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1.
Abstract

Hydrology and Water Management are key areas of applied science in the current world economy. Increasingly hydrologiste are looking to satellite remote sensing to help meet their needs for near real‐time data to measure, monitor and model water in the environment. However, progress has been hindered by the lack of a dedicated series of hydro‐logical satellites.

The paper summarises studies undertaken on an international basis in order to influence satellite, sensor and ground segment design operations to suit the needs of water management.  相似文献   

2.
Differentiation between benthic habitats, particularly seagrass and macroalgae, using satellite data is complicated because of water column effects plus the presence of chlorophyll-a in both seagrass and algae that result in similar spectral patterns. Hyperspectral imager for the coastal ocean data over the Indian River Lagoon, Florida, USA, was used to develop two benthic classification models, SlopeRED and SlopeNIR. Their performance was compared with iterative self-organizing data analysis technique and spectral angle mapping classification methods. The slope models provided greater overall accuracies (63–64%) and were able to distinguish between seagrass and macroalgae substrates more accurately compared to the results obtained using the other classifications methods.  相似文献   

3.
Ocean-colour remote sensing in optically shallow waters is influenced by contribution from the water column depth as well as by the substrate type. Therefore, it is required to include the contribution from the water column and substrate bottom type for bathymetry estimation. In this report we demonstrate the use of Artificial Neural Network (ANN) based approach to spectrally distinguish various benthic bottom types and estimate depth of substrate bottom simultaneously in optically shallow waters. We have used in-water radiative transfer simulation modeling to generate simulated top-of-the-water column reflectance the four major benthic bottom types viz. sea grass, coral sand, green algae and red algae using Hydrolight simulation model. The simulated remote sensing reflectance, for the four benthic bottom types having benthic bottom depth up to 30 m were generated for moderately clear waters. A multi-layer perceptron (MLP) type neural network was trained using the simulated data. ANN based approach was used for classification of the benthic bottom type and simultaneous inversion of bathymetry. Simulated data was inverted to yield benthic bottom type classification with an accuracy of ~98% for the four benthic substrate types and the substrate depth were estimated with an error of 0% for sea grass, 1% for coral sand and 1–3% for green and red algae up to 25 m, whereas for substrate bottom deeper than 25 m depth the classification errors increased by 2–5% for three substrate bottom types except sea grass bottom type. The initial results are promising which needs validation using the in-situ measured remote sensing reflectance spectra for implementing further on satellite data.  相似文献   

4.
In order to evaluate the potentials of IRS‐1A Linear Imaging Self‐scanning Sensor (LISS‐I) data for geological and geomorphological applications and also to compare the IRS‐1A LISS‐I data with Landsat Thematic Mapper (TM) data, a study has been attempted for parts of Uttar Pradesh and Madhya Pradesh in Northern India. The first four spectral bands of Landsat TM sensor data which are similar and close to IRS‐1A LISS‐I senor have been utilised for the comparative evaluation. Various techniques employed for both the data set to derive the required geology and geomorphology related information include (i) band combination (ii) spectral response analysis (iii) principal component analysis (iv) supervised classification techniques and (v) visual observation of various outputs generated by the above methods. The Optimum Index Factor (OIF) method adopted for selecting suitable band combinations showed similar OIF rankings for IRS‐1A LISS‐I data and Landsat TM data. It has been visually observed that the band combination 1, 3 & 4 offers relatively better feature display. The spectral responses derived for various major geologic rock units such as Deccan Trap, Vindhyan Formation, Bundelkhand Granite and for a few landcovers such as surface water bodies and black soil show striking similarity in pattern for both LISS‐I and TM. The Principal Component (PC) analysis of both data sets suggested that the total scene brightness tends to dominate in the first PC. The percentage information contributed by PCs 1&2 as also by PCs 1,2 & 3 in both the LISS‐I and TM are comparable. It was observed from the classified image generated by performing supervised classification with a maximum likelihood algorithm that major geomorphic landforms were clearly distinguishable. Thus the qualitative and quantitative evaluation of both IRS‐1A LISS‐I and Landsat TM data showed that significant similarities exist between them. The study also revealed that IRS‐1A LISS‐I data can be effectively used for deriving geology and geomorphology related details.  相似文献   

5.
Visual interpretation of satellite images could help in the identification of present and past landforms. An attempt has been made to identify the palaeochannels of the Cauvery river in Karnataka state through visual interpretation of IRS-1C, LISS III False Colour Composites (FCC). In order to assess their inter-relationship with other hydrogeomorphic elements, various geomorphic units have been mapped. Major geomorphic units like alluvial plain, pediplain, valley fill. residual hill, ridges, meander scar, channel bars and water bodies have been demarcated. Considering the hydrogeomorphic setup of the palaeochannels. it is inferred that the disposition of palaeochannels of the area are controlled by the geology and structure and the prevailing geomorphic process.  相似文献   

6.
An empirical study was performed assessing the accuracy of land use change detection when using satellite image data acquired ten years apart by sensors with differing spatial resolutions. Landsat/Multi‐spectral Scanner (MSS) with Landsat/Thematic Mapper (TM) or SPOT/High Resolution Visible (HRV) multi‐spectral (XS) data were used as a multi‐data pair for detecting land use change. The primary objectives of the study were to: (1) compare standard change detection methods (e.g. multi‐date ratioing and principal components analysis) applied to image data of varying spatial resolution; (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice‐versa in the registration process: and (3) determine if Landsat/TM or SPOT/ HRV(XS) data provides more accurate detection of land use changes when registered to historical Landsat/MSS data.

Ratioing multi‐sensor, multi‐date satellite image data produced higher change detection accuracies than did principal components analysis and is useful as a land use change enhancement technique. Ratioing red and near infrared bands of a Landsat/MSS‐SPOT/HRV(XS) multi‐date pair produced substantially higher change detection accuracies (～10%) than ratioing similar bands of a Landsat/MSS ‐ Landsat/TM multi‐data pair. Using a higher‐resolution raster grid of 20 meters when registering Landsat/MSS and SPOTZHRV(XS) images produced a slightly higher change detection accuracy than when both images were registered to an 80 meter raster grid. Applying a “majority”; moving window filter whose size approximated a minimum mapping unit of 1 hectare increased change detection accuracies by 1–3% and reduced commission errors by 10–25%.  相似文献   

7.
Abstract

Tectonic mapping and geologic evolution of a region were historically conducted on the basis of field observations. After the advent of remote sensing technology, tectonic mapping became much easier and structural mapping through imagery has gained credibility and suitability in regional mapping, tectonic evolution and modeling. In this regard, an attempt has been made to make use of the satellite technology to bring out the structural trends and the fracture/lineament pattern in Biligirirangan region of Northern Tamil Nadu through satellite remote sensing. The folded architecture in Biligirirangan region has evolved from structural trends. The subsurface structures of the region were derived through resistivity contours and resistivity images created by GIS software.

The surficial information derived from the satellite imagery and subsurface structures derived from the resistivity contours and images were integrated with field observations. This integration has given a clear tectonic picture of the Biligirirangan region and the tectonic structures were then analysed for tectonic forces, evolution and modeling.

The study determined that the Structural trends were mostly in a N‐S direction and the folds were of isoclinal type with alternating synclinal and anticlinal folds of an easterly dipping nature. These folds in conjunction with the lineaments have brought out the palaeostress pattern of the Biligirirangan region. The study further suggests that the regional compressive force trending in ENE‐WSW direction was responsible for the present configuration of folds. In addition, the study also focuses the efficacy of the satellite imagery in tectonic analysis and the resistivity contours and images for the subsurface structural analysis.  相似文献   

8.
Abstract

The output from any spatial data processing method may contain some uncertainty. With the increasing use of satellite data products as a source of data for Geographical Information Systems (GIS), there have been some major concerns about the accuracy of the satellite‐based information. Due to the nature of spatial data and remotely sensed data acquisition technology, and conventional classification, any single classified image can contain a number of mis‐classified pixels. Conventional accuracy evaluation procedures can report only the number of pixels that are mis‐classified based on some sampling observation. This study investigates the spatial distribution and the amount of these pixels associated with each cover type in a product of satellite data. The study uses Thematic Mapper (TM) and SPOT multispectral data sets obtained for a study area selected in North East New South Wales, Australia. The Fuzzy c‐Means algorithm is used to identify the classified pixels that contained some uncertainty. The approach is based on evaluating the strength of class membership of pixels. This study is important as it can give an indication of the amount of error resulting from the mis‐classification of pixels of specific cover types as well as the spatial distribution of such pixels. The results show that the spatial distribution of erroneously classified pixels are not random and varies depending on the nature of cover types. The proportions of such pixels are higher in spectrally less clearly defined cover types such as grasslands.  相似文献   

9.

Forest vegetation of Vindhyan range located in the north of G.B. Pant Sagar (dam) has been subjected to degradation due to high biotic pressure caused by the installation of thermal power plants, coal mining, heavy cattle grazing etc. In the present study Landsat TM FCC of 1∶250,000 scale was visually analysed with respect to forest vegetation types, crown density and structure along with other landuse/land cover classes. ExceptShorea robusta (Sal) andLagerstroemia parviflora (Lendia) all forest vegetation types show higher percentage of degradation and under-stocked condition with respect to their areal extent under study. Overall classification accuracy of the forest types has been found to be 88.94%. This indicates that for obtaining reliable mapping accuracy in dry deciduous areas, satellite remote sensing data of appropriate season is essential.

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10.
Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative remotely sensed imagery and quantitative data, such as aerosol optical depth which is the basic unknown parameter for any atmospheric correction method in the pre‐processing of satellite imagery. This article presents a new method for retrieving aerosol optical thickness directly from satellite remotely sensed imagery for short wavelength bands in which atmospheric scattering is the dominant contribution to the at‐satellite recorded signal. The method is based on the determination of the aerosol optical thickness through the application of the contrast tool (maximum contrast value), the radiative transfer calculations and the ‘tracking’ of the suitable darkest pixel in the scene. The proposed method that needs no a‐priori information has been applied to LANDSAT‐5 TM, LANDSAT‐7 ETM+, SPOT‐5 and IKONOS data of two different geographical areas: West London and Cyprus. The retrieved aerosol optical thickness values show high correlations with in‐situ visibility data acquired during the satellite overpass. Indeed, for the West London area a logarithmic regression was fitted for relating the determined aerosol optical thickness with the in‐situ visibility values. A high correlation coefficient (r2= 0.82; p= 0.2) was found. Plots obtained from Tanre et al. (1979, 1990) and Forster (1984 ) were reproduced and estimates for these areas were generated with the proposed method so as to compare the results. The author's results show good agreement with Forster's aerosol optical thickness vs. visibility results and a small deviation from Tanre's model estimates.  相似文献   

11.
The spectroradiometric retrieved reflectance of a local crop, namely, beans (Phaseolus vulgaris), is directly compared to the reflectance of Landsat 5TM and 7ETM+ atmospherically corrected and uncorrected satellite images. Also, vegetation indices from the same satellite images—atmospherically corrected and uncorrected—are compared with the corresponding vegetation indices produced from field measurements using a spectroradiometer. Vegetation Indices are vital in the estimation of crop evapotransiration under standard conditions (ETc) because they are used in stochastic or empirical models for describing crop canopy parameters such as the Leaf Area Index (LAI) or crop height. ETc is finally determined using the FAO Penman-Monteith method adapted to satellite data, and is used to examine the impact of atmospheric effects. Regarding the reflectance comparison, the main problem was observed in Band 4 of Landsat 5TM and 7ETM+, where the difference, for uncorrected images, was more than 20% and statistically significant. Results regarding ETc show that omission or ineffective atmospheric corrections in Landsat 5TM,/7ETM+ satellite images always results in a water deficit when estimating crop water demand. Diminished estimated crop water requirements can result in a reduction in output or, if critical, crop failure. The paper seeks to illustrate the importance of removing atmospheric effects from satellite images designated for hydrological purposes.  相似文献   

12.
The Regione del Veneto (Italy) is cooperating with the University of California, Santa Barbara and other researchers in Italy and the U.S.A. to develop a system of econometric crop production modeling. Five crops are to be included in this project: small grains (wheat and barley), corn, sugar beets, soybeans, orchards and vineyards. A critical part of the crop yield modeling process is the identification of crops using multispectral satellite data. This paper explores two strategies to improve crop classification accuracies: (1) use of ancillary data stored in digital format and (2) use of multitemporal data. Ancillary information stored on digital files were used in this research to remove (mask) non‐agricultural areas from satellite image data. Comparison between the classification of masked and unmasked images showed that improvement ranged from 3% to 26% depending on crop type. The multidate classification was performed by compiling an image of transformed spectral bands and three TM‐5 bands. The transformed bands were TM band 4 over TM band 3. Based on the work conducted in this study it is clear that crop type determination from satellite imagery is possible for small field agricultural areas such as those found in Italy.  相似文献   

13.
Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) data were digitally analyzed for forest type identification in the Kisatchie Ranger District, Kisatchie National Forest, Louisiana. Ground‐verification maps were produced from field surveys and interpretation of 1.12,000 and 1: 58,000 color‐infrared (CIR) aerial photography of nine compartments. Stand boundary and soils maps were input to a digital Geographic Information System (GIS) with the Landsat and ground‐verification data.

‐ Unsupervised classifications of the Landsat data did not identify the above cover types well. Supervised classifications were tested by stand agreement to the ground verification. The highest four‐class agreement was obtained for the TM classification (76 percent). Three‐class (open, pine, and hardwoods) stand agreements (81 (MSS) and 85 (TM) percent) were not significantly different as tested by analysis of variance (alpha level 0.1).  相似文献   

14.
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15.
Abstract

Grazing changes plant species composition of grassland ecosystems by selective removal and trampling. Grazing also alters soil physical and biogeochemical properties and can dramatically change hydrologic processes that can impact water budgets and quality. For these reasons, practical means are needed to assess grazing management practices and its impacts upon the land. This study examines whether a grazing intensity and range condition gradient can be detected in spectral reflectance characteristics of grasslands in northeastern Kansas. Multitemporal Landsat Thematic Mapper (TM) data, the normalized difference vegetation index (NDVI), and field data collected concurrent with the TM overpasses, were used in the analysis. Correlation analysis was used to examine relationships between spectral data and biophysical data. Next, the study sites within each grassland type were classified into three spectrally similar clusters. Grazing intensity, range condition, and biophysical characteristics were summarized for each spectral cluster and compared.

The results suggest that NDVI may be used as a surrogate for living biomass for both grassland types and may be useful for predicting grazing intensity in native warm season grasslands. And while there appeared to be relationships between total living and non‐living cover, and TM NIR and MIR bands, there were no direct relationships between spectral characteristics and grazing intensity or range condition.  相似文献   

16.
Abstract

Photogeological techniques were used to analyze Landsat‐TM images of the Paraiba State, which resulted in the identification of the following structures: lineaments of regional extent, short en echelon lineaments, intricate ramification of the wrench system, and infrastructures among major lineaments and circular or ring structures. This lineament map was correlated to existing geological maps, to areas of known hydrothermal mineralization (Cu, Au, Mo, Ni, W and Ti), and the lineament map was verified in the field reconnaissance. Due to lack of systematic studies of the geology and natural resources of the region the mineral exploration is still in rudimentary stages. The objective of this research is to emphasize the detection and analysis of lineaments, their patterns, and geometry and their relations with the occurrence of mineral resources and its exploration in areas as yet explored. A large number of mineral‐bearing pegmatites of the region are controlled by major lineaments and associated minor lineaments. It is believed that the structures of interest in search for mineral deposits are warping part of the minor shear zones, the intersections of short and regional lineaments, and the circular features.  相似文献   

17.
The detection of buried archaeological remains using satellite remote sensing is still an open question in archaeological research. This research investigates how the phenological stages of crops can be used support the detection of buried archaeological remains. Ground remote sensing data using the GER-1500 spectroradiometer were obtained from two sites. One site was the Neolithic settlements in central Greece and the other was in Alampra village in Cyprus. For the latter, an archaeological environment was simulated and ground spectroradiometric measurements were systematically acquired over the different phases of the phenological cycle of barley crops. The acquired in situ reflectance measurements have been converted to "in-band" reflectance values of the Landsat TM/ETM+ using the satellite relative spectral responses filters (RSR). Based on the proposed methodology, 97 Landsat MSS, TM, and ETM+ satellite images were acquired (covering a period from 1983 to 2011), for the Thessalian (Greek) site. It has been found that phenological-cycle observations can provide valuable information for identifying buried archaeological remains. Such observations may be used in cases where the spatial resolution of satellite imagery is not high and therefore cannot help support the detection of archaeological remains using standard interpretation techniques.  相似文献   

18.
Changes in shoreline, coral reef and seafloor have been mapped using remote sensing satellite data of IRS LISS-III (1998), IRS LISS-II (1988), Survey of India Topographic sheet (1969), Naval Hydrographic Chart (NHO) 1975 and bathymetry data (1999) with ARC-INFO and ARC-VIEW GIS. The analysis of multi-date shoreline maps showed that 4.34 and 23.49 km2 of the mainland coast and 4.14 and 3.31 km2 areas of island coast have been eroded and accreted, respectively, in the Gulf of Mannar. The analysis of multi-date coral reef maps showed that 25.52 km2 of reef area and 2.16 km2 of reef vegetation in Gulf of Mannar have been lost over a period of ten years. The analysis of multi-date bathymetry data indicates that the depth of seafloor has decreased along the coast and around the islands in the study area. The average reduction of depth in seafloor has been estimated as 0.51m over a period of twenty four years. The increased suspended sediment concentration due to coastal and island erosion, and raised reef due to emerging of coast by tectonic movement are responsible for coral reef degradation in the Gulf of Mannar. Validation by ground truth has confirmed these results.  相似文献   

19.
Abstract

On November the 13th of 1985, the City of Armero (Colombia) was destroyed by debris flows generated by a reactivation of the Nevado del Ruiz Volcano. The flows ocurred in at least three principal pulses, as was observed by the disater's survivors. Landsat TM 5 data processing was carried out in subscenes taken before and after the lahar sedimentation.

False color composites were generated and combined with the geological information available in order to visualize the magnitude of the catastrophe and the flow characteristics. Taking advantage of Landsat TM 5 images with high spectral resolution, a detailed photogeological mapping of the three principal pulses of the debris flows was carried out. Landsat TM 5 proved to be a powerful complementary source of information for hazard assesment of these catastrophic debris flows. The images were used in addition to ground‐based information, and were an easy way to help ordinary people and decision makers understand such hazardous volcanic situations.  相似文献   

20.
Abstract

Short time‐intervals for complex response in unfamiliar areas cause refugee‐relief organisations to have a strong need for timely and up‐to‐date geographic information of the environment during humanitarian operations. The objective of this study is to provide an overview of relief organisations' need for detailed geographic information, and to assess the potential of the upcoming very high spatial resolution (VHSR) satellite sensors to provide this geographic information by mapping refugee camps and their environment on an operational basis. To demonstrate the use of VHSR satellite technology in relief operations, a pilot proof‐of‐concept study using a 1992 Russian KVR‐lOOO 2 m resolution panchromatic image of the six refugee camps in the Qala en Nahal settlement scheme in the Sudan was performed. The VHSR satellite sensor image was found to be useful for mapping refugee camp environmental parameters, such as land use, roads, rivers, and water sources, as well as camp infrastructure, including geographic positioning of camps, housing, and street network. The image also allowed for detailed camp area estimates. In addition, a statistically significant relationship between camp area and population was revealed for refugee camps included in this study. In operational use of VHSR satellite sensor data, relief agencies should be aware of the limitations of optical satellite images, in particular their reduced applicability during cloudy conditions.  相似文献   

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