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doi: 10.1080/014311698214541pmid: N/A
In this paper, the evolution of thermal structures in the Alboran Sea with the help of NOAA images is analysed. A temporal and spatial Empirical Orthogonal Function (EOF) analysis (principal components analysis) has been performed using 12 monthly maximum images calculated from 48 daily AVHRR images taken with a weekly periodicity along the year 1993. The first spatial EOF mode (38.87% variance), which is very similar to the mean of all images, shows a very strong west Alboran sea gyre with a warm centre and cold water surrounding it. The east gyre is not so strong. The second spatial mode (17.65% variance) describes the seasonal behaviour of the water near the Spanish coast from Malaga to Cape Gata. On the other hand, the temporal EOF analysis yields a strongly dominant first mode (93.50% variance) representing the basin seasonal warming and cooling.
Hu, Zhenglin; Chen, Yizong; Islam, Shafiqul
doi: 10.1080/014311698214550pmid: N/A
The scaling-multiscaling properties of passive microwave remotely sensed soil moisture images from the Washita '92 experiment are investigated. Analysis of moments of the soil moisture shows a log-log linearity of moments with spatial scale and the concavity of corresponding slopes with the order of moments. These properties suggest a deviation from simple scaling and the possible presence of multiscaling. By decomposing the soil moisture images into large-scale and small-scale fluctuation parts using wavelet transforms, it is shown that the small-scale fluctuation features obey a simple scaling law. The implications for such a decomposition and the coupling between the large-scale and small-scale features are discussed.
Verma, K. S.; Saxena, R. K.; Hajare, T. N.; Kumar, S. C. Ramesh
doi: 10.1080/014311698214569pmid: N/A
Soil crop management interaction influence on spectral vegetation indices (SVIs) and dry matter (DM) in different growth stages of gram crop were studied through an experiment. Significant differences in the values of IR/R and NDVI in the branching stage (St1: 20.17***, 14.06***) and the pod development stage (St2: 12.73***, 8.48**) and non-significant differences in pod maturity stage (St3: 0.193, 0.023) indicate that plant, soil and management interactions have yielded significant difference up to St2. The values of coefficient of variation (Cv) show the significant differences in DM production between the soils (St1: 43.5***, St2: 228.5***, St3: 36.3***) and treatment (St1: 10.8***, St2: 6.6**, St3: 2.9). These variation are well in agreement with the changes which have taken place in the values of SVIs, as it can be clearly seen that the increase in SVIs corresponds with the consistent increase in DM up to stage 2. The significant differences between SVIs values between soils and treatments and the positive correlation with DM at St2, justifies their consideration in estimating the yield of gram crop under variable soil and management conditions. The regression relation of DM with NDVI in three soils and four management factors has yielded 12 regression models in order to predict DM/grain production using SVI's values in St2. Based on goodness of fit and considering the highest R2 value, the best yield prediction models for S1, S2 and S3 soils are (i) y 0.91 0.03 NDVI (R2 0.42) S1 soils (ii) y 1.89 0.06 NDVI (R2 0.96) S2 soils (iii) y 3.85 0.46 NDVI (R2 0.32) S3 soils.
doi: 10.1080/014311698214578pmid: N/A
A pixel block intensity modulation (PRIM) method has been developed to add spatial detail to Landsat Thematic Mapper (TM) thermal band TM6 images in regions with sufficient topography. The method uses 30 m resolution TM reflective spectral band images (TM1-5 and 7) to modulate the relevant TM6 image on the basis of its 120m resolution thermal pixel blocks. Topographic detail in each 120m resolution pixel block of the TM6 image is thus recovered, without altering the average thermal digital number level of the block, by the spatial information recorded in the reflective spectral bands at 30m resolution. Tests confirm that the PBIM can effectively integrate topographic spatial detail from reflective spectral bands with TM6 images while retaining the fidelity of the original thermal spectral information. PBIM is also applicable, as a general method, for data fusion of multispectral and panchromatic images with different spatial resolutions. Bearing in mind that, for space-borne remote sensing, the spatial resolution of the thermal band will continue to be lower than that of VISSWIR and panchromatic bands in the multispectral sensor systems of the next generation, such as Enhanced Thematic Mapper Plus, the PBIM method will remain a useful technique for enhancing thermal imagery data for some time.
doi: 10.1080/014311698214587pmid: N/A
We evaluated Landsat Thematic Mapper (TM) imagery to map forest survival after a wildfire using single-date and multi-date TM imagery. In addition, landscape patterns were measured to describe the wildfire effects on successional stage patterns, and their impacts on wildlife habitat. The study site was the 1991 Warner Creek Burn, covering 3669 ha, on the Willamette National Forest in western Oregon, USA. Regressions of TM band transformations were used to estimate forest survival. Single-date TM 4/5 accounted for 73% (P 0.0001) of the variation in post-burn canopy cover, whereas the TM difference (by ratio) imagery with stratification by pre-fire tasseled cap (TC) wetness explained 78% (P 0.0001). Verification of the best models using additional data in observed versus predicted post-burn canopy cover confirmed these results. The pre-fire landscape had a matrix of closed mature/old-growth stands comprising 77% of the area. After the burn, the early seral/rock stage expanded, the open mature/old-growth stage was created, and the closed mature/old-growth stage was reduced and fragmented. Overall habitat diversity and edge increased after the burn, but interior habitat decreased.
Pachepsky, Y. A.; Ritchie, J. C.
doi: 10.1080/014311698214596pmid: N/A
Fractal geometry is a useful tool for the analysis of landscape data. In this study fractal scaling was applied to high-resolution landscape data collected with a profiling laser altimeter. The objective of this work was to assess the persistence of scaling differences over time. Data were collected at the United States Department of Agriculture (USDA), Agriculture Research Service (ARS) Jornada Experimental Range in New Mexico, USA in May and September 1995 and February 1996 over a grass-dominated site, a shrub-dominated site, and a transitional area between shrub- and grass-dominated sites along four transects at each site for each date. Root-mean-square (RMS) roughness was scaledependent and had more than one range of self-affine scaling. Different numbers of self-affine scaling intervals, boundaries of intervals, and fractal dimensions over these intervals were associated with different land covers. A linearity measure was applied to find intervals of fractal scaling. The number and boundaries of fractal scaling intervals appeared to be persistent over the year. Grass and shrub sites had two and four linearity intervals respectively. The transitional site had a pattern of scaling that was intermediate between grass and shrub sites. The lowest fractal dimensions at small scales of 6-30 m corresponded to the maximum vegetation in September.
doi: 10.1080/014311698214604pmid: N/A
Clear cutting in tropical forests is common. A newer phenomenon, selective logging, is evident in Amazonia when examined with high-resolution satellite data. We have quantified selective logging by digitizing satellite imagery and have found that it is much more difficult to detect than clear cutting. Selective logging is likely under-reported in satellite imagery-based estimates of change in Amazonia as the visible signal of selective logging may be evident for only a limited time. We have found that the areas affected by selective logging have increased over time and have become more widely distributed. Little land selectively logged, perhaps 10%, was converted to pasture. Selective logging altered 12% of the total forested area of one study region, yet was undetectable in satellite imagery three years later. It is unclear how long the visual clues of selective logging will remain apparent in satellite imagery in subsequent years.
doi: 10.1080/014311698214613pmid: N/A
Models used in remote sensing are based on the assumed relationship between measured radiances and the physical parameters of the soil surface. A number of them are semi-empirical, in the sense that they contain constants adjusted to take account of in situ experiments, generally carried out on a given type of medium. Once validated in situ, these models are applied to large scale areas with global radiances. In this paper, we demonstrate that constants taken to be appropriate for in situ experiments are no longer appropriate for global radiances. For remote sensing applications, we demonstrate that these constants must be determined by a new least square cost function. Finally, we evaluate, for various simulated cases using the LAI and the APAR models, the magnitude of gain of the new method for space applications, when compared to classical examples.
doi: 10.1080/014311698214622pmid: N/A
Radargrammetry is a method that generates topographic maps from homologous points of stereoscopic radar images and a stereomodel taking into account the flightpath parameters and the geometry of radar beams. Here, we propose an algorithm that calculates the elevation of homologous points included in Synthetic Aperture Radar images obtained by parallel same-side facing airborne flightpaths. Furthermore, we develop an automatic search of homologous points by a method of shape recognition determined by a threshold on the pixel radiometry gradient. With this algorithm, we generate a topographic map of the Kilauea volcano (Hawaii) from AIRSAR images.
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