Hyperspectral Remote Sensing Classifications: A Perspective Survey

Classification of hyperspectral remote sensing data is more challenging than multispectral remote sensing data because of the enormous amount of information available in the many spectral bands. During the last few decades, significant efforts have been made to investigate the effectiveness of the traditional multispectral classification approaches on hyperspectral data. Formerly extensively established conventional classification methods have been dominated by the advanced classification approaches and many pre‐processing techniques have been developed and incorporated in hyperspectral classification. A perspective survey of hyperspectral remote sensing classification approaches is presented here. It comprehensively highlights the taxonomy of major classification approaches reported during the last two decades and describes an experimental evaluation of a few major classification algorithms. Recent advancements in the development of classification approaches are also emphasized with a set of guidelines for achieving better classification performances.     

关于我国1957年旧重力基本网的精度与系统转换

简述了原国家重力基本网(57网)的历史和技术要点,详细地分析了57网的各类误差和产生原因,提出了新、旧系统转换的方法。本文研究表明,57网基本点相对观测的实际精度约为±0.06mgal,仪器平均值误差为1.6×10~(-4)。基本点重力值含-13.56mgal的基准误差和1.9×10~(-4)的尺度差,并含有±0.1～0.2mgal的非线性系统误差。对基本点实行新、旧系统转换误差为±0.05mgal,基本不损失其观测精度。     

IDENTIFYING AND ASSESSING PROBLEM AREAS IN SOIL EROSION SURVEYS USING AERIAL PHOTOGRAPHS

Gully erosion has for many years been a problem in Rhodesia1s Tribal Trust Lands. This paper describes how Soil Conservation Service staff, with no previous ground knowledge of these areas, used good quality 1/25,000 scale aerial photographs to measure the extent of the gully erosion and to pinpoint erosion “black spots.” This enabled quick and reliable estimates of the cost of reclamation work to be made without the need for time-consuming field survey. The survey method discussed is capable of wide application wherever gully erosion occurs and needs to be brought under control.     

Segmentation of SAR image using statistical separability rule

Journal of the Indian Society of Remote Sensing - In order to develop fully the application of Synthetic Aperture Radar (SAR) data, special image analysis techniques are required. In the present...     

Resourcesat (IRS-P6) value added data products

Remote sensing data products need to meet stringent geodetic and geometric accuracy specifications irrespective of intended user applications. Georeferencing is the basic processing step towards achieving this goal. Having known the imaging geometry and mechanism, the mathematical models built with the use of orbit and attitude information of the spacecraft can correct the remote sensing data for its geometric degradations only up to system level accuracy (IRS-P6 DP Team, 2000). The uncertainties in the orbit and attitude information will not allow the geometric correction model to generate products of accuracy that can meet user requirements unless Ground Control Points (GCP) are used as reference geo-location landmarks. IRS-P6 data processing team has been entrusted with developing a software system to generate data products that will have desired geodetic and geometric accuracies with known limitations. The intended software system is called the Value Added Data Products System (VADS). Precision corrected, Template Registered, Merged and Ortho Rectified products are the value added products planned with VADS.     

Habitat evaluation for sarus crane in the Keoladeo National Park using IRS LISS III and pan merged data and GIS

The Keoladeo National Park, Bharatpur, a man-made fresh water wetland carved out of a natural depression on the floodplain of two minor tributaries of the Yamuna-Gambhir and the Banganga is the country’s finest waterfowl habitat. This important wetland was set aside as a bird sanctuary in 1956 and it was elevated to the status of a National Park in 1981. It was also designated a Ramsar site- a wetland of international importance under the Ramsar convention. This important wetland has distinction of being the only Indian wetland to be included under both the Ramsar and the World Heritage convention. The attempt has been made to evaluate the habitat of Sarus crane in the Keoladeo National Park using satellite data — IRS LISS III and PAN merged product and GIS. Geocoded data of IRS —1C LISS III of 21 March 1999 on 1: 50,000 scale and PAN data of March 17, 1999 were used to generate the vegetation cover type map and open water. The maps showing drainage, human habitations, contours, roads, etc. were prepared using the Survey of India topographical sheets and contour map of park area. Information regarding habitat parameters was collected from the existing literature and field observations. The Sarus crane mainly fed in the wetland on the rhizome ofNymphaea sp.,Scirpus tuberosus andEleocharis plantaginea. As there were changes in their habitat requirements at different seasons, the sighting of Sarus crane in each habitat were recorded along with the time and activity during observation. The most utilized habitat for the entire period of study was moderately wet grassland followed by pools. The pools were used mainly during the summer. The water depth requirement observed was between 30–40 cm and 20–40 cm. The suitability maps for Sarus crane were then generated using all remote sensing based and conventional information using rule based equations in the GIS within the Keoladeo National Park.     

Check dam positioning by prioritization of micro-watersheds using SYI model and morphometric analysis — Remote sensing and GIS perspective

Sediment Yield Index (SYI) model and results of morphometric analysis have been used to prioritize watersheds and to locate sites for checkdam positioning in Tarafeni watershed in Midnapur district. West Bengal. Various thematic maps such as land use/land cover, slope, drainage, soil etc. were prepared from 1RS ID LISS III digital data, SOI toposheets of 1:50,000 scale and other reference maps. Morphometric parameters such as bifurcation ratio (R_b). drainage density (D_d), texture ratio (T), length of overland flow (L_o), stream frequency (F_u), compactness coefficient (C_c), circularity ratio (R_c), elongation ratio (E_r), shape factor (B_s) and form factor (R_f) were computed. Automated demarcation of prioritization of micro-watersheds was done by using GIS overlaying technique by assigning weight factors to all the identified features in each thematic map and ranks were assigned to the morphometric parameters. Five categories of priority viz., very high, high, medium, low and very low, were given to all the watersheds in both the methods. Sixty-two micro-watersheds using SYI method and twenty-three micro-watersheds using morphometric have been prioritized as very high priority. Final priority map was prepared by considering the commonly occurred very high-prioritized micro-watersheds in both SYI model and morphometric analysis. Twenty-four suitable sites were identified for check dam construction in 21 highly prioritized watersheds. It is proved that integrated study of SYI model and morphometric analysis yield good result in prioritization of watersheds.     

Multi-reference evaluation of uncertainty in earth orientation parameter measurements

Uncertainties in polar motion and length-of-day measurements are evaluated empirically using several data series from the space-geodetic techniques of the global positioning system (GPS), satellite laser ranging (SLR), and very long baseline interferometry (VLBI) during 1997–2002. In the evaluation procedure employed here, known as the three-corner hat (TCH) technique, the signal common to each series is eliminated by forming pair-wise differences between the series, thus requiring no assumed values for the “truth” signal. From the variances of the differenced series, the uncertainty of each series can be recovered when reasonable assumptions are made about the correlations between the series. In order to form the pair-wise differences, the series data must be given at the same epoch. All measurement data sets studied here were sampled at noon (UTC); except for the VLBI series, whose data are interpolated to noon and whose UT1 values are also numerically differentiated to obtain LOD. The numerical error introduced to the VLBI values by the interpolation and differentiation is shown to be comparable in magnitude to the values determined by the TCH method for the uncertainties of the VLBI series. The TCH estimates for the VLBI series are corrupted by such numerical errors mostly as a result of the relatively large data intervals. Of the remaining data sets studied here, it is found that the IGS Final combined series has the smallest polar motion and length-of-day uncertainties.     

GGM02 – An improved Earth gravity field model from GRACE

A new generation of Earth gravity field models called GGM02 are derived using approximately 14 months of data spanning from April 2002 to December 2003 from the Gravity Recovery And Climate Experiment (GRACE). Relative to the preceding generation, GGM01, there have been improvements to the data products, the gravity estimation methods and the background models. Based on the calibrated covariances, GGM02 (both the GRACE-only model GGM02S and the combination model GGM02C) represents an improvement greater than a factor of two over the previous GGM01 models. Error estimates indicate a cumulative error less than 1 cm geoid height to spherical harmonic degree 70, which can be said to have met the GRACE minimum mission goals. Electronic Supplementary Material Supplementary material is available in the online version of this article at