Remote sensing of the colour and temperature of volcanic lakes

Crater lakes on active volcanoes act as heat and chemical traps, and are amenable to surveillance from space. By use of all seven spectral bands, the Landsat Thematic Mapper (TM) can simultaneously measure: (i) lake surface temperature, (ii) lake surface area, and (iii) lake colour which is related to water chemistry. Use of the total instrument in this way enhances its utility for volcano surveillance. This work examines TM data for crater lakes at the following volcanoes: Ruapehu (New Zealand), Taal (Philippines), Kawah Ijen and Kelut (Indonesia), Poas (Costa Rica), and Apoyeque and Jiloa (Nicaragua). Observatory data indicate that lake surface temperatures derived by TM band 6 are typically 1-4°C less than contemporaneously measured bulk temperatures, probably due to the skin effect, the difference between water bulk and surface temperature. For Ruapehu, TM band 6 hotspots coincide approximately with known upwelling sites above volcanic vents on the lakebed. Field observations at Kawah Ijen show that the skin effect (< 3°C) is strongly correlated with windspeed: wind gusts peaking at ≈ 5m s^?1 caused rapid decreases in surface temperature of ≈ 0.5-1.0°C. These fluctuations are small compared with the magnitude of volcanogenic changes in lake temperature and do not reduce the utility of infrared surveillance. TM-derived water surface spectral reflectances indicate high concentrations of suspended chemical sediment in the most active crater lakes: Ruapehu, Poás and Ijen. For Ruapehu, imaged on two dates, the later scene reveals an upwelling slick, bright in bands 5 and 7, possibly composed of hollow sulphur spherules emitted from a subaqueous vent. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) and Enhanced Thematic Mapper (ETM +) both due for launch in 1998, will offer improved capabilities for remote surveillance of crater lakes.     

Remote sensing of US cornbelt areas sensitive to the El Ni@o-Southern Oscillation

A 16-year time-series (1982-1997) of monthly maximum Normalized Difference Vegetation Index (NDVI) values derived from coarse-scale Advanced Very High Resolution Radiometer (AVHRR) satellite images was investigated for its application in identifying agricultural regions sensitive to El Ni@o-Southern Oscillation (ENSO) impacts. Cumulative NDVI values over the growing season were used to test the temporal and spatial sensitivity of rainfed agricultural regions in the US cornbelt to ENSO climate teleconnections. The correlation (R) between NDVI anomalies and yield anomalies aggregated to the Agricultural Statistics Division (ASD) level was 0.59 (significant at the 99% level). Sea surface temperatures (SSTs) from the NINO3 region (between +5.0° and m 5.0° latitude and 90.0° and 180.0° west longitude in the Pacific Ocean), an indicator of the ENSO phenomenon, were significantly but weakly correlated with growing season NDVI anomalies, precipitation anomalies, and yield anomalies. Two classification schemes for El Niño, La Niña and Neutral years related to the crop growing season were applied--one based on simultaneous Pacific NINO3 SSTs (spring-summer), and one based on following winter Pacific NINO3 SSTs. The strongest differences in Vegetation Condition Index (VCI) spatial patterns among the three ENSO categories were found using the following winter SST classification. Classification of ENSO years is a key issue in analysing ENSO impacts on agriculture as represented by the NDVI, because the regularity of annual agricultural seasons is not synchronous with the quasi-regular Pacific SST cycles.     

Remote sensing of foliar chemistry

Remotely sensed data are being used to estimate foliar chemical content as a result of our need for the information and our increasing ability to understand and measure foliar spectra. This paper reviews how stepwise multiple regression and deconvolution have been used to extract chemical information from foliar spectra, and concludes that both methods are useful, but neither is ideal. It is recommended that the focus of research be modeling in the long term and experimentation in the short term. Long-term research should increase our understanding of the interaction between radiation and foliar chemistry so that the focus of research can move from leaf model to canopy model to field experiment. Short-term research should aim to design experiments in which remotely sensed data are used to generate unambiguous and accurate estimates of foliar chemical content.     

Carbon dioxide of Pu`u`O`o volcanic plume at Kilauea retrieved by AVIRIS hyperspectral data

A remote sensing approach permits for the first time the derivation of a map of the carbon dioxide concentration in a volcanic plume. The airborne imaging remote sensing overcomes the typical difficulties associated with the ground measurements and permits rapid and large views of the volcanic processes together with the measurements of volatile components exolving from craters. Hyperspectral images in the infrared range (1900-2100 nm), where carbon dioxide absorption lines are present, have been used. These images were acquired during an airborne campaign by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over the Pu`u` O`o Vent situated at the Kilauea East Rift zone, Hawaii. Using a radiative transfer model to simulate the measured up-welling spectral radiance and by applying the newly developed mapping technique, the carbon dioxide concentration map of the Pu`u` O`o Vent plume were obtained. The carbon dioxide integrated flux rate were calculated and a mean value of 396 ± 138 t d^− 1 was obtained. This result is in agreement, within the measurements errors, with those of the ground measurements taken during the airborne campaign.     

Remote sensing of fires with the TRMM VIRS

Although the Visible and Infrared Scanner (VIRS) instrument on board the Tropical Rainfall Measuring Mission (TRMM) satellite is designed primarily to study precipitation, it offers a new opportunity for the remote sensing of fire activity in regions within 40 of the equator. VIRS is a five-channel imaging spectroradiometer with bands ranging from 0.6 to 12 mu m. Its similarity to the Advanced Very High Resolution Radiometer (AVHRR), which has operated since 1978 on board the National Oceanic and Atmospheric Administration (NOAA) satellite series, is no coincidence, as a primary objective of VIRS is to provide an important link between TRMM precipitation measurements and those derived from other current and historical satellite sensors. The similarity of the VIRS infrared bands, in particular, to those of AVHRR provides a foundation for fire detection, which has been clearly demonstrated for AVHRR. However, VIRS offers some additional capabilities which should enable it to make an important contribution to the remote sensing of fire.     

Remote sensing of rice crop areas

Rice means life for millions of people and it is planted in many regions of the world. It primarily grows in the major river deltas of Asia and Southeast Asia, such as the Mekong Delta, known as the Rice Bowl of Vietnam, the second-largest rice-producing nation on Earth. However, Latin America, the USA, and Australia have extensive rice-growing regions. In addition, rice is the most rapidly growing source of food in Africa. Rice is therefore of significant importance to food security in an increasing number of low-income food-deficit countries. This review article gives a complementary overview of how remote sensing can support the assessment of paddy rice cultivation worldwide. This article presents and discusses methods for rice mapping and monitoring, differentiating between the results achievable using different sensors of various spectral characteristics and spatial resolution. The remote sensing of rice-growing areas can not only contribute to the precise mapping of rice areas and the assessment of the dynamics in rice-growing regions, but can also contribute to harvest prediction modelling, the analyses of plant diseases, the assessment of rice-based greenhouse gas (methane) emission due to vegetation submersion, the investigation of erosion-control-adapted agricultural systems, and the assessment of ecosystem services in rice-growing areas.     

Remote sensing of phytoplankton functional types

The principal goal in early missions of satellite-borne visible spectral radiometry (ocean colour) was to create synoptic fields of phytoplankton biomass indexed as concentration of chlorophyll-a. In the context of climate change, a major application of the results has been in the modelling of primary production and the ocean carbon cycle. It is now recognised that a partition of the marine autotrophic pool into a suite of phytoplankton functional types, each type having a characteristic role in the biogeochemical cycle of the ocean, would increase our understanding of the role of phytoplankton in the global carbon cycle. At the same time, new methods have been emerging that use visible spectral radiometry to map some of the phytoplankton functional types. Here, we assess the state of the art, and suggest paths for future work.     

Determination of volcanic dust deposition from El Chichon using ground and satellite data

Major volcanic eruptions of EI Chichon on 28 March 1982, 3 April 1982 and 4 April 1982 produced heavy tephra falls in surrounding areas. Data from the NOAA-6 and NOAA-7 satellites were used to determine the extent of the tephra falls. The satellite data showed a larger area of tephra deposition than was reported from conventional ground measurements     

Remote sensing image fusion using the curvelet transform

This paper presents an image fusion method suitable for pan-sharpening of multispectral (MS) bands, based on nonseparable multiresolution analysis (MRA). The low-resolution MS bands are resampled to the fine scale of the panchromatic (Pan) image and sharpened by injecting highpass directional details extracted from the high-resolution Pan image by means of the curvelet transform (CT). CT is a nonseparable MRA, whose basis functions are directional edges with progressively increasing resolution. The advantage of CT with respect to conventional separable MRA, either decimated or not, is twofold. Firstly, directional detail coefficients matching image edges may be preliminarily soft-thresholded to achieve a noise reduction that is better than that obtained in the separable wavelet domain. Secondly, modeling of the relationships between high-resolution detail coefficients of the MS bands and of the Pan image is more fitting, being accomplished in the directional multiresolution domain. Experiments are carried out on very-high-resolution MS + Pan images acquired by the QuickBird and Ikonos satellite systems. Fusion simulations on spatially degraded data, whose original MS bands are available for reference, show that the proposed curvelet-based fusion method performs slightly better than the state-of-the art. Fusion tests at the full scale reveal that an accurate and reliable Pan-sharpening, little affected by local inaccuracies even in the presence of complex and detailed urban landscapes, is achieved by the proposed method.     

Remote sensing of the state of crops and soils

Various techniques as well as some general problems of agricultural remote sensing are discussed, with emphasis on the development of techniques to assess soil productivity (humus content) and the slate of crops (weediness, etc.). The techniques considered were tested in conditions of the southern part of the USSR European territory (the Ukraine, Moldavia). Applications of the technique have been exemplified.     

Remote sensing applications in the Australian Bureau of Meteorology

Abstract

The space age for the Bureau of Meteorology arrived in December 1963 with the first direct receipt in Australia of visual images of clouds from the US TIROS-8 satellite. Since that time, the successful application of advances in satellite data, products and services has brought dramatic improvements to most aspects of the Bureau's operations and research. This paper documents the developments of the past 25 years by describing the Bureau's current national infrastructure for the reception, processing and dissemination of meteorological satellite data and the way in which satellite data and systems are used to improve the Bureau's services. The meteorological satellite has emerged not only as a highly cost-effective primary observation platform, providing an increasingly diverse range of meteorological data, but also as a vital communications medium for both general meteorological information and the interrogation of complementary observational systems. The prospects for further major advances in the application of satellite information within the Bureau are very high. During the early 1990s and beyond, the next generation of active remote sensing technology will replace the current passive sensor technology deployed in the international meteorological satellite network. As a result, further improvement in the ability of the Australian meteorological community to describe quantitatively the dynamic and thermodynamic structure of the atmospheric and marine environment is confidently predicted.     

Concurrent remote sensing of Arctic sea ice from submarine and aircraft

Abstract

In May 1987 a concurrent remote sensing study of Arctic sea ice from above and below was carried out. A submarine equipped with sidescan and upward looking sonar collaborated with two remote sensing aircraft equipped with passive microwave, synthetic aperture radar (SAR), a laser profilometer and an infrared radiometer. By careful registration of the three tracks it has been possible to find relationships between ice type, ice morphology and thickness, SAR backscatter and microwave brightness temperatures. The key to the process has been the sidescan sonar's ability to identify ice type through differences in characteristic topography. Over a heavily ridged area of mainly multiyear ice there is a strong positive correlation between SAR backscatter and ice draft or elevation. We also found that passive and active microwave complement each other in that SAR has a high contrast between open water and multiyear ice, while passive microwave has a high contrast between open water and first-year ice.     

Remote sensing based estimation of evapotranspiration rates

A remote sensing based method is presented for calculating evapotranspiration rates (λE) using standard meteorological field data and radiometric surface temperature recorded for bare soil, maize and wheat canopies in Denmark. The estimation of λE is achieved using three equations to solve three unknowns; the atmospheric resistance (r_ae ), the surface resistance (r_s ) and the vapour pressure at the surface (e_s ) where the latter is assessed using an empirical expression. The method is applicable, without modification, to dense vegetation and moist soil, but for a dry bare soil, where the effective source of water vapour is below the surface, the temperature of the evaporating front (T_s *) can not be represented by the measured surface temperature (T_s ). In this case (T_s -T_s *) is assessed as a linear function of the difference between surface temperature and air temperature. The calculated λE is comparable to latent heat fluxes recorded by the eddy covariance technique.     

Remote sensing applications in the Southeast Sumatra coastal environment

The coastal lowland swamps, rivers and estuarine areas north of Palembang, South Sumatra constitute a resource base likely to be extensively exploited during the next several years. Activities such as swamp forest logging, extensive fisheries, movement of government sponsored transmigrants and Buginese settlers into the area have intensified in recent years. Palembang is an important port which is difficult to maintain at sufficient depth to allow use by deep water ships, thereby creating interest in a coastal port location. In the near future it will be necessary to develop a multiple resource use management strategy based on national priorities, local needs and ecological constraints. Landforms, vegetation patterns, sediment and erosion sites, land use dynamics, settlement patterns and albedo are analysed from a time series of aerial photographs and LANDSAT imagery. The results, correlated with field data, indicate patterns of ecological constraints and resource use dynamics that have implications for development over much of the eastern coast of Sumatra.     

Remote sensing of leaf water content in the near infrared

A stochastic leaf radiation model was used to predict leaf spectral reflectance as a function of leaf water content for a dicot leaf. Simulated spectral reflectances were analyzed to quantify reflectance differences between different equivalent water thicknesses. Simulated results coupled with consideration of atmoshperic transmission properties and the incident solar spectral irradiance at the earth's surface resulted in the conclusion that the 1.55–1.75 μm region was the best-suited wavelength interval for satellite—platform remote sensing of plant canopy water status in the 0.7–2.5 μm region of the spectrum.     

Remote sensing of salinity in the San Francisco Bay Delta

Salinity of the San Francisco Bay Delta has been studied for the past seven decades. There is a significant gradient in salinity within this estuarine system that influences the growth and distribution of phytoplankton as well as the abundance and migration of shrimp and fish population. Several government agencies which have jurisdictions over this area are attempting to gather extensive data for effectively monitoring of this estuary. Repetitive remotely sensed data acquired from Landsat may be considered by these agencies as having the potential to provide a cost-effective method for gathering and processing water quality related data. In this study, Landsat multispectral scanner (MSS) data and color and color infrared photographs acquired from a U-2 aircraft were combined with surface measurements for salinity mapping of the San Francisco Bay Delta. The salinity measurements and U-2 photography were obtained simultaneously and coincident with landsat overpass. A regression model was developed between the surface truth data and Landsat digital data for 29 preselected sample sites and was then extended to the entire study area. The results included a salinity map of the study area and the statistical summaries. The results were in general agreement with the reported distribution of salinity values in the literature for the same time of the year. Based on the results and the associated analyses of natural color and color infrared photographs and Landsat color composite imagery, it was concluded that: (1) it was virtually impossible, at least within this test site, to establish any quantitative judgement regarding the salinity values by visual interpretation of the imagery; and (2) the present study constitutes the first effort to successfully use Landsat digital data for salinity mapping, by means of digital processing, for this geographic area.