Results on potential use of simulated IRS-1C WiFS data for crop monitoring

Some of the basic requirements for cropping system analysis are updated information on crops grown, their phenological behaviour, method and duration of establishment and harvest, inter and intra crop variability, sequential cropping patterns. The next generation Indian Remote Sensing Satellite with high repeat cycle opens new possibility of crop surveys to derive such information. In this study, an attempt has been made to analyse cropping system at district level using simulated IRS-1C Wide Field Sensor (WiFS) data. Data acquired for nineteen dates during 1992–93 season for Bardhaman district, West Bengal has been used. It was feasible to derive accurate information on cropping pattern, crop rotation, crop duration, progress of harvest, crop growth profiles and annual crop acreage using multidate data. It was observed that even a seven to eight day interval of data acquisition during critical growth periods significantly affected classification and identification accuracy.     

Agricultural drought assessment at disaggregated level using AWiFS/WiFS data of Indian Remote Sensing satellites

Spatial differences in drought proneness and intensity of drought caused by differences in cropping patterns and crop growing environments within a district indicate the need for agricultural drought assessment at disaggregated level. The objective of this study is to use moderate resolution satellite images for detailed assessment of the agricultural drought situation at different administrative units (blocks) within a district. Monthly time composite NDVI images derived from moderate resolution AWiFS (60 m) and WiFS (180 m) images from Indian Remote Sensing satellites were analysed along with ground data on rainfall and crop sown areas for the kharif seasons (June – November) of 2002 (drought year), 2004 (early season drought) and 2005 (good monsoon year). The impact of the 2002 meteorological drought on crop area in different blocks of the district was assessed. The amplitude of crop condition variability in a severe drought year (2002) and a good year (2005) was used to map the degree of vulnerability of different blocks in the district to agricultural drought. The impact of early season deficit rainfall in 2004 on the agricultural situation and subsequent recovery of the agricultural situation was clearly shown. Agricultural drought assessment at disaggregated level using moderate resolution images is useful for prioritizing the problem areas within a district to undertake, in season drought management plans, such as alternate cropping strategies, as well as for end of the season drought relief management actions. The availability of ground data on rainfall, cropping pattern, crop calendar, irrigation, soil type etc., is very crucial in order to interpret the seasonal NDVI patterns at disaggregated level for drought assessment. The SWIR band of AWiFS sensor is a potential data source for assessing surface drought at the beginning of the season.     

National Wheat Acreage Estimation for 1995-96 Using Multi-Date IRS-1C WiFS Data

I he aim of the piesent study was to suggest an approach for national level acreage estimation for wheat using satellite remote sensing data and demonstrate its perfromantee Multi-date moderate resolution (188 m) IRS-IC WiFS data sets were used as the core data Sampie segment approach with stratified random sampling was used for the data analysis For making meaningful comparisons over time, multi-date sets were geometncally registered and radiometrically normalised by extracting pseudo-invariant Features and performing regression analysis on the digital numbers of such features The corrected multi-temporal data sets were used in hierarchical classification scheme. The results of this exercise are presented. It appeals that there is an overestimatoin of wheat acreage The sampling effieieney was also low, indicating need to improve sampling strategy Some of the problems encountered and the corrections planned to overcome them are also discussed     

Delineation of surface waterlogged areas in parts of bihar using IRS-1C LISS-III data

Pre-monsoon and post-monsoon surface waterlogged areas were delineated using satellite remote sensing data for Muzaffarpur, Vaishali and Saran districts of North Bihar. Digital data of IRS-1C LISS-III sensor acquired on December 7, 1998 and April 6, 1999 were analyzed using digital image processing software-ERDAS Imagine 8.3.1. The surface waterlogged areas were delineated using modeling technique which is the most advanced and accurate method. Using the modeling technique, a pixel is classified as water if the digital number (DN) value of its Near Infra Red (NIR) band is less than the DN value of the Red band and the Green band, and the Normalized Difference Water Index (NDWI) is greater than or equal to 0.32. The pre-monsoon surface waterlogged areas are found to be 14.02, 23.61 and 9.61 km² while the post-monsoon surface waterlogged areas are found to be 231.83, 118.19 and 176.06 km² for Muzaffarpur, Vaishali and Saran districts, respectively. Also, land use/land cover maps were prepared.     

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.     

Application of digital elevation model and orthoimages derived from IRS-1C pan stereo data in monitoring variations in glacial dimensions

An attempt has been made to study variations in the glacier extent over a period of time using digital elevation model (DEM) and orthoimages derived from IRS-1C PAN stereo pairs of 1997–98 and topographical map surveyed during 1962–63. DEM and orthoimages have been generated using integrated software developed for processing of IRSIC/ID panchromatic stereo data using the softcopy photogrammetric workstation. Case studies of two glaciers, i.e. the Janapa garang and Shaune garang glaciers of the Basapa basin, a sub-basin of Satluj River in India, have been presented here. Generation of DEM has been followed by the estimation of its accuracy. PAN images were interpreted for identification of the snout of the glaciers. The geographical locations of the snouts on the images were compared with the location as mapped on the topographical map of the study area. To verify satellite observations, field investigations were carried out at Shaune garang glacier area. The Janapa garang and the Shaune garang are observed to have retreat of 596m and 923 m respectively. Reduction in the thickness of ice in the deglaciated part of the Shaune garang glacier was estimated on the basis of change in the elevations of the glacial surface from 1963 to 1998.     

Short-Term and Long-Term Geomorphological dynamics of mangalore spits using IRS-1A/1C data

The city of Mangalore is situated at the confluence of rivers Gurpur and Netravati. Two spits are formed in this area, i.e., northern spit of “Bengre” and the southern spit of “Ullal” as the rivers flow close and parallel to the seashore for some distance. The spits have been subjected to constant geomorphological changes in length, width, position, accretion and erosion patterns etc., for the past several decades. A seawall was constructed in 1984 around the tip of Bengre spit and another one along the shoreline of Ullal spit in 1987, by the Government of Karnataka in order to prevent the spits from being eroded. Two breakwaters were also constructed in 1992 near the estuarine mouth as part of the development of old Mangalore Port. The paper presents the results of a study undertaken to identify the geomorphologic changes that occurred in the area, using 1RS-1A/1C data for the years of 1988, 1994. 1996. The study clearly demonstrated that the 1RS data could be effectively utilized for monitoring the geodynamics of an area. It was observed that the spits were highly unstable earlier. However, the construction of seawalls was helpful in arresting the migration of the estuarine mouth and in stabilizing the spits against coastal erosion.     

Study of crop discrimination by simulated IRS 1C LISS-III data

A study on crop discrimination was carried out using simulated IRS 1C LISS-III data produced using visible (to simulate B2, B3) and NIR (to simulate B4) channels from SPOT and middle infrared (MIR) channel (to simulate B5) from TM over a previously investigated test site, characterized by multiple crops and small fields, in Sabarkantha district (Gujarat). The separability amongst dominant kharif season crops, namely, cotton, groundnut, maize, pigeonpea, between crops and various natural vegetation classes was investigated using Jeffries-Matusita (JM) distance, a pair-wise inter-class separability measure. The study highlighted the capability of simulated LISS-III data to be useful in identifying and labelling small fields and the 4-band data set (B2345, i.e., simulated LISS-III) to significantly improve the separability amongst various crops and vegetation over two 3-band sets (B234, equivalent to SPOT)and B345.     

Pass processing of IRS-1C/1D PAN subscene blocks

This paper describes a method for pass processing of IRS-1C/1D imagery acquired by the three CCD arrays of the panchromatic (PAN) camera. It is based on the fact that during a single pass, the image data stream from the three CCD arrays of the PAN camera can be adjusted together as a single image, exploiting the knowledge of the internal geometry and the angular relationships between the CCD arrays. The geometry of this extended image can be rectified with a single ground control point (GCP). A full PAN scene consists of nine subscenes, each with a dimension of 23.5 km×23.5 km. The method is not restricted in the number of continuous full scenes (in the same pass) that can be adjusted. The scale variations between the images from the three detectors are corrected by computing the relative focal lengths of detectors 1 and 3 with respect to detector 2. Two tests were conducted to verify the accuracy of the adjustment procedure. Average root-mean-square (RMS) errors of ±10.5 m in the latitude direction and ±11.3 m in the longitude direction were obtained with a single surveyed GCP and a set of survey points used as checkpoints. The results of the tests show that the adjustment of full PAN scenes, as proposed in this paper, is an effective means of reducing the number of GCPs required for precise determination of ground coordinates.     

Evaluation of potential usefulness of irs-1c wifs simulated data for dryland rabi sorghum crop discrimination

Two band simulad WiFS data for five dates correspfonding to rabi sorghun growing season of 1993-94 has been generated for Aurangabad district of Maharashtra. Ground truth data has been used for supervised classificatioa of one date raw image and five date NDVI of simulated WiFS data and the results were compared with those derived from single date IRS LISS I data. Analysis of classification accuracies indicate that single date WIFS data gives slightly lower accuracy of 79 per cent against 81 per cent obtained for single date LISS I data. Overall accuracy for 5-date WiFS data is 96 per cent which shows that classification performance of five date WiFS NDVI data is far superior to the single date data of the IRS-IC WiFS as well as the IRS LISS I. The study thus shows the importance of temporal domain of data acquisition in sorghum crop discrimination, Growth profile for sorghum and other crop classes were generated from multidate WiFS derived NDVI data. Differences in growth profiles of sorghum vigour classes as well as amongst different crop types and forests corroborate the premise of better discrimination of crop types and their vigour on multidate remotely sensed data.     

Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R ². The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R ² exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.     

Discrimination of newly planted and ratoon crops of sugar cane using multidate IRS-1C liss III data: A knowledge based approach

An advanced and accurate information of sugar cane production is an important component for the management of sugar cane industry. Remote Sensing is most viable technique which can provide the above information well in advance. Stratified sampling technique practiced in Crop Acreage and Production Estimation (CAPE) programme holds good for major crops with non-overlapping growth stages. Discrimination of ratoon and newly planted sugar cane crop is a challenging task. Single date remote sensing data does not suffice to discriminate the above two types of sugar cane. In the present paper, an attempt has been made to show how two date remote sensing data coupled with knowledge based approach dramatically improves the classification accuracy (98%) of sugar cane crop as compared to the stratified sampling approach (less than 90%). This has been demonstrated in a case study comprising parts of two districts of western Uttar Pradesh.     

ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.     

Application of IRS-1A data for delineating buried channels in Southern part of Allahabad district of Uttar Pradesh

Two buried channels were identified in southern part of Allahabad district based on the visual interpretation of IRS-1 A LISS II FCC followed by detailed study of aerial photographs and cheks. It has been concluded on basis of the configuration of the channels that these were initially joined forming one channel which flowed from east to west although the present master slope of the area is from west to east. The present reversal of the drainage might have been caused by the neo-tectonic activity in the area. The buried channels provide potential ground water reservoirs in the area as proved by a few boreholes drilled on the channels. Some part of the area has become waterlogged due to the seepage of water from the canals cutting across one of the buried channels.     

Evaluation of Cartographic accuracy of IRS-1A LISS II data for upgrading linear details on the existing maps (A case study of Chandigarh area)

Considering the fest pace of development, up-to-date maps have become imperative in developmental planning. Conventional map updating techniques are expensive and time consuming. The present paper makes an attempt to tackle the problem using GIS techniques. Maps generated from IRS-1A LISS II data and Survey of India (SOI) toposheets were used as input maps in GIS. These maps were overlaid to obtain the positional errors at road junction points. The area statistics of each sector were calculated taking the SOI map as reference data. The results show that the areas calculated from LISS II data and SOI map are well comparable and the deviations are within 10%, whereas the positional accuracy (MSE) of points is within 30 m. The study demonstrates that the IRS-1A LISS II data can be used for updating of maps on scale 1:100,000 and smaller in areas where linear features are identifiable in the IRS LISS II image.     

An evaluation of supervised classifiers for indirectly detecting salt-affected areas at irrigation scheme level

Soil salinity often leads to reduced crop yield and quality and can render soils barren. Irrigated areas are particularly at risk due to intensive cultivation and secondary salinization caused by waterlogging. Regular monitoring of salt accumulation in irrigation schemes is needed to keep its negative effects under control. The dynamic spatial and temporal characteristics of remote sensing can provide a cost-effective solution for monitoring salt accumulation at irrigation scheme level. This study evaluated a range of pan-fused SPOT-5 derived features (spectral bands, vegetation indices, image textures and image transformations) for classifying salt-affected areas in two distinctly different irrigation schemes in South Africa, namely Vaalharts and Breede River. The relationship between the input features and electro conductivity measurements were investigated using regression modelling (stepwise linear regression, partial least squares regression, curve fit regression modelling) and supervised classification (maximum likelihood, nearest neighbour, decision tree analysis, support vector machine and random forests). Classification and regression trees and random forest were used to select the most important features for differentiating salt-affected and unaffected areas. The results showed that the regression analyses produced weak models (<0.4 R squared). Better results were achieved using the supervised classifiers, but the algorithms tend to over-estimate salt-affected areas. A key finding was that none of the feature sets or classification algorithms stood out as being superior for monitoring salt accumulation at irrigation scheme level. This was attributed to the large variations in the spectral responses of different crops types at different growing stages, coupled with their individual tolerances to saline conditions.     

Forest cover mapping of East district,Sikkim using IRS-1A LISS II satellite data

Remote sensing techniques have been applied to classify tour density classes within each of the forest type along with other major landuse/landcover classes in the East district, Sikkim using IRS-1A LISS II satellite data pertaining to the period of November, 1988. The shadow problem in rugged terrain and difficulty in acquiring cloud free data for different seasons pose problems to achieve considerable mapping accuracy. In the present study, the forests of the district were delineated through supervised classification techniques using maximum likelihood algorithm into five forest types as sal forests, subtropical broad-leaved forests, Himalayan wet temperate forests, Rhododendron forests and alpine forests. The alpine forests were further stratified into two categories as moist alpine scrub and dry alpine scrub. The statistical data obtained from the present study shows that 55.47 percent of the total geographical area of the East district was under forest cover. An overall accuracy of more than 85 percent in correctly delineating forest classes was achieved.     

Evaluation of EO-1 hyperion data for agricultural applications

The present study was carried out to evaluate the satellite-based hyperspectral data available from Hyperion onboard EO-1 of NASA for agricultural applications. The study was carried out for Daurala block of Meerut district, using data of March 2005. The preliminary data analysis showed that there are 196 usable bands out of a total of 242 bands. Principal component (PC) analysis showed that about 99% of the information explained in 10 PCs. The atmospherically corrected reflectance, derived from satellite data had good agreement with the ground reflectance, observed using handheld spectroradiometer, with r² ranging from 0.85 to 0.98. A set of twenty most usable bands was selected by the criteria of maximum contribution to first five PCs and the band combinations with least inter-band correlations.     

基于激光测高数据的丹江口水库水位变化监测

针对多源星载激光测高数据监测湖泊水位变化问题,该文选取2003—2009年ICESat/GLAH14全球地表高程数据、2018年10月—2019年8月的ICESat-2/ATL13全球内陆水体高程数据,提取丹江口水库多期水位变化数据,最后利用水位站实测水位对其准确度进行了验证,并分析了丹江口水库年度水位变化规律。结果表明,丹江口水库水位呈现明显的季节性变化,每年11月达到较高水位,3月降至较低水位;由ICESat/GLAH14数据估算水库水位的精度为16 cm,ICESat-2/ATL13数据集估算水库水位的精度达到10 cm。因此,ICESat-2/ATL13数据用于内陆水体水位变化监测具有很高的可行性。     

A comparative evaluation of IRS-1A LISS-II and landsat MSS images using computer-aided lineament data analysis

Lineament patterns detected from remotely sensed data provide useful information to geoscientists, specially in the study of basement tectonics, groundwater targetting and mineral exploration. Improvements in the spatial resolution of satellite images have resulted in the detection of short and faint lineaments which have hitherto gone unnoticed The IRS-1A LISS-II data offers a significant improvement in spatial resolution as compared to the Landsat MSS. A set of computer programmes developed for analysis of lineaments were used to study the parameters such as lineament frequency, length and density in order to quantify the added information derived using IRS-1A LISS-II images. The incremental contribution of LISS-II images are of the order of 100 per cent for lineament frequency and about 60 per cent for total line kilometers of lineaments detected.