Moré G., Serra P., Pons X. (2011) Multitemporal flooding dynamics of rice fields by means of discriminant analysis of radiometrically corrected remote sensing imagery. International Journal of Remote Sensing. 32: 1983-2011.EnllaçDoi: 10.1080/01431161003645816
An automatic classifier based on a discriminant analysis (DA) was used to classify eight classes in relation to different stages of rice fields during the flooding season. This methodology is characterized by the fact that, once the training phase has been carried out, training areas are not required to perform new classifications. If the images have been radiometrically corrected in a consistent way, the classifier can be used in a retrospective mode using past images. For this study, the training phase was conducted with data taken in October 2006 and January 2007 while the automatic classifier was applied to a total of 10 Landsat-5 Thematic Mapper (TM) images from the 2004-05 and 2006-07 seasons. An average level of accuracy of 93.4% (range 89.7-98.7%) demonstrates the capability of the method to obtain high-quality and quasi-instantaneous classifications and to carry out retrospective studies even when training areas are not available for past dates. Two examples of how the method can be used are included in this article: (i) a study of the temporal evolution of flooding covers by period and (ii) the use of vector enrichment as a thematic updating tool for the cadastre. An additional objective of the study was to analyse the importance of the different bands to ascertain the suitability of alternative sensors with spectral configurations other than those provided by Landsat. This analysis demonstrates that the absence of shortwave infrared (SWIR) bands results in a decrease of almost nine percentage points in the accuracy levels of the classification while the blue band can be excluded with minimal impact on the results. © 2011 Taylor & Francis.
Zabala A., Pons X. (2011) Effects of lossy compression on remote sensing image classification of forest areas. International Journal of Applied Earth Observation and Geoinformation. 13: 43-51.EnllaçDoi: 10.1016/j.jag.2010.06.005
Lossy compression is being increasingly used in remote sensing; however, its effects on classification have scarcely been studied. This paper studies the implications of JPEG (JPG) and JPEG 2000 (J2K) lossy compression for image classification of forests in Mediterranean areas. Results explore the impact of the compression on the images themselves as well as on the obtained classification. The results indicate that classifications made with previously compressed radiometrically corrected images and topoclimatic variables are not negatively affected by compression, even at quite high compression ratios. Indeed, JPG compression can be applied to images at a compression ratio (CR, ratio between the size of the original file and the size of the compressed file) of 10:1 or even 20:1 (for both JPG and J2K). Nevertheless, the fragmentation of the study area must be taken into account: in less fragmented zones, high CR are possible for both JPG and J2K, but in fragmented zones, JPG is not advisable, and when J2K is used, only a medium CR is recommended (3.33:1 to 5:1). Taking into account that J2K produces fewer artefacts at higher CR, the study not only contributes with optimum CR recommendations, but also found that the J2K compression standard (ISO 15444-1) is better than the JPG (ISO 10918-1) when applied to image classification. Although J2K is computationally more expensive, this is no longer a critical issue with current computer technology. © 2010 Elsevier B.V.
Gerard F., Petit S., Smith G., Thomson A., Brown N., Manchester S., Wadsworth R., Bugar G., Halada L., Bezák P., Boltiziar M., de Badts E., Halabuk A., Mojses M., Petrovic F., Gregor M., Hazeu G., Mücher C.A., Wachowicz M., Huitu H., Tuominen S., Köhler R., Olschofsky K., Ziese H., Kolar J., Sustera J., Luque S., Pino J., Pons X., Roda F., Roscher M., Feranec J. (2010) Land cover change in Europe between 1950 and 2000 determined employing aerial photography. Progress in Physical Geography. 34: 183-205.EnllaçDoi: 10.1177/0309133309360141
BIOPRESS ('Linking Pan-European Land Cover Change to Pressures on Biodiversity'), a European Commission funded 'Global Monitoring for Environment and Security' project, produced land cover change information (1950-2000) for Europe from aerial photographs and tested the suitability of this for monitoring habitats and biodiversity. The methods and results related to the land cover change work are summarized. Changes in land cover were established through 73 window and 59 transect samples distributed across Europe. Although the sample size was too small and biased to fully represent the spatial variability observed in Europe, the work highlighted the importance of method consistency, the choice of nomenclature and spatial scale. The results suggest different processes are taking place in different parts of Europe: the Boreal and Alpine regions are dominated by forest management; abandonment and intensification are mainly encountered in the Mediterranean; urbanization and drainage are more characteristic of the Continental and Atlantic regions. © The Author(s) 2010.
Marcer A., Garcia V., Escobar A., Pons X. (2010) Handling historical information on protected-area systems and coverage. An information system for the Natura 2000 European context. Environmental Modelling and Software. 25: 956-964.EnllaçDoi: 10.1016/j.envsoft.2010.03.011
Protected-area coverage is an internationally-recognized surrogate indicator for measuring biodiversity conservation. To measure trends in biodiversity conservation over time, historical records on protected-area boundaries are needed. Protected-area systems represent a challenge in information management for public environmental organizations. Protected areas may be subjected to changes which must follow a mandatory multiple-step administrative process. A wealth of information is generated which needs to be stored in a way that eases the handling process and for future reference. We present an information system which handles both change on protected-area boundaries over time and their related administrative processes. It also provides distributed data maintenance functionality as well as integrated alphanumeric, file and cartographic information handling. We discuss the actual implementation of the system for handling Natura 2000 sites in the Catalan and Spanish contexts. The designed system is applicable to other European Union member states. © 2010 Elsevier Ltd. All rights reserved.
Zabala A., Gonzalez-Conejero J., Serra-Sagrista J., Pons X. (2010) JPEG2000 encoding of images with NODATA regions for remote sensing applications. Journal of Applied Remote Sensing. 4: 0-0.EnllaçDoi: 10.1117/1.3474978
The aim of this work is to, within the JPEG2000 framework, enhance the coding performance obtained for images that contain regions without useful information, or without information at all, here named as NODATA regions. In Geographic Information Systems (GIS) and in Remote Sensing (RS), NODATA regions arise due to several factors, such as geometric and radiometric corrections, atmospheric events, the overlapping of successive layers of information, etc. Most coding systems are not devised to consider these regions separately from the rest of the image, sometimes causing a loss in the coding efficiency and in the post-processing applications. We propose two approaches that address this issue; the first technique (Average Data Region, ADR) is carried out as simple pre-processing and the second technique (Shape-Adaptive JPEG2000, SA-JPEG2000) modifies the coding system to avoid the regions without information. Experimental results, performed on data from real applications and different scenarios, suggest that the proposed approaches can achieve, e.g., for SA-JPEG2000, a Signal-to-Noise Ratio improvement of about 8 dB. Moreover, in a post-processing application such as a digital classification, the best classification results are obtained when the proposed approaches SA-JPEG2000 and ADR are applied. © 2010 Society of Photo-Optical Instrumentation Engineers.
Blanes I., Zabala A., Moré G., Pons X., Serra-Sagristà J. (2008) Classification of hyperspectral images compressed through 3D-JPEG2000. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5179 LNAI: 416-423.EnllaçDoi: 10.1007/978-3-540-85567-5-52
Classification of hyperspectral images is paramount to an increasing number of user applications. With the advent of more powerful technology, sensed images demand for larger requirements in computational and memory capabilities, which has led to devise compression techniques to alleviate the transmission and storage necessities. Classification of compressed images is addressed in this paper. Compression takes into account the spectral correlation of hyperspectral images together with more simple approaches. Experiments have been performed on a large hyperspectral CASI image with 72 bands. Both coding and classification results indicate that the performance of 3d-DWT is superior to the other two lossy coding approaches, providing consistent improvements of more than 10 dB for the coding process, and maintaining both the global accuracy and the percentage of classified area for the classification process. © 2008 Springer-Verlag Berlin Heidelberg.
Cristóbal J., Ninyerola M., Pons X. (2008) Modeling air temperature through a combination of remote sensing and GIS data. Journal of Geophysical Research Atmospheres. 113: 0-0.EnllaçDoi: 10.1029/2007JD009318
Air temperature is involved in many environmental processes such as actual and potential evapotranspiration, net radiation and species distribution. Ground meteorological stations provide important local data of air temperature, but a continuous surface for large and heterogeneous areas is also needed. In this paper we present a hybrid methodology between Remote Sensing and Geographical Information Systems to retrieve daily instantaneous, mean, maximum and minimum air temperatures (2002-2004) as well as monthly and annual mean, maximum and minimum air temperatures (2000-2005) on a regional scale (Catalonia, northeast of the Iberian Peninsula) by means of multiple regression analysis and spatial interpolation techniques. To perform multiple regression analysis we have used geographical and multiresolution remotely sensed variables as predictors. The geographical variables we have included are altitude, latitude, continentality and solar radiation. As remote sensing predictors, we have selected those variables that are most closely related with air temperature such as albedo, land surface temperature (LST) and NDVI obtained from Landsat-5 (TM), Landsat-7 (ETM+), NOAA (AVHRR) and TERRA (MODIS) satellites. The best air temperature models are obtained when remote sensing variables are combined with geographical variables: averaged R2 = 0.60 and averaged root mean square error (RMSE) = 1.75°C for daily temperatures, and averaged R2 = 0.86 and averaged RMSE = 1.00°C for monthly and annual temperatures. The results also show that combined models appear in a higher frequency than only geographical or only remote sensing models (87%, 11 % and 2% respectively) and that LST and NDVI are the most powerful remote sensing predictors in air temperature modeling. Copyright 2008 by The American Geophysical Union.
Olivet M., Aloy J., Prat E., Pons X. (2008) Health services provision and geographic accessibility [Oferta de servicios de salud y accesibilidad geográfica]. Medicina Clinica. 131: 16-22.EnllaçDoi: 10.1016/S0025-7753(08)76470-4
This study describes the health services available in Catalonia, Spain as part of the situation analysis of the healthcare map, setting a starting point for the process of adapting services to the needs of the population. It also includes an analysis of the geographic accessibility to healthcare centres in the public health system, through the use of a geographic information system (GIS), with geo-referencing variables and calculations of travel times and distances. The principal results show,on one hand, the adaptation of the Catalan healthcare network to the distribution of the population, with a high level of geographic proximity of the services to the population, and a high degree of capillarity, principally in primary healthcare; and on the other hand, the importance that GIS tools and procedures may acquire in healthcareplanning is highlighted. © 2008 Elsevier España S.L.
Serra P., Pons X. (2008) Monitoring farmers' decisions on Mediterranean irrigated crops using satellite image time series. International Journal of Remote Sensing. 29: 2293-2316.EnllaçDoi: 10.1080/01431160701408444
The main purpose of this study is to present a methodology for mapping and monitoring temporal signatures of Mediterranean crops over several years in irrigated areas, and to study their inter-annual dynamics. These goals were achieved by remote sensing using 36 Landsat images from 2002 to 2005. Four crop maps, one for each year, with six agricultural categories and a thematic accuracy of 93%, 95%, 96% and 94% were obtained using a hybrid classifier. A mean of nine images produced these highly accurate results, but the absence of one image in the growth period of 2002 resulted in lower accuracies, particularly in fruit trees (85% of user accuracy). This highlights the importance of a multi-temporal approach based on a relatively large number of images. After the classification results were validated, two parameters were used to characterize the dynamics of the four crops (rice, maize, alfalfa and fruit trees): greenness, extracted from the Normalized Difference Vegetation Index (NDVI), and wetness, calculated from the Tasselled Cap Wetness (TCW) Index. In order to differentiate the wetness origin of crops, an analysis of local daily precipitation (which could cause significant anomalies in the TCW coefficients) and water stored in the Susqueda reservoir (which may result in farmers making important management decisions when water is limited) was conducted during this four-year period. After applying statistical analysis, the results showed that, of the four crops analysed, rice, alfalfa and fruit trees had more stable dynamics than maize, which was planted later in case of water deficit at the beginning of the irrigation campaign (in 2002) and earlier when the deficit occurred later (in 2005).
Serra P., Pons X., Saurí D. (2008) Land-cover and land-use change in a Mediterranean landscape: A spatial analysis of driving forces integrating biophysical and human factors. Applied Geography. 28: 189-209.EnllaçDoi: 10.1016/j.apgeog.2008.02.001
This article develops a spatial analysis applied to examine the main driving forces of land-cover and land-use (LCLU) change in a Mediterranean region. Three different tools have been used in order to differentiate LCLU changes, driving forces and landscape dynamics. LCLU changes have been quantified with remote sensing techniques, driving forces have been analysed with multiple logistic regressions combining biophysical and human variables, whereas landscape dynamics have been quantified using different metrics. Results show the intensification of subsidised herbaceous crops on the coastal agricultural plain, the abandonment of olive trees and vineyards in the transitional area and forest restoration in the mountainous subregion. © 2008 Elsevier Ltd. All rights reserved.
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