Evaluation and use of Resourcesat-I data for agricultural applications

Resourcesat-1 satellite offers a unique opportunity of simultaneous observations at three different spatial scales through LISS-IV, LISS-III^* (improved LISS-III) and AWiFS sensors from a common platform. The sensors have enhanced capabilities in terms of spectral, spatial and radiometric resolution as compared to earlier Indian Remote sensing Satellite sensors. This paper summarizes the results of various studies such as evaluation of sensor characteristics, inter-sensor comparison studies, derivation and validation of surface reflectance measurements, quantification of improvements due to Resourcesat-1 sensors, and their use for various agricultural applications. The studies presented in this paper demonstrate that suit of sensors onboard Resourcesat-1 satellite provides better prospects for several agricultural applications like crop identification, discrimination and crop inventory for some major Indian crops, than its predecessors on IRS satellites.     

Utilization of Resourcesat-1 data for improved crop discrimination

Subsequent to the launch of the state-of-art third generation Indian Remote Sensing satellite, Resourcesat-1, studies have been conducted to understand the capabilities of the on-board sensors for crop discrimination. The paper discusses the unique capabilities of the AWiFS, LISS-III and LISS-IV sensors in terms of their dimensionality, radiometry and spatial resolutions for crop discrimination and monitoring. The studies have indicated better crop discriminability especially using the short wave infrared data in 1.55–1.70 μm data among the spectrally confusing land cover classes, attributed to the relative differences of water contents. 10-bit radiometry of AWiFS data in four bands has been observed to be a better discriminant. Intrafield variability was very well captured by the LISS-IV data revealing the potential of data for applications like precision farming. The studies have revealed that potential of Resourcesat-1 data becoming the workhorse for several agricultural applications.     

A novel method for enhancement of radiometric resolution using image fusion

The Resourcesat-I satellite is equipped with different types of sensors with varied characteristics. For the effective utilization of the available multi-sensor, multi-temporal, multi-spectral and multi-radiometric data from these sensors, fusion of digital image data has become a valuable technique. Image fusion enhances the information content and helps in better discrimination of various land cover types. The Resourcesat-1 has equipped with three sensors, AWiFS, LISS-III and LISS-IV, which are having identical spectral resolutions, with different spatial, radiometric and temporal resolutions. The spatial resolutions ratio of the data set for merging are required to be maximum of 1:6, where as the data sets (AWiFS and LISS-III) that are used in the current study are having the ratio of 1:2.5 approximately. A novel merging technique is designed, which retains the multi-spectral response of the input data in the output data. The merged data set provides the higher spatial and radiometric resolutions. In order to evaluate the fusion merits quantitatively, all the data sets are digitally classified and studied the output classes for homogeneity and clear discrimination. A comprehensive comparative study is carried out between the fused image and the LISS-III image based on the contingency matrix and the scatter plots, which demonstrates the strength of fused image for discriminating the object classes at 23.5 m spatial and 10-bit radiometric resolutions. The merged data set gives the improved classification accuracy.     

Direct delivery of remote sensing data to user computer systems using satellite-based data broadcast techniques

The remote sensing applications are growing very rapidly with the availability of high-resolution data from the state of the art satellites like IRS-1C/1D/P4. The advancement in computer hardware and software in the area of remote sensing also enhance the growth of remote sensing applications. IRS-1C/1D/P4 provides data with the resolution of 5.6m in panchromatic mode giving more information of the ground area covered. The remote sensing satellites with high-resolution sensors and wide coverage capabilities will provide the data with better resolution, coverage and revisit to meet the growing application needs. Many applications like crop acreage and yield estimation, draught monitoring and assessment, flood mapping, waste land mapping, mineral prospectus, forest resource survey etc., have become an integral part of the resources management system in the developing countries. These resource management systems need the data to be transferred in real time or near real time for processing. The transfer of data in real time or near real time calls for advanced data delivery techniques to deliver the data as quickly as possible. Processing of remote sensing data can be performed even on low cost personal computers, which in turn further increases the remote sensing applications enabling by setting up the processing centers even at grass root level i.e., at district, taluk or village level. Setting up of processing centers at grass root level demands for quick, cost effective and efficient data delivery mechanism to transfer remote sensing data with or without value added services. The digital revolution has reached broadcasting with the introduction of direct broadcasting of digital data. These modify the traditional data transfer techniques by separating the actual service from the transmission system, thus enabling the distribution of any kind of digital data to stationary, portable or mobile terminals. This allows remote sensing data to reach a large number of users simultaneously and independent of their location. This article highlights the concepts, possibilities, and implementation mechanisms to realize the remote sensing data transfer through direct broadcasting technique and enhance remote sensing applications.     

Precision real-time navigation of LEO satellites using global positioning system measurements

Continued advancements in remote sensing technology along with a trend towards highly autonomous spacecraft provide a strong motivation for accurate real-time navigation of satellites in low Earth orbit (LEO). Global Navigation Satellite System (GNSS) sensors nowadays enable a continuous tracking and provide low-noise radiometric measurements onboard a user spacecraft. Following the deactivation of Selective Availability a representative real-time positioning accuracy of 10 m is presently achieved by spaceborne global positioning system (GPS) receivers on LEO satellites. This accuracy can notably be improved by use of dynamic orbit determination techniques. Besides a filtering of measurement noise and other short-term errors, these techniques enable the processing of ambiguous measurements such as carrier phase or code-carrier combinations. In this paper a reference algorithm for real-time onboard orbit determination is described and tested with GPS measurements from various ongoing space missions covering an altitude range of 400–800 km. A trade-off between modeling effort and achievable accuracy is performed, which takes into account the limitations of available onboard processors and the restricted upload capabilities. Furthermore, the benefits of different measurements types and the available real-time ephemeris products are assessed. Using GPS broadcast ephemerides a real-time position accuracy of about 0.5 m (3D rms) is feasible with dual-frequency carrier phase measurements. Slightly inferior results (0.6–1 m) are achieved with single-frequency code-carrier combinations or dual-frequency code. For further performance improvements the use of more accurate real-time GPS ephemeris products is mandatory. By way of example, it is shown that the TDRSS Augmentation Service for Satellites (TASS) offers the potential for 0.1–0.2 m real-time navigation accuracies onboard LEO satellites.     

An automated seamless mosaicing system of multi-charge coupled devices of panchromatic data

Panchromatic data of pixel resolution 5.8 m obtained from IRS-1C and IRS-1D satellites proved to be very useful for mapping purposes. One of the popular data product is the 70 km swath mosaic which is covered by a combination of 3 CCD line sensors, each with 4096 pixels. Each CCD-line sensor with different imaging times causes geometric problems of mosaicing three strips data together. In this paper, we propose the details of the design elements of system that caters to the need for accurate and automatic multi strip image registration without any second resampling of the data. The systematic geometric correction grid mapping is improved to facilitate accurate mosaicing by automatic image registration task that makes use of the overlap data within image strips and image registration is achieved up to sub-pixel level.     

Quality assessment of FORMOSAT-3/COSMIC and GRACE GPS observables: analysis of multipath, ionospheric delay and phase residual in orbit determination

The precise orbit determination antennas of F3/C and GRACE-A satellites are from the same manufacturer, but are installed in different configurations. The current orbit accuracy of F3/C is 3 cm at arcs with good GPS data, compared to 1 cm of GRACE, which has a larger ratio of usable GPS data. This paper compares the qualities of GPS observables from F3/C and GRACE. Using selected satellites and time spans, the following average values for the satellite F3/C and satellite A of GRACE are obtained: multipath effect on the pseudorange P1, 0.78 and 0.38 m; multipath effect on the pseudorange P2, 1.03 and 0.69 m; occurrence frequency of cycle slip, 1/29 and 1/84; standard error of unit weight, 4 and 1 cm; dynamic–kinematic orbit difference, 10 and 2 cm. For gravity determination using F3/C GPS data, a careful selection of GPS data is critical. With six satellites in orbit, F3/C’s large amount of GPS data will make up the deficiency in data quality.     

天绘一号03星三线阵/多光谱载荷影像质量评价

2015年10月26号发射的天绘一号03星是中国传输型立体测绘卫星天绘一号系列的第3颗卫星。三线阵和多光谱影像数据是天绘一号卫星的重要数据,用于立体测绘、彩色融合、遥感观测等多种用途。因此,为了推动天绘一号03卫星影像数据早日为相关领域提供服务,本文采用客观评价的方法,对天绘一号03星的三线阵和多光谱影像质量进行了全面的评价分析。评价结果显示(天绘一号)03星的清晰度、对比度、细节能量、边缘能量、功率谱、信息容量指标值远高于天绘一号01、02星。说明天绘一号03星三线阵/多光谱影像在地物细节和边缘纹理特征的描述上优于天绘一号01、02星,同时载荷接收的信息量远高于天绘一号01、02星。天绘一号03星较高的信噪比指标说明其载荷抑制噪声的能力优于天绘一号01、02星。边缘辐射畸变和增益调整畸变表明在辐射均匀程度上,天绘一号03星三线阵/多光谱影像介于天绘一号01和02星之间。因此,与同类天绘一号01,02星的三线阵与多光谱影像相比,天绘一号03星影像质量有着显著的提高。     

Remote sensing data from IRS satellites — past, present and the future

Under Indian Remote Sensing Satellite Programme, so far seven satellites have been launched to provide land, water, agricultural and Oceanographic information for resources monitoring and management under National Natural Resources Management System. The continuity of the data services is planned by way of providing improved multi-spectral data, panchromatic data, and oceanographic/atmospheric data, in the future also. The various errors in the satellite data namely radiometric and geometric errors which are to be corrected on ground before the data is put for use have been explained. The characteristics of the future satellites are also described in this article.     

Combining the FCM Classifier with Various Kernels to Handle Non-linearity of Class Boundaries

This article presents the use of kernel functions in fuzzy classifiers for an efficient land use/land cover mapping. It focuses on handling mixed pixels obtained from a remote sensing image by considering non-linearity between class boundaries. It uses kernel functions combined with the conventional fuzzy c-means (FCM) classifier. Kernel-based fuzzy c-mean classifiers were applied to classify AWiFS and LISS-III images from Resourcesat-1 and Resourcesat-2 satellites. Optimal kernels were obtained from eight single kernel functions. Fractional images generated from high resolution LISS-IV image were used as reference data. Classification accuracy of the FCM classifier increased with 12.93%. Improvement in overall accuracy shows that non-linearity in the dataset was handled adequately. The inverse multiquadratic kernel and the Gaussian kernel with the Euclidean norm were identified as optimal kernels. The study showed that overall classification accuracy of the FCM classifier improved if kernel functions were included.     

Influence of Atmospheric Water Vapour on IRS NIR Measurements for Detecting Vegetation Signal. Part I: A Simulation Study Using MODTRAN

Quantitative remote sensing involving accurate estimation of vegetation properties relies greatly on the measurements of the near infrared (NIR) channel because of unique interaction property between light and leaf. It is generally assumed that the NIR measurements are made in the absence of atmospheric absorption. However, relatively weak water vapour absorption features still persist in the NIR channel, which has bearing on the quantitative estimates of the vegetation properties and long-term data series. This paper reports the results of a study that was carried out to infer the possible influence of the atmospheric water vapour (WV) on the NIR measurements (0.77–0.86 μm) of Indian Remote Sensing (IRS) satellite sensors through radiative transfer simulations using MODTRAN model. The study also suggests and evaluates the alternate band-positions for the NIR channel to improve the IRS NIR measurements. It was observed that the water absorption features present around 0.810 μm reduces the WV transmission of IRS NIR channel from 1 to 0.91 when atmospheric WV content increased from 0 to 6 g/cm² and thus hampered the NIR reflectance by 14% as compared to reference signal. A significant improvement of the order of 6.5 to 12% in the NIR reflectance and 4.2 to 7% in NDVI was observed, when IRS NIR channel was split into NIR1 (0.775–0.805 μm) and NIR2 (0.845–0.875 μm) channels by avoiding the WV absorption features. The companion paper in this issue (Pandya et al. 2011) will support results of this simulation study through the EO1-Hyperion data analysis.     

Orbit determination of the Lunar Reconnaissance Orbiter

We present the results on precision orbit determination from the radio science investigation of the Lunar Reconnaissance Orbiter (LRO) spacecraft. We describe the data, modeling and methods used to achieve position knowledge several times better than the required 50–100 m (in total position), over the period from 13 July 2009 to 31 January 2011. In addition to the near-continuous radiometric tracking data, we include altimetric data from the Lunar Orbiter Laser Altimeter (LOLA) in the form of crossover measurements, and show that they strongly improve the accuracy of the orbit reconstruction (total position overlap differences decrease from ~70 m to ~23 m). To refine the spacecraft trajectory further, we develop a lunar gravity field by combining the newly acquired LRO data with the historical data. The reprocessing of the spacecraft trajectory with that model shows significantly increased accuracy (~20 m with only the radiometric data, and ~14 m with the addition of the altimetric crossovers). LOLA topographic maps and calibration data from the Lunar Reconnaissance Orbiter Camera were used to supplement the results of the overlap analysis and demonstrate the trajectory accuracy.     

Orbit determination of the SELENE satellites using multi-satellite data types and evaluation of SELENE gravity field models

The SELENE mission, consisting of three separate satellites that use different terrestrial-based tracking systems, presents a unique opportunity to evaluate the contribution of these tracking systems to orbit determination precision. The tracking data consist of four-way Doppler between the main orbiter and one of the two sub-satellites while the former is over the far side, and of same-beam differential VLBI tracking between the two sub-satellites. Laser altimeter data are also used for orbit determination. The contribution to orbit precision of these different data types is investigated through orbit overlap analysis. It is shown that using four-way and VLBI data improves orbit consistency for all satellites involved by reducing peak values in orbit overlap differences that exist when only standard two-way Doppler and range data are used. Including laser altimeter data improves the orbit precision of the SELENE main satellite further, resulting in very smooth total orbit errors at an average level of 18 m. The multi-satellite data have also resulted in improved lunar gravity field models, which are assessed through orbit overlap analysis using Lunar Prospector tracking data. Improvements over a pre-SELENE model are shown to be mostly in the along-track and cross-track directions. Orbit overlap differences are at a level between 13 and 21 m with the SELENE models, depending on whether 1-day data overlaps or 1-day predictions are used.     

Landsat系列卫星光学遥感器辐射定标方法综述

Landsat系列卫星自1972发射以来,已经连续提供了40多年的中等分辨率多光谱遥感数据,广泛应用于农业、水资源管理、灾害响应等领域。目前,很多研究人员开始考虑利用这些数据开展中分辨率尺度的长时间序列地表定量信息监测,更加精细地反映局地甚至全球气候变化。开展这些研究的前提在于对数据进行辐射定标,并通过不同卫星的交叉辐射传递保证数据辐射精度的一致性。从Landsat 1到Landsat 8,随着遥感器性能和数据获取能力的提升,辐射定标方法不断更新,涉及发射前实验室定标、内定标灯方法、全孔径太阳定标器方法、交叉定标方法、场地定标方法等。本文在对Landsat系列卫星的遥感器性能进行分类、归纳、对比的基础上,系统梳理了Landsat系列卫星遥感器辐射定标方法发展过程以及不同定标方法的优缺点,特别是对定标精度的影响。Landsat系列卫星辐射定标的发展过程为遥感数据高精度定量化应用提供了非常重要的基础,未来辐射定标方法不但要随着新型遥感器研制而更新,更要注重多源遥感数据的交叉验证以及全过程辐射定标方法的完善与应用,保障遥感数据辐射定标精度的一致性。     

气象卫星发展回顾与展望

回顾了国际气象卫星和中国风云气象卫星的发展,综述了气象卫星在图像解译、定量产品应用和数据同化方面的成就以及辐射校正技术的进步。围绕大气科学,特别是数值天气预报对天基观测的需求,展望了未来气象卫星的技术发展方向。     

“天绘一号”卫星在轨辐射定标方法

在轨辐射定标包括相对辐射定标和绝对辐射定标, 它是提高遥感数据定量化精度的关键步骤和重要方法。本文阐述了基于均匀场地分区综合的相对辐射定标方法、基于反照率的绝对辐射定标方法及其基本原理, 并首次将其应用于“天绘一号”卫星上的高分辨、多光谱和三线阵相机的辐射定标中。研究结果表明, 相对辐射定标过程去除了卫星图像的条带噪声, 且保存了图像细节;然后, 使用反照率基法, 通过在敦煌场地铺设灰阶靶标, 测量卫星过顶时的地物目标反射率光谱和大气信息, 对“天绘一号”卫星传感器进行了绝对辐射定标;最后, 使用辐射定标结果来反演地物反射率, 与实测的地物反射率相比误差小于5%, 验证了在轨辐射定标系数的有效性。     

Resourcesat-1 mission planning,analysis and operations—Outline of key components

Resourcesat-1 is a global mission which provides continuity to the earth resources monitoring missions earlier launched by India. Resourcesat-1 is designed to have an improvement in the payload camera characteristics providing multi-spectral imaging capability in high resolution. This paper provides an overview of mission planning and analysis aiding spacecraft configuration, pre-launch simulations and operations, early-orbit operations and the on-orbit operational guidelines for Resourcesat-1. Mission planning involved integrating and inter-relating the efforts of space and ground systems in realizing the operational system which provides the continuity of satellite-based remote sensing data to the user community. Mission analysis related to contiguous imaging requirement of LISS-4 payload, resulted in a spacecraft yaw steering during imaging operations. Pre-launch simulation involved development of a software spacecraft simulator to be used as a tool for network tests, training of spacecraft operation personnel and validating the spacecraft health monitoring software. The required operations that were performed on the spacecraft to characterize and establish the on-orbit configuration for the normalization of daily operations are addressed in the sections relating to early orbit operations and on-orbit operational guidelines.     

The Z/I Imaging Digital Camera System

Market needs for airborne and spaceborne imagery used in photogrammetry and GIS applications are changing. Fundamental changes in sensors, platforms and applications are currently taking place. Most recently, new high resolution spaceborne sensors have become available. Besides classical photogrammetry, new thematic applications will drive the future image market. Savings in cost and time, together with the need for higher and reproducible radiometric resolution or spectral information will push forward the change from analogue to digital imagery. High resolution satellites will compete with airborne film-based photography and digital camera systems.
With the availability of a digital airborne camera, it is possible to completely close the digital chain from image acquisition to exploitation and data distribution. The key decision regarding the camera design in this case is whether a linear or area array sensor should be used. In view of the high geometric accuracy requirements in photogrammetry, Z/I Imaging has focused development on a digital camera based on an area sensor. An essential aspect of this decision was not only the aerial camera system, but also the entire photogrammetric process to the finished photographic or mapping product. If this point of view is adopted, it becomes clear that the development of a digital camera involves more than simply exchanging film for silicon. Aspects such as data transfer rates, in-flight data processing and storage, image archiving, georeferencing, colour fusion, calibration and preprocessing have the same influence on the economic assessment of a digital camera system. This paper describes current development activities and application aspects of a digital modular airborne camera system.     

Influence of Atmospheric Water Vapour on IRS NIR Measurements for Detecting Vegetation Signal. Part II: Validation of Simulation Results using Hyperion Data

This is the second paper of the series on the influence of the atmospheric water vapour (WV) on IRS NIR measurements. In the first paper (Pandya et al. 2011) a simulation study was presented where through the radiative transfer calculations it was shown that the variation of 0 to 6 g/cm² in the WV hampered the IRS NIR reflectance up to 14%. In that study splitting of IRS NIR (0.770–0.860 μm) into two bands, such as NIR1 (0.775–0.805 μm) and NIR2 (0.845–0.875 μm) was also proposed, which facilitated a considerable improvement in NIR reflectance as well as in NDVI. Objective of the present paper is to validate the findings of simulation study with the use of EO1-Hyperion data. An improvement of the order of 7% in the top-of-atmosphere reflectance over vegetation target was obtained from the satellite data analysis, which is in good agreement to that of simulation results (3.7 to 7.9%) for the continental WV conditions of 1 to 3 g/cm². This is also true for NDVI values, which illustrated a good agreement between the satellite observations (2.5%) and simulation results (2 to 4.6%) for the magnitude of improvement. Findings of the present study are preliminary in the nature but it provides a basis for enhanced NIR observations for future IRS sensors.     

中国空间辐射测量基准技术

为确保数据的定量化应用,国际航天遥感大国始终围绕定标技术开展研究,定标精度不断提高。在经历数十年发展之后,受传统的遥感载荷定标系统设计以及地面辐射校正技术理论极限的制约,目前遥感卫星辐射定标停留在太阳反射谱段2%,红外谱段0.2 K的不确定性水平,其精度难以继续提高。进入21世纪,气候变化问题成为全球关注的热点,全球气候变化研究对遥感卫星辐射测量精度提出了前所未有的要求。ASIC³（Achieving Satellite Instrument Calibration for Climate Change）报告指出,为了有效检测全球气候变化信号,准确预测气候变化,遥感卫星观测必须长期保持在太阳反射谱段0.3%、红外谱段0.1 K,太阳总辐射0.01%的不确定性水平。为了迎接这一挑战,欧洲和美国相继提出了CLARREO计划和TRUTHS计划,试图通过发射具有超高辐射测量精度的基准卫星,在监测气候变化信号的同时,标定其他遥感卫星,提升全球遥感卫星整体定标精度。同期,中国也提出了空间辐射测量基准技术的概念,并在“十二五”和“十三五”,通过国家高技术研究发展计划和国家重点研发计划持续支持星上相变固定点黑体、空间低温辐射计等尖端技术的研发,进而逐渐形成发射空间辐射测量基准卫星的路线图。从目前发展态势上看,中国有可能成为第一个建立空间辐射测量基准的国家,率先实现卫星平台辐射观测直接向国际单位（SI）的溯源。