J. S. Parihar

Evaluation of RADARSAT Standard Beam data for identification of potato and rice crops in India

Abstract The Canadian satellite RADARSAT launched in November 1995 acquires C-band HH polarisation Synthetic Aperture Radar (SAR) data in various incident angles and spatial resolutions. In this study, the Standard Beam S7 SAR data with 45°–49° incidence angle has been used to discriminate rice and potato crops grown in the Gangetic plains of West Bengal state. Four-date data acquired in the 24-day repeat cycle between January 2 and March 15, 1997 was used to study the temporal backscatter characteristics of these crops in relation to the growth stages. Two, three and four-date data were used to classify the crops. The results show that the backscatter was the lowest during puddling of rice fields and increased as the crop growth progressed. The backscatter during this period changed from −18 dB to −8 dB. This temporal behaviour was similar to that observed in case of ERS-SAR data. The classification accuracy of rice areas was 94% using four-date data. Two-date data, one corresponding to pre-field preparation and the other corresponding to transplantation stage, resulted in 92% accuracy. The last observation is of particular interest as one may estimate the crop area as early as within 20–30 days of transplantation. Such an early estimate is not feasible using optical remote sensing data or ERS-SAR data. The backscatter of potato crop varied from −9 dB to −6 dB during the growth phase and showed large variations during early vegetative stage. Two-date data, one acquired during 40–45 days of planting and another at maturing stage, resulted in 93% classification accuracy for potato. All other combinations of two-date data resulted in less than 90% classification accuracy for potato.

Comparative evaluation of the sensitivity of multi‐polarized multi‐frequency SAR backscatter to plant density

Interaction of synthetic aperture radar (SAR) with vegetation is volumetric in nature, hence SAR is sensitive to the variation in vegetation density. At the same time SAR is also sensitive to other target properties such as canopy structure, canopy moisture, soil moisture and surface roughness of the underlying soil. However, the sensitivity of SAR backscatter to the vegetation density depends upon the frequency, polarization and angle of incidence at which the SAR is operated. This paper provides comparative evaluation of the sensitivity of multi‐frequency and multi‐polarized SAR backscatter to the plant density of Prosopis juliflora, a thorny plant. Monitoring of P. juliflora is of importance as the state forest department introduced it to arrest the spread of desert. In carrying out this study, data from the SIR‐C/X‐SAR mission over parts of Gujarat, India, have been used. In the present study, the variation of multi‐frequency (L and C) and multi‐polarized (HH, VV and VH) SAR backscatter with plant density has been studied. The results clearly indicate that cross‐polarized SAR backscatter at longer wavelength is the appropriate choice for the quantitative retrieval of plant density.

Role of middle infrared bands of Landsat thematic mapper in determining the classification accuracy of rice

Abstract Accuracy of discriminating rice crop from other vegetation classes investigated using different band combinations of Landsat Thematic Mapper (TM) data over an area in Orissa state of India. Colour-infrared (CIR)aerial photographs of 1:18,000 scale were used to prepare base maps at 1:5,000 scale to identify training areas. A maximum likelihood classification of the training class pixels were done using three band combinations viz. TM 1234, TM 2345, TM 2347, Classification accuracy using different band combinations was computed from the error matrices of classified training class pixels. The results showed that the classification accuracy of rice was significantly greater in TM 2345 and TM 2347 band combinations than in TM 1234.

Wheat acreage estimation for Haryana using satellite digital data

This paper summarizes the procedures adopted and results obtained since 1985–86 for wheat inventory for Haryana using satellite digital data (MSS: 1985–86 to 1987–88, LISS-I: 1988–89 onwards). The approach followed is based on sample segments (10 × 10 km during 1985–86 to 1988–89, 7.5 × 7.5 km during 1989–90) and 10 percent sampling fraction and stratified sample design. There has been consistent improvement in accuracy over the years as judged from lower biases when compared with Bureau of Economics and Statistics (BES) acreage estimates and higher precision. In 1989–90, the state-level estimate achieved an accuracy goal of 90 percent at 90 percent confidence interval. A number of studies which have been carried out to study effect of choice of sensor, acquisition date, stratification approach, classification procedure on wheat inventory are also mentioned.

Spectral characteristics of sensors onboard IRS-1D and P6 satellites: Estimation and their influence on surface reflectance and NDVI

This paper reports the results of a modeling study carried out with two objectives, (1) to estimate and compare effective spectral characteristics (central wavelength, bandwidth and bandpass exo-atmospheric solar irradiance Eo) of various spectral channels of LISS-III, WiFS, LISS-III*, LISS-IV and AWiFS onboard Indian Remote Sensing Satellites IRS-ID and P6 using moment method based on the laboratory measurements of sensor spectral response, and (2) to quantify the influence of varying sensor spectral response on reflectance and Normalized Difference Vegetation Index (NDVI) measurements using surface reflectance spectra corresponding to different leaf area index conditions of crop target obtained through field experiment. Significant deviation of 4 to 14 nm in central wavelength and 1.6 to 14.07 nm in spectral width was observed for the corresponding channel of IRS sensors. Coefficient of variation of the order of 0.1 to 1.11% was noticed in Eo among various IRS sensors, which could induce a difference of 0.72 to 3.35% in the estimation of top of atmosphere reflectance for crop target. The variation in spectral response of IRS sensors implied a relative difference of the order of 0.91 to 3.38% in surface reflectance and NDVI measurements. Polynomial approximations are also provided for spectral correction that can be utilized for normalizing the artifacts introduced due to differences in spectral characteristics among IRS sensors.

Spatiotemporal modelling of methane flux from the rice fields of India using remote sensing and GIS

Rice fields have been accredited as an important source of anthropogenic methane, with estimates of annual emission ranging from 47 to 60 Tg per year, representing 8.5–10.9% of total emission from all sources. In this study, attempts have been made to derive the spatial and temporal pattern of methane emitted from the rice lands of India using an integrated methodology involving satellite remote sensing and geographic information system (GIS) techniques. Multidate SPOT VGT 10‐day Normalized Difference Vegetation Index (NDVI) composite data for a complete year were used to map the rice area, delineate single‐ and double‐cropped rice areas, crop calendar and growth stages. Rainfall, digital elevation and irrigation data were integrated to stratify the rice area into distinct categories related to methane emission. Preliminary analysis of the methane emission pattern was carried out using published values. The results show that around 91% of total methane emission results from wet‐season rice, contributing 4.66 Tg per year. The temporal pattern shows that August and September are the months of peak emission during the wet season, and March and April during the dry season.

Pre-harvest state level wheat acreage estimation using IRS-IA LISS-I data in Punjab (India)

Abstract Wheat acreage of the state of Punjab, India was estimated using single-acquisition Indian Remote Sensing Satellite (IRS)-1A LISS-I digital data during the 1988–89 wheat season. The methodology consisted of stratified sample design, a 10 km by 10 km sample segments, a 10 per cent sample fraction and MXL-supervised classification. Data of February 1989 were used and results were available by 11 April 1989, before the start of harvesting. The estimated acreage of 3–128±0–171 million hectares (Mha) of wheat compares favourably with the Governments estimate of 3–156 Mha. This satisfies the goal of 90 per cent accuracy at 90 per cent confidence level.

Concurrent use of active and passive microwave remote sensing data for monitoring of rice crop

Estimation of crop area, growth and phenological information is very important for monitoring of agricultural crops. However, judicious combination of spatial and temporal data from different spectral regions is necessary to meet the requirement. This study highlights the use of active microwave QuikSCAT Ku-band scatterometer and Special Sensor Microwave/Imager (SSM/I) passive microwave radiometer data to derive information on important phenological phases of rice crop. The wetness index, a weekly composite product derived using brightness temperatures from 19, 37 and 85 GHz channels of SSM/I, was used to identify the puddling period. Ku-band scatterometer data provided the signal of transplanted rice seedlings since they acts as scatterers and increases the backscattering. Dual peak nature of temporal backscatter curve around the heading stage of rice crop was observed in Ku-band. The decrease of backscatter after first peak was associated with the threshold value of 60% crop canopy cover. The symmetric (Gaussian) and asymmetric (lognormal) curve fits were attempted to derive the date of initiation of the heading phase. The temporal signature from each of these sensors was found to complement each other in crop growth monitoring. Image showing pixel-wise timings of heading stage revealed the differences exists in various parts of the study area.

Comparative performance of thematic mapper middle-infrared bands in crop discrimination

Single-date classification accuracies of wheat, mustard and gram were investigated using Landsat TM data of five acquisition dates (24 January, 9, 16, 25 February and 12 March 1988) and combinations of three (TM234, TM345, TM347) and four (TM1234, TM2345, TM2347) bands over an irrigated, optimum-fertility site in Hisar (Haryana). Differences in classification accuracies were tested for significance using paired sample t-test. Inclusion of middle-infrared (MIR) bands (TM5, TM7) improved the classification accuracies in all cases except TM347 for wheat and gram. Classification accuracies with TM5 were significantly higher than comparable combinations having TM7. Lower classification accuracies with TM7 are probably due to higher within-class variability of this band.

Effect of acquisition date and TM spectral bands on wheat, mustard and gram classification accuracies

Single date classification accuracies of wheat, mustard and gram were investigated using TM data of five acquisition dates (January 24, February 9, 16,25 and March 12, 1988) and four band-combinations (TM 234 TM 345, TM 1234 and TM 2345) over an irrigated, optimum fertility site in Hisar (Haryana). Accuracies for wheat and gram were lowest on January 24 for all band-combinations and improved with later acquisitions. An interaction between acquisition date and band combination was apparent as accuracies with most optimal combinations remained high over the period from February 9 to March 12 ,while those with sub optimal combinations fluctuated widely from one date to another. The band-combinations which included middle-infrared (TM 2345 and TM 345) showed highest accuracies irrespective of crop and acquisition date while band combination of TM 234 consistently had lowest accuracies.