Remote monitoring of Mount Erebus Volcano,Antarctica, using Polar Orbiters: Progress and Prospects

Mount Erebus (Antarctica) is a remote and inhospitable volcano, where field campaigns are possible only during the austral summer. In addition to continuously monitoring seismic instruments and video cameras, data from scanners flown aboard polar orbiting space-craft, such as the Thematic Mapper (TM) and Advanced Very High Resolution Radiometer (AVHRR), can contribute to continuous, year-round monitoring of this volcano. Together these data allow measurement of the temperature of, thermal and gas flux from, and mass flux to a persistently active lava lake at Erebus' summit. The monitoring potential of such polar-orbiting instruments is enhanced by the poleward convergence of sub-spacecraft ground-tracks at the Erebus latitudes, permitting more frequent return periods than at the equator. Ground-based observations show that the Erebus lava lake was active with an area of ～2800m2 and sulphur dioxide (SO2) flux of (230 +/- 90)td-1 prior to September 1984. AVHRR-based lake area and SO2 flux estimates are in good agreement with these measurements, giving (2320 +/- 1200)m2 and (190 +/- 100)td-1, respectively, during 1980. However during late-1984 the lava lake became buried, with TM data showing re-establishment of the lake, with a TM-derived surface temperature of 578-903 C, by January 1985. Following these events, ground-based lake area and SO2 flux measurements show that the lake area and SO2 flux was lower (180-630m2 and 9-91td-1, respectively). This is matched by a decline in the AVHRR- and TM-derived rate of magma supply to the lake from 330 167kgs-1 prior to 1984 to 30-76kgs-1 thereafter. Clearly, a reduction in magma supply to, and activity at, the lava lake occurred during 1984. We look forward to using data from such future polar-orbiting sensors as the Moderate Resolution Imaging Spectrometer (MODIS), Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), Enhanced Thematic Mapper (ETM+) and Advanced Along Track Scanning Radiometer (AASTR) to contribute to high (once a day) temporal resolution measurement and monitoring of activity at this volcano. Such analyses will in turn contribute to a more complete understanding of how this volcano works.     

A near real-time dual-band-spatial approach to determine the source of increased radiance from closely spaced active volcanoes in coarse resolution satellite data

Bezymianny and Kliuchevskoi volcanoes (Kamchatka) present a danger as both inject ash into North Pacific air routes. Current automated monitoring algorithms do not distinguish them in real time due to their mutual proximity (10 km) and poor geolocation accuracy of Advanced Very High Resolution Radiometer (AVHRR) data. Contrasting mid- and thermal infrared volcanic radiances are influenced by (1) differences in temperature and eruptive style of Bezymianny's andesite and Kliuchevskoi's basalt and (2) different temperatures of the non-volcanic portion of pixels located over their summits, due to different elevations. Data from 571 AVHRR images show the latter is more significant. Discriminant function analysis using summit and regional band 4 pixel-integrated radiant temperatures (pirT) correctly identifies the source volcano of a thermal anomaly in 89% of cases. Weather permitting, a spatial component can be added, leading to improved accuracy. The approach used here can also be applied at other closely spaced volcanoes with substantially different summit elevations.     

Spatial attributes of AVHRR imagery for environmental monitoring

Abstract

Spatial analysis of Advanced Very High Resolution Radiometer (AVHRR) data at Global Area Coverage (GAC) and High Resolution Picture Transmission (HRPT) resolution shows that structural information is detectable across a range of scales and that different biomes exhibit different detectable spatial characteristics. The spatial patterns observed in GAC and HRPT data are similar at coarse resolutions. Differences between the two are observed where point phenomena occur, and where scene objects are generally linear. The undersampling in GAC data generation can cause artificial contiguity and artificial disunity to appear in the image of any scene. The spatial structure observed in GAC image data must therefore be considered unreliable, at least at the scale of the GAC AVHRR resolution-cell size. However, the use of the spatial domain in studies of surface phenomena operating at scales greater than that of the resolution-cell size are unlikely to be limited by the undersampling effects. Indeed, the spatial temporal evolution of structure in AVHRR images may provide important indicators of regional environmental change.     

Automated,high temporal resolution,thermal analysis of Kilauea volcano,Hawai'i,using GOES satellite data

Thermal data are directly available from the Geostationary Operational Environmental Satellites (GOES) every 15 minutes at existing or inexpensively installed receiving stations. This data stream is ideal for monitoring high temperature features such as active lava flows and fires. To provide a near-real-time hot spot monitoring tool, we have developed, tested and installed software to analyse GOES data on-reception and then make results available in a timely fashion via the web. Our software automatically: (1) produces hot spot images and movies; (2) uses a thresholding procedure to generate a hot spot map; (3) updates hot spot radiance and cloud index time series; and (4) issues a threshold-based e-mail alert. Results are added to http://volcano1.pgd.hawaii.edu/goes/ within ～12 minutes of image acquisition and are updated every 15 minutes. Analysis of GOES data acquired for effusive activity at Kilauea volcano (Hawai'i) during 1997-98 show that short (<1 hour long) events producing 100m long (10² to 10³ m²) lava flows are detectable. This means that time constraints can be placed on sudden, rapidly evolving efflusive events with an accuracy of 7.5 minutes. Changes in activity style and extent can also be documented using hot spot size, intensity and shape. From radiance time series we distinguish (1) tube-fed activity (low radiance, <10 MW m² m^-1); (2) activity pauses (no radiance); (3) lava lake activity (low radiance, <5 MW m² m^-1); (4) short (<3 km long) flow extension (moderate radiance, 10-20 MW m² m ¹ ); and (5) 12 km long flow extension (high radiance, 15-30 MW m² m^-1). The ability of GOES to detect short-lived effusive events, coupled with the speed with which GOES-based hot spot information can be processed and disseminated, means that GOES offers a valuable additional volcano monitoring tool.     

The limitations and potential of AVHRR GAC data for continental scale fire studies

Global Area Coverage (GAC) data from the Advanced Very High Resolution Radiometer (AVHRR) are available on a daily basis, dating back to July 1981. The AVHRR's 3·55–3·93 μm channel is suitable for detection of terrestrial hot spots, such as bushfires. The long-term archives and global cover make the GAC a potentially valuable data source for large scale fire studies. However, these data are sampled spatially through a combination of line skipping and averaging. This study shows that the sampling affects the sensitivity of GAC for fire detection in relation to ecosystem and season. The GAC are found to provide a reasonable measure of fire activity in grassland and open b'ush savannah, but to perform poorly in the forest margins. Overall at least 79 per cent of fires detected with non-sampled AVHRR data are missed by the GAC. This severely limits the use of GAC data for quantitative fire studies. The GAC does appear to provide a reasonable measure of fire calendar (i.e., variations in fire activity with time) and on a continental scale successfully identifies the main regions of fire activity. The potential of these data for continental scale fire studies is illustrated through the preliminary analysis of 277 GAC mosaics of Africa for the period September 1988 to August 1989.     

Insight into ground deformations at Lascar volcano (Chile) from SAR interferometry, photogrammetry and GPS data: Implications on volcano dynamics and future space monitoring

We present a detailed study of Lascar volcano (Chile) based on the combination of satellite, aerial and ground-based data, in order (i) to better characterize the deformation style of Andean explosive volcanoes, and (ii) to provide new insights on the potential of space techniques to monitor active volcanic deformations on such edifices. Lascar is one of the most active volcanoes in Central Andes characterized by a recent cyclic activity. Additionally, it is located in favourable conditions for radar imaging. Lascar thus offers very good conditions for studying large to small scale ground deformations associated with volcano dynamics. The analysis of InSAR (Synthetic Aperture Radar interferometry) time series data from the European and Japanese satellites (ERS, JERS) acquired between 1993 and 2000, encompassing three eruptive events, confirmed the absence of broad far-field deformation signal. Thus during the recent activity of Lascar we discard significant magmatic input at depth. The following approaches were used to improve the InSAR signal / noise ratio in order to detect possible local deformation. We carried out a quantitative evaluation of the potential tropospheric contribution in INSAR interferograms for the Salar de Atacama-Lascar area using radar (ASAR-ENVISAT) and spectrometer (MODIS) data. We also used an accurate aerial photogrammetric and GPS constrained DEM in our InSAR data reprocessing. We find a co-eruptive ground-deformation confined into the summit crater for the 1995 eruption. This deformation has spatial dimension of 500 by 400 m and relates to a subsidence of crater floor up to 17 mm. We interpret it as pressure or volume decrease at subsurface levels below the active crater. Our study made it possible to image a new near-field volcanic deformation confined within the summit crater of the Lascar volcano. It also demonstrates that the combination of precise photogrammetry DEM and INSAR data can significantly improve our ability to remotely sense subtle surface deformation on these explosive volcanoes. This methodology might contribute to better understand volcano dynamics and to complement their monitoring in remote areas.     

AVHRR for monitoring global tropical deforestation

Abstract

Advanced Very High Resolution Radiometer (AVHRR) data have been used to assess the dynamics of forest transformations in three parts of the tropical belt. A large portion of the Amazon Basin has been systematically covered by Local Area Coverage (LAC) data in the 1985-1987 period. The analysis of the vegetation index and thermal data led to the identification and measurement of large areas of active deforestation. The Kalimantan/Borneo forest fires were monitored and their impact was evaluated using the Global Area Coverage (GAC) 4 km resolution data. Finally, High Resolution Picture Transmission (HRPT) data have provided preliminary information on current activities taking place at the boundary between the savanna and the forest in the Southern part of West Africa. The AVHRR approach is found to be a highly valuable means for carrying out deforestation assessments in regional and global perspectives.     

Global data sets for land applications from the Advanced Very High Resolution Radiometer: an introduction

The Advanced Very High Resolution Radiometer (AVHRR) has become one of the most important sensors for monitoring the terrestrial environment at resolutions of 1 km to very coarse resolutions of 15 km and greater. To make these data suitable for scientific and other applications considerable effort has been devoted to the creation of global data sets. Experience has demonstrated that even for a relatively simple sensor such as the AVHRR, the task of creating global data set is fraught with difficulties and that a number of iterations have been necessary despite considerable efforts in the specification of users' requirements

Four types of data processing streams, overlapping in time, have occurred in the creation of global data sets from the AVHRR. The first three data processing streams were all based on the reduced resolution, Global Area Coverage (GAC) data set, which is collected globally every day. In the first data processing stream a much reduced data set was created in the form of the Global Vegetation Index (GVI) product: revised improved versions of the product have been produced. In the second data processing stream an improved product was created by workers at NASA's Goddard Space Flight Center with higher spatial resolution but which until recently has only been available by continent. This has resulted in the creation of a number of regional data sets. In the third data processing stream operational creation of global data sets at moderately coarse resolution (c. 8 km) is being initiated. The most notable example of this data processing stream is part of NASA's Pathfinder project and stems in large part directly from the second data processing stream: it will involved production of a reprocessed improved global data set for the period from 1982 to the present. In the fourth data processing stream the full potential of the AVHRR in terms of its spatial resolution is being realized, through the generation of a global data set at 1 1 km resolution data.     

Volcano detection and monitoring using AVHRR data: the Krafla eruption, 1984

Abstract. Many volcanic eruptions go essentially unmonitored. Potentially the Advanced Very High Resolution Radiometer (AVHRR), with its global coverage, frequent return period, and sensitivity in the thermal infrared, represents a data source capable of monitoring surface volcanic activity unrecorded by ground observations or other satellite sensors. In this study an attempt is made to demonstrate this potential by extracting information for the 1984 eruption at Krafla, Iceland. Seven cloud-free AVHRR images were available for the 14 day period of eruptive activity. The surface activity was detectable as a major thermal anomaly in all three of the longer wavelength channels and was vigorous enough during one night-time pass to be detectable in the near-infrared channel (0.725-1.1μm). Channel 2 and 4 radiance data were used to calculate the size and temperature of sub-pixel heat sources within the lava flow field, and a heat source at 1050° C was estimated as occupying an area of approximately 240000 m², which was distributed across 20 pixels. Detection and measurement of volcanic heat sources at such short wavelengths using low spatial resolution data has rarely been reported before. Field reports and maps were used to guide and confirm the analysis. Digital number variations within the anomaly could be related to various known features of the eruption. To monitor the eruption a weighted average method was derived and used to sharpen up the images, and the density sliced sharpened images enabled the development of the eruption to be mapped. Results compared well with field reports, suggesting that AVHRR and similar systems could be a useful source of data for monitoring eruptions where contemporaneous field observations are unavailable or incomplete.     

Regression and ratio estimators to integrate AVHRR and MSS data

Regression and ratio estimators are used to integrate AVHRR-GAC and Landsat MSS digital data to estimate forest area in the continental United States. Forestlands are enumerated for the 48 contiguous states using five different AVHRR-GAC data sets. The five GAC data sets tested, each with a spatial resolution of 4 km, were composed of different combinations of vegetation index and thermal data acquired over the nine month growing period in 1984. Twenty Landsat MSS scenes were selected countrywide and used to calibrate AVHRR forest estimates. Results indicated that the GAC and MSS forest estimates were not highly correlated; R² values ranged from 0.5 to 0.7. Although the ratio of means and linear regression corrections were, on the average, closer to national U.S. Forest Service forest area estimates, these correction procedures did not consistently improve GAC estimates of forest area. GAC forest area estimates tended to be high in densely forested regions such as the northeast and low in sparsely forested areas. This fact, and the low correlation coefficients, indicate that AVHRR data should be used for primary stratification (with MSS as the second stage) and not as an auxiliary variable in a regression correction procedure.     

Objective assessment of the NOAA global vegetation index data product

Abstract

For the last 10 years the U.S. National Oceanic and Atmospheric Administration has produced an experimental Global Vegetation Index (GVI) data set for terrestrial vegetation research. These data, sampled from advanced very high resolution radiometer (AVHRR) observations, have served as a primary stimulus for global-scale vegetation research but have, so far, not been adequately evaluated. This study reviews the GVI production procedures and compares the resultant observations with a more comprehensive compilation of the AVHRR data being produced at the NASA Goddard Space Flight Center. There are many aspects of the GVI production procedures which could be improved to achieve the desired objectives. In particular, the mapping and sampling procedures employed provide measurements which only approximate the observed GAC measurements. The GVI NDVI record varies more than ±NDVI units (～ 7 per cent of signal) from the GAC record and, in general, seriously underestimates the GAC NDVI measurements. The NDVI portion of the GVI record is compromised through use of digital numbers rather than calibrated reflectance. NDVI measurements from the calibrated channels of the GVI data set produces values that compare favourably with the GAC measurements, but with considerable residual variance. Calculation of a 3 by 3 pixel average of the GVI NDVI measurements reduces residual variance between the data sets to ±0.018 NDVI units (～3 per cent of signal). Decay of sensor calibration and orbital overpass time, experienced by all the AVHRR sensors, as well as differences in these parameters between the sensors are not addressed but the results suggest the importance of accounting for these factors. These results indicate that GVI data sets, following adequate reprocessing, provide reasonable estimates of major regional contrasts in vegetation activity but should not be employed to evaluate local or minor trends.     

Quality of TOPSAR topographic data for volcanology studies at Kilauea Volcano, Hawaii: An assessment using airborne lidar data

We use airborne lidar data for the summit area of Kilauea Caldera, Hawaii, to explore the utility of topographic data collected by the TOPSAR airborne interferometric radar for volcanology studies. The lidar data are processed to a spatial resolution of 1 m/pixel, compared to TOPSAR with a spatial resolution of 5 m. Over a variety of fresh volcanic surfaces (pahoehoe and aa lava flows, ash falls and fluvial fans), TOPSAR data are shown to have a typical vertical offset compared to the lidar data of no more than ∼2-3 m. Larger differences between the two data sets and TOPSAR data drop-outs are found to be concentrated around steep scarps such as the walls of pit craters and ground cracks associated with the Southwest Rift Zone. A comparison of these two data sets is used to explore the utility of TOPSAR to interpret the topography of volcanic features close to the spatial resolution of TOPSAR, such as spatter ramparts, fractures, a perched lava flow, and eroded ash deposits. Comparison of the TOPSAR elevation and the lidar first-return minus the return from the ground surface (the so-called “bald Earth” data) for vegetated areas reveals TOPSAR penetration into the tree canopy is typically at least 10% and no more than ∼50%, although a wide range of penetration values from 0% to 90% has been identified. Our results are significant because they show that TOPSAR data for volcanoes can reliably be used to measure regional slopes and the thickness of lava flows, and have value for the validation of coarser spatial resolution digital elevation data (such as SRTM) in areas where lidar data have not been collected.     

Eruptive history of Dubbi volcano,northeast Afar (Eritrea), revealed by optical and SAR image interpretation

A study of the remote Dubbi volcano, located in the northeastern part of the Afar triangle, Eritrea, was carried out using JERS-1 Synthetic Aperture Radar (SAR) and Landsat Thematic Mapper (TM) imagery. It investigated the last known eruption of Dubbi volcano in 1861, the only volcano in Afar for which historical reports indicate a major explosive eruption. Various image processing techniques were tested and compared in order to map different volcanic units, including effusive and explosive products. Principal component analysis and optical-SAR fusion were found to be useful to determine the extent of the 1861 pumice deposits surrounding the volcano. SAR imagery revealed old lava flows buried below tephra deposits, emphasizing the ground penetrating property of the L-band (HH polarization). The interpretation obtained from satellite imagery was cross-checked with sparse historical testimonies and available ground-truth data. Two scenarios are proposed for the 1861 eruptive sequences in order to estimate the volumes of lava flows erupted and the timing of explosive and effusive activity. Identified as a bimodal basaltic-trachytic eruption, with a minimum volume of 1.2 km³ of hawaiite lava and a minimum area of 70 km² of trachytic pumice, it represents the largest known historic eruption in the Afar triangle. This paper raises the issue of the potential volcanic hazards posed by Dubbi, which concern both the local population and the maritime traffic using the strategic route of the Red Sea.     

NASA EOS Terra ASTER: Volcanic topographic mapping and capability

Up-to-date, accurate topographic data are a crucial resource for volcanic research and risk mitigation efforts, in particular, for modeling volcanic flow processes at a detailed spatial resolution. In this paper, we examine the utility of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument currently operating on the NASA Terra satellite, which provides near infrared (VNIR) stereo imaging from which topography can be derived. We wrote software to generate digital elevation models (DEMs) from the ASTER level 1A product, which employs an automated stereo matching technique to calculate the parallax offsets between the images acquired by the nadir- and aft-looking sensors. Comparison of ASTER DEMs with DEMs derived from other sources (digitized 1:50 K topographic maps and aerial interferometric radar) at Ruapehu volcano reveal an RMS error of about 10 m for the ASTER DEM, in the absence of significant atmospheric water vapor. A qualitative assessment of surface features showed that the ASTER DEM is superior to the interpolated 1:50 K map product but falls short of the detail provided by aerial interferometric radar, especially in terms of stream channel preservation. A second ASTER DEM was generated for Taranaki volcano, where previously only 1:50 K topographic map data were available. Although the 2000 Space Shuttle radar topography mission (SRTM) will largely remedy the previous global paucity of adequate topographic data at volcanoes, such as Taranaki, we anticipate the problem that at active volcanoes, the topography may change significantly following activity, rendering the SRTM data inaccurate. With the high temporal coverage of the dataset, ASTER not only provides a means to update significant (>10 m) topographic measurements at active volcanoes via a time-series of DEMs, but also provides a simultaneous means to map surface cover and localized land-use via the near infrared sensors. Thus we demonstrate the potential for up-to-date volcanic economic risk assessment using geographic information systems (GIS) analysis.     

Scale considerations in vegetation monitoring using AVHRR data

Abstract

The Advanced Very High Resolution Radiometer (AVHRR) is currently the only operational remote sensing system capable of providing global daily data which can be used for vegetation monitoring. These data are available with resolution cell sizes ranging from around one to 20 km on a side, though the temporal and spatial extent of cover at each resolution is variable. In this paper Normalized Difference Vegetation Index temporal curves derived from AVHRR at different resolutions are compared over both agricultural and natural tropical vegetation types. For the agricultural regions the length of growing season and major breaks of slope associated with key crop development events are equally well shown at coarse and fine resolution. Detailed examination of the curves reveals differences thought to result from temporal changes in landscape structure. Temporal curves derived from AVHRR data at dilTerent spatial resolutions shows that the spatial organization of both agricultural and natural landscapes, tropical forest in this case, changes throughout a single season. Transitions across major ecological zones are detected across a range of resolutions, though the undersampling employed in the generation of the coarser resolution products is found to exert some limitations on the spatial representivity of these data; this varies both with geographical area and time. These observations highlight the importance of a consideration of scale when using AVHRR data for vegetation monitoring, and emphasize the need for dilTerent scales of observation (both in temporal and spatial terms) for different problems and at different times of the year.     

Application of thematic mapper short wavelength infrared data for the detection and monitoring of high temperature related geoenvironmental features

Abstract

The short wavelength infrared region (0·7-3·0μm) has manifold applications in the detection and monitoring of geoenvironmental features, such as coal mine fire, oil well fire, active volcanoes, industrial hot spots, etc. These features are essentially characterized by high temperatures and often release aerosols and greenhouse gases into the atmosphere. In the present article, an attempt has been made to study the applications of Thematic Mapper (TM) Short Wavelength Infrared (SWIR) bands (4, 5 and 7) data for the detection and monitoring of these high temperature related geoenvironmental features. The rationale of using the SWIR data for temperature related studies is also discussed in brief. The pixel-integrated and sub-pixel temperatures have been calculated using the TM SWIR bands data for an active volcano (Barren Island volcano), coal mine fire (Jharia Coal Field) and industrial hot spots (Bokaro Steel Plant).     

Post-emplacement lava subsidence and the accuracy of ERS InSAR digital elevation models of volcanoes

Repeat-pass synthetic aperture radar interferometry (InSAR) using data acquired by the ERS platforms is an attractive method for acquiring topographic data of volcanoes. Caution is advised, however, when using this technique in regions covered by young, thick lava flows. In this study, the magnitude of post-emplacement subsidence associated with the 1991-93 lava flow at Mount Etna, Sicily, was measured using differential radar interferometric techniques, and it was found that the rates of subsidence are large enough to contribute a significant component to the measured phase shift, even in ERS data acquired on consecutive orbits. It demonstrates the detrimental effect that such phase shifts have on the accuracy of digital elevation models derived by repeat-pass radar interferometry.     

Monitoring active volcanism with the Autonomous Sciencecraft Experiment on EO-1

The ability to monitor and rapidly react to remote detection of volcanic activity has been greatly improved through use of the Autonomous Sciencecraft Experiment (ASE), an advanced software application installed on a spacecraft in Earth orbit. ASE is a NASA New Millennium Program experiment demonstrating science-driven autonomous command and control of a spacecraft. Flying on the Earth Observing-1 (EO-1) spacecraft, ASE successfully detected thermal emission from the Mt. Erebus lava lake on 7 May 2004, having analyzed a Hyperion hyperspectral data product on board the spacecraft. EO-1 was re-tasked by ASE to obtain a follow-up observation 7 h later and sent a notification of detection of volcanic activity to the ground. The entire process was carried out autonomously. Initial acquisition to receipt on the ground of the positive detection took less than 3 h, a process that without ASE would have taken weeks. The ASE Thermal Classifier has detected several styles of effusive volcanic activity: active lava lakes, pahoehoe flow fields, open channel flows and lava domes. ASE successfully demonstrated that science-driven spacecraft operation greatly enhances science return per returned byte through the identification of the most valuable data, allowing prioritization of downlink products and the discarding of null data sets. This technology has applications on missions elsewhere in the solar system. Modified thermal classifiers can be used for detecting and monitoring active volcanism on the jovian satellite Io, the neptunian moon Triton, and searching for active volcanism on Mars and icy satellites. The success of ASE is an incentive for future instrument and mission designers to consider on-board data-processing requirements (especially data storage capacity, number of processors and processor speed, and RAM) in order to take advantage of this flight-proven technology.     

Estimation of methane emission from West Siberian wetland by scaling technique between NOAA AVHRR and SPOT HRV

Wetlands are one of the most important ecosystems in the world and at the same time they are presumed to be a source of methane gas, which is one of the most important greenhouse gases. The West Siberian wetlands is the largest in the world and remote sensing techniques can play an important role for monitoring the wetland.High spatial resolution satellite data are effective for monitoring land cover type changes, but can't cover a wide area because of a narrow swath width. On the other hand, global scale data are indispensable in covering a large area, but are too coarse to get the detailed information due to the low spatial resolution. It is necessary to devise a method for the fusion of the data with different spatial resolutions for monitoring the scale-differed phenomena.In this paper, firstly, a SPOT HRV image near Plotnikovo mire was used to map four wetland ecosystems (birch forest, conifer forest, forested bog and open bog) supplemented by field observation. Then, spectral mixture analysis was performed between NOAA AVHRR and SPOT HRV data acquired on the same day.Secondly, field observations were scaled up with these different spatial resolution satellite data. Each of the wetland ecosystem coverage fraction at the sub-pixel level was provided by spectral mixture analysis. Field observation shows that the mean rate of CH₄ emission from forested bog and open bog averaged 21.1 and 233.1 (mg CH₄/m²/day), respectively. The methane emission from the area was estimated by multiplying these average methane emission rates and the fraction coverage in each AVHRR pixel.Finally, the total methane emission over AVHRR coverage was estimated to be 9.46 (10⁹ g CH₄/day) and the mean methane emission over AVHRR coverage was calculated as 59.3 (mg CH₄/m²/day). We could conclude that this mean value is within the probabilistic variability as compared with the airborne measurement results.     

Identifying deforestation in Brazil using multiresolution satellite data

MSS, LAC, GAC and GOES data were used to delineate the extent of deforestation in Rondonia, Brazil, in order to identify those satellite data sources appropriate for monitoring deforestation on a continental/subcontinental scale. These data were processed to differentiate forest from non-forest (cleared, colonized areas) using two different classification procedures. The first procedure utilizes all available spectral bands of data in conjunction with a maximum likelihood classifier to discriminate cleared areas from primary forest. The technique is called probability thresholding. The second employs the red and nearinfrared spectral data to calculate a vegetation index which is subsequently thresholded from forest/non-forest delineation. Ground reference data were not available; the 80m (spatial resolution) MSS digital data products served as the reference data source. The 1·1 km LAC, 4 km GAC and 0·9 km GOES (visible band) images were compared with the MSS imagery. Areal comparisons indicated that (i) the LAC data are capable of adequately delineating colonization clearings in the Amazon; (ii) the spatial resolution of'uhe GAC data is too large to delineate linear clearings of varying length (tens to hundreds of kilometres) up to 2 km wide reliably, (iii) the visible GOES data were of little utility due to excessive data noise and (iv) probability thresholding procedures discriminated forest from non-forest more accurately than vegetation-index thresholding procedures. The results indicate that LAC data used in conjunction with probability thresholding offer the best data-source/classification-procedure combination. MSS data may be used when and where available as a ground reference data source in order to define the AVHRR threshold which most accurately discriminates cleared areas from primary forest.