INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 5, No 2, 2014

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1 INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 5, No 2, 2014 Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research article ISSN Integration of high resolution satellite data, DEM and GIS for large scale mapping A case study from lower 1, Singh S.K. 1, Dharumarajan S 1, Dipak sarkar 2 1N.B.S.S & L.U.P (ICAR), Block DK, Sector-II, Salt Lake-Kolkata , West Bengal, India 2N.B.S.S & L.U.P (ICAR), Amaravati Road, Nagpur , Maharashtra, tapati07@yahoo.co.in ABSTRACT The present paper deals with the technique of large scale mapping using satellite data of 5.8m resolution accompanied by DEM in GIS environment essential for farm level planning and development. The study area is located in the lower gangetic alluvial plain of India where elevation ranges from 5 to 14 meter above Mean Sea Level (MSL). Digital interpretation of IRS P6 LISS IV satellite image in conjunction with Survey of India topographical maps and ASTERGDEM of 30meter resolution and subsequent ground data helped to prepare PPU (Physiographic cum photomorphic unit) map which were further correlated with elevation and NDVI values. Soils occurring in different PPU were examined and PPU-soil relationship was developed. The technique of mapping thus can be extended through faster as well as precision mapping at farm level with plot wise information for site-specific management on cost-effective basis. Keywords: Large scale mapping, remote sensing, lower gangetic alluvial plain, Physiographic cum photomorphic unit, PPU-soil relationship 1. Introduction Over the past few decades planners and researchers are highly concerned with precision farming and crop management that requires detail inventory and characterization of the farm or group of farms in order to make realistic, economically viable and environmentally sound crop production decision. For this purpose large scale mapping (1:25,000 or more) and database is the prerequisite as because small and medium scale (1:1M to 1:50,000) data pose problems sometimes not proper due to their coarse resolution. Depending upon the area concerned, either physiographic mapping and/or soil mapping or both are taken into consideration based on catena or toposequence concept. In most cases, landform classification by photo interpretation is considered as the primary step to prepare soil map since landform delineations are mostly associated directly with natural soil bodies (Buringh 1960). In recent trend, there has been the interest in replacing or supplementing the expert judgment of the surveyor by the use of digital terrain analysis (Moore et al 1993; Gessler et al 1995; Bell et al 2000). Rapid development of remote sensing and GIS provide new approaches to meet the demand related modeling (Mermut and Egwarnan 2001; Saheli et al. 2003) which allow to express the relationship explicitly and mathematically for rapid production of output relevant to meet the environment and socio-economic demand. Irvin et al. (1997) were among the first to use terrain parameters to derive soil landscape elements and provide more objective basis for production of soil maps. They compared automated classification of landform with that of the manual delineations by Aerial Photo Interpretation (API) using a small study area. The surface features associated with different land use/land cover reflected on satellite image provide good information to delineate boundaries Submitted on August 2014 published on November

2 accurately through systematic interpretation. This reduces time and traversing for validating soil boundaries. The present study deals with the technique for large scale mapping using high resolution satellite data in continuation of the previous work done for the same area mapped at 1:250,000 (Soil Survey Staff 1992) and 1:50,000 scale (Sarkar et al.2001). 2. Study area The study area is Polba-Dadpur and Chinsurah-Mogra block of Hugli district in Lower Gangetic Alluvial plain of India (Figure 1) covering nearly 18,000 ha area. The mean elevation varies nearly 5 to 14 meter above mean sea level (MSL) and local relief varies from nearly level plain (0-1% slope) to very gently sloping plain (< 2% slope) developed on the alluvium borne by Hugli river in the east and Damodar river in the west. The area is characterized by sub-humid tropical climate with Hyperthermic temperature regime; Ustic soil moisture regime. Paddy is the principal crop followed by vegetables especially potato and other mixed vegetables, wheat and mustard in rabi season including summer vegetables with sporadic distribution of plantations like mango, banana etc. Figure 1: Location map of the study area 346

3 3. Methodology 3.1 Data and Datasets Map overlay techniques coupled with statistical analysis to describe the quantitative relationship between landscape components: landform-land use-soil have been worked out as follows 1. Interpretation of topographical maps and digital elevation model for relief identification 2. Digital image interpretation for land use and land cover study 3. Ground truth verification and soil sampling 4. Automated data management and analysis in GIS 5. Soil laboratory analysis 6. Farm level soil mapping Elevation and slope database prepared for the study area combining with ASTERGDEM of 30 meter resolution and topographical maps of 1:50,000 scales having numbers 79A/4, 79A/8, 79B/1 and 79B/5 prepared by Survey of India. Digital interpretation of IRS-P6 LISS IV satellite image was interpreted using NDVI [(NIR - RED) / (NIR + RED)] techniques for land use and land cover study. The flow chart for the methodology of large scale mapping is shown in figureure 2. Figure 2: Flow chart showing methodology of soil mapping 3.2. Physiographic mapping A series of maps at 1:250,000 and 1:50,000 scales had been consulted for the study area. As the study area is small with single morpholithological character i.e. alluvium; morphometry viz. relief amplitude and slope derived from DEM is considered as basic discriminating criteria for mapping. The area represents a vast monotonous plain with a relief difference of 0 to 2% as such it poses problems to identify landforms observed in surface form. Therefore 347

4 DEM was used as an additional variable with satellite image as the vegetation/ crop cultivation is largely governed by altitude which ultimately helps to divide the area into discrete segments. Following this idea, relationship was established between altitude and land use after transferring raster properties (DEM) into vector attributes (Land use) in GIS environment using TNT mips Pro. Finally a detailed PPU (Physiographic-cum-photomorphic unit) map layer generated and legend was given in continuation of the previous physiographic legend which was further correlated with NDVI values. In this PPU map first, second and third letter represents parent material/physiography, fourth letter presents slope, fifth and sixth letter with subscript of seventh letter (if any) represents landform and lastly eighth and/or ninth letter with subscript (if any) represents land use with image characteristics (Figure 3). Figure 3: Explanation of (a) Physiography cum photomorphic unit and (b) Soil mapping legend 3.3 Ground truth verification and soil sampling Ground truth was done to verify the PPU in the field and depending upon the variation of PPU soil sampling sites were selected. Detailed soil profile study was carried out as per the norms laid down in the soil survey manual (Soil Survey Staff 1993). Soil samples with auger boring were done for specific PPU, soils were correlated and series were identified with phases. Horizon wise soil samples were collected from the representative sites for physical and chemical analysis as per standard methodology. At each site the variation in morphological and site characteristics of soils were studied and recorded. The soil samples of representative soil profile were collected for further studies in the laboratory. Finally soils were classified according to latest Soil Taxonomy (Soil Survey Staff 2003). 3.4 Soil mapping legend Delineation of soil boundaries was made by observing soil characteristics by auger boring observation. Soil distributions were mapped at 25,000 scale showing soil series association and their phases. As the study area represents monotonous flat terrain with negligible relief difference in slope, erosion and stoniness the phases were identified mainly by surface texture. Therefore soil legend depicts the name of series (first one to two letters) followed by surface texture (one to four letters) for phase identification (Figure 3). 4. Results and discussion As per the physiographic mapping of 1:250,000 scale prepared by NBSS & LUP, the study area comes under Bengal basin mainly alluvium and have a great impact on geomorphic units that have occurred under different formation. Two major slope categories were identified i.e. nearly level plain (0-1%) occupying an area of 1,921.7 ha (50.8% of total study area), very gently sloping plain (1-2%) cover an area of 11,568.8 ha (41.9% of total study area). Rest of the area near Hugli river bank comprises of gently sloping (2-3%) area covering nearly ha (7.3% of total study area). The bank of river Hugli (2 to 4 km wide) stands out on 348

5 levee (12 to 14 meter above MSL) which is stable in nature. This levee can be subdivided into subunits viz. 1) upper levee and 2) lower levee. The upper levee is densely populated and occupies an area of 4,950 ha. The lower levee which is the back slope of upper levee formed terraced land with altitudinal range of 10 to 12 meter occupied by plantation. Rest of the area is level plain which was further subdivided into three categories viz. concave, convex and straight slope. 4.1 PPU mapping Different land use/land cover categories were identified in the study area and correlated with altitude by transferring raster properties (DEM) into vector (Land use). From the relationship between altitude and land use (Figure-4) it has been observed that major habitation is found within the altitude of 13 to 14 meters demarcated as Upper levee although habitation is also distributed sporadically throughout the block. Plantation is found within 11 to 13 meters marked as Lower levee. Figure 4: Relationship between altitude and raster cell under different land use category Paddy growing area is mainly concentrated within 5 to 6 meters marked as level plain with concave slope which was further differentiated by their high and low moisture status. Potato growing area with dark pink tone is found to be concentrated within 5 to 8 meters demarcated as level plain with convex slope. Transition zone between paddy and potato growing area comprises mixed vegetable growing area having light pink tone as image characteristics are concentrated within 5 to 7 meters altitude marked as level plain with straight slope. The elements of PPU include parent material/ physiography, slope with curvature or local relief, land use and land cover based on which six units were identified (table 1). These PPU were correlated with NDVI values of field crops and established a definite relation with physiographic units when compared (Table 2). Although the study area covers nearly 18,000 ha of Polba-Dadpur and Chinsurah-Mogra block of the Hugli district detailed PPU (Physiographic cum photomorphic unit) map of two clusters has been shown (Figure 5a). Puinan cluster is located in the western part and Gotu cluster in the eastern part of the block each covering four villages. 349

6 Figure 5a and 5b: Physiography-cum-photomorphic unit map and soil map of study area 350

7 Sl no. Table 1: Description of PPU (Physiographic-cum-Photomorphic Unit) PPU Description Tone 1 Bab4Le1H 2 Bab4Le2Pl 3 Bab4CeP1 4 Bab4CeP2 5 Bab4CxV1 6 Bab4CxV2 Bengal basin alluvial plain, nearly level to very gently sloping upper levee under habitation Bengal basin alluvial plain, nearly level to very gently sloping lower levee under plantation Bengal basin alluvial plain, nearly level to very gently concave slope under paddy cultivation having high moisture Bengal basin alluvial plain, nearly level to very gently concave slope under paddy cultivation having low moisture Bengal basin alluvial plain, nearly level to very gently convex slope under vegetable cultivation dominantly potato Bengal basin alluvial plain, nearly level to very gently convex slope under mixed type of vegetable cultivation Bluish tone mixed with red Dark reddish tone Dark bluish tone Light bluish tone Dark pink Light pink Table 2: Relationship between NDVI and PPU NDVI Value Field crops PPU Minimum Maximum paddy cultivation having low Bab4CeP2 moisture paddy cultivation having high moisture Bab4CeP mixed type of vegetable cultivation Bab4CxV vegetable cultivation dominantly potato Bab4CxV PPU-soil relationship Soil is the result of combined activity and reciprocal influence of parent material, plant and organisms, climate, age of the land and topography. These were termed as soil formers or factors of soil formations. The relation may be expressed as S= f (cl, o,r,p,t ) where S denotes any soil property such as ph, nitrogen, clay; cl, environment climate (rainfall, temperature); o, flora and fauna as biosphere organisms; r, elevation, slope and depth of water table as relief; p, parent material; and t, time or age of land (Jenny, 1941). Soils of alluvial plain are formed under mode of formation. The soils identified in each PPU of Puinan and Gotu cluster are depicted in figure 5b with description of soil mapping units (Table 3 and 4) and characteristics of different soil series (Table 5). 351

8 Table 3: Description of Soil mapping units in Puinan Cluster Map unit Soil Unit Pu-l 5 Da-c Pusil Rasl Dasic Dasicl Nasicl Nacl PPU Units Bab4Cx V1 Bab4Cx V1 Bab4Cx V1 Bab4Ce P1 Bab4Ce P2 Bab4Ce P1 Bab4Cx V 2 Bab4Cx V 2 Soil series Puinan Puinan Ramnaga r Dadpur Dadpur Dadpur Natungr am Natungr am Description Very deep, well drained, coarse-loamy soils with silt loam surface texture on nearly level convex slope upland with slight erosion Very deep, well drained, coarse-loamy soils with loam surface texture on nearly level convex slope upland with slight erosion Very deep, well drained, fine-loamy soils with sandy loam surface texture on nearly level convex slope upland with slight erosion Very deep, poorly drained, fine soils with clay surface texture on nearly level concave slope lowland with very slight erosion Very deep, poorly drained, fine soils with clay surface texture on nearly level concave slope lowland with very slight erosion Very deep, poorly drained, fine soils with silty clay loam surface texture on nearly level concave slope lowland with very slight erosion Very deep, Moderately well drained, fine soils with silty clay loam surface texture on nearly level transition land between upland and lowland with slight erosion Very deep, Moderately well drained, fine soils with clay loam surface texture on nearly level transition land between upland and lowland with slight erosion Soil Taxonomy Fine-silty, Fine-silty, Fine-loamy, aplustepts Fine, Endoaquepts Fine, Endoaquepts Fine, Endoaquepts Fine,, Endoaquepts Fine,, Endoaquepts 352

9 Table 4: Description of Soil mapping units in Gotu Cluster Map unit 2 Soil Unit PPU Units Soil series 1 Da-c Bab4CeP2 Dadpur 3 4 Ra-l 5 Ra-sil Bab4CeP1 Bab4CeP1 Bab4CxV1 Bab4CxV1 Gotu Gotu 6 Go-sil Bab4Le 2Pl Gotu 7 Dasic Dasicl Gosicl Bab4Le 2Pl Ramnagar Ramnagar Gotu Description Very deep, poorly drained, fine soils with clay surface texture on nearly level concave slope lowland with very slight erosion Very deep, poorly drained, fine soils with clay surface texture on nearly level concave slope lowland with very slight erosion Very deep, poorly drained, fine soils with silty clay loam surface texture on nearly level concave slope lowland with very slight erosion Very deep, well drained, fine-loamy soils with loam surface texture on nearly level convex slope upland with slight erosion Very deep, well drained, fine-loamy soils with silt loam surface texture on nearly level convex slope upland with slight erosion Very deep, well drained, fine silty soils with silt loam surface texture on nearly level to very gently sloping levee with slight erosion Very deep, well drained, fine silty soils with silty clay loam surface texture on nearly level to very gently sloping levee with slight erosion Soil Taxonomy Fine, Endoaquepts Fine-silty, mixed Fine-silty, mixed Fine-loamy, Fine-loamy, Fine-silty, mixed Fine-silty, mixed Table 5: Physical and chemical characteristics of soils Depth (cm) Horizon Particle size distribution (%) Sand silt clay ph (1:2.5) EC OC (%) CEC Cmol (+) Kg- 1 Gotu - Fine-silty, mixed Exchangeable cations Cmol (+) Kg-1 Mg+ Na+ + Ca+ + K Ap Bw Bw C C Dadpur - Fine,, Endoaquepts Ap

10 Bw1g Bw2g Bw3g Bw4g Puinan- Coarse-silty, Fluvaquents Ap A C C C C Ramnagar- Fine-loamy, Ap Bw Bw C C Natungram- Fine,, Endoaquepts Ap Bw Bw Bw Bw C Bab4Le2Pl (Bengal basin alluvial plain, nearly level to very gently sloping lower levee under plantation) Levee soil (Bab4Le2Pl) consists of very deep, well drained very gently sloping levee and have yellowish brown to dark yellowish brown silt loam to silty clay loam surface soil and dark brown to very dark grayish brown, silty clay loam to silt loam sub surface soil. Yellowish brown to dark yellowish brown mottles present in the profiles. Levee soil is mostly occupied by banana and mango plantation. The levee soil (Gotu series) is a member of finesilty, family of Bab4CeP1 (Bengal basin alluvial plain, nearly level to very gently concave slope low land under paddy cultivation having high moisture) The Bab4CeP1 soil (Dadpur series) consists of very deep, poorly drained; very dark grayish brown to dark brown silt clay to silty clay loam surface soil and dark gray to very dark grayish, with yellowish brown to dark yellowish brown mottles, having silty clay to clayey sub surface soil and medium sized iron and manganese concretions are common throughout the profile. The soil of Bab4CeP1 (Dadpur series) is a member of fine, family of Endoaquepts. 354

11 Bab4CeP2 (Bengal basin alluvial plain, nearly level to very gently concave slope under paddy cultivation having low moisture) The Bab4CeP2 soil (Dadpur series) consists of very deep, poorly drained, very fine texture soils and have dark brown clayey surface texture with very dark grayish brown to very dark gray, clay to silty clay texture in subsurface. Medium sized iron and manganese concretions present throughout the profile. This soil of Bab4CeP2 (Dadpur series) is a member of fine, family of Endoaquepts Bab4CxV1 (Bengal basin alluvial plain, nearly level to very gently convex slope under vegetable cultivation dominantly potato) The Bab4CxV1 soil consists of very deep, well drained to moderately well drained, sandy loam to loam soils on the surface and silty loam to silty clay loam in the sub surface. Two soil series was identified in Bab4CxV1 unit. Puinan soil series consists of very deep, well drained, coarse loamy texture in control section. The colour of soil in control section varies from light yellowish brown to grayish brown. The soils have yellowish brown to dark yellowish brown mottles in the profile. Puinan soil series is a member of fine-silty, family of. Ramnagar soil series consists of very deep, well drained, fine-loamy texture in control and have dark brown loam to silt loam surface soil dark brown to very dark grayish brown, clay loam to loam sub surface soil with yellowish brown to brownish yellow mottles in the profile. Ramnagar soil series is a member of fine-loamy, family of Bab4CxV2 (Bengal basin alluvial plain, nearly level to very gently convex slope under mixed type of vegetable cultivation) The Bab4CxV2 soil (Natungram series) consists of very deep, moderately well drained, fine, dark brown, moderately acidic, silty clay loam to clay loam texture surface soils and dark brown to very dark gray, silty clay to silt loam texture sub surface soils. Medium sized iron and manganese concretions are present in the profile. The Bab4CxV2 soil (Natungram series) is a member of fine, family of Endoaquepts. 5. Conclusion From the study it can be concluded that applying the technique of large scale mapping using high resolution satellite data accompanied by DEM in GIS environment helps developing PPU-soil relationship for site-specific management on cost-effective basis especially at farm level. Once the PPU-soil relationship established it can be extended for faster mapping at precision level with plot wise information on morphology, resource potential and constraints. 6. References 1. Bell, J.C., D.F. Grigaland P.C.Bates. (2000), A soil-terrain model for estimating spatial patterns of soil organic carbon. P In J.P.Wilson and J.Gallant (ed.) Terrain analysis: Principles and applications. Wiley & Sons. New York 2. Buringh, P. (1960), The application of aerial photographs in soil surveys. Manual of Photographic Interpretation. American Society of Photogrammetry. Washington DC 355

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