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An integrated approach for potato crop intensification using temporal remote sensing data
PHOTOGRAMMETRY 81REMOTE SENSING ISPRS Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
An integrated approach for potato crop intensification using temporal remote sensing data S. Panigrahy *, M. Chakraborty Agricultural Resources Division (RSAG), Space Applications Centre (ISRO), Ahmedabad 380053, India
Received 9 January 1997; accepted 25 July 1997
Abstract Temporal remote sensing data, along with soil, physiographic rainfall and temperature information, were modelled to derive a potato-growing environment index. This was used to identify the agriculture areas suitable for growing potato crops in the Bardhaman district, West Bengal, India. The crop rotation information derived from multi-date Indian Remote Sensing satellite (IRS) LISS-I data were used to characterize the present utilization pattern of the identified area. The result showed that around 99,000 ha agricultural area was suitable for growing potato crops. At present, only 36-38% of this area is under potato cultivation. Around 15% of the area goes to summer rice, and is thus not available for potato crop cultivation. The rest of the identified area, amounting to around 45,000 ha (4U8%), lies fallow after the harvest of kharif rice. This area thus, if given priority under the potato crop intensification programme initiated by the Government of West Bengal, has a high probability of success. 0 1998 Elsevier Science B.V. AI1 rights reserved. Keywords:
crop intensification;
site suitability;
potato; remote sensing; GIS; physiography; soil
1. Introduction West Bengal is one of the major potato growing states of India, having a 25% share in the national production (Anon., 1993). The crop was introduced in the state as early as 1902 (Pushkarnath, 1969). However, it entered into commercial cultivation only 3 decades ago. The state has recorded a steady increase in the acreage under this crop during the past 10 years. Currently around 230,000 ha is under potato cultivation in the state. Though the crop was first introduced in the Darjeeling hills, commercial agriculture thrived best in the plains of Gangetic Bengal. Potato (Solanum tuberosum, L.), being a * Corresponding author. Fax: +91 079 462 677.
temperate plant, thrives best under certain climatic, soil and physiographic conditions. Adaptation of the plant to local climate has been successfully carried out through plant breeding and plant propagation methods. Three districts, Hughli, Bardharnan and Midnapore, contribute more than 80% to the state production. Since this crop is under the growing phase in these districts, there is still a large potential area available for this cultivation. The all lndia potato improvement project aims to intensify the growing of potatoes in different areas through an ideal cropping pattern and crop rotation. The present work was carried out to develop a procedure to identify the most suitable areas as an input for planning to implement such projects. Satellite remote sensing is one of the best tools
0924-2716/98/$19.00 0 1998 Elsevier Science B.V. All rights reserved. PIZ SO924-2716(97)00029-4
S. Panigrahy, M. Chakraborty/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
available to derive accurate and timely information on the spatial distribution of crops over large areas. Crop inventory using space-borne remote sensing data is more than a decade old in India (Anon., 1994). Data from the Indian Remote Sensing satellites IRS lA, 1B have been used successfully to obtain production forecast of rice and mustard crops in West Bengal (Panigrahy et al., 1993). Satellite remote sensing data along with other collateral data can be used in a geographic information system (GIS) to derive information on potential growing areas and current areas under any particular crop. In addition, one can integrate crop rotations being practised to characterize the utilization pattern of the identified sites. This will optimise the integrated crop intensification schemes envisaged by the Department of Agriculture for sustainable increase in crop production. This paper presents the methodology used for the identification and characterization of the potential potato growing area in the Bardhaman district of W. Bengal using temporal satellite digital data from different sensors in a GIS environment. 2. Study area The study area is the Bardhaman district in West Bengal, lying between 86”50’and 88”30’E and 23”OO and 24”OO’N.The district has a geographic area of 702,925 ha within 33 blocks. Around 62.5% of the area is under agricultural use (SAC, 1995). Potato is grown as an irrigated crop during December-March. Generally, medium late varieties are grown having a duration of 3-3.5 months. As reported by the state agricultural statistics, the crop is spread over 13 blocks in the eastern part of the district. 3. Materials and methods The Indian Remote Sensing Satellites (IRS) 1A and 1B provide data in the red, blue, green and NIR bands with 72 m (LISS-I) and 36.5 m (LISS-II) spatial resolution. IRS 1C Wide Field Sensor (WiFS) provides data in the red and NIR bands with 188 m spatial resolution with a 5-day temporal resolution. In this study, LISS I data acquired on January 21, 1993, January 14, 1994, and January 06, 1995 were used to delineate the common intensive sites being under potato crops in the district. IRS 1C WiFS data
55
acquired on January 21 and 30, 1996 were used to map the spatial distribution of potato crops in the district at a scale of 1: 250,000. Soil and physiography information were derived from the maps prepared at a scale of 1: 250,000 by the National Bureau of Soil Survey and Land Use Planning, Calcutta. A geographic data base of the area was created using the Survey of India (SOI) topographic map on a scale of 1: 250,000. The district and block boundaries were digitised using Universal Transverse Mercator (UTM) projection, All remote sensing data were brought into this geographic base through map to image and image to image registration following standard methods of affine transformation and resampling. The soil and physiographic units were digitised in the vector mode. The vectors were then rasterised to the image data base. Ground truth data collected for each season from 1992 to 1994 were used to generate training class signature and classify IRS LISS I data of the corresponding year. These classified images were used to delineate the area which was consistently under potato cultivation in all the three years. The characteristics of this area were used to model the potato growing environment by integrating the soil data, physiography, rainfall and temperature of the sites. The derived indices were then used to delineate the total area having similar growing conditions in the district. The area thus identified formed the potential potato area of the district. IRS 1C WiFS data acquired on January 26 and 30, 1996 were classified using a maximum likelihood classifier and the spatial distribution of potato was mapped at a scale of 1: 250,000. This was used to delineate the suitable area which was not currently under potato cultivation. Crop rotation information was then used to characterize this area in terms of their current utilization practices. Multi date IRS LISS I data acquired between October 25, 1992 and March 17, 1993 were used to derive the crop rotation practice of the district. The details of the methodology used and results obtained for crop rotation mapping are given by Panigrahy and Sharma (1997). Using the crop rotation information, the areas were categorised as (1) currently growing potato, (2) currently under other crops, and (3) currently left fallow. The sites of the third category were characterized as priority areas for potato cultivation. The overall
56
S. Panigrahy, M. Chakraborty /ISPRS Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
0 Intensive Pota StteLl
-
soa
Pbyslo.
Temp. dbase
UtUlsation Pattern of New Area
Fig. 1. Methodology used to identify and characterise the potato growing area in the Bardhaman district.
methodology adopted in this study is schematically shown in Fig. 1. The work was carried out using EAWPACE image processing software on the IBM RS 6000/37T computer system. Raster-based GIS functions in ‘Imageworks’ and ‘Xpace’ modules of EAWPACE were used to create raster layers of the soil and physiography of the area. Daily rainfall and temperature data of ten years (1985-1994) for the crop season (October-January) recorded at different locations were used to derive contours through extrapolation. The modelling facility of ‘Xpace’ was used to analyse the raster layers to obtain the indices. ‘Imageworks’ was used to map the spatial distribution of areas having the required indices. This allowed the use of image processing and GIS in an integrated manner which was required for this analysis. 4. Results and discussion Potato is a herbaceous crop grown as a row crop. The crop is sown during late November to early December. After the initial stabilization period the crop growth is very fast. It attains its full vegetative growth by mid-January and appears bright red in the False Colour Composite (FCC) of IRS LISS-I
data (red, green and NIR bands) acquired during the second half of January (Fig. 2). Thus, data acquired during January 15-30 were found suitable to classify the potato crop. Analysis of multi-year data showed that the crop was grown in more than twelve blocks in the district. However, only in four blocks did the crop occupy a large contiguous area. These blocks were Memari I and II, Kalna and Jamalpur. The statistics gathered by the Department of Agriculture records indicated that these were the traditional areas in the state growing potato. The intensive common sites used to model potato growable indices thus mostly belonged to these four blocks. There were twenty categories of soil types in the district. The predominant soil type was clay loam. The district has two distinct physiographic units: the low dissected plateau on the western part, and the alluvial plain. The former has nine sub-units and the later has fourteen sub-units. The analysis of temperature and rainfall data showed no significant variation within the sites. The mean annual rainfall was between 1250 and 1300 mm, more than 90% of this being received during May to September. The mean monthly rainfall during the potato season (November-January) was between 10 and 15 mm. The mean minimum and maximum temperature during November-January was 20°C and 27°C respectively. Hence, these two parameters were not further used in the modelling. The soil and physiography were thus found to be the controlling factors for potato cultivation in this area. The crop was found to be grown in only a few physiographic units. Recent flood plain and meander flood plain sub-units in the alluvial plains were found to be the most dominant physiography for potato, followed by levee and flood plain. Thus, out of the 23 physiographic units, only four were found to be of significance for potato growing. Among the twenty soil categories, six were found to be associated with the potato growing area. Sandy loam, silt loam, and loam were the most significant soils followed by silty clay loam and clay loam. There were a total of fourteen combinations between these four physiographic and six soil categories. Ten out of these fourteen categories were adjudged as the major growing environments (Table 1). The characteristics of these classes were used to delineate similar areas in the district. Potato crop, like most other members
S. Panigrahy, M. Chakraborty /ISPRS Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
57
Fig. 2. Spatial distribution of potato crops as observed in an intensive site in the FCC of IRS 1B LISS-I data acquired during January.
Table 1 Physiographic and soil type combinations found suitable for growing potato crops in the study district Sl. No.
Physiography
Soil
1 2 3 4 5 6 I 8 9 10
18 18 18 18 19 19 19 19 17 14
14 16 19 10 19 16 14 10 19 14
Physiography: 18 is meander flood plain, 19 is recent flood plain, 17 is levee, 14 is flood plain. Soil type: 1Ois loam to clay loam, 14 is sandy loam, 16 is silt loam, and 19 is silt loam to clay loam.
of the Solanaceae family thrives best on soils where adequate nourishment is available in the top layer. The root growth is restricted to S-10 inches of the surface layer. The horizontal expansion of the root and the stolon is known to be best in sandy loam and silt loam soils (Sikka, 1974; Sikka et al., 1974). The physiographic units belonging to different categories of the flood plains assure annual enrichment of nour-
ishment and optimum moisture to the roots. Thus, the indices derived were in accordance to the plant requirement. The total area of the district having these conditions was found to be a little more than 150,000 ha. The agricultural area mask derived from temporal LISS I data, was used to delineate the agricultural area suitable for growing potato crops. The estimated area was around 99,000 ha. Out of this, currently around 35,000 ha are under this crop as derived using IRS 1C WiFS data of January 1996. Fig. 3a shows the potato distribution in the region in IRS 1C WiFS FCC (red and NIR). The potato area mapped at 1:250,000 using WiFS data of two dates is shown in Fig. 3b. As observed from the analysis, there is still a large potential for expanding the potato area (see Fig. 4). The crop rotations practised in the district indicated that only 15% of this area goes to the summer rice, and the rest lies fallow after the harvest of kharif rice. Three blocks (Mangalkote, Bhatar and Ketugram) showed large contiguous areas suitable for this crop, which remain fallow after the harvest of kharif rice. A ground survey of the area indicated that the lack of irrigation facilities is the reason behind the kharif-based single cropping system. Since the area lies in the alluvial plains and has a high
58
S. Panigrahy, M. Chukraborry/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
S. Panigrahy, M. Chakraborty/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
59
Fig. 4. Additional area identified as suitable for growing potato crops in the district mapped at 1 : 250,000 shown with block boundaries.
groundwater potential, this can be exploited in an irrigation system for potato farming. Thus, it is logical to conclude that these three blocks, if included in the potato development scheme (implemented by State Department of Agriculture), could be more successful. 5. Conclusion Digital image processing of space-borne remote sensing data in conjunction with soil and physiography data were used to prescribe and delineate the most favourable growing environments for potato crops in the Bardhaman district. This approach is particularly required for the vegetable, horticultural
and other crops which require a particular environment for a successful introduction. Traditionally, most of these crops are grown by the farmers through their experience and following expert advice of agricultural officials through demonstration field trials. Thus, the areas where this crop is grown intensively, can very well be used to model the growing environment for that region. IRS LISS I data were found to be suitable for generating district level information on crop rotation, agricultural area masks and areas under a particular crop. The Agricultural Ministry envisages a sustainable increase in agricultural production through various schemes such as the integrated cereal, cotton, sugarcane, and potato crops (Anon., 1995). The methodology described in
Fig. 3. (a) Spatial distribution of potato crops in the region as observed in IRS IC WiFS FCC of January 26, 1996. (b) Map derived from classified WIFS data at a scale of 1: 250,000.
60
S. Panigrahy, M. Chakraborty/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
this paper can be used to derive information which will be a direct input in such programmes. Since the block is the unit for implementation of such schemes, the WIFS data can be used to identify and qualify the potential blocks. For a detailed planning, the LISS II/III sensor with its high spatial resolution can be used. Thus the remote sensing data currently available from different sensors of the Indian Remote Sensing satellites can be used in a complementary way to derive information as an input to the planning and implementation of integrated crop production schemes. Acknowledgements The authors are thankful to the Department of Agriculture, W. Bengal for providing crop statistics and other relevant information useful for this work. Support and guidance rendered by Shri J.S. Patihar, Head, ARD is thankfully acknowledged. All data used in this study and ground truth information collected were under the Crop Acreage and Production Estimation Project sponsored by the Ministry of Agriculture, Govt. of India.
References Anon., 1993. Horticultural statistics. National Horticultural Board, Ministry of Agriculture, Govt. of India, 309 pp. Anon., 1994. Estimates of area and production of principal crops in West Bengal. Directorate of Agriculture, Govt. of West Bengal, Calcutta, 87 pp. Anon., 1995. Striving for higher sustainable productivity through block level planning. Crops Division, Department of Agriculture and Cooperation, Ministry of Agriculture, Govt. of India, 6 PP. Panigrahy, S., Shanna, S.A., 1997. Mapping of crop rotation using multi date Indian Remote Sensing Satellite digital data. ISPRS J. Photogramm. Remote Sensing 52 (2). 85-91. Panigrahy, S., Sharma, S.A., Kundu, N., 1993. Preharvest production forecast of kharif rice for the season 1992-93 in Gangetic W. Bengal using satellite digital data. Scientific Note, RSAMISACICAPE-IIlSN/19/93, Space Applications Centre, Ahmedabad. Pushkarnath, 1969. Potatoes in India. Indian Council of Agricultural Research, New Delhi. SAC, 1995. Manual for crop production forecasting using spaceborne remotely sensed dam. Technical Note, RSAMlSAC/CAPE-IVlN/46/95, Space Applications Centre, Ahmedabad. Sikka, L.C., 1974. New potato varieties and their character. Indian Farming 24, 11-13. Sikka, L.C., Singh, A.K., Malhotra, V.P., 1974. High intensity farming with potatoes in the north-west plains. Indian Farming 24,29-31.
An integrated approach for potato crop intensification using temporal remote sensing data S. Panigrahy *, M. Chakraborty Agricultural Resources Division (RSAG), Space Applications Centre (ISRO), Ahmedabad 380053, India
Received 9 January 1997; accepted 25 July 1997
Abstract Temporal remote sensing data, along with soil, physiographic rainfall and temperature information, were modelled to derive a potato-growing environment index. This was used to identify the agriculture areas suitable for growing potato crops in the Bardhaman district, West Bengal, India. The crop rotation information derived from multi-date Indian Remote Sensing satellite (IRS) LISS-I data were used to characterize the present utilization pattern of the identified area. The result showed that around 99,000 ha agricultural area was suitable for growing potato crops. At present, only 36-38% of this area is under potato cultivation. Around 15% of the area goes to summer rice, and is thus not available for potato crop cultivation. The rest of the identified area, amounting to around 45,000 ha (4U8%), lies fallow after the harvest of kharif rice. This area thus, if given priority under the potato crop intensification programme initiated by the Government of West Bengal, has a high probability of success. 0 1998 Elsevier Science B.V. AI1 rights reserved. Keywords:
crop intensification;
site suitability;
potato; remote sensing; GIS; physiography; soil
1. Introduction West Bengal is one of the major potato growing states of India, having a 25% share in the national production (Anon., 1993). The crop was introduced in the state as early as 1902 (Pushkarnath, 1969). However, it entered into commercial cultivation only 3 decades ago. The state has recorded a steady increase in the acreage under this crop during the past 10 years. Currently around 230,000 ha is under potato cultivation in the state. Though the crop was first introduced in the Darjeeling hills, commercial agriculture thrived best in the plains of Gangetic Bengal. Potato (Solanum tuberosum, L.), being a * Corresponding author. Fax: +91 079 462 677.
temperate plant, thrives best under certain climatic, soil and physiographic conditions. Adaptation of the plant to local climate has been successfully carried out through plant breeding and plant propagation methods. Three districts, Hughli, Bardharnan and Midnapore, contribute more than 80% to the state production. Since this crop is under the growing phase in these districts, there is still a large potential area available for this cultivation. The all lndia potato improvement project aims to intensify the growing of potatoes in different areas through an ideal cropping pattern and crop rotation. The present work was carried out to develop a procedure to identify the most suitable areas as an input for planning to implement such projects. Satellite remote sensing is one of the best tools
0924-2716/98/$19.00 0 1998 Elsevier Science B.V. All rights reserved. PIZ SO924-2716(97)00029-4
S. Panigrahy, M. Chakraborty/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
available to derive accurate and timely information on the spatial distribution of crops over large areas. Crop inventory using space-borne remote sensing data is more than a decade old in India (Anon., 1994). Data from the Indian Remote Sensing satellites IRS lA, 1B have been used successfully to obtain production forecast of rice and mustard crops in West Bengal (Panigrahy et al., 1993). Satellite remote sensing data along with other collateral data can be used in a geographic information system (GIS) to derive information on potential growing areas and current areas under any particular crop. In addition, one can integrate crop rotations being practised to characterize the utilization pattern of the identified sites. This will optimise the integrated crop intensification schemes envisaged by the Department of Agriculture for sustainable increase in crop production. This paper presents the methodology used for the identification and characterization of the potential potato growing area in the Bardhaman district of W. Bengal using temporal satellite digital data from different sensors in a GIS environment. 2. Study area The study area is the Bardhaman district in West Bengal, lying between 86”50’and 88”30’E and 23”OO and 24”OO’N.The district has a geographic area of 702,925 ha within 33 blocks. Around 62.5% of the area is under agricultural use (SAC, 1995). Potato is grown as an irrigated crop during December-March. Generally, medium late varieties are grown having a duration of 3-3.5 months. As reported by the state agricultural statistics, the crop is spread over 13 blocks in the eastern part of the district. 3. Materials and methods The Indian Remote Sensing Satellites (IRS) 1A and 1B provide data in the red, blue, green and NIR bands with 72 m (LISS-I) and 36.5 m (LISS-II) spatial resolution. IRS 1C Wide Field Sensor (WiFS) provides data in the red and NIR bands with 188 m spatial resolution with a 5-day temporal resolution. In this study, LISS I data acquired on January 21, 1993, January 14, 1994, and January 06, 1995 were used to delineate the common intensive sites being under potato crops in the district. IRS 1C WiFS data
55
acquired on January 21 and 30, 1996 were used to map the spatial distribution of potato crops in the district at a scale of 1: 250,000. Soil and physiography information were derived from the maps prepared at a scale of 1: 250,000 by the National Bureau of Soil Survey and Land Use Planning, Calcutta. A geographic data base of the area was created using the Survey of India (SOI) topographic map on a scale of 1: 250,000. The district and block boundaries were digitised using Universal Transverse Mercator (UTM) projection, All remote sensing data were brought into this geographic base through map to image and image to image registration following standard methods of affine transformation and resampling. The soil and physiographic units were digitised in the vector mode. The vectors were then rasterised to the image data base. Ground truth data collected for each season from 1992 to 1994 were used to generate training class signature and classify IRS LISS I data of the corresponding year. These classified images were used to delineate the area which was consistently under potato cultivation in all the three years. The characteristics of this area were used to model the potato growing environment by integrating the soil data, physiography, rainfall and temperature of the sites. The derived indices were then used to delineate the total area having similar growing conditions in the district. The area thus identified formed the potential potato area of the district. IRS 1C WiFS data acquired on January 26 and 30, 1996 were classified using a maximum likelihood classifier and the spatial distribution of potato was mapped at a scale of 1: 250,000. This was used to delineate the suitable area which was not currently under potato cultivation. Crop rotation information was then used to characterize this area in terms of their current utilization practices. Multi date IRS LISS I data acquired between October 25, 1992 and March 17, 1993 were used to derive the crop rotation practice of the district. The details of the methodology used and results obtained for crop rotation mapping are given by Panigrahy and Sharma (1997). Using the crop rotation information, the areas were categorised as (1) currently growing potato, (2) currently under other crops, and (3) currently left fallow. The sites of the third category were characterized as priority areas for potato cultivation. The overall
56
S. Panigrahy, M. Chakraborty /ISPRS Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
0 Intensive Pota StteLl
-
soa
Pbyslo.
Temp. dbase
UtUlsation Pattern of New Area
Fig. 1. Methodology used to identify and characterise the potato growing area in the Bardhaman district.
methodology adopted in this study is schematically shown in Fig. 1. The work was carried out using EAWPACE image processing software on the IBM RS 6000/37T computer system. Raster-based GIS functions in ‘Imageworks’ and ‘Xpace’ modules of EAWPACE were used to create raster layers of the soil and physiography of the area. Daily rainfall and temperature data of ten years (1985-1994) for the crop season (October-January) recorded at different locations were used to derive contours through extrapolation. The modelling facility of ‘Xpace’ was used to analyse the raster layers to obtain the indices. ‘Imageworks’ was used to map the spatial distribution of areas having the required indices. This allowed the use of image processing and GIS in an integrated manner which was required for this analysis. 4. Results and discussion Potato is a herbaceous crop grown as a row crop. The crop is sown during late November to early December. After the initial stabilization period the crop growth is very fast. It attains its full vegetative growth by mid-January and appears bright red in the False Colour Composite (FCC) of IRS LISS-I
data (red, green and NIR bands) acquired during the second half of January (Fig. 2). Thus, data acquired during January 15-30 were found suitable to classify the potato crop. Analysis of multi-year data showed that the crop was grown in more than twelve blocks in the district. However, only in four blocks did the crop occupy a large contiguous area. These blocks were Memari I and II, Kalna and Jamalpur. The statistics gathered by the Department of Agriculture records indicated that these were the traditional areas in the state growing potato. The intensive common sites used to model potato growable indices thus mostly belonged to these four blocks. There were twenty categories of soil types in the district. The predominant soil type was clay loam. The district has two distinct physiographic units: the low dissected plateau on the western part, and the alluvial plain. The former has nine sub-units and the later has fourteen sub-units. The analysis of temperature and rainfall data showed no significant variation within the sites. The mean annual rainfall was between 1250 and 1300 mm, more than 90% of this being received during May to September. The mean monthly rainfall during the potato season (November-January) was between 10 and 15 mm. The mean minimum and maximum temperature during November-January was 20°C and 27°C respectively. Hence, these two parameters were not further used in the modelling. The soil and physiography were thus found to be the controlling factors for potato cultivation in this area. The crop was found to be grown in only a few physiographic units. Recent flood plain and meander flood plain sub-units in the alluvial plains were found to be the most dominant physiography for potato, followed by levee and flood plain. Thus, out of the 23 physiographic units, only four were found to be of significance for potato growing. Among the twenty soil categories, six were found to be associated with the potato growing area. Sandy loam, silt loam, and loam were the most significant soils followed by silty clay loam and clay loam. There were a total of fourteen combinations between these four physiographic and six soil categories. Ten out of these fourteen categories were adjudged as the major growing environments (Table 1). The characteristics of these classes were used to delineate similar areas in the district. Potato crop, like most other members
S. Panigrahy, M. Chakraborty /ISPRS Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
57
Fig. 2. Spatial distribution of potato crops as observed in an intensive site in the FCC of IRS 1B LISS-I data acquired during January.
Table 1 Physiographic and soil type combinations found suitable for growing potato crops in the study district Sl. No.
Physiography
Soil
1 2 3 4 5 6 I 8 9 10
18 18 18 18 19 19 19 19 17 14
14 16 19 10 19 16 14 10 19 14
Physiography: 18 is meander flood plain, 19 is recent flood plain, 17 is levee, 14 is flood plain. Soil type: 1Ois loam to clay loam, 14 is sandy loam, 16 is silt loam, and 19 is silt loam to clay loam.
of the Solanaceae family thrives best on soils where adequate nourishment is available in the top layer. The root growth is restricted to S-10 inches of the surface layer. The horizontal expansion of the root and the stolon is known to be best in sandy loam and silt loam soils (Sikka, 1974; Sikka et al., 1974). The physiographic units belonging to different categories of the flood plains assure annual enrichment of nour-
ishment and optimum moisture to the roots. Thus, the indices derived were in accordance to the plant requirement. The total area of the district having these conditions was found to be a little more than 150,000 ha. The agricultural area mask derived from temporal LISS I data, was used to delineate the agricultural area suitable for growing potato crops. The estimated area was around 99,000 ha. Out of this, currently around 35,000 ha are under this crop as derived using IRS 1C WiFS data of January 1996. Fig. 3a shows the potato distribution in the region in IRS 1C WiFS FCC (red and NIR). The potato area mapped at 1:250,000 using WiFS data of two dates is shown in Fig. 3b. As observed from the analysis, there is still a large potential for expanding the potato area (see Fig. 4). The crop rotations practised in the district indicated that only 15% of this area goes to the summer rice, and the rest lies fallow after the harvest of kharif rice. Three blocks (Mangalkote, Bhatar and Ketugram) showed large contiguous areas suitable for this crop, which remain fallow after the harvest of kharif rice. A ground survey of the area indicated that the lack of irrigation facilities is the reason behind the kharif-based single cropping system. Since the area lies in the alluvial plains and has a high
58
S. Panigrahy, M. Chukraborry/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
S. Panigrahy, M. Chakraborty/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
59
Fig. 4. Additional area identified as suitable for growing potato crops in the district mapped at 1 : 250,000 shown with block boundaries.
groundwater potential, this can be exploited in an irrigation system for potato farming. Thus, it is logical to conclude that these three blocks, if included in the potato development scheme (implemented by State Department of Agriculture), could be more successful. 5. Conclusion Digital image processing of space-borne remote sensing data in conjunction with soil and physiography data were used to prescribe and delineate the most favourable growing environments for potato crops in the Bardhaman district. This approach is particularly required for the vegetable, horticultural
and other crops which require a particular environment for a successful introduction. Traditionally, most of these crops are grown by the farmers through their experience and following expert advice of agricultural officials through demonstration field trials. Thus, the areas where this crop is grown intensively, can very well be used to model the growing environment for that region. IRS LISS I data were found to be suitable for generating district level information on crop rotation, agricultural area masks and areas under a particular crop. The Agricultural Ministry envisages a sustainable increase in agricultural production through various schemes such as the integrated cereal, cotton, sugarcane, and potato crops (Anon., 1995). The methodology described in
Fig. 3. (a) Spatial distribution of potato crops in the region as observed in IRS IC WiFS FCC of January 26, 1996. (b) Map derived from classified WIFS data at a scale of 1: 250,000.
60
S. Panigrahy, M. Chakraborty/ISPRS
Journal of Photogrammetry & Remote Sensing 53 (1998) 54-60
this paper can be used to derive information which will be a direct input in such programmes. Since the block is the unit for implementation of such schemes, the WIFS data can be used to identify and qualify the potential blocks. For a detailed planning, the LISS II/III sensor with its high spatial resolution can be used. Thus the remote sensing data currently available from different sensors of the Indian Remote Sensing satellites can be used in a complementary way to derive information as an input to the planning and implementation of integrated crop production schemes. Acknowledgements The authors are thankful to the Department of Agriculture, W. Bengal for providing crop statistics and other relevant information useful for this work. Support and guidance rendered by Shri J.S. Patihar, Head, ARD is thankfully acknowledged. All data used in this study and ground truth information collected were under the Crop Acreage and Production Estimation Project sponsored by the Ministry of Agriculture, Govt. of India.
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