An application of GIS and Remote Sensing for Analysis of Agricultural Development-Induced Changes in Land Use: A case study in Lao PDR pdf

An application of GIS and Remote Sensing for Analysis of Agricultural Development-Induced Changes in Land Use: A case study in Lao PDR By Boundeth Southavilay1), 2), Teruaki Nanseki 3) The 30th APAN Meeting August 2010, in Hanoi, Vietnam 1) Graduate school of Bioresource and Bioenvironmental Science, Kyushu University, Japan 2).Department of Planning, Ministry of Agriculture and Forestry, Lao PDR 3) Faculty of Agriculture, Kyushu University, Japan E-Mails: boundeth_jong@yahoo.com; nanseki@agr.kyushu-u.ac.jp Contents Introduction Statement of problems Objectives Materials and Methods Study area Results and Discussions Conclusions Introduction • In the last decade, in Laos GIS and Remote sensing (RS) has not much used in countrywide, including agriculture sector did not applied this technique for their agricultural development and land use planning • A meanwhile, in that times agriculture lands in Laos were transformed from subsistence farming in uneconomic-sized farms to commercial and market-oriented farms These transformed sometimes happens in improperly ways and induced to change in land use and land covers by despoilment of forest covers and traditional farming system • The problems above due to lack of an appropriate tool in terms of integrated spatial data on land use/land covers However, recently GIS and remote sensing has been using in several types of works in both government and private agencies As we know, GIS and remote sensing have an important role in linkage and analysis of such data, in particular for detection, interpretation, area calculation, monitoring and future estimating Therefore, this study applied GIS and remote sensing for analysis the land use pattern changes Statement of Problems • After 1999, the landscape in the study area has been changed cause of policy implementation such as rubber plantation and irrigation system were installed in the area, and than this place was changed in dynamics way of land use system • The forest area was destroyed by increasingly shifting cultivation and rubber plantation areas • Lack of an appropriate tool for decision support system in terms of land use decision Rubber plantation Shifting cultivation Objectives • To illustrate the change detection of land use and land covers • To create a tool for decision support system in the watershed land use planning by created land zoning Materials and Methods Materials • • • • Satellite images: – Landsat ETM+ (25 January 1999), LIG format • Resolution – 30 m (band 1-5,7) – 15 m panchromatic – Landsat ETM+ (12 March 2004), BIL format • Resolution – 25 m (band 1-5,7) – 15 m panchromatic GIS data bases with thematic maps (Road networks, River networks, Village points, Contour line, DEM and Ground check pointfrom GPS) Topography map 1:100,000 (Schema F-47-142 and F-47-130) Software: ArcView3.2a and Idrisi 32 Methods Geometric correction- to georeference maps to a map coordination system – – Change pixels size- because the pixel sizes of two images are different (30m and 25m) – Image 1999 was registered to local topography maps with 15 ground control points root-mean-square (RMC) error = 0.45 pixels Image 2004 was registered with registered of image 1999 (image to image) RMC= 0.14 pixels Change pixel 30m of image 1999 to 25m of image 2004 NDVI compositing utility – NDVI is useful for identifying of the green leaf from other objects (water, soil…) It is expressed value -1 to with representing non vegetation – NDVI solve the shadow problem NDVI image NDVI= (b4-b3)/(b4+b3) Methods (cont.) • Images interpretation by Supervised classification Training area (AOI) • Supervised classification – Maximum likelihood method The training area from two images 345, and 2ndvi7 in the1999 and 2004 – classified to 11 classes • Create zone by overlaid three physical data (Ground data, GIS data and image classification) The area is located in the northern Laos, Lat: 65º07'16" to 67º59'13" Long: 222º79'96" to 225º56'22" 43 villages Study area 1250msl 300msl • • Area 696 km2 • Watershed boundary area = 22 km2 • Elevation from 300 to 1,235 msl 10 The lowland farms are located between 300 to 450 msl Results and Discussions • The result of interpretation of two images ETM+1999 and ETM+2004, it provided two land use maps of 1999 and 2004 In each map was classified into 11 categories of land use/land cover types Land covers 1999 Land covers 2004 Intensive of changed areas 11 1999 land use classes 2004 Km2 % Km2 % Dark evergreen forest 199.54 28.66 148.7 21.4 Bright evergreen forest 173.94 24.99 134.8 19.4 Disturbed forest/fallow 164.27 23.60 305.1 43.8 Bamboo 22.98 3.30 12.4 1.8 Field crop 32.53 4.67 4.0 0.6 Wet paddy 24.08 3.46 23.6 3.4 0 10.5 1.5 22.56 3.24 0 Reservoir 0.02 0.00 6.6 0.9 Mekong 6.62 0.95 3.1 0.4 Sandy area 1.70 0.24 4.1 0.6 47.92 6.88 43.2 6.2 696.2 100.00 696.2 Results of Maximum Likelihood Classification of two images 1999 and 2004 100.0 Irrigation paddy Bare land/Wet soil Shrub/other crops Total Changes land use classes Changed Dark evergreen forest Bright evergreen forest Disturbed forest/fallow Bamboo Field crop Wet paddy Irrigation paddy Bare land/Wet soil Reservoir Mekong Sandy area Shrub/other crops Km2 Percentage (%) -50.84 -39.14 140.83 -10.58 -28.53 -0.48 10.5 -22.56 6.6 -3.52 2.4 -4.72 -25.48 -22.50 85.73 -46.04 -87.70 -1.99 -100.00 -53.17 141.18 -9.85 Change rate (%km2/year) -5.10 -4.50 17.15 -9.21 -17.54 -0.40 0.00 -20.00 0.00 -10.63 28.24 12 -1.97 Cheng detection • • The change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times (Singh, 1989) The change detection of land use and land cover of the study area was analyzed by cross-classification technique– by overlaid of two land use maps 2004 1999 + = = The change detection provides the characteristic changes of each land use type 13 Legend: DT‐ Disturbed forest/fallow EF‐ Evergreen forest FC‐ Field crop BB‐ Bamboo BL‐Bare land WPD‐ Wet paddy IPD‐ Irrigation paddy RV‐ Reservoir 14 detection of land use/land cover by crossclassification during 1999 to 2004 No Land use change 1999-2004 Pixels Hectares Km2 % Disturbed > Evergreen Forest 42676 2,667.25 26.67 3.83 Evergreen Forest > Disturbed 215062 13,441.38 134.41 19.31 Field crop > Disturbed 35353 2,209.56 22.10 3.17 Bare land > Disturbed 38975 2,435.94 24.36 3.50 Disturbed > Field crop 867 54.19 0.54 0.08 Wet paddy > Field crop 932 58.25 0.58 0.08 Disturb > Wet paddy 5504 344.00 3.44 0.49 Bare land > Wet paddy 7702 481.38 4.81 0.69 Disturbed > Irrigation paddy 5883 367.69 3.68 0.53 10 Field crop > Irrigation paddy 476 29.75 0.30 0.04 11 Wet paddy > Irrigation paddy 5398 337.38 3.37 0.48 12 Disturbed > Reservoir 2627 164.19 1.64 0.24 13 Wet paddy > Reservoir 1941 121.31 1.21 0.17 14 Evergreen Forest > Bare land 3297 206.06 2.06 0.30 15 Disturbed > Bare land 20361 1,272.56 12.73 1.83 16 No changes 726786 45,424.13 454.24 During years land use types were changed to shifting cultivation: 18,100ha 65.25 Total 1113840 69615 696.15 100.00 15 Land use changed in watershed boundary May,1999 March, 2004 Dense forest Open forest Shifting cultivation Bamboo Field crop Wet paddy Irrigated paddy field Reservoir Shrub land/other Dense forest Open forest Shifting cultivation Bamboo Field crop Wet paddy Bare land Shrub land/other Hectares 14000 Irrigated paddy (dry season) 12000 Area (ha) 1999 Land use types Land use/land cover changes from 1999 to 2004 Reservoir 10000 Bare land/wet soil 8000 Field crop 6000 2004 % Hectares % 202.44 0.92 0.00 0.00 467.82 2.14 551.38 2.51 0.00 0.00 830.69 3.79 46.44 0.21 831.81 3.79 356.69 1.63 Wet paddy (rainy season) 2000 0.00 Bamboo 4000 0.00 952.56 4.34 740.25 3.37 Shrub/other crops Year Dense forest Mix-deciduous forest Bamboo Shifting cultivation Field crop Wet paddy Irrigation paddy Bare land/wet soil Reservoir Shrub/other crops 1596.69 7.28 1524.56 6.95 Mixed-deciduous forest 5286.25 24.10 2827.38 12.8 Dense forest 5813.31 26.50 4112.13 18.7 Shifting cultivation 6061.94 27.64 11657.81 53.1 21935.50 100.0 21935.5 100.0 Total areas 16 Zonation Ground information  Combine land use  type/land holding  in the villages Population and  village location GIS data Raster maps: Slope,  DEM Vector maps: river,  boundary Watershed Zonation  map  Remote Sensing Composite/NDVI  maps  Land use/land  cover Decision Support  Land use planning  • The zone was created by overlaid of three physical information (Ground data, GIS data and satellite imagery data) • The zonation can be regarded as a tool for sustainable agricultural development in the watershed area 17 Suggestion zones for sustainable of watershed management Buffer zone Conservation zone This zone is designed to link between development and conversation zones Land use option: field crop, fruit tree and commercial tree Area covered 25% The main purpose of this zone is to protect forest covers because this zone included headwater, district protected area and high forest cover and biodiversity Area covered 43% Development zone  The development zone includes integrated farming systems and more commonly associated with upland areas Located along the river banks and foothills Land use options: paddy, fish ponds, rice/fish, terraced paddy, grazing, field crops, fruit trees, commercial tree Area covered: 32% 18 The optional land use for sustainable agricultural development in the watershed area x=Restricted potential, xx=Medium potential, xxx=High potential, o=not considered appropriate 19 The existing of land cover in the study area Development zone Conservation zone Conservation zone Buffer zone Conservation zone Buffer zone Development zone 21 Conclusions For 1st objective 1.The total areas of the fallow forest were doubly increased from 16,427 in 1999 to 30,510 in 2004 This land use type was high potential to be mixed by different types of land use such as disturbed forest/fallow forest/shifting cultivation/rubber plantation 2.Based on our results suggest that after irrigation dam was constructed, several types of land use areas were changed (decreased/increased) and fragmented (field crop, evergreen forest, fallow forest) as a result of both farmers who lost their lands and turned to clear-cut forest areas for upland rice cultivation, and private investment on commercial tree (rubber plantation) 22 Conclusions (cont.) For 2nd objective 1.The tool for decision support system in sustainable of agricultural development in this study is the land use zoning was created by GIS and remote sensing technique By created main land use zones Conservation zone Buffer zone Development (Agricultural) zone 2.These zones can be the most important tools for agricultural development planning because it provided integrated information on social and physical aspects of the study area 23 Thank you very much for your kind attention 24 ... recently GIS and remote sensing has been using in several types of works in both government and private agencies As we know, GIS and remote sensing have an important role in linkage and analysis of. .. data, in particular for detection, interpretation, area calculation, monitoring and future estimating Therefore, this study applied GIS and remote sensing for analysis the land use pattern changes. .. than this place was changed in dynamics way of land use system • The forest area was destroyed by increasingly shifting cultivation and rubber plantation areas • Lack of an appropriate tool for