Rice-acreage estimation for Orrisa using remotely sensed data

Rice is one of the most important foodgrains grown in India. Attempts have been made to estimate kharif rice acreage of Orissa state since 1986 using digital remote sensing data from Landsat MSS/TM and/or IRS-1A. Accuracies of the estimates obtained have been evaluated against BES (Bureau of Economics and Statistics) estimate. This paper describes the methodology adopted for rice acreage estimation of Orissa state, the results obtained for three years, i.e. 1986–87, 1988–89 and 1989–90, and their accuracy.     

Multiple forecasts of kharif rice in orissa state-four year experience of fasal pilot study

Considering the requirement of multiple pre-harvest crop forecasts, the concept of Forecasting Agricultural output using Space, Agrometeorology and Land based observations (FASAL) has been formulated. Development of procedure and demonstration of this technique for four in-season forecasts for kharif rice has been carried out as a pilot study in Orissa State since 1998. As the availability of cloud-free optical remote sensing data during kharif season is very poor for Orissa state, multi-date RADARSAT SCANSAR data were used for acreage estimation of kharif rice. Meteorological models have been developed for early assessment of acreage and prediction of yield at mid and late crop growth season. Four in-season forecasts were made during four kharif seasons (1998-2001); the first forecast of zone level rice acreage at the beginning of kharif crop season using meteorological models, second forecast of district level acreage at mid growth season using two-date RADARSAT SCANSAR data and yield using meteorological models, third forecast at late growth season of district level acreage using three-date RADARSAT SCANSAR data and yield using meteorological models and revised forecast incorporating field observations at maturity. The results of multiple forecasts have shown rice acreage estimation and yield prediction with deviation up to 14 and 11 per cent respectively. This study has demonstrated the potential of FASAL concept to provide inseason multiple forecasts using data of remote sensing, meteorology and land based observations.     

Kharif rice acreage estimation in Orissa using NOAA-AVHRR data

Rice-acreage estimation of Orissa state was carried out using single-date NOAA-AVHRR data. Selection of optimum date of data acquisition for this purpose was studied using data of six acquisition dates viz. October, 3, 12, 21, 29, November 7 and 26, 1989. Comparative performance of MXL classification of two NOAA bands (Band-1: 0.58–0.68 μm and Band-2: 0.73–1.10 μm) and Normalised Difference Vegetation Index (NDVI) derived from these two-band data was examined. Acreage thus estimated was compared against Bureau of Economics and Statistics (BES) estimate of the same year. The acreage estimation obtained by two band classification was closer to BES estimate than that based on NDVI. Data acquired in the month of October have given better estimate for state level rice acreage than that acquired in the month of November.     

District wise yield models of rice in Bihar based on water requirement and meteorological data

Pre-harvest crop production forecast has been successfully provided by remote sensing technique. However, the probability to get cloud-free optical remote sensing data during kharif season is poor. Microwave data having the capability to penetrate cloud is used in the absence of cloud free optical remote sensing data. Yield models in broad band frequency range are in development stage. Meteorological yield models are developed and predicted yield is combined with area estimated by remote sensing data to provide rice production forecast. This paper describes the methodology adopted for improving the predictability of rice yield before harvest of the crop in Bihar province by taking into consideration meteorological parameters during its growth cycle upto October. Models developed using fortnightly meteorological data have been found to give reasonably fair indications of expected yield of rice in advance of harvest. The yield predictions have been made based on meteorological data and effective rainfall based on water requirement calculations representing a group of districts under similar agro-climatic zones, which could be further improved by incorporating meteorological data of individual districts within each group.     

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.     

Earth observations during space shuttle flight STS‐41: Discovery's mission to planet earth

Abstract

Multi‐temporal ERS‐1 SAR data acquired over a large agricultural region in West Bengal was used to classify kharif crops like rice, jute and sugarcane. Rice crop grown under lowland management practice showed a temporal characteristic. The dynamic range of backscatter was highest for this crop in temporal SAR data. This was used to classify rice using temporal SAR data. Such temporal character was not observed for the other study crops, which may be due to the difference in cultivation practice and crop calendar. Significant increase in backscatter from the ploughed fields was used to derive information on onset and duration of land preparations. Synergistic use of optical remote sensing data and SAR data increased the separability of rice crop from homesteads and permanent vegetation classes.     

Agrometeorological rice yield modelling in Karnal

District-level Agromet rice yield model was developed using rice yields of past fourteen years (1981–1994) and meteorological data such as minimum-maximum temperature and sunshine hours in the Karnal district of Haryana state. The Growing Degree Days (GDD), Temperature Difference (TD) and Accumulated Sunshine hours (ASH) were calculated and integrated over three different crop growth phases to study their influence on district-level rice yield. The three growth phases considered for analysis were Active Vegetative Phase (AVP), Reproductive Phase (RP) and Maturity Phase (MP). A two step linear statistical technique was adopted for multiple linear regression analysis. In the first step, best possible subset of independent variables were selected by leaps and bounds technique. In the second step, the multiple regression for each selected subset were carried out and variance, regression coefficients and residuals were computed. The selected subset of independent variables constitute TD at AVP and RP, GDD at RP and ASH at AVP and RP, which resulted in best multiple regression model with R² 0.842 and SEOE 0.663. This model explains about 84 per cent variability in the district-level rice yields. The model predicted 2.537 t ha^?1 rice yield for the kharif 1995 season.     

Irrigation Water Requirements and Supply Analysis in Dehradun Region—An Integrated Remote Sensing and GIS Approach

The paper focuses on analysing the irrigation water supply and demand of different crops under three main canals for kharif and rabi seasons in Dehradun region of Uttaranchal state. Crop acreage maps of rabi and kharif seasons have been prepared using LANDSAT TM 5 digital data by applying different image processing and classification techniques. Crop water and irrigation water requirements of different crops have been computed using CROPWAT computer program. Canal discharges have been compared with the irrigation water planning and management and found to be more than the irrigation water requirements in many months, that shows the need of revising the irrigation water management.     

Derivation of indices using remote sensing data to evaluate cropping systems

This paper presents the work done in Bathinda District of Punjab state of India for evaluating the cropping system efficiency using multi-date, multi-year and multi-sensor satellite based remote sensing data along with various spatial and non-spatial collateral data. Three efficiency indices, such as Multiple Cropping Index (MCI), Area Diversity Index (DI), Cultivated Land Utilization Index (CLUI), have been worked out to characterize the cropping systems. The salient findings point out that, the MCI has, increased remarkably. A further increase is possible by only taking a third crop. The ADI has increased in kharif (rainy) season, due to introduction of rice in the cotton belt, however in rabi (winter) season the ADI has reduced nearly to one, showing it to be a mono-cropped situation. The CLUI is low (> 0.5) in many blocks, showing there is a great scope to improve it. Since in summer the land is remaining unutilized, a summer crop can very well be taken up to improve it.     

Analysis of temporal sar and optical data for rice mapping

This study investigates the potential of multi-temporal signature analysis of satellite imagery to map rice area in South 24 Paraganas district of West Bengal. Two optical data (IRS ID LISS III) and three RADARSAT SAR data of different dates were acquired during 2001. Multi-temporal SAR backscatter signatures of different landcovers were incorporated into knowledge based decision rules and kharif landcover map was generated. Based on the spectral variation in signature, the optical data acquired during rabi (January) and summer (March) season were classified using supervised maximum likelihood classifier. A co-incidence matrix was generated using logical approach for a combined “rabi-summer” and “kharif-rabi-summer” landcover mapping. The major landcovers obtained in South 24 Paraganas using remote sensing data are rice, water, aquaculture ponds, homestead, mangrove, and urban area. The classification accuracy of rice area was 98.2% using SAR data. However, while generating combined “kharif-rabi-summer” landcovers, the classification accuracy of rice area was improved from 81.6% (optical data) to 96.6% (combined SAR-Optical). The primary aim of the study is to achieve better accuracy in classifying rice area using the synergy between the two kinds of remotely sensed data.     

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

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.     

Irrigation command area inventory and assessment of water requirement using IRS-1B satellite data

Monitoring the crop acreage and irrigation water requirements vis-a-vis irrigation water supplies is important to obtain a realistic view of the “irrigation potential” and “potential utilised”. Satellite data provides information on crop area and thereby net irrigation water requirements of crops. A pilot study was taken up in Mahendragarh distributary canal in Haryana State to estimate net irrigation water requirement of crops under 17 minors for kharif and rabi seasons of 1992–93 period using IRS-1B satellite geocoded FCC images. These water requirements, when analysed with canal and tubewell water supplies for crops, show largescale deficiencies in the irrigation command area.     

Mapping and monitoring of Rann (tidal) ingress in Banni Plains,Kachchh, Gujarat using multi-temporal satellite data

The Rann ingress into the ‘Banni Plains’ of Kachchh district, Gujarat which is famous for the sprawling grasslands supporting significant cattle population is taking place at an alarming rate. This has resulted in the desertion of many villages due to intrusion of Rann waters. In the present investigation multi-date satellite data has been analysed to map and monitor the Rann ingress during the period 1975 to 1989. Detailed analysis has brought out that the inundation is quite rapid affecting about 244 sq. km area during 1960–1989 period. Mapping of the creeks has also been done to understand the possible mechanism of ‘Rann ingress’.     

Derivation of crop phenological parameters using multi-date SPOT-VGT-NDVI data: A case study for Punjab

Crop phenological parameters, such as the start and end time of the crop growth, the total length of the growing season, time of peak vegetation and rate of greening and senescence are important for planning crop management and crop diversification/intensification. Multi-temporal remote sensing data provides opportunity to characterize the crop phenology at regional level. This study was conducted during the kharif season of the year 2001–02 for Punjab. The ten-day Normalised Difference Vegetation Index (NDVI) composite products, with 1 km spatial resolution, available from the Vegetation sensor onboard SPOT4 were used for the study. Twenty-one temporal datasets from May 1, 2001 to November 21, 2001 were used. Logical modelling approach was followed to compute the minimum and maximum NDVI, the amplitude of NDVI, the threshold NDVI during sowing and harvest, the crop duration, integrated NDVI and skewness of profile. The analysis showed that before July beginning, in the whole of Punjab, sowing/planting was over. It was found that the crop emergence in the eastern part of the state started earlier than the western region. The maximum NDVI, which represented peak vegetative stage, was above 0.7 and occurred mostly during August. The duration of crops ranged between 90–140 days, with majority between 110–120 days. Total integrated NDVI in Punjab was generally above 60. Using principal component analysis and divergence analysis seven best metrics were selected for crop discrimination.     

Temporal behaviour of surface waterlogged areas using spaceborne multispectral multitemporal measurements

Waterlogging and subsequent salinization and/or alkalization is the major land degradation problem in the irrigation commands of the semi-arid regions. Information on the nature, extent and spatial distribution of waterlogged areas is a pre-requisite for restoration of fertility, which has hitherto been generated conventionally. Realising the potential of spaceborne multispectral measurements in providing reliable information on spatial patterns of waterlogged areas in a timely and cost-effective manner, a study was taken up to delineate and monitor the spatial distribution pattern of waterlogged areas in Mahanadi command Stage-I covering parts of Orissa state, eastern India using Landsat-TM, Indian Remote Sensing satellite (IRS-1A) Linear Imaging Self-Scanning Sensor (LISS-II) and IRS-ID LISS-III data. A systematic on-the-screen visual interpretation approach after geo-referencing and radiometric normalization of digital multispectral data in a Silicon Graphics work station using ERDAS/ IMAGINE software was followed to realize the objectives. Results point to a significant increase in the spatial extent of waterlogged areas. Seasonally waterlogged areas increased from 29330 ha to 33421 ha and permanent waterlogged areas from 10870 ha to 12973 ha during the period 1988–89 to 1999–2000. Methodology and results are discussed in detail.     

In-season time series analysis of Resourcesat-1 AWiFS data for estimating irrigation water requirement

AWiFS sensor on board IRS-P6 (Resourcesat-1), with its unique features—wide swath and 5-day revisit capability provides excellent opportunities to carry out in-season analysis of irrigated agriculture. The study carried out in Hirakud command area, Orissa State indicated that the progression of rice crop acreage could be mapped through analysis of time series AWiFS data set. The spectral emergence pattern of rice crop was found useful to identify the period of rice transplantation and its variability across the command area. This information, integrated with agro-meteorological data, was used to quantify 10-daily canal-wise irrigation water requirement. A comparison with field measured actual irrigation supplies indicated an overall supply adequacy of 88% and showed wide variability at lateral canal level ranging between 18% and 109%. The supply pattern also did not correspond with the chronological variations associated with crop water requirement, supplies were 15% excess during initial part of season (December and January) and were 20.1% deficit during later part of season (February to April). Rescheduling the excess supplies of the initial period could have reduced the deficit to 15% during peak season. The study has demonstrated the usefulness of AWiFS data to generate the irrigation water requirement by mid-season, subsequent to which 38% supplies were yet to be allocated. This would support the irrigation managers to reschedule the irrigation water supplies to achieve better synchronization between requirement and supply leading to improved water use efficiency.     

Evaluating patterns of temporal glacier changes in Greater Himalayan Range,Jammu & Kashmir,India

To account for the variable response of the Himalayan glaciers towards climatic warming during the recent past, an attempt has been made in the present study to evaluate the changes in glacier area and shift in glacier snout position of selected glaciers in a part of the Greater Himalayan Range (GHR), Jammu & Kashmir (J&K), India. Multi-temporal satellite images of different years viz. 1975, 1989, 1992, 2001 and 2007 were used for mapping the boundaries of glaciers. Among the three observation periods (1975–1989/1992, 1989/1992–2001 and 2001–2007), during 1989/1992–2001 the majority of the glaciers exhibited considerable decrease in area. In contrast during 2001–2007, some glaciers exhibited increase in area indicating comparatively cooler climatic conditions as compared to the previous period. With reference to snout retreat, all the glaciers had a fluctuating trend of retreat during the observation periods although the retreat rate was higher during 1989/1992–2001 in some glaciers.     

Coastal geomorphology and sediment distribution mapping using Landsat—TM digital data —A study in Coastal area of parts of Orissa,India

An area of about 1100 sq.km forming a part of east coast of India was taken for digital analysis using the VAX 11/780 image analysis computer system. The data used for the analysis is Thematic mapper data of Landsat 5. By using the maximum likelihood algorithm and the existing ground truth, the area was classified geomorphologicall.. In addition a qualitative mapping of suspended sediments of coastal waters in Bay of Bengal around the estuary of Dhamra river in Orissa has been carried out. In seventeen classes, eleven correspond to geomorphic units and six belongs to different categories of sediments concentration in Coastal waters.     

Study of spectral signatures for exploration of Bauxite ore deposits in Panchpatmali,India

Spectral analysis technique has been utilized to identify the Bauxite mineral occurrences in Panchpatmali, Orissa, India. Spectral processing of Landsat ETM+ data has been carried out by converting the digital data from quantized and calibrated values to reflectance values. Minimum noise fraction transformation is used to determine the inherent dimensionality of reflected Landsat ETM+ data, to segregate noise in the data, and to reduce the computational requirements for subsequent processing and interactively to locate pure pixels within the data-set, projecting n-dimensional scatterplots. Spectral processing results are displayed in the form of images corresponding to each group of pixels (endmembers). Mixed tune matched filtering method has been applied on Landsat ETM+ images which gave three score (abundance) images for three different classes (endmembers) such as Bauxite, vegetation and soil. Further, mineralized zones are identified using image fusion of ERS-2 SAR and Landsat ETM+ data using intensity-hue-saturation technique.     

Delineation of ground water potential zones in a hard Rock Terrain of Bargarh District, Orissa using IRS data

In the present paper, various groundwater potential zones for the assessment of groundwater availability in a hard rock terrain have been delineated with the help of hydrogeological parameters using satellite IRS- 1B-LISS-II digital data. Area selected for this study is a part of Bargarh district, Orissa, India covering an area of about 680 square km. Satellite data has been used to prepare geological-cum-lineaments, geomorphological, landuse and drainage maps. The various thematic maps have been integrated with the help of Geographic Information System to demarcate the poor to excellent groundwater potential zones. Weightage has been given to various groundwater controlling factors to the total groundwater potential in each segment of study area. Subsequently, several sites were selected and pumping tests carded out in the area. The results show that among others, lineaments as well as drainage density are the most important contributory factors in the groundwater potential of various geomorphic units in the area of investigation.