Data Mining Paradigm in the Study of Air Quality

Air pollution is a serious global problem that threatens human life and health, as well as the environment. The most important aspect of a successful air quality management strategy is the measurement analysis, air quality forecasting, and reporting system. A complete insight, an accurate prediction, and a rapid response may provide valuable information for society’s decision-making. The data mining paradigm can assist in the study of air quality by providing a structured work methodology that simplifies data analysis. This study presents a systematic review of the literature from 2014 to 2018 on the use of data mining in the analysis of air pollutant measurements. For this review, a data mining approach to air quality analysis was proposed that was consistent with the 748 articles consulted. The most frequent sources of data have been the measurements of monitoring networks, and other technologies such as remote sensing, low-cost sensors, and social networks which are gaining importance in recent years. Among the topics studied in the literature were the redundancy of the information collected in the monitoring networks, the forecasting of pollutant levels or days of excessive regulation, and the identification of meteorological or land use parameters that have the most substantial impact on air quality. As methods to visualise and present the results, we recovered graphic design, air quality index development, heat mapping, and geographic information systems. We hope that this study will provide anchoring of theoretical-practical development in the field and that it will provide inputs for air quality planning and management.Facultad de Ciencias Exacta

Prediction models for estimating pruned biomass obtained from Platanus hispanica Münchh. used for material surveys in urban forests

The amount of urban biomass waste derived from pruning operations represents a potential source of bioenergy little studied or considered in local bio-economies. This research focused on direct quantification of lignocellulosic residual biomass yielded during tree pruning, characterization of basic tree parameters and development of indirect biomass prediction models. Sample individuals of 30 Platanus hispanica Munchh. with mean diameter at breast height 23.56 cm, crown diameter 8.44 m, crown base height 3.76 m, and total height 11.57 m were examined. Wood formed 43.34% of pruned biomass before the drying process and wood moisture content in wet basis reached 40.16%. Mean quantity of dry biomass obtained per tree was 23.98 kg and standard deviation was 15.16 kg. Allometric relationships were analyzed. Significant coefficients of determination were observed for dry biomass and diameter at breast height (R-2 = 0.87), as well as for dry biomass and conical and parabolic crown volume (R-2 = 0.78). The best result (R-2 = 0.93) was obtained from a multiple regression model with several explicative variables. Indirect biomass prediction equations and characteristics of yielded residuals derived from this research can be useful for biomass planning and management purposes. These equations can be implemented for urban inventories, and the application of logistic models. The significance of this topic is beyond doubt for urban environment, especially for the possibilities of reducing carbon dioxide emissions and perspectives of biomass utilization as a biofuel. (C) 2013 Elsevier Ltd. All rights reserved.Sajdak, M.; Velázquez Martí, B.; López Cortés, I.; Fernández Sarriá, A.; Estornell Cremades, J. (2014). Prediction models for estimating pruned biomass obtained from Platanus hispanica Münchh. used for material surveys in urban forests. Renewable Energy. 66:178-184. doi:10.1016/j.renene.2013.12.005S1781846

Residual biomass calculation from individual tree architecture using terrestrial laser scanner and ground-level measurements

Large quantity of residual biomass with possible energy and industrial end can be obtained from management operations of urban forests. The profitability of exploiting this resource is conditioned by the amount of existing biomass within urban community ecosystems. Prior research pointed out that residual biomass from Platanus hispanica and other tree species can be calculated from dendrometric parameters. In this study, two approaches have been analyzed: First, applicability of TLS was tested for residual biomass calculation from crown volume. In addition, traditional models for residual biomass prediction were developed from dendrometric parameters (tree height, crown diameter, and diameter at breast height). Next, a comparison between parameters obtained with both methodologies (standard methodologies vs TLS) was carried out. The results indicate a strong relationship (R2 = 0.906) between crown diameters and between total tree heights (R2 = 0.868). The crown volumes extracted from the TLS point cloud were calculated by 4 different methods: convex hull; convex hull by slices of 5 cm height in the XY plane; triangulation by XY flat sections, and voxel modeling. The highest accuracy was found when the voxel method was used for pruned biomass prediction (R2 = 0.731). The results revealed the potential of TLS data to determine dendrometric parameters and biomass yielded from pruning quitar of urban forestsFernández-Sarría, A.; Velázquez Martí, B.; Sajdak, M.; Martinez, L.; Estornell Cremades, J. (2013). Residual biomass calculation from individual tree architecture using terrestrial laser scanner and ground-level measurements. Computers and Electronics in Agriculture. 93:90-97. doi:10.1016/j.compag.2013.01.012S90979

Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre

[EN] Juglans regia L. (walnut) is a tree of significant economic importance, usually cultivated for its seed used in the food market, and for its wood used in the furniture industry. The aim of this work was to develop regression models to predict crown parameters for walnut trees using a terrestrial laser scanner. A set of 30 trees was selected and the total height, crown height and crown diameter were measured in the field. The trees were also measured by a laser scanner and algorithms were applied to compute the crown volume, crown diameter, total and crown height. Linear regression models were calculated to estimate walnut tree parameters from TLS data. Good results were obtained with values of R2 between 0.90 and 0.98. In addition, to analyze whether coarser point cloud densities might affect the results, the point clouds for all trees were subsampled using different point densities: points every 0.005 m, 0.01 m, 0.05 m, 0.1 m, 0.25 m, 0.5 m, 1 m, and 2 m. New regression models were calculated to estimate field parameters. For total height and crown volume good estimations were obtained from TLS parameters derived for all subsampled point cloud (0.005 m – 2 m).[ES] Juglans regiaL. (nogal) es un árbol de importancia económica por el fruto que proporciona y por su madera utilizada en la industria del mueble. El objetivo de este trabajo fue calcular modelos de regresión para estimar los pa-rámetros altura total, altura, diámetro y volumen de copa de nogales utilizando datos registrados mediante un escáner láser terrestre. Un conjunto de 30 árboles fueron escaneados y se aplicaron algoritmos para calcular los parámetros anteriores, que también se midieron en campo utilizando técnicas tradicionales. Se obtuvieron buenos resultados, con valores de R2 entre 0,90 y 0,98 para todos los parámetros. Además, para analizar la relación entre la densidad de puntos registrada y la precisión en la estimación de los parámetros de los nogales, las nubes de puntos de todos los árboles fueron sub-muestreadas utilizando diferentes distancias de separación entre puntos: 0,005 m, 0,01 m, 0,05 m, 0,1 m, 0,25 m, 0,5 m, 1 m y 2 m. Se calcularon nuevos modelos de regresión con los datos muestreados obteniéndose buenas estimaciones de los parámetros para todos los conjuntos de datos.The authors appreciate the financial support provided by the regional government of Spain (Conselleria d'Educacio, Cultura i Esport Generalitat Valenciana) in the framework of the Project GV/2014/016.Estornell, J.; Velázquez-Martí, A.; Fernández-Sarría, A.; López-Cortés, I.; Martí-Gavilá, J.; Salazar, D. (2017). Estimation of structural attributes of walnut trees based on terrestrial laser scanning. Revista de Teledetección. (48):67-76. https://doi.org/10.4995/raet.2017.7429SWORD677648Belsley. D.A. 1991. Conditioning Diagnostics: Collinearity and Weak Data in Regression. John Wiley & Sons.Chianucci, F., Puletti, N., Giacomello, E., Cutini, A., & Corona, P. (2015). Estimation of leaf area index in isolated trees with digital photography and its application to urban forestry. Urban Forestry & Urban Greening, 14(2), 377-382. doi:10.1016/j.ufug.2015.04.001Corona, P., Agrimi, M., Baffetta, F., Barbati, A., Chiriacò, M. V., Fattorini, L., … Mattioli, W. (2011). Extending large-scale forest inventories to assess urban forests. Environmental Monitoring and Assessment, 184(3), 1409-1422. doi:10.1007/s10661-011-2050-6Fernández-Sarría, A., Martínez, L., Velázquez-Martí, B., Sajdak, M., Estornell, J., & Recio, J. A. (2013). Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements. Computers and Electronics in Agriculture, 90, 176-185. doi:10.1016/j.compag.2012.09.017Gil, E., Llorens, J., Llop, J., Fàbregas, X., & Gallart, M. (2013). Use of a Terrestrial LIDAR Sensor for Drift Detection in Vineyard Spraying. Sensors, 13(1), 516-534. doi:10.3390/s130100516Greaves, H. E., Vierling, L. A., Eitel, J. U. H., Boelman, N. T., Magney, T. S., Prager, C. M., & Griffin, K. L. (2015). Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial LiDAR. Remote Sensing of Environment, 164, 26-35. doi:10.1016/j.rse.2015.02.023Keightley, K. E., & Bawden, G. W. (2010). 3D volumetric modeling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74(2), 305-312. doi:10.1016/j.compag.2010.09.005Manes, F., Incerti, G., Salvatori, E., Vitale, M., Ricotta, C., & Costanza, R. (2012). Urban ecosystem services: tree diversity and stability of tropospheric ozone removal. Ecological Applications, 22(1), 349-360. doi:10.1890/11-0561.1MAAM. 2015. Encuesta sobre superficies y rendimientos cultivos (ASYRCE). Encuesta de marco de áreas de Espa-a. Ministerio de Agricultura, Alimentación y Medio Ambiente de Espa-a, 44 pp.Rosell, J. R., Llorens, J., Sanz, R., Arnó, J., Ribes-Dasi, M., Masip, J., … Palacín, J. (2009). Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology, 149(9), 1505-1515. doi:10.1016/j.agrformet.2009.04.008Rosell Polo, J. R., Sanz, R., Llorens, J., Arnó, J., Escolà, A., Ribes-Dasi, M., … Palacín, J. (2009). A tractor-mounted scanning LIDAR for the non-destructive measurement of vegetative volume and surface area of tree-row plantations: A comparison with conventional destructive measurements. Biosystems Engineering, 102(2), 128-134. doi:10.1016/j.biosystemseng.2008.10.009Rosell, J. R., & Sanz, R. (2012). A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Computers and Electronics in Agriculture, 81, 124-141. doi:10.1016/j.compag.2011.09.00

Incidence of diabetes in patients treated with antipsychotics in primary care

Cartas al directorS

Estimating residual biomass of olive tree crops using terrestrial laser scanning

[EN] Agricultural residues have gained increasing interest as a source of renewable energy. The development of methods and techniques that allow to inventory residual biomass needs to be explored further. In this study, the residual biomass of olive trees was estimated based on parameters derived from using a Terrestrial Laser Scanning System (TLS). To this end, 32 olive trees in 2 orchards in the municipality of Viver, Central Eastern Spain, were selected and measured using a TLS system. The residual biomass of these trees was pruned and weighed. Several algorithms were applied to the TLS data to compute the main parameters of the trees: total height, crown height, crown diameter and crown volume. Regarding the last parameter, 4 methods were tested: the global convex hull volume, the convex hull by slice volume, the section volume, and the volume measured by voxels. In addition, several statistics were computed from the crown points for each tree. Regression models were calculated to predict residual biomass using 3 sets of potential explicative variables: firstly, the height statistics retrieved from 3D cloud data for each crown tree, secondly, the parameters of the trees derived from TLS data and finally, the combination of both sets of variables. Strong relationships between residual biomass and TLS parameters (crown volume parameters) were found (R2 = 0.86, RMSE = 2.78 kg). The pruning biomass pre- diction fraction was improved by 6%, in terms of R2, when the variance of the crown-point elevations was selected (R2 = 0.92, RMSE = 2.01 kg). The study offers some important insights into the quantification of residual biomass, which is essential information for the production of biofuel.Fernández-Sarría, A.; López- Cortés, I.; Estornell Cremades, J.; Velázquez Martí, B.; Salazar Hernández, DM. (2019). Estimating residual biomass of olive tree crops using terrestrial laser scanning. International Journal of Applied Earth Observation and Geoinformation. 75:163-170. https://doi.org/https://doi.org/10.1016/j.jag.2018.10.019S1631707

Estimation of shrub biomass by airborne LiDAR data in small forest stands

The presence of shrub vegetation is very significant in Mediterranean ecosystems. However, the difficulty involved in shrub management and the lack of information about behavior of this vegetation means that these areas are often left out of spatial planning projects. Airborne LiDAR (Light Detection And Ranging) has been used successfully in forestry to estimate dendrometric and dasometric variables that allow to characterize forest structure. In contrast, little research has focused on shrub vegetation. The objective of this study was to estimate dry biomass of shrub vegetation in 83 stands of radius 0.5 m using variables derived from LiDAR data. Dominant species was Quercus coccifera, one of the most characteristic species of the Mediterranean forests. Density of LiDAR data in the analyzed stands varied from 2 points/m(2) to 16 points/m(2), being the average 8 points/m(2) and the standard deviation 4.5 points/m(2). Under these conditions, predictions of biomass were performed calculating the mean height, the maximum height and the percentile values 80th, 90th, and 95th derived from LiDAR in concentric areas whose radius varied from 0.50 m to 3.5 m from the center of the stand. The maximum R(2) and the minimum RMSE for dry biomass estimations were obtained when the percentile 95th of LiDAR data was calculated in an area of radius 1.5 m, being 0.48 and 1.45 kg, respectively. For this radius, it was found that for the stands (n = 39) where the DTM is calculated with high accuracy (RMSE lower than 0.20 m) and with a high density of LiDAR data (more than 8 points/m(2)) the R(2) value was 0.73. These results show the possibility of estimating shrub biomass in small areas when the density of LiDAR data is high and errors associated to the DTM are low. These results would allow us to improve the knowledge about shrub behavior avoiding the cost of field measurements and clear cutting actions. (C) 2011 Elsevier B.V. All rights reserved.Estornell Cremades, J.; Ruiz Fernández, LÁ.; Velázquez Martí, B.; Fernández Sarriá, A. (2011). Estimation of shrub biomass by airborne LiDAR data in small forest stands. Forest Ecology and Management. 262(9):1697-1703. doi:10.1016/j.foreco.2011.07.026S16971703262

Estimation of wood volume and height of olive tree plantations using airborne discrete-return LiDAR data

The aim of this study is to analyze methodologies based on airborne LiDAR (light detection and ranging) technology of low pulse density points (0.5m(-2)) for height and volume quantification of olive trees in Viver (Spain). A total of 29 circular plots, each with a radius of 20m, were sampled and their volumes and heights were obtained by dendrometric methods. For these estimations, several statistics derived from LiDAR data were calculated in each plot. Regression models were used to predict volume and height. The results showed good performance for estimating volume (R-2=0.70) and total height (R-2=0.67).The authors appreciate the financial support provided by the Spanish Ministerio de Ciencia e Innovacion (Ministry for Science & Innovation) within the framework of the project AGL2010-15334 and by the Vice-Rectorate for Research of the Universitat Politecnica de Valencia [Grant PAID-06-12-3297; SP20120534].Estornell Cremades, J.; Velázquez Martí, B.; López Cortés, I.; Salazar Hernández, DM.; Fernández-Sarría, A. (2014). Estimation of wood volume and height of olive tree plantations using airborne discrete-return LiDAR data. GIScience and Remote Sensing. 51(1):17-29. https://doi.org/10.1080/15481603.2014.883209S1729511Estornell, J., Ruiz, L. A., Velázquez-Martí, B., & Fernández-Sarría, A. (2011). Estimation of shrub biomass by airborne LiDAR data in small forest stands. Forest Ecology and Management, 262(9), 1697-1703. doi:10.1016/j.foreco.2011.07.026García, M., Riaño, D., Chuvieco, E., & Danson, F. M. (2010). Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data. Remote Sensing of Environment, 114(4), 816-830. doi:10.1016/j.rse.2009.11.021Hyyppa, J., Kelle, O., Lehikoinen, M., & Inkinen, M. (2001). A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners. IEEE Transactions on Geoscience and Remote Sensing, 39(5), 969-975. doi:10.1109/36.921414Kim, Y., Yang, Z., Cohen, W. B., Pflugmacher, D., Lauver, C. L., & Vankat, J. L. (2009). Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-footprint lidar data. Remote Sensing of Environment, 113(11), 2499-2510. doi:10.1016/j.rse.2009.07.010Moorthy, I., Miller, J. R., Berni, J. A. J., Zarco-Tejada, P., Hu, B., & Chen, J. (2011). Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology, 151(2), 204-214. doi:10.1016/j.agrformet.2010.10.005Næsset, E. (2004). Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project. Scandinavian Journal of Forest Research, 19(6), 554-557. doi:10.1080/02827580410019544Popescu, S. C. (2007). Estimating biomass of individual pine trees using airborne lidar. Biomass and Bioenergy, 31(9), 646-655. doi:10.1016/j.biombioe.2007.06.022Popescu, S. C., Wynne, R. H., & Nelson, R. F. (2002). Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size. Computers and Electronics in Agriculture, 37(1-3), 71-95. doi:10.1016/s0168-1699(02)00121-7Velázquez-Martí, B., Estornell, J., López-Cortés, I., & Martí-Gavilá, J. (2012). Calculation of biomass volume of citrus trees from an adapted dendrometry. Biosystems Engineering, 112(4), 285-292. doi:10.1016/j.biosystemseng.2012.04.011Velázquez-Martí, B., Fernández-González, E., Estornell, J., & Ruiz, L. A. (2010). Dendrometric and dasometric analysis of the bushy biomass in Mediterranean forests. Forest Ecology and Management, 259(5), 875-882. doi:10.1016/j.foreco.2009.11.027Velázquez-Martí, B., Fernández-González, E., López-Cortés, I., & Salazar-Hernández, D. M. (2011). Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. Biomass and Bioenergy, 35(7), 3208-3217. doi:10.1016/j.biombioe.2011.04.042Yu, X., Hyyppä, J., Kaartinen, H., & Maltamo, M. (2004). Automatic detection of harvested trees and determination of forest growth using airborne laser scanning. Remote Sensing of Environment, 90(4), 451-462. doi:10.1016/j.rse.2004.02.00

Different methodologies for calculating crown volume of Platanus hispanica trees by terrestial laser scanner and comparison with classical dendrometric measurements

Terrestrial laser scanners (TLSs) are used in forestry and fruit culture applications to perform a threedimensional geometrical characterization of trees and so make it easier to develop management systems based on that information. In addition, this data can improve the accuracy of dendrometric variable estimations, such as crown volume, obtained by standard methods. The main objective of this paper is to compare classical methods for crown volume estimation with the volumes obtained from the processing of point clouds obtained using a terrestrial laser scanner (TLS) on urban Platanus hispanica trees. This will allow faster quantification of residual biomass from pruning and therefore an improved management in future. The methods applied using TLS data were also evaluated in terms of processing speed. A set of 30 specimens were selected and their main dendrometric parameters (such as diameter breast height, crown diameter, total height, and distance from the crown base to the soil) were manually measured using classical methods. From these dendrometric parameters, the apparent crown volumes were calculated using three geometric models: cone, hemisphere, and paraboloid. Simultaneously, these trees were scanned with a Leica ScanStation2. A laser point cloud was registered for each tree and processed to obtain the crown volumes. Four processing methods were analyzed: (a) convex hull (an irregular polyhedral surface formed by triangles that surround the crown) applied to the whole point cloud that forms the crown; (b) convex hull using slices of 10 cm in height from the top to the base of the crown; (c) XY triangulation in horizontal sections; and (d) voxel discretization. All the obtained volumes (derived from classical methods and TLS) were assessed and compared. The regression equations that compare the volumes obtained by dendrometry and those derived from TLS data showed coefficients of determination (R2) greater than 0.78. The highest R2 (0.89) was obtained in the comparison between the volume calculated using a paraboloid and flat sections, which was also the fastest method. These results show the potential of TLS for predicting the crown volumes of urban trees, such as P. hispanica, to help improve their management, especially the quantification of residual biomass.The authors appreciate the financial support provided by the Spanish Ministry of Science and Innovation in the framework of the Project AGL2010-15334 and by the Generalitat Valenciana in the framework of the Project GV/2012/003.Fernández-Sarría, A.; Martínez, L.; Velázquez Martí, B.; Sajdak, M.; Estornell Cremades, J.; Recio Recio, JA. (2013). Different methodologies for calculating crown volume of Platanus hispanica trees by terrestial laser scanner and comparison with classical dendrometric measurements. Computers and Electronics in Agriculture. 90(1):176-185. https://doi.org/10.1016/j.compag.2012.09.017S17618590

Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain)

[EN] The abandonment of agricultural plots entails a low economic productivity of the land and a higher vulnerability to wildfires and degradation of affected areas. In this sense, the local government of Galicia is promoting new methodologies based on high-resolution images in order to classify the territory in basic and generic land uses. This procedure will be used to control the sustainable management of plots belonging to the Land Bank. This paper presents an application study for maintaining and updating land use/land cover geospatial databases using parcel-oriented classification. The test is performed over two geographic areas of Galicia, in the northwest of Spain. In this region, forest and shrublands in mountain environments are very heterogeneous with many private unproductive plots, some of which are in a high state of abandonment. The dataset is made of high spatial resolution multispectral imagery, cadastral cartography employed to define the image objects (plots), and field samples used to define evaluation and training samples. A set of descriptive features is computed quantifying different properties of the objects, i.e. spectral, texture, structural, and geometrical. Additionally, the effect on the classification and updating processes of the historical land use as a descriptive feature is tested. Three different classification methodologies are analyzed: linear discriminant analysis, decision trees, and support vector machine. The overall accuracies of the classifications obtained are always above 90 % and support vector machine method is proved to provide the best performance. Forest and shrublands areas are especially undefined, so the discrimination between these two classes is low. The results enable to conclude that the use of automatic parcel-oriented classification techniques for updating tasks of land use/land cover geospatial databases, is effective in the areas tested, particularly when broad and well defined classes are required.The authors appreciate the collaboration and support provided by Xunta de Galicia, Sociedade para o Desenvolvemento Comarcal de Galícia, and Banco de Terras de Galicia. The financial support provided by the Spanish Ministerio de Ciencia e Innovación in the framework of the projects CGL2010-19591/BTE and CGL2009-14220 is also acknowledged.Hermosilla, T.; Díaz Manso, J.; Ruiz Fernández, LÁ.; Recio Recio, JA.; Fernández-Sarría, A.; Ferradáns Nogueira, P. (2012). Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain). Applied Geomatics. 4(4):245-255. https://doi.org/10.1007/s12518-012-0087-zS24525544Arikan M (2004) Parcel-based crop mapping through multi-temporal masking classification of landsat 7 images in Karacabey, Turkey. Int Arch Photogramm Remote Sens Spat Inf Sci 35:1085–1090Balaguer A, Ruiz LA, Hermosilla T, Recio JA (2010) Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification. Comput Geosci 36(2):231–240Balaguer-Besser A, Hermosilla T, Recio JA, Ruiz LA (2011) Semivariogram calculation optimization for object-oriented image classification. Model Sci Educ Learn 4(7):91–104Blaschke T (2010) Object based image analysis for remote sensing. ISPRS J Photogramm 65(1):2–16Cohen Y, Shoshany M (2000) Integration of remote sensing, GIS and expert knowledge in national knowledge-based crop recognition in Mediterranean environment. 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Servizo de Publicacións e Intercambio Científico, Santiago de Compostela, Spain, pp 31–44Dupas CA (2000) SAR and LANDSAT TM image fusion for land cover classification in the Brazilian Atlantic Forest Domain. Int Arch Photogramm Remote Sens XXXIII(Part B1):96–103El Kady M, Mack CB (1992) Remote sensing for crop inventory of Egypt’s old agricultural lands. Int Arch Photogramm Remote Sens 29:176–185Everitt BS, Dunn G (2001) Applied multivariate data analysis, 2nd edn. Edward Arnold, LondonHaralick RM, Shanmugam K, Dinstein I (1973) Texture features for image classification. IEEE Transact Syst Man Cybern 3(6):610–622Hermosilla T, Almonacid J, Fernández-Sarría A, Ruiz LA, Recio JA (2010) Combining features extracted from imagery and lidar data for object-oriented classification of forest areas. Int Arch Photogramm Remote Sens Spat Inf Sci 38(4/C7)Hernández Orallo J, Ramírez Quintana MJ, Ferri Ramírez C (2004) Introducción a la minería de datos. 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