Spectral separability of tropical forest cover classes

Abstract

Spectral separability analysis of various tropical forest cover classes as recorded on Landsat MSS data were carried out for two test areas of northeastern India. The results indicated that two density classes of forests and two edaphic forest types formed spectrally separable classes but some of the important physiognomic units could not be reliably separated using Landsat MSS data in a spectrally complex tropical forest environment.     

Evaluation of several classification schemes for mapping forest cover types in Michigan †

Abstract

Landsat MSS data were evaluated for mapping forest cover types in the northern Lower Peninsula of Michigan. The study examined seasonal variations, interpretation procedures and vegetation composition/distribution and their effect on overall classification accuracy and ability to identify individual pine species. Photographic images were used for visual interpretations while digital analysis was performed using a common (ERDAS) microcomputer image processing system. The classification schemes were evaluated using contingency tables and were ranked using the KAPPA statistic. The various classification schemes were ranked differentially according to study site location. Visual interpretation procedures ranked best, or least accurate, depending on the spatial distribution and complexity of the forest cover. Supervised classification techniques were more accurate than unsupervised clustering over all sites and seasons. Maximum likelihood classification of June data was superior to any digital classification technique of February data. The study indicates that classification accuracy is more dependent on the composition and distribution of forests in the northern Lower Peninsula of Michigan than on the selection of a particular classification scheme.     

Cover: On the nature of the South Tibetan Detachment Zone (STDZ), Kumaun Himalayas

Abstract

Abstract. Some fractures in the crust are expressed at the surface as a field of point-like features that have developed in response to usually fluid processes within those fractures. We describe two complementary quantitative methods for analysing such point-like features from remotely-sensed imagery in terms of structural alignment. The two-point azimuth method is probabilistic and tests for the existence of regional and field-wide structural anisotropies. By contrast, the Hough transform method is deterministic and locates specific alignments. These methods have been applied to a Landsat Multispectral Scanner (MSS) image of the Pinacate Volcanic Field in north-west Mexico. The point-like features of interest are cinder cones and maars. The results reveal a northerly structural anisotropy and specific alignments, trending mainly northerly and north-northwesterly, have been mapped. This application was limited by the relatively coarse spatial resolution of the MSS image used. However, although only 71 per cent of the cones mapped on the ground were detected on the MSS image, joint analysis of the two data sets yielded comparable results and a significant improvement on previous qualitative analysis of the ground data. The dual method used here could be applied to other fields of geological point-like features.     

Display and enhancement of gridded aeromagnetic data of the Solway Basin

Abstract

The British Geological Survey has completed the conversion of both aeromagnetic and gravity survey records to a digital data base. This paper examines some of the uses of the aeromagnetic data base. Rendering digitized aeromagnetic data as a rectangular grid of interpolated anomaly values allows regional variations in subsurface magnetization to be displayed as images rather than contoured maps. Images of the magnetic field are more appropriate for visual interpretation and can be enhanced using standard methods of digital image processing. The optimum method is a combination of directional first-derivative filtering to impart the illusion of side illumination, with spectral colouring of the 8-bit range of DN, the former being used to modulate the brightness of the latter. As well as many of the known regional magnetic features of the Solway Basin, this method highlights several trends that were unsuspected.     

Determining the rate of forest conversion in Mato Grosso,Brazil, using Landsat MSS and AVHRR data

Abstract

AVHRR-LAC thermal data and Landsat MSS and TM spectral data were used to estimate the rate of forest clearing in Mato Grosso, Brazil, between 1981 and 1984. The Brazilian state was stratified into forest and non-forest. A list sampling procedure was used in the forest stratum to select Landsat MSS scenes for processing based on estimates of fire activity in the scenes. Fire activity in 1984 was estimated using AVHRR-LAC thermal data. Slate-wide estimates of forest conversion indicate that between 1981 and 1984, 353966 ha ±77 000 ha (0·4 percent of the state area) were converted per year. No evidence of reforestation was found in this digital sample. The relationship between forest clearing rate (based on MSS-TM analysis)and fire activity (estimated using AVHRR data)was noisy (R²= 0·41). The results suggest that AVHRR data may be put to better use as a stratification tool rather than as a subsidiary variable in list sampling.     

Shuttle radar mapping with diverse incidence angles in the rainforest of Borneo

Abstract

Shuttle Imaging Radar-B (SIR-B) images, obtained at two different incidence angles were analysed for discrimination and mapping of vegetation in the rainforest of Borneo. In an area of coastal lowland three units of forest canopy and two units of open surface cover were distinguished and mapped. The backscatter characteristics of the units were compared and analysed by ratioing digital image data of sample sites against digital data of reference sites. The ratios show that the backscatter for each surface unit is clustered in separate, mostly non-overlapping, domains at both incidence angles. Different rates of change with incidence angle indicate a strong angular dependence in the dominant backscatter mechanism of swamp that is not apparent for the other units. A corresponding digitally coregistered Landsat multispectral scanner (MSS) image helped to verify the spatial distribution of the mapped units in the coastal lowland. In the interior upland three major forest species associations that have contrasted canopy structures were not discriminated on the SIR-B images. Owing to perennial cloud cover the distribution and extent of the different canopies cannot be determined from Landsat MSS or other images obtained at optical wavelengths. The ability to discriminate and map different forest canopies in the interior of Borneo requires a wider radar response capability which may be obtainable at shorter wavelengths and with multipolariz-ation states.     

Improving geological mapping in the Arabian Shield using Landsat Thematic Mapper imagery—Jabal Duhayyah area

Abstract

The Jabal Duhayyah area spans the contact between two tectonic zones of the southern Arabian Shield. By utilising principal components analysis of the Landsat-TM data, it was easy to locate this contact precisely as well as to improve and update available geological maps. Previously unmapped lithologics were distinguished and mapped during the processing of the images. Field-checking confirmed these findings and a new geological map was constructed.

Satellite imagery (e.g. Landsat) could be a valuable mapping tool in the well-exposed Arabian Shield, even where it is already mapped at the 1:100000 scale.     

Relationship between Landsat MSS data and forest tree parameters

Abstract

Band ratios, indices and radiance in the four channels of the Multi-spectral Scanner (MSS) on the Landsat-4 satellite for October 1984 and March 1985 were correlated with mean tree parameters of teak plantations (age, mean tree height, mean tree diameter at breast height, mean canopy diameter, mean canopy volume). The Landsat MSS data for March (when teak trees are leafless) were more suitable than the Landsat MSS data for October for categorizing tree parameters.     

Coastal definition using Landsat data†

Abstract

An automated technique is described, for extracting land-water boundaries from Landsat MSS images by means of ‘density contour-threading’ of the band 7 data. The resulting coastlines, etc. can then be transformed to fit any map projection—in particular the British National Grid—with the aid of selected ground control points.     

Variability of Landsat MSS spectral responses of forests in relation to stand and site characteristics

Abstract

The use of field measures of slope angle, slope aspect, cover type, crown size and crown density is evaluated in appraising the variability of Landsat Multispectral Scanner (MSS) spectral responses for 182 sample sites within Crater Lake National Park, Oregon. Multiple linear regression models indicate that 73, 72, 71 and 57 percent of the variation in the mean response of MSS bands 4, 5, 6 and 7, respectively, was explained by the environmental variables entered into the models. In general, crown size and crown density are less important in altering spectral response than terrain orientation. This type of analysis is useful in guiding field work for remote sensing studies into areas that are environmentally diverse and which are, therefore, capable of significantly altering the spectral response of cover types.     

Concepts,processing and results

Abstract

Investigations have been carried out in the Wadi Araba–Jordan Graben area to trace the relationship between diagnostic signals received from Landsat Thematic Mapper (TM) data and several mineralized ground districts. To meet the objectives, different approaches, involving ratioing, principal component analysis and IHS-decorrelation processing, are used to enhance diagnostic features associated with hydrothermally altered areas. Using ratio techniques the best suited approach is given by a colour combination of band ratios 5/7, 4/3 and 7/4. In principle, comparable results can be generated by a combination of the principle components (PCs) 2, 4 and 3 in this succession. However, the ratio and PC approaches often fail to accentuate clearly the diagnostic features. Main reasons are attributable to similarities in relative intensities of vegetation and minerals and to disadvantages that arise through the techniques themselves. Decorrelated and filtered colour composites of TM bands 1, 4 and 7 have proved to be more successful for delineation of known and unknown mineralizations by the presence of alteration guide minerals such as iron oxides and phyllosilicates. In addition, the resulting final products of the decorrelation concept can be used for carefully directed field work, as spectral and structural information are enhanced simultaneously.     

Suspended sediment dynamics from repetitive Landsat data

Abstract

Repetitive Landsat CCT data were used to monitor the motion of non-uniformly distributed suspended sediments in a New Zealand tidal basin. The movement of such suspended sediment was followed using all four MSS bands with non-uniformly distributed suspended sediment being differentiated from bottom features by the data from two satellite overpasses. As pan of this study penetration depths of 45-50±5 cm and 10-15 ±5 cm were found for channels MSS 5 and MSS 6 over the sediment-laden tidal inlet. The difference in penetration depths within each MSS band was ascribed to differing concentrations of uniformly distributed suspended sediments between the two overpasses.     

Change detection techniques

Timely and accurate change detection of Earth's surface features is extremely important for understanding relationships and interactions between human and natural phenomena in order to promote better decision making. Remote sensing data are primary sources extensively used for change detection in recent decades. Many change detection techniques have been developed. This paper summarizes and reviews these techniques. Previous literature has shown that image differencing, principal component analysis and post-classification comparison are the most common methods used for change detection. In recent years, spectral mixture analysis, artificial neural networks and integration of geographical information system and remote sensing data have become important techniques for change detection applications. Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, different algorithms are often compared to find the best change detection results for a specific application. Research of change detection techniques is still an active topic and new techniques are needed to effectively use the increasingly diverse and complex remotely sensed data available or projected to be soon available from satellite and airborne sensors. This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature.

Abbreviations used in this paper

6S second simulation of the satellite signal in the solar spectrum

ANN artificial neural networks

ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer

AVHRR Advanced Very High Resolution Radiometer

AVIRIS Airborne Visible/Infrared Imaging Spectrometer

CVA change vector analysis

EM expectation–maximization algorithm

ERS-1 Earth Resource Satellite-1

ETM+ Enhanced Thematic Mapper Plus, Landsat 7 satellite image

GIS Geographical Information System

GS Gramm–Schmidt transformation

J-M distance Jeffries–Matusita distance

KT Kauth–Thomas transformation or tasselled cap transformation

LSMA linear spectral mixture analysis

LULC land use and land cover

MODIS Moderate Resolution Imaging Spectroradiometer

MSAVI Modified Soil Adjusted Vegetation Index

MSS Landsat Multi-Spectral Scanner image

NDMI Normalized Difference Moisture Index

NDVI Normalized Difference Vegetation Index

NOAA National Oceanic and Atmospheric Administration

PCA principal component analysis

RGB red, green and blue colour composite

RTB ratio of tree biomass to total aboveground biomass

SAR synthetic aperture radar

SAVI Soil Adjusted Vegetation Index

SPOT HRV Satellite Probatoire d'Observation de la Terre (SPOT) high resolution visible image

TM Thematic Mapper

VI Vegetation Index     

Vegetation spatial variability and its effect on vegetation indices

Abstract

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification programme. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12·7 per cent in determining these areas. NDVI values less than 0·3 represented fractional vegetated areas of 5 per cent or less, while a value of 0·7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0·89 and 0·95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.     

Effet de la reésolution spatiale sur des proprieeacute;teés statistiques des images satellites: une eétude de cas

Abstract

The instruments on such satellites as Landsat or SPOT present the advantage provided by high spatial resolution. This advantage is tempered by their low time resolution. Therefore, it is not always possible to monitor seasonal variations of parameters such as the normalized vegetation index. The AVHRR instrument on board the NOAA satellites has a very high repetitivity but a very low spatial resolution. In our research we proposed to monitor the normalized vegetation index with this low-resolution instrument. It is therefore of interest to examine the relations between high- and low-resolution images for using the AVHRR data as a means of interpolation between two MSS images. This problem is addressed here using satellite images of an important agricultural region in France. In terms of the transformation of the mean radiometric values, it is shown that a linear transformation exists to calculate the AVHRR data from those of the MSS. but the relation presents a strong dependency on the observed scene. The effect on the higher-order statistical properties is studied through the transformation of the images textures by progressively degrading the MSS images. It is shown that a threshold, which depends on the scene, exists on the resolution below which all statistical information disappears.     

Multi-channel higher-order local autocorrelation for object detection on satellite images

ABSTRACT

An automatic object-detection method is necessary to facilitate the efficient analysis of satellite images consisting of multispectral images. Considering that the relationship between spectrums is important for discriminating objects in multispectral images. This paper proposes a feature extraction method that can capture both spatial and spectral relationships of the multispectral images. Moreover, image preprocessing and dimensionality reduction procedures are introduced for stable feature extraction. In this study, we conducted experiments for detecting two types of objects by using Landsat 8 images. The proposed method improved the detection performance relative to other image features.     

Location of kimberlites using Landsat Thematic Mapper images and aerial photographs: the Redondao diatreme,Brazil

Abstract

Landsat Thematic Mapper images and aerial photographs were used in the detection of kimberlile-derived materials in the Redondao test site. In this area kimberlite-derived soils show a flora constituted mainly by grasses and shrubs, which differ from the surrounding savanna-park (cerrado) vegetation cover. Band-ratio images were able to distinguish kimberlite-derived materials by enhancing areas with different vegetation covers. However, the coarse spatial resolution of Landsat-TM images compared with the spatial variability of the study area, and the removal of topographic shadowing effects on ratio images blurred several landscape features. To increase discrimination, Landsat Thematic Mapper ratio images were merged with digitized aerial photographs through intensity, hue and saturation (IHS) colour transforms. The resulting merged colour composite highlighted the spatial and spectral features of the study area permitting an accurate definition of the kimberlite-derived materials within the Redondao diatreme.     

Agreement assessment of NOAA/AVHRR NDVI with Landsat TM NDVI for mapping burned forested areas

Meteorological satellites are appropriate for operational applications related to early warning, monitoring and damage assessment of forest fires. Environmental or resources satellites, with better spatial resolution than meteorological satellites, enable the delineation of the affected areas with a higher degree of accuracy. In this study, the agreement of two datasets, coming from National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Landsat TM, for the assessment of the burned area, was investigated. The study area comprises a forested area, burned during the forest fire of 21-24 July 1995 in Penteli, Attiki, Greece. Based on a colour composite image of Landsat TM a reference map of the burned area was produced. The scatterplot of the multitemporal Normalized Difference Vegetation Index (NDVI) images, from both Landsat TM and NOAA/AVHRR sensors, was used to detect the spectral changes due to the removal of vegetation. The extracted burned area was compared to the digitized reference map. The synthesis of the maps was carried out using overlay techniques in a Geographic Information System (GIS). It is illustrated that the NOAA/AVHRR NDVI accuracy is comparable to that from Landsat TM data. As a result NOAA/AVHRR data can, operationally, be used for mapping the extent of the burned areas.     

Remote sensing monitoring of ocean colour in Pearl River estuary

The study attempts to provide additional understanding of the long-term evolution of water quality in the Pearl River estuary and Hong Kong coastal areas by monitoring the ocean colour from remote sensing images. The extensively inter-connected river network of Pearl River estuary has a large catchment area and its environmental deterioration due to rapid economic growth is significant. The data received by Landsat satellites, over a time period of more than 20 years, were used to evaluate the evolution of water clarity. The study shows the historical varying of sea colour in these areas and image processing methods for extracting the ocean colour features of Landsat images are suggested. The algorithm of 'Gradient Transition' was used to calibrate the result images and the comparing method was used to process and analyse remote sensing images of Case 2 water.     

Radiometric comparison of the LANDSAT-5 TM and MSS sensors

Abstract

This paper analyses the radiometric accuracy of LANDSAT-5 Thematic Mapper (TM) data and of LANDSAT-5 Multispectral Scanner (MSS) data, using concurrent TM and MSS images recorded simultaneously over the city of Montreal, Quebec, Canada. The data sets were obtained from the Canada Centre for Remote Sensing (CCRS), and have been preprocessed for geometric correction, and for radiometric 23calibration utilizing the in-flight calibration lamp data. The comparison of the TM and MSS normalized apparent reflectances computed for 12 different typical cover types using the post-launch calibration dynamic ranges shows the relevance of the CCRS processing systems. The significant linear regressions, obtained between channels from the two sensors, and the analysis of the ground reflectance corrected for atmospheric absorption and scattering as well as for pixel adjacency effects, can serve both to assess detector degradation with time and to rescale data to match those from other LANDSAT sensors.