International Journal of Remote Sensing

Kohiyama, M.; Hayashi, H.; Maki, N.; Higashida, M.; Kroehl, H. W.; Elvidge, C. D.; Hobson, V. R.

doi: 10.1080/01431160310001595033pmid: N/A

The disaster information system, the Early Damaged Area Estimation System (EDES), was developed to estimate damaged areas of natural disaster using the night-time imagery of the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS). The system employs two estimation methods to detect the city lights loss or reduction as possible impacted areas; one is the bi-temporal images (BTI) method and the other is the time-series images (TSI) method. Both methods are based on significance tests assuming that brightness of city lights fluctuates as normal random variables, and the BTI method is simplified by introducing the assumption that the standard deviation of city lights fluctuation is constant. The validity of the estimation method is discussed based on the result of the application to the 2001 Western India earthquake disaster. The estimation results identify the damaged areas distant from the epicentre fairly well, especially when using the TSI method. The system is designed to estimate the global urban damage and to provide geographic information through the Internet within 24 h after a severe disaster event. The information is expected to support the disaster response and relief activities of governments and non-governmental organizations.

Jin, Y.-Q.; Yan, F.

doi: 10.1080/01431160310001618806pmid: N/A

A massive sandstorm enveloped most of northern China during Spring 2002. Monitoring the evolution of sandstorm and desertification has become one of the most serious problems for China's environment. Since 1989, one of the most advanced and operational passive microwave sensors is the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I) operated at seven channels (19, 37, 85 GHz with vertical and horizontal polarization and 22 GHz with vertical polarization only). In this paper, the sandstorm and desertification indexes, SDI and DI, are derived from the radiative transfer equation, and are employed with multi-channel measurements of the DMSP SSM/I for monitoring the sandstorm and desertification in northern China. Some SSM/I data in 1997 and 2001 are employed. The algorithm of the Getis statistics is developed to categorize the spatial correlation and its evolution during these days. It is demonstrated that the SSM/I indexes, SDI and DI, and its Getis statistics are well applicable for monitoring the sandstorm and desertification.

Mäkynen, M.; Hallikainen, M.

doi: 10.1080/01431160310001647697pmid: N/A

Backscattering signatures of various Baltic Sea ice types and open water leads were measured with the helicopter-borne C- and X-band Helsinki University of Technology scatterometer (HUTSCAT) during six ice research campaigns in 1992–1997. The measurements were conducted at incidence angles of 23° and 45°. The HUTSCAT data were assigned by video imagery into various surface type categories. The ground data provided further classification of the HUTSCAT data into different snow wetness categories (dry, moist and wet snow). Various basic statistical parameters of backscattering signature data were used to study discrimination of open water leads and various ice types. The effect of various physical parameters (e.g. polarization, frequency, snow condition) on the surface type discrimination was investigated. The results from the data analysis can be used to help the development of sea ice classification algorithms for space-borne SAR data (e.g. Radarsat and Envisat). According to the results from the maximum likelihood classification it is not possible to reliably distinguish various surface types in the SAR images only by their backscatter intensity. In general, the best ice type discrimination accuracy is achieved with C-band VH-polarization σ° at an incidence angle of 45°.

Nichol, J. E.; Vohora, V.

doi: 10.1080/01431160310001618770pmid: N/A

A coherent pattern of system noise observable on all visible wavebands of Landsat Thematic Mapper images over homogeneous surfaces such as waterbodies is regarded as serious enough to impair visual interpretation and affect image analysis results. The noise is removable using iterative median filtering in the spatial domain, which requires much less processing time than removal by frequency domain Fourier transform. The significance of the error introduced to the images by the noise is evaluated in terms of water quality parameters in the study area, and methods for removal of the noise are described.

Barbini, R.; Colao, F.; De Dominicis, L.; Fantoni, R.; Fiorani, L.; Palucci, A.; Artamonov, E. S.

doi: 10.1080/01431160310001618086pmid: N/A

The ENEA (Italian Agency for New Technologies, Energy and the Environment) lidar fluorosensor (ELF), aboard the research vessel Italica, measured continuously surface chlorophyll-a concentrations during the Italy–New Zealand and New Zealand–Italy transects (13 November–18 December 2001 and 28 February–1 April 2002, respectively). The ELF measurements were compared with the data collected by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). This study pointed out advantages, disadvantages and possible synergies of lidar fluorosensor and spaceborne radiometers. In particular, the SeaWiFS and MODIS bio-optical algorithms have been calibrated with the ELF measurements. The differences between the performances of the two spaceborne radiometers are also briefly discussed.

Hu, C.; Nababan, B.; Biggs, D. C.; Muller-Karger, F. E.

doi: 10.1080/01431160310001618789pmid: N/A

Variations of bio-optical properties at oceanographic sampling stations, although important for satellite data validation and algorithm development, have rarely been documented or studied. Using flow-through data and water samples collected from the flow-through system and Niskin bottles at ∼260 stations between summer 1998 and spring 1999 in the north-east Gulf of Mexico (27.5° to 30.4° N, 90° to 80° W), we study the variability of several properties, including chlorophyll-a concentration and Gelbstoff absorption, at the sampling stations. It is found that the standard deviations for both Gelbstoff and chlorophyll are less than 10% of the mean values for more than 90% of the stations, including the coastal stations where water is turbid or Case II. High variations are found in the frontal regions near river plumes. At several stations chlorophyll-a and Gelbstoff vary by nearly two-fold due to spatial and/or temporal variations of the properties near the plume waters. This suggests that for water samples collected from moderately coloured waters (chlorophyll-a >0.25 mg m−3) or coastal river plume waters, special care should be taken to validate the sample data by using multiple samples, a continuous flow-through system, or a concurrent satellite data product map. Otherwise large uncertainties are likely to occur when these data are used to validate satellite estimates.

Liu, Yuanbo; Nishiyama, Soichi; Yano, Tomohisa

doi: 10.1080/01431160310001606647pmid: N/A

Although change detection algorithms for temporal remote sensing images have been compared using various datasets, there is no general agreement on their performance for separating change and no-change. This study compared image differencing, image ratioing, image regression, and principal component analysis (PCA) from a mathematical perspective. Error analysis showed that no-change pixels with errors are expected to be located within an error zone in bi-temporal space. Bi-temporal space consists of two temporal axes of target pixel values observed successively. All algorithms confine a no-change area to a zone delineating change and no-change pixels in the space. Image ratioing defines a fan-like sector as a no-change area, generally unsuitable for change detection. The other algorithms confine a no-change area to a strip-like zone. Image differencing defines a no-change zone with a fixed slope, leading to its inability to specify flexibly the error zone that varies with different conditions. In the examined case, image regression and standardized PCA (SPCA) achieved the best performance for change detection, followed by PCA, image differencing, and image ratioing.

Varotsos, C. A.; Cracknell, A. P.

doi: 10.1080/0143116031000115067pmid: N/A

The number of sunspots is characterized by a long-term temporal variation, reaching its maximum or its minimum approximately every 11 years (the solar cycle). This variation, in turn, has an effect in terms of variation in the global climate. Since 1979, the use of satellite-borne radiometers has enabled accurate measurements of total solar irradiance (TSI). For instance, the sunspot numbers that are scaled to correspond to Nimbus-7 TSI observations for 1979–1993 show little long-term trend. However, while the observations of different extremes of the solar cycle, which are available from 1749, seem irregular in time and magnitude and difficult to quantify, they appear to have a strong correlation between them when they are sorted pairwise according to their size rather than sequentially in time. A similar relation holds among the solar cycle lengths (periods) and the solar cycle extremes, which, in parallel, obey a linear relation that is reminiscent of the Gutenberg–Richter seismic law. This can be used for a probabilistic approach to forecast solar parameters that are connected to global climate.Based on the reasonable assumption that the basic parameters like extremes and length of the 11-year solar cycle are associated with the energy oscillating between the dipolar and quadrupolar phases of the cycle, it is concluded that these parameters obey a power-law distribution similar to that of the Gutenberg–Richter seismic law.The question of whether solar activity is deterministically chaotic is also investigated by exploring the behaviour of the main characteristics of the 11-year solar cycle. This is done by constructing return maps of solar cycle strength and duration, which seem to take the familiar up–down U shape, implying both non-linearity and re-injection. The results suggest that there might exist a coupling between two or three different non-linear deterministic dynamical systems on the Sun, depending on which variable of the solar cycle is being considered.

Kandirmaz, H. M.; Yeg˘i˙ngi˙l, L˙.; Peştemalci, V.; Emrahog˘lu, N.

doi: 10.1080/01431160310001618743pmid: N/A

Many studies have indicated that the estimation of solar irradiation at ground level using meteorological satellite data has been an alternative and easy method compared to classical methods. In the present work, the incident of solar radiation over Turkey has been estimated at ground level between July 1997 and December 1998. Statistical regressions between ground data and digital satellite data, measured in the visible band (0.4–1.1 µm) by Meteosat radiometer, have been determined and these regression parameters have been used to estimate solar radiation at ground level. This is the so-called statistical method, which uses a simple model because satellites measure only a few parameters among the many that govern radiative transfers.The visible image (C3D) data used in the present work was Meteosat Wefax type. While pursuing our studies the mean daily sum of global solar radiation over Turkey has been determined to be 18.44 MJ m−2 d−1 with a correlation coefficient of 0.96. The rms error for the mean daily sum has been evaluated as 1.92 MJ m−2 d−1. The monthly mean daily sum of solar radiation has been determined with an rms error of 1.82 MJ m−2 d−1 in two years. During this period the maximum value of the daily sum has been found to occur in June 1998 as 28.47 MJ m−2 d−1, whereas the minimum has been found to occur in December 1998 as 7.35 MJ m−2 d−1. The evaluation procedure, results and possible sources of error are suggested and possible ways of improving the method are described and discussed.

Ricotta, C.

doi: 10.1080/01431160310001618130pmid: N/A

In thematic maps, information is traditionally represented in a one-pixel–one-class method, which assumes each pixel in the map can be assigned unambiguously to a single class. The introduction of fuzzy classifications overcomes the traditional limitations on the mutually exclusive nature of map classes assigning varying levels of class membership for individual map pixels. However, the accuracy of fuzzy classifications is difficult to evaluate as conventional measures of classification accuracy are appropriate only for conventional one-pixel–one-class representations. This is a major barrier to the wider adoption of fuzzy classifications. In this paper, a parametric generalization of Morisita's index, first proposed in the ecological literature, is introduced whose members have varying sensitivities to the presence of rare and abundant thematic map classes. Due to its simplicity, the proposed index may be used to summarize the classification accuracy of fuzzy thematic maps obtained by softening the output of a maximum likelihood classification.