Landsat thematic mapper studies of land cover spatial variability related to hydrology

The Landsat 4 and 5 Thematic Mapper (TM) provides increased spatial, spectral, and radiometric capability relative to the Multispectral Scanner (MSS). Visual inspection of TM imagery confirms this. Land cover detail is evident that would be of use in watershed management and planning activities. Specific studies have been conducted in Georgia, West Virginia, Michigan and Maryland to compare MSS and TM for urbanizing watersheds, wetlands, and floodplain mapping situations. These studies show that only modest improvements in classification accuracy (Anderson Level I/II) have been achieved using existing classification approaches. An attempt to identify the visibly apparent interstate highways and secondary and residential streets in TM data via conventional approaches failed due to an inability to derive separable spectral signatures. The basis for a non-parametric approach to classification is presented in which roads are identified by locating linear local minima in the greenness transformed dimension. Preliminary results indicate that such a method provides more reliable road locations than MSS or TM used singly.     

Applicationof remote sensing techniques in geological studies of various mineralized belts in India. (National paper on IGCP — 143)

Geological interpretation, analysis and evaluation of LANDSAT and airborne MSS data, panchromatic and colour infrred photographs and spectral reflectance data for a number of test sites in different mineralized belts in India have led to certain significant results. Lithological discrimination on digitally processed enhanced MSS data products has helped in further subdivisions of major rock groups. Lineament pattern analyses reveals three prominent sets of fractures in Indian Precambrian Shield with predominant ENE-WSW megalineament probably representing earliest deep crustal fractures and subsequent NNW-SSE and NE-SW fractures, associated with polyphase tectonic movements. Correlation of structures and mineralization indicate structural control for most of the mineralized belts with intersecting locii type concentration of ore deposits in some cases. In a few cases control of mineralization is lithology and stratigraphy. Spectral groundtruth and laboratory studies indicate that major rock types have characteristic spectral patterns (signatures) which would be useful for lithological mapping by automatic classification techniques. The work also has led to the improvement of enhanced MSS data products for geological studies.     

Sensor data for forest policy information

NASA-Ames Research Center has investigated the role and performance capabilities of the Landsat Multi-Spectral Scanner (MSS) for forest policy analysis for the past four years in cooperation with the California Department of Forestry. A thorough series of studies, from a statewide land cover map to smaller, highly detailed studies including collateral data, have been conducted with a view to comprehensive forest policy needs. The strengths and limitations of MSS data have been evaluated. Some observations about the information needed from new satellite sensors such as the Thematic Mapper are discussed against this background.     

Remote sensing salt marsh biomass and stress detection

A hand-held radiometer was used to gather spectral radiance data simulating bands 3, 4 and 5 of the Landsat-D Thematic Mapper. Variations in biomass of the salt marsh plant $\text{Spartina alterniflora}$ were highly correlated to changes in spectral radiance expressed as the vegetation index or the infrared index. Negative stresses like increased soil salinity and increased concentrations of copper or zinc yielded reductions in biomass which were detected spectrally. Positive stresses like freshwater and sewage effluent additions produced an increase in biomass which also were detected using spectral data. The demonstrated detection of biomass from spectral data was expanded spatially and temporally to estimate net primary productivity of a salt marsh. Remote sensing estimates of production ranged from 5 to 20% of estimates from harvest data. Future applications of this biomass estimation technique, employing data gathered from satellite platforms and from the ground, are discussed for salt marsh systems.     

改进的GPS掩星滑动频谱方法

在大气多路径和噪声的条件下,高斯白噪声会造成滑动频谱方法获得的弯曲角与真值之间的偏离,无法获得较好的反演结果。为此,文章提出了一种改进的滑动频谱方法,即利用信号的振幅和谱能量信息对滑动频谱方法进行修正,削弱了信号中噪声的影响,与真值较为接近。分别用改进前后两种方法对中华卫星三号计划（Constellation Observing System for Meteorology, Ionosphere and Climate,COSMIC）的掩星进行反演,并将其折射率计算结果和通过全谱反演方法获得的折射率一起,与欧洲中期天气预报中心（European Centre for Medium Range Weather Forecasts,ECMWF）的分析场资料进行了统计比较。结果表明：改进的滑动频谱方法删除了信号中的部分噪声,减少了系统偏差;与全谱反演方法进行比较,发现两者具有相当的反演精度。     

Experiment for mapping land cover and it’s change in southeastern Sri Lanka utilizing 250 m resolution MODIS imageries

Utilizing freely available MODIS NDVI and Natural color imageries of 250 m spatial resolution produced by NASA, an experiment was made to map land-cover and its change with an emphasis on vegetation cover in southeastern Sri Lanka, which plays a vital role for control of green house gas. For the change detection purpose, 1987 land cover map made by present authors from Landsat MSS image and extensive ground truth survey data was used as the base map. The result of the experiment shows that MODIS data are useful to make a land cover map of 250 m spatial resolution for tropical areas with high cloud coverage like Sri Lanka. It was found that the forest cover decrease amounted as large as 21% in 19 years time span in southeastern Sri Lanka, the prominent forest region of the country. On the other hand homestead/vegetation and mixed vegetation/scrub dominant categories increased by 13.7% and 7.1%, respectively. These changes are considered due to a large clearance of forest areas for agriculture and building houses to accommodate increasing inhabitants.     

Landsat image data quality studies

The July 1982 launch of Landsat-4 was immediately followed by a two-year comprehensive set of detailed investigations sponsored by the National Aeronautics and Space Administration (NASA) at Goddard Space Flight Center (GSFC). The Landsat Image Data Quality Analysis (LIDQA) research plans for these investigations were specified prior to launch, so that minimum time would be lost in assessing the performance of the long-awaited Thematic Mapper (TM) sensor that Landsat-4 carried in addition to a fourth Multispectral Scanner (MSS). The LIDQA investigations have been substantially completed, and have shown that the TM is a very good spaceborne multispectral radiometer, and has met or exceeded most of its design goals. TM's new short-wave infrared (SWIR) spectral capability yielded improved mineral and plant discrimination compared to the MSS, as anticipated by ground-based and airborne TM simulations. Moreover, the improved spatial resolution and geometric accuracy of Landsat-4 and the TM have resulted in satellite image maps exceeding 1:100,000 U.S. map accuracy standards. Finally, based on an information entropy measure, principal component analysis, and classification results, TM data has been shown to approach its theoretical limit in information content per pixel, exceeding the MSS by at least a factor of two.     

一种计算开伞动载的实用方法

依据海因里奇开伞动力理论,在计算个表充满时间的连续方程中,考虑了伞顶孔,伞顶部分大透气量织物面积,以及伞衣中、下部分织物透气量对开伞动载的影响。引用了非线性的阻力特征文化曲线［２］,计算伞衣充气过程中阻力特征的变化。并考虑了伞衣充气过程初始瞬时的阻力特征,假设在伞衣初始充气时期的一段时间中,进气口直径为常值,数值上等于［４（ＣＡ）０／Ｃ（ｓｔ）π）］（１／２）。计算实例表明,计算结果与实测数据相比较,其一致性是比较满意的。     

Merging Landsat and spaceborne radar data over Tunisia

Synthetic Aperture Radar data were acquired over Tunisia by Seasat in Aug. 1978 and by SIR-A in Nov. 1981. The radar images are contrasted to the Landsat scenes overlapping the same area. The Landsat images were taken in Aug. 1978 and in Sept. 1981. In this study, subareas of the SIR-A and MSS images are registered to the corresponding Seasat data (1313 lines by 1970 samples). The test site is located East of Kairouan, Tunisia. It is a low relief area with subdesertic climatic conditions. This region was selected for it has been surveyed by both Seasat and SIR-A providing perpendicular radar illumination directions. The multispectral and multitemporal coregistered data set enables comparisons between the systems (radar versus MSS, and Seasat versus SIR-A), and change detection in the desertification processes and on the surface of the playas.     

Inferring non-point pollution from land cover analysis

Best Management Practices (BMP's) in farming were found to significantly reduce agricultural non-point water pollution in Central Indiana. Through the implementation of systems of conservation tillage practices and structural measures at the farm level, reductions in runoff were achieved, thereby minimizing erosion and subsequent sedimentation and pollution of the surface water system.These conclusions resulted from a three and one-half year study entitled, “The Indiana Heartland Model Implementation Project” administered by the Indiana Heartland Coordinating Commission, involving cooperation and coordination of farmers, citizens, and a multi-agency, multi-disciplinary team comprised of four universities and numerous governmental agencies. The U.S. Environmental Protection Agency funded research, while the U.S. Department of Agriculture provided cost share monies for BMP implementation.A comprehensive geographically encoded computer-aided data base was constructed which included information on land cover, elevation, slope, aspect, soils, etc. Land cover map files were compiled through remote sensing including Landsat MSS digital data and low altitude color infrared aerial photography sources. This digital data base was suited for spatial and statistical analyses and transferred easily as input to Purdue University's ANSWERS Model for further watershed assessment. The ANSWERS Model is a distributed deterministic model which simulates the monitored reaction of subwatersheds to actual storm events. Through this model inferences were made as to the expected water quality improvements, given BMP's were implemented at critical areas for erosion throughout both watersheds.     

Red edge measurements for remotely sensing plant chlorophyll content

The feasibility of using the wavelength of the maximum slope of the red edge of leaf reflectance spectra (λ_re) as an indication of plant chlorophyll status was examined in the laboratory for single leaves of several species. λ_re for each sample was determined by derivative reflectance spectroscopy. A high positive correlation was found between λ_re and leaf chlorophyll content for all species, although there were some differences in the quantitative nature of the relationship for plants of different types. The position of the red edge was found to be unaffected by simulated change in ground cover, but multiple leaf layers produced a shift in its position. Appropriate spectral measurements and processing for obtaining useful information from the red edge are discussed, and the potential of the red edge in relation to other spectral measurements is considered.     

Evaluation of thematic mapper data for mapping forest,agricultural and soil resources

Color composite TM film products which include TM5, TM4, and a visible band (TM1, TM2, or TM3) are superior to composites which exclude TM4 for discriminating most forest and agricultural cover types and estimating area proportions for inventory and sampling purposes. Clustering a subset of TM data results in a spectral class map which groups diverse forest cover types into spectrally and ecologically similar areas suitable for use as a stratification base in traditional forest inventory practices. Analysis of simulated Thematic Mapper data indicate that the location and number of TM spectral bands are suitable for detecting differences in major soil properties and characterizing soil spectral curve form and magnitude.     

Main conclusions of the international colloquium on “Spectral Signatures of Objects in Remote Sensing”

The colloquium held in Avignon (France) from September 8th to 11th 1981 within the framework of the International Society for Photogrammetry and Remote Sensing, was the first international meeting to be given over exclusively to the question of spectral signatures.A number of general conclusions can be drawn from the working sessions :- present day knowledge is much more advanced concerning visible and near infrared than for thermal infrared and (more particularly) micro-waves ;- irrespective of the spectral range studied, radiometric signals reflected or emitted by a vegetative canopy are closely related to its geometry ;- the combination of the vertical and oblique views of a given zone should provide additional data leading to finer discrimination between different crops at any given time ;- by using polarization of light, it should be possible to identify certain phenological stages.     

Retrieval of vegetation equivalent water thickness from reflectance using genetic algorithm (GA)-partial least squares (PLS) regression

This study aimed to investigate the performance of genetic algorithms coupled with partial least squares (GA-PLS) modeling of spectral reflectance in retrieving equivalent water thickness (EWT) at leaf and canopy level. A genetic algorithm was used to identify a subset of spectral bands sensitive to the variation in EWT, and PLS was then applied to relate the identified bands to EWT values. GA-PLS was applied to leaf level reflectance available from LOPEX dataset, and canopy data includes reflectance simulated by a leaf radiative transfer model PROSPECT and a canopy radiative transfer model SAILH and acquired by airborne visible/infrared imaging spectrometer (AVIRIS). The results indicate that GA-PLS has the capability of retrieving EWT from leaf and canopy reflectance, and achieved good estimation accuracy, i.e. low root mean square errors (RMSE) and high squared correlation coefficients (R²). For the retrieval at leaf level, the estimation accuracy can be as good as RMSE = 0.0019 g/cm² and R² = 0.939 or better. For the retrieval at canopy level, the model accuracy is RMSE = 0.0061 g/cm² and R² = 0.966 or better when PROSPECT-SAILH simulated reflectance was used; when AVIRIS image spectra were used, the model accuracy is RMSE = 0.0094 g/cm² and R² = 0.8734 for the calibration, and RMSE = 0.0132 g/cm² and R² = 0.7756 for the validation. These results from GA-PLS modeling support the conclusion that GA-PLS has the potential to be applied to AVIRIS, Hyperion and HyMap imagery for retrieving EWT. The selected bands for the AVIRIS datasets differ from those for the LOPEX and PROSPECT-SAILH simulated datasets, and this inconsistence of the selected bands for different datasets indicates that the GA-PLS method has the advantage of tuning the optimum bands for PLS regression and accommodating the effects of confounding factors.     

Preliminary evaluation of the landsat-4 thematic mapper data for mineral exploration

Landsat-4 Thematic Mapper (TM) data recorded over an arid terrain were analyzed to determine the applicability of using of TM data for identifying and mapping hydrothermally altered, potentially mineralized rocks. Clays, micas, and other minerals bearing the OH anion in specific crystal lattice positions have absorption bands in the 2.2-μm region (TM channel 7, TM7) and commonly lack features in the 1.6-μm region (TM5). Channel ratios TM5/TM7, TM5/TM4, and TM3/TM1 were combined into a color-ratio-composite (CRC) image and used to distinguish hydrothermally altered rocks, unaltered rocks, and vegetation. These distinctions are made possible by using the TM5 and TM7, channels which are not available in the Landsat multispectral scanner (MSS). Digital masking was used to eliminate ambiguities due to water and shadows. However, some ambiguities in identification resulted between altered volcanic rocks and unaltered sedimentary deposits that contained clays, carbonates, and gypsum, and between altered volcanic rocks and volcanic tuffs diagenetically altered to zeolites. However, compared to MSS data, TM data should greatly improve the ability to map hydrothermally altered rocks in arid terrains.     

Prospecting in glaciated terrain-integrating airborne and Landsat MSS

The effects of a glacially enriched zone of trace elements on soils and vegetation in the Thetford Mines area of Quebec were investigated using ground information plus digital Multispectral Scanner (MSS) data from airborne and Landsat sensors. The enriched zone was developed during the last glaciation when a southeastward flowing glacier eroded and dispersed an ultrabasic outcrop that had anomalous levels of Ni, Cu, Co, Cr, Mg and Fe.The dispersal train of enriched trace elements was detectable over an area at least 70 × 15 km ‘down-ice’ from the outcrop. In this zone total Ni concentrations in the soil ranged from background levels of 10 ppm to levels in excess of 1800 ppm. The dominant tree species, $\text{Abies}$$\text{balsamea}$ (balsam fir) and $\text{Picea glauca}$ (white spruce) reflect the soil anomaly with higher concentrations of trace elements in their tissue and lower concentrations of chlorophyll.An unsupervised enhancement of Landsat imagery showed that a tonal discontinuity was caused by a vegetation segregation related to the heavy metal enrichment soils. A detailed study based on Landsat MSS data was able to establish regional patterns of chlorophyll production by certain plant species closely related to the ultrabasic dispersal train. Multi-channel airborne MSS data confirmed the Landsat soil-plant patterns.     

P—平稳过程的最大ch熵谱估计

研究少平稳随机序列在Chrestenson变换意义下的功率谱密度及其最大熵估计问题,得到了功率谱密度函数与熵率的关系公式及最大熵谱估计的正规方程。在采样数据个数为p~m的情况下,最大熵谱估计可直接由已知的有限自相关数据表示。这些结果与Fourier意义下的功率谱密度估计有很大的不同。     

Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal’s cultivation, steppes and bar soil.     

Hydrologic appraisal of rivers plan-form at confluence zone — A case study using Landsat MSS data

In river systems confluences and bifurcations are typical features whose effects are largely dependent on the specific characteristics of the rivers involved. The study makes an attempt to analyse the planform configuration at the confluence zone of the Wainganga and Khobragadi rivers in the central part of India. The data used are the Landsat MSS CCT data of date 17.12.1972 for scene 154-046 and black and white aerial photographs of November, 1969. Supervised method of classification using maximum likelihood classification method is employed. The study confirms that the discharge and sediment transport in the individual rivers constitute the dominating factors in the changes of planform geometry at a confluence. The usefulness of the Landsat MSS data and digital analysis techniques. for generating the necessary data inputs for the study is also validated.     

Using the MIR bands in vegetation indices for the estimation of grassland biophysical parameters from satellite remote sensing in the Alps region of Trentino (Italy)

Development of new methods for estimating biophysical parameters can be considered one of the most important targets for the improvement of grassland parameters estimation at full canopy cover. In fact, accurate assessment methods of biophysical characteristics of vegetation are needed in order to avoid the uncertainties of carbon terrestrial sinks.

Remote sensing is a valid tool for scaling up ecosystem measurements towards landscape levels serving a wide range of applications, many of them being related to carbon-cycle models. The aim of this study was to test the suitability of satellite platform sensors in estimating grassland biophysical parameters such as LAI, biomass, phytomass, and Green herbage ratio (GR). Also, we wanted to compare some of the most common NIR and red/green-based vegetation indices with ones that also make use of the MIR band, in relation to their ability to predict grassland biophysical parameters.

Ground-truth measurements were taken on July 2003 and 2004 on the Monte Bondone plateau (Italian Alps, Trento district) in grasslands varying in land use and management intensities. From satellite platforms, an IRS-1C-LISS III image (18/07/2003; 25 m resolution in the visible-NIR and 70 m resolution in the MIR) and a SPOT 5 image (27/07/2004, 10 m resolution in the visible-NIR and MIR) were used.

LAI, biomass, and phytomass measurements showed logarithmic relationships with the investigated NIR and red/green-based indices. GreenNDVI showed the highest R² values (0.59, IRS 2003; 0.60, SPOT 2004). Index saturation occurred above approximately 100–150 g m⁻² of biomass (LAI 1.5–2). On the other hand, GR relationships were shown to be linear. MIR-based indices performed better than NIR and red/green-based ones in estimating biophysical variables, with no saturation effect. Biomass showed a linear regression with Canopy Index (MIR/green ratio) and with the Normalised Canopy Index (NCI) calculated as a normalised difference between MIR and green bands (IRS: R² = 0.91 and 0.90, respectively. SPOT: R² = 0.63 and 0.64). Similar correlations could also be found for LAI and phytomass, and GR predictability was shown to be higher than NDVI and GreenNDVI. According to these results obtained in the investigated areas, phytomass, biomass, LAI, and GR are linearly correlated with the investigated MIR band indices and as a result, these parameters could be estimated from the adopted satellite platforms with limited saturation problems.