author reports on application of MODIS dataset for land cover mapping and monitoring its changes for the period from 2001 to 2003 in Vietnam by using 32 day composite dataset released by the University of Maryland This is the first attempt of using satellite data to monitor land cover in country-wide scale in Vietnam Though it is

relatively short time data series, some trend of land cover change reflecting both positive and negative impact of development to the environment have been addressed in the paper

2 MODIS 500M 32- DAY COMPOSITE

MODIS 32-day composite is a product of Global Land Cover Facility, University of Maryland This product is derived from MODIS level 3 surface reflectance product called MOD09A1 (8-day Surface Reflectance Composites) There are eleven composites for each Julian year from the first day to 360th day The last 5 days of the year is included in the first period of the next year There are seven spectral channels included in the dataset which are listed in the Table 1

Table 1 Spectral channels of MODIS 32-day composite

Channel Wavelength (nm) Description

6 1628-1652 Short wave infrared:(similar to

Landsat band 5)

7 2105-2155 Short wave infrared:(similar to

Landsat band 7)

Figure 1 Example of cloud free MODIS composite of Vietnam

Spatial resolution of the data is 500m for all channels On the figure 1 is example of the dataset of Vietnam for the first four months of the year 2002 Color composite was made using channels 6 assigned to red, 2 to green and 1 to blue The original data is in Goodes global projection To facilitate data integration among the MODIS and other GIS database, the MODIS dataset was reprojected into latitude and longitude grid and cut according to boundary of Vietnam

3 GASC ALGORITHM FOR CLASSIFICATION OF LAND COVER

GASC (Graphical Analysis of Spectral Reflectance Curve) algorithm is an algorithm developed by Nguyen Dinh Duong in the framework of ADEOS-II GLI Research Announcement for classification of land cover using multitemporal and multispectral remote sensing data (Nguyen Dinh Duong, 1997) The nature of GASC algorithm is to find out spectral invariant that will help to easily classify land cover objects according to their spectral reflectance characteristics This method assumes that different land cover object have different spectral reflectance pattern, that should be stable for certain remote sensing sensor with fixed observing spectral channel composition The image invariants used for classification are: modulation of the spectral reflectance curve, total reflected radiance index (Nguyen Dinh Duong, 1998), channel ratios and ratios of difference to sum of radiance for all spectral channel pairs The GASC algorithm has been developed for analysis of both single date and multi-date dataset The multi-date GASC algorithm was applied for classification of MODIS 32-day composite Working principle of the GASC algorithm is shown on Figure 2 The classification of land cover is supported by ground truth database which is consisted of more then 6000 GPS ground photos taken in Vietnam since 1997 to present The ground truth database was used for both training samples selection and classification result validation validation (Figure 3)

Figure 2 Principle of GASC algorithm for classification of land cover

Figure 3 Ground truth database and GPS photos

4 CLASSIFICATION RESULT AND CHANGE ANALYSIS

The above described classification methodology has been used in conjunction with IGBP land cover classification system The basic IGBP system containing 17 major categories of global land cover has been modified and reduced to 14 classes of land cover for Vietnam They are: close evergreen broadleaf forest, open evergreen broadleaf forest, shrub, deciduous broadleaf forest, evergreen needle leaf forest, mangrove, grass land, mosaic, crop land, wetland, barren land, sandy surface, fruit trees and water Land cover of Vietnam for the years 2001, 2002 and 2003 has been classified by the same table of legend with 14 categories Figure 4 shows land cover of Vietnam over the study period The table 2 gives statistics computation of land cover in Vietnam for each year in both hectare and percentages In general, there are not big changes in land cover during the three years period If we look at details we could find out that there are some changes in area of close evergreen broadleaf forest This type of forest has been increased about 2 % since 2001 This change can be explained mostly by successful reforestation process in North of Vietnam Figure 5 demonstrates spatial forest change in North of Vietnam The deciduous forest that dominates

in Tay Nguyen high land is decreasing about 1.7 % since 2001 This is probably caused by conversion of forest land into coffee and rubber plantation Tay Nguyen highland is famous

by basaltic soil which is very suitable for coffee, rubber and other long-term commercial tree plantation In the last twenty years, the Tay Nguyen highland has been extensively exploited for agricultural production The spontaneous conversion of forest land into coffee and rubber

plantation has brought some serious environmental impact in a form of extreme flooding or droughts Spatial visualization of the change of deciduous forest can be seen on Figure 6 It seems that grass land is gaining in area There is about 1.6 % of grass land has been increased The other land cover categories seem remain unchanged even there are some fluctuations in their area which can be treated as noise in MODIS data itself

Figure 4 Land cover of Vietnam from 2001 (left), 2002 (middle) to 2003 (right) Table 2 Statistics computation of land cover of Vietnam

2001 2002 2003

No Class

Area ( ha) ( % ) Area ( ha) ( % ) Area ( ha) ( % )

1 Close evergreen broadleaf forest 5530300 15.5 6306825 17.7 6317025 17.7

2 Open evergreen broadleaf forest 4076250 11.5 4385025 12.3 4259700 12.0

4 Deciduous broadleaf forest 2401800 6.7 1991525 5.6 1770800 5.0

5 Evergreen needle leaf forest 344250 1.0 189800 0.5 155375 0.4

8 Mosaic 6568125 18.5 5689825 16.0 5707450 16.0

11 Barren land 1248775 3.5 651300 1.8 840675 2.4

Figure 5 Land cover change of North of Vietnam

Figure 6 Land cover change over Tay Nguyen high land

4 CONCLUSION

The MODIS time series data is quite useful for monitoring of land cover and other associated environmental characteristics as demonstrated in the paper Though this is very initial result obtained in Vietnam condition, however, the following general conclusions could

be made:

- The 32 day MODIS dataset can be used for land cover mapping and its long

term monitoring

- The GASC algorithm which uses all land channels for analysis is quite useful

for classification with multitemporal dataset and allows to extract enough detail land cover categories

- Due to the large coverage of the MODIS dataset, monitoring of land cover in

regional and continental scale has became realistic This activity requires collaboration among scientists in the region in both ground truth collection and change analysis assessment

5 ACKNOWLEDGEMENT

The author would like to thank all staff of EISA who have been actively involved in this research A part of budget used for conducting this research has been allocated from Basic Research Program so thanks also belong to the management board Specially the author would like to thank GLCF, University of Maryland for providing the data Without the effort

of University of Maryland the research could not be accomplished

6 REFERENCES

Nguyen Dinh Duong, 1997 Graphical Analysis of Spectral Reflectance Curve Proceedings

of the 18th Asian Conference on Remote Sensing, Kuala Lumpur, Malaysia

Nguyen Dinh Duong, 1998 Total Reflected Radiance Index- An Index to Support Land Cover Classification Proceedings of the 19th Asian Conference on Remote Sensing, Manila, Philippines