Zabala A., Pons X., Aulí-Llinàs F., Serra-Sagristà J. (2008) Image compression effects in visual analysis. Proceedings of SPIE - The International Society for Optical Engineering. 7084: 0-0.EnllaçDoi: 10.1117/12.798572
This study deals with the effects of lossy image compression in the visual analysis of remotely sensed images. The experiments consider two factors with interaction: the type of landscape and the degree of lossy compression. Three landscapes and two areas for each landscape (with different homogeneity) have been selected. For every of the six study area, color 1:5000 orthoimages have been submitted to a JPEG2000 lossy compression algorithm at five different compression ratios. The image of every area and compression ratio has been submitted to on-screen photographic interpretation, generating 30 polygon layers. Maps obtained using compressed images with a high compression ratio present high structural differences regarding to maps obtained with the original images. On the other hand, the compression of 20% obtains values only slightly different from those of the original photographic interpretation, but these differences seem owed to the subjectivity of the photographic interpretation. Therefore, this compression ratio seems to be the optimum since it implies an important reduction of the image size without determining changes neither in the topological variables of the generated vector nor in the obtained thematic quality.
Casas M.C., Herrero M., Ninyerola M., Pons X., Rodríguez R., Rius A., Redaño A. (2007) Analysis and objective mapping of extreme daily rainfall in Catalonia. International Journal of Climatology. 27: 399-409.EnllaçDoi: 10.1002/joc.1402
The main objective of this study is to determine the maximum daily precipitation in Catalonia for several established return periods with a high spatial resolution. For this purpose, the maximum daily rainfall annual series from 145 pluviometric stations of the Instituto Nacional de Meteorología (INM) (Spanish Weather Service) in Catalonia have been analyzed. Using the L-moments method of Hosking, every series has been fitted by the extreme value distribution function of Gumbel. From this fitting, the maximum daily precipitation for each of the pluviometric stations corresponding to return periods between 2 and 500 years, have been determined. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems (GIS) techniques, have been used as the initial field for the analysis. The maximum daily precipitation at 1 km2 spatial resolution on Catalonia has been objectively determined by the method employed, and structures with wavelength longer than approximately 35 km can be identified. The results show that places where the maximum daily precipitation values are expected are the zone of Guilleries in the Transversal Range, in the highest zones of the Catalan Pyrenees and Cape Creus zone at the northeastern end of Catalonia and in the south, around the Prelittoral Mountain Range between the Mountains of Prades and Montsià. A good fit between the distribution of minimum values and the driest Catalan areas has been found, the lowest values being on the western end of the Central Basin. Copyright © 2006 Royal Meteorological Society.
Serra P., Pons X. (2007) Temporal signatures of Mediterranean irrigated crops using satellite image time series. Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images. : 0-0.EnllaçDoi: 10.1109/MULTITEMP.2007.4293037
This work summarizes the methodology applied A for monitoring the temporal signatures of some Mediterranean irrigated crops using 26 Landsat-5&7 TM&ETM+ images, from 2002 to 2005. The obtained four crop maps, one for each year, allows monitoring dynamics of maize, alfalfa and fruit trees with a thematic accuracy high than 90%. ©2007 IEEE.
Moré G., Pons X., Serra P. (2006) Improvements on classification by tolerating NoData values application to a hybrid classifier to discriminate mediterranean vegetation with a detailed legend using multitemporal series of images. International Geoscience and Remote Sensing Symposium (IGARSS). : 192-195.EnllaçDoi: 10.1109/IGARSS.2006.54
Natural and crop vegetation phenologic data become indispensable when creating thematically and geographically detailed maps through satellite images classification. Several date acquisition is necessary to achieve this cartography. However, the presence of clouds, shadows, snow, etc, is usual when many different dates are used and that fact implies an important loss in classifiable surface. This work presents a hybrid classifier designed to deal with the common problems appeared in the classification of Mediterranean vegetation. Specifically, IsoMM, the first phase of the hybrid methodology, is an unsupervised classifier that allows a better use of temporal series thanks to a particular treatment of NoData values (or missing values) in the images. This methodology has been applied to a Mediterranean forestry zone with a legend of eleven categories and has been compared to a Maximum Likelihood classifier. The presented improvements allow classifying more surface than a common NoData treatment strategy (wheter unsupervised, Maximum Likelihood classification or the extraction of a problematic date) and achieving high accuracy level.
Bielsa I., Pons X., Bunce B. (2005) Agricultural abandonment in the north eastern Iberian Peninsula: The use of basic landscape metrics to support planning. Journal of Environmental Planning and Management. 48: 85-102.EnllaçDoi: 10.1080/0964056042000308166
Land abandonment is an important cause of changes in landscape patterns in the Mediterranean area. There is a need to monitor land use and land cover changes in order to provide quantitative evidence of the relationship between land abandonment and the formation of new landscape patterns. Appropriate management policies to encourage sustainable development can then be developed. This paper describes how to monitor landscape dynamics using different temporal land use and land cover data generated from field survey and airborne information. The results showed that the abandonment of agricultural land generally results in an increase of vegetation biomass. This process leads to homogenization of the landscape. In addition, abandonment promotes fragmentation of agricultural land. Based on these results, the paper discusses the implications for rural management policies concerning the abandonment of agricultural land and suggests recommendations for the development of such policies. © 2005 University of Newcastle upon Tyne.
Salvador R., Lloret F., Pons X., Piñol J. (2005) Does fire occurrence modify the probability of being burned again? A null hypothesis test from Mediterranean ecosystems in NE Spain. Ecological Modelling. 188: 461-469.EnllaçDoi: 10.1016/j.ecolmodel.2004.12.017
Two main causes have been proposed as drivers of fire regime in Mediterranean-type ecosystems: fuel build-up and weather conditions. If fuel build-up is the main cause, then areas recently burned will not burn again until some years later. Contrarily, if weather is the main cause, then all areas will burn irrespective of their age. We have devised a statistical test aimed to distinguish between these two hypotheses. To use the test is necessary to know the spatial distribution of fires during a period of time as long as possible. Then, a percolation algorithm procedure is applied to mimic the location, extent, and perimeter/area ratio of the real fires, independently of previous fire occurrence. This model is run many times and each run is considered a realization under the null hypothesis that a pixel burns irrespectively of whether it was burnt in the previous years. The actual number of pixels burned twice is then compared to the histogram of the probability density function of pixels burned twice, which is obtained from the simulations. Actual values falling in the right tail of the distribution point to a clumped pattern (fires tend to be more abundant in some locations), while falling in the left tail will indicate a segregated pattern (burning reduces the probability of further fires in the same site). The method was applied to three different areas of Catalonia (NE Spain) by comparing the actual fires from 1975 to 1998 to the pattern obtained from random fire simulations. An aggregated pattern was obtained in two of the studied areas when the origin of the simulated fires was located randomly, indicating that fires were not uniformly distributed in the territory. When the simulations were started at the centroids of the real fires, the null hypothesis of independence from previous fires was not rejected, and the fuel-driven assumption was not supported. In the third area, results were inconclusive because two large fires, occurred in 1994, totally changed the results obtained until then. © 2005 Elsevier B.V. All rights reserved.
Díaz-Delgado R., Lloret F., Pons X. (2004) Statistical analysis of fire frequency models for Catalonia (NE Spain, 1975-1998) based on fire scar maps from Landsat MSS data. International Journal of Wildland Fire. 13: 89-99.EnllaçDoi: 10.1071/WF02051
This paper estimates fire frequency in Catalonia (NE Spain) for the last quarter of the 20th Century (1975-1998) from historical burned area maps. Remote sensing images provided perimeters of fires ≥30 ha, which were used to characterize the temporal patterns of fire occurrence in Catalonia. Several fire frequency models were used to reproduce the observed pattern of wildfires occurrence in the study period. Natural fire rotation period was estimated to be 133 years. Poisson tests were carried out to check random fire occurrence either along the time period or across the analysed region. Observed fires were not randomly generated either in space or in time, despite being sampled using two different plot sizes. This sampling design was also used for Mean Fire Interval (MFI) analysis, which allowed us to significantly fit a Weibull distribution to the observed proportion of fire intervals (for both sample sizes), enabling us to estimate the hazard of burning, mortality, and survivorship functions. Finally, MFI was also applied to forest regions of Catalonia, which are defined according to forest management plans based on their homogeneous climatic conditions. Such an analysis revealed relevant differences in forest management and their consequences on fire occurrence.
Vicente-Serrano S.M., Pons-Fernández X., Cuadrat-Prats J.M. (2004) Mapping soil moisture in the central Ebro river valley (northeast Spain) with Landsat and NOAA satellite imagery: A comparison with meteorological data. International Journal of Remote Sensing. 25: 4325-4350.EnllaçDoi: 10.1080/01431160410001712990
This paper analyses and maps the spatial distribution of soil moisture using remote sensing: National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and Landsat-Enhanced Thematic Mapper (ETM+) images. The study was carried out in the central Ebro river valley (northeast Spain), and examines the spatial relationships between the distribution of soil moisture and several meteorological and geographical variables following a long, intense dry period (winter 2000). Soil moisture estimates were obtained using thermal, visible and near-infrared data and by applying the 'triangle method', which describes relationships between surface temperature (Ts) and fractional vegetation cover (F r). Low differences were found between the soil moisture estimates obtained using AVHRR and ETM+ sensors. Soil moisture estimated using remote sensing is close to estimations obtained from climate indices. This fact, and the high similarity between estimations of both sensors, suggests the reasonable reliability of soil moisture remote sensing estimations. Moreover, in estimations from both sensors the spatial distribution of soil moisture was largely accounted for by meteorological variables, mainly precipitation in the dry period. The results indicate the high reliability of remote sensing for determining areas affected by water deficits and for quantifying drought intensity. © 2004 Taylor and Francis Ltd.
Díaz-Delgado R., Lloret F., Pons X. (2003) Influence of fire severity on plant regeneration by means of remote sensing imagery. International Journal of Remote Sensing. 24: 1751-1763.EnllaçDoi: 10.1080/01431160210144732
In this paper we analyse the interactions between fire severity (plant damage) and plant regeneration after fire by means of remote sensing imagery and a field fire severity map. A severity map was constructed over a large fire (2692 ha) occurring in July 1994 in the Barcelona province (north-east of Spain). Seven severity classes were assigned to the apparent plant damage as a function of burning intensity. Several Landsat TM and MSS images from dates immediately before and after the fire were employed to monitor plant regeneration processes as well as to evaluate the relationship with fire severity observed in situ. Plant regeneration was monitored using NDVI measurements (average class values standardized with neighbour unburned control plots). Pre-fire NDVI measurements were extracted for every plant cover category (7), field fire severity class (7), and spatial cross-tabulation of both layers (33) and compared to post-fire values. NDVI decline due to fire was positively correlated with field fire severity class. Results show different patterns of recovery for each dominant species, severity class and combination of both factors. For all cases a significant negative correlation was found between damage and regeneration ability. This work leads to a better understanding of the influence of severity, a major fire regime parameter on plant regeneration, and may aid to manage restoration on areas burned under different fire severity levels.
Serra P., Pons X., Saurí D. (2003) Post-classification change detection with data from different sensors: Some accuracy considerations. International Journal of Remote Sensing. 24: 3311-3340.EnllaçDoi: 10.1080/0143116021000021189
Change detection from remote sensing data is often done by simple overlay of classified maps. However, such analyses can contain a significant proportion of boundary errors, especially when combining data from different sensors. This paper presents a protocol that allows reliable post-classification comparisons by taking into account classification accuracies, landscape fragmentation, planimetric accuracies, pixel sizes and grid origins. The proposed protocol has been applied, with little extra effort, in a fragmented agricultural Mediterranean zone using MSS (1970s) and TM (1990s) images. Applying the protocol, change detection had an accuracy of 85.1%, while for a direct overlay it was only 43.9% accurate. The drawback of this method is that it reduces the useful area of comparison. As the accuracy of individual classifications is critical, the paper also describes and tests a hybrid classifier that combines an unsupervised classification approach with training areas. This approach has proved more successful than maximum likelihood classifiers.
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