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.     

On-line learning control of autonomous underwater vehicles usingfeedforward neural networks

A neural-network-based learning control scheme for the motion control of autonomous underwater vehicles (AUV) is described. The scheme has a number of advantages over the classical control schemes and conventional adaptive control techniques. The dynamics of the controlled vehicle need not be fully known. The controller with the aid of a gain layer learns the dynamics and adapts fast to give the correct control action. The dynamic response and tracking performance could be accurately controlled by adjusting the network learning rate. A modified direct control scheme using multilayered neural network architecture is used in the studies with backpropagation as the learning algorithm. Results of simulation studies using nonlinear AUV dynamics are described in detail. The robustness of the control system to sudden and slow varying disturbances in the dynamics is studied and the results are presented     

A reindeer herder's perspective on caribou, weather and socio-economic change on the Seward Peninsula, Alaska

Non-climate variables shape vulnerability and adaptive capacity to climate change. Here, we describe how recent environmental and socio-economic developments have transformed reindeer herding and perceptions of weather on the Seward Peninsula, Alaska. The reindeer industry has shrunk considerably since the early 1990s, when the winter range of the Western Arctic Caribou Herd expanded, and over 17 000 reindeer mixed with migrating caribou and left the region. Socio-economic and environmental repercussions make the continuation of herding tenuous, and erode the ability of herders to cope with weather variability, among other perturbations. We present a case study of one herder's annual cycle, and juxtapose physical drivers of herding activities, including weather-station and herder observations of local weather variability, with socio-economic factors. There is an increased urgency to access and monitor reindeer with caribou present, but herding plans are constrained by lower economic returns and the need to spend more time in non-herding jobs. Although weather is a greater concern now for immediate herd access, standard weather data are largely irrelevant to the mechanics of herding, whereas variables pertaining to the timing of biotic events (e.g., synchrony of spring break-up and calving) and visibility are attributed to lost herding opportunities. Short-term responses to weather conditions stem from more long-term vulnerability associated with caribou presence, reduced herd size, difficulties affording snowmobile maintenance or crew assistance, and dwindling market opportunities. We emphasize the environmental and socio-economic interactions that affect vulnerability and adaptive capacity for modern herding.     

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.     

Downstream changes in antimony and arsenic speciation in sediments at a mesothermal gold deposit in British Columbia,Canada

This study investigates Sb speciation in sediments along the drainage of the Upper Peter adit at the Bralorne Au mine in southern British Columbia, Canada, and compares the behavior of Sb with that of As. The Upper Peter mineralization consists of native Au in quartz-carbonate veins with 1 wt.% sulfides dominated by pyrite and arsenopyrite although stibnite, the primary Sb-bearing sulfide mineral, can be locally significant. Dissolved Sb concentrations can reach up to 349 μg L⁻¹ in the mine pool. Sediments were collected for detailed geochemical and mineralogical characterization at locations along the 350-m flow path, which includes a 100-m shallow channel within the adit, a sediment settling pond about 45 m beyond the adit portal and an open wetland another 120 m farther downstream. From the mine pool to the wetland outlet, dissolved Sb in the drainage drops from 199 μg L⁻¹ to below the detection limit due to the combined effect of dilution and removal from solution. Speciation analyses using X-ray absorption near-edge structure (XANES) spectroscopy indicate that Sb(III)–S accounts for around 70% of total Sb in the sediments in the main pool at the far end of the adit. At a short distance (24 m) downstream of the main adit pool, however, Sb(III)–O and Sb(V)–O species represent ?50% of total Sb in the bulk sediments, indicating significant oxidation of the primary sulfides inside the adit. Although Sb appears largely oxidized in the bulk samples collected near the portal, Sb(III)–S species are nevertheless present in the <53-μm fraction, suggesting a higher oxidation rate for stibnite in the coarser grains, possibly due to galvanic interaction with pyrite. Secondary Sb species released from the sulfide oxidation are most likely sorbed/co-precipitated with Fe-, Mn-, and Al-oxyhydroxides along the flow channel in the adit and in the sediment settling pond, with the Fe phase being the dominant sink for Sb.     

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.     

Operational Data Assimilation System for the Kuroshio South of Japan: Reanalysis and Validation

We describe an operational ocean data assimilation system for the Kuroshio and its validation using a nine-year reanalysis (historical run from 1993 to 2001) dataset of upper-ocean state estimation in the North Pacific. The horizontal structure of volume transport of the Ryukyu Current System (RCS) is shown from the reanalysis: The RCS is connected to the flow of the subtropical gyre, and its volume transport gradually increases from south-east of Okinawa (5–10 Sv) to the east of Amami-Ohshima Island (20 Sv). Comparing the reanalysis with independent observations on the southeast slope of the Amami-Ohshima Island indicates that the root mean square differences (RMSDs) are 0.076 (0.037) m/s in the period of December 1998 to November 1999 (November 1999 to November 2000) respectively. The reanalysis field has a bias (3.1 Sv) of the volume transport of the RCS and the RMSD (3.5 Sv) which is larger than the observed variability (2.81 Sv). Surface velocity and the Kuroshio axis south of Japan are also examined. Comparison of the reanalysis and ADCP data gave maximum RMSD of 0.749 (0.271) m/s in the strong (weak) current regions, respectively. The annual mean value of the axis error is 19 km in 1998. The RMSD of the error is at most 50 km, in 294 cases in the observation period, which is smaller than the observed root mean square variability of the axis (64 km). This revised version was published online in July 2006 with corrections to the Cover Date.