Object-Based Greenhouse Mapping Using Very High Resolution Satellite Data and Landsat 8 Time Series

Greenhouse mapping through remote sensing has received extensive attention over the last decades. In this article, the innovative goal relies on mapping greenhouses through the combined use of very high resolution satellite data (WorldView-2) and Landsat 8 Operational Land Imager (OLI) time series within a context of an object-based image analysis (OBIA) and decision tree classification. Thus, WorldView-2 was mainly used to segment the study area focusing on individual greenhouses. Basic spectral information, spectral and vegetation indices, textural features, seasonal statistics and a spectral metric (Moment Distance Index, MDI) derived from Landsat 8 time series and/or WorldView-2 imagery were computed on previously segmented image objects. In order to test its temporal stability, the same approach was applied for two different years, 2014 and 2015. In both years, MDI was pointed out as the most important feature to detect greenhouses. Moreover, the threshold value of this spectral metric turned to be extremely stable for both Landsat 8 and WorldView-2 imagery. A simple decision tree always using the same threshold values for features from Landsat 8 time series and WorldView-2 was finally proposed. Overall accuracies of 93.0% and 93.3% and kappa coefficients of 0.856 and 0.861 were attained for 2014 and 2015 datasets, respectively

A Quantitative Assessment of Forest Cover Change in the Moulouya River Watershed (Morocco) by the Integration of a Subpixel-Based and Object-Based Analysis of Landsat Data

A quantitative assessment of forest cover change in the Moulouya River watershed (Morocco) was carried out by means of an innovative approach from atmospherically corrected reflectance Landsat images corresponding to 1984 (Landsat 5 Thematic Mapper) and 2013 (Landsat 8 Operational Land Imager). An object-based image analysis (OBIA) was undertaken to classify segmented objects as forested or non-forested within the 2013 Landsat orthomosaic. A Random Forest classifier was applied to a set of training data based on a features vector composed of different types of object features such as vegetation indices, mean spectral values and pixel-based fractional cover derived from probabilistic spectral mixture analysis). The very high spatial resolution image data of Google Earth 2013 were employed to train/validate the Random Forest classifier, ranking the NDVI vegetation index and the corresponding pixel-based percentages of photosynthetic vegetation and bare soil as the most statistically significant object features to extract forested and non-forested areas. Regarding classification accuracy, an overall accuracy of 92.34% was achieved. The previously developed classification scheme was applied to the 1984 Landsat data to extract the forest cover change between 1984 and 2013, showing a slight net increase of 5.3% (ca. 8800 ha) in forested areas for the whole region

Comunicación visual mediante técnicas GIS en el litoral del Campo de Dalías: la defensa costera de los pueblos del interior

[ES] La vigilancia de la costa para la protección de las poblaciones establecidas en el interior ha sido uno de los principales problemas en la provincia de Almería durante una parte importante de nuestra Edad Moderna. Debido a esto, se planificó y desarrolló toda una infraestructura defensiva y de observación de la llegada de corsarios y piratas a las costas almerienses. Con el presente trabajo se pretende, en primer lugar, dar importancia a estas estructuras desde un punto de vista paisajístico, turístico y cultural, mediante técnicas GIS de creación de cuencas visuales. Por otro lado, del solapamiento entre cuencas visuales, o su ausencia, se pueden extraer conclusiones desde el punto de vista arqueológico, como parte de un proyecto cuyo objetivo es la investigación de la conexión visual entre las defensas costeras y las poblaciones del interior.[EN] Monitoring of the coast for the protection of the in-land populations has been one of the main problems in the province of Almería during a significant part of Modern Age. Due to this was planned and developed an entire infrastructure defensive and observational in view of the arrival of pirates and corsairs to the coast of Almería. With the present work it is tried firstly to give importance to these structures from a landscape point of view, tourism and culture through GIS techniques to create view sheds. On the other, from overlapping each different view shed, their presence or absence, can give useful conclusions for the archaeology science, as a part of a research project on the visual connection between the coastal defenses and in-land populations.Villanueva Ojeda, E.; García Lorca, AM. (2012). Comunicación visual mediante técnicas GIS en el litoral del Campo de Dalías: la defensa costera de los pueblos del interior. Virtual Archaeology Review. 3(6):93-97. https://doi.org/10.4995/var.2012.4455OJS939736ARAMBURU, Mª.P., CIFUENTES, P., ESCRIBANO, R., GONZÁLEZ, S. (1994): Guía para la elaboración de estudios del medio físico. Contenido y metodología. Ministerio de Obras Públicas y Transportes. Secretaría de Estado para las Políticas del Agua y el Medio Ambiente, Madrid.CARA BARRIONUEVO, L., CARA RODRÍGUEZ, J. (1986): "El poblamiento Andalusí en el Campo de Dalías Oriental (Almería): Discontinuidades y permanencias.", en Boletín del I.E.A., 1986.CRESSIER, P. (1984): "El Castillo y la división territorial en la Alpujarra medieval: del hisn a la ta'a / Le Château et la division territoriale dans l'Alpujarra médievale: du hisn à la ta'a.", en Mélanges de la Casa de Velazquez, nº XX, pp. 115-144. http://dx.doi.org/10.3406/casa.1984.2413CRESSIER, P. (1986): "Dalías y su territorio: Un grupo de alquerías musulmanas de la Baja Alpujarra (Provincia de Almería) / Dalías et son territoire: Un groupe d'alquerías musulmanes de la Basse Alpujarra (Province d'Almería).", en Actas del XII Concreso de la U.E.A.I. Málaga, 1984, Madrid, 1986, pp. 205-228.ESRI (2001): ArcGIS Spatial Analyst: Advanced GIS Spatial Analysis Using Raster and Vector Data. ESRI White Papers, December 2001.ESRI (2002): ArcGIS 3D Analyst: Three-Dimensional Visualization, Topographic Analysis, and Surface Creation. ESRI White Papers, January 2002.GIL ALBARRACÍN, A., CAPEL, H. (2004): Documentos sobre la defensa de la costa del Reino de Granada (1497-1857). Temas locales. Almería.KIDNER, D.B.; SPARKES, A.J.; DOREY, M.I.; WARE, J.M.; JONES, C.B. (2001): "Visibility Analysis with the Multiscale Implicit TIN", en Transactions in GIS, nº 5(1), pp. 19-37.LLOBERA, M. (2003): "Extending GIS-based visual analysis: the concept of 'Visualscapes'", en International Journal of Geographical Information Sciences, nº 17, pp. 25-48.LLOBERA, M.; FÁBREGA-ÁLVAREZ, P.; PARCERO-OUBIÑA, C. (2011): "Order in movement: a GIS approach to accesibility", en Journal of Archaeological Science, nº 38, pp. 843-851.MARTÍNEZ LILLO, S.; MATALANA UREÑA, A.; SÁEZ LARA, F. (1997): "La aplicación de los SIG como planteamiento de la organización del espacio en la Marca Media andalusí: el sistema de atalayas en la Cuenca del Jarama (Madrid)", en Los SIG y el análisis espacial en Arqueología. Madrid, pp. 273-308.McCOY, M.D.; LADEFOGED, T.N. (2009): "New Developments in the Use of Spatial Technology in Archaeology", en Journal of Archaeological Science, nº 17, pp. 263-295.RIGGS, P.D.; DEAN, D.J. (2007): "An investigation into the Causes of Errors and Inconsistencies in Predicted Viewsheds", en Transactions in GIS, nº 11 (2), pp. 175-196.RUESTES, C. (2008): "Social organization and human space in North-Eastern Iberia during the Third Century BC", en Oxford Journal of Archaeology, nº 27, pp. 359-386.SÁNCHEZ SEDANO, Mª. P. (1988): "Arquitectura musulmana en la provincia de Almería", en Boletín del I.E.A.WHEATLEY, D.W.; GARCÍA SANJUÁN, L.; MURRIETA FLORES, P.A.; MÁRQUEZ PÉREZ, J. (2010): "Approaching the landscape dimension of the megalithic phenomenon in Southern Spain", en Oxford Journal of Archaeology, nº 29(4), pp. 387-405

Greenhouse Crop Identification from Multi-Temporal Multi-Sensor Satellite Imagery Using Object-Based Approach: A Case Study from Almería (Spain)

A workflow headed up to identify crops growing under plastic-covered greenhouses (PCG) and based on multi-temporal and multi-sensor satellite data is developed in this article. This workflow is made up of four steps: (i) data pre-processing, (ii) PCG segmentation, (iii) binary preclassification between greenhouses and non-greenhouses, and (iv) classification of horticultural crops under greenhouses regarding two agronomic seasons (autumn and spring). The segmentation stage was carried out by applying a multi-resolution segmentation algorithm on the pre-processed WorldView-2 data. The free access AssesSeg command line tool was used to determine the more suitable multi-resolution algorithm parameters. Two decision tree models mainly based on the Plastic Greenhouse Index were developed to perform greenhouse/non-greenhouse binary classification from Landsat 8 and Sentinel-2A time series, attaining overall accuracies of 92.65% and 93.97%, respectively. With regards to the classification of crops under PCG, pepper in autumn, and melon and watermelon in spring provided the best results (Fβ around 84% and 95%, respectively). Data from the Sentinel-2A time series showed slightly better accuracies than those from Landsat 8

Improving georeferencing accuracy of Very High Resolution satellite imagery using freely available ancillary data at global coverage

While impressive direct geolocation accuracies better than 5.0 m CE90 (90% of circular error) can be achieved from the last DigitalGlobe’s Very High Resolution (VHR) satellites (i.e. GeoEye-1 and WorldView-1/2/3/4), it is insufficient for many precise geodetic applications. For these sensors, the best horizontal geopositioning accuracies (around 0.55 m CE90) can be attained by using third-order 3D rational functions with vendor’s rational polynomial coefficients data refined by a zero-order polynomial adjustment obtained from a small number of very accurate ground control points (GCPs). However, these high-quality GCPs are not always available. In this work, two different approaches for improving the initial direct geolocation accuracy of VHR satellite imagery are proposed. Both of them are based on the extraction of three-dimensional GCPs from freely available ancillary data at global coverage such as multi-temporal information of Google Earth and the Shuttle Radar Topography Mission 30 m digital elevation model. The application of these approaches on WorldView-2 and GeoEye-1 stereo pairs over two different study sites proved to improve the horizontal direct geolocation accuracy values around of 75%

Classification of urban areas from GeoEye-1 imagery through texture features based on Histograms of Equivalent Patterns

A family of 26 non-parametric texture descriptors based on Histograms of Equivalent Patterns (HEP) has been tested, many of them for the first time in remote sensing applications, to improve urban classification through object-based image analysis of GeoEye-1 imagery. These HEP descriptors have been compared to the widely known texture measures derived from the gray-level co-occurrence matrix (GLCM). All the five finally selected HEP descriptors (Local Binary Patterns, Improved Local Binary Patterns, Binary Gradient Contours and two different combinations of Completed Local Binary Patterns) performed faster in terms of execution time and yielded significantly better accuracy figures than GLCM features. Moreover, the HEP texture descriptors provided additional information to the basic spectral features from the GeoEye-1's bands (R, G, B, NIR, PAN) significantly improving overall accuracy values by around 3%. Conversely, and in statistic terms, strategies involving GLCM texture derivatives did not improve the classification accuracy achieved from only the spectral information. Lastly, both approaches (HEP and GLCM) showed similar behavior with regard to the training set size applied

3GPP QoS-based scheduling framework for LTE

This paper proposes the design of a scheduling framework for the downlink of the Long Term Evolution (LTE) system with the objective of meeting the Quality of Service (QoS) requirements as defined by the QoS architecture of the 3G Partnership Project (3GPP) specifications. We carry out a thorough review of 3GPP specifications analyzing the requirements of the 3GPP QoS architecture. LTE bearers may be associated with a Guaranteed Bit Rate (i.e., GBR bearers) or not (i.e., non-GBR bearers). Additionally, the specifications establish a Packet Delay Budget (PDB) to limit the maximum packet transfer delay. To achieve our goal, we design a channel-aware service discipline for GBR bearers which is able to fulfill not only the GBR but also the PDB. Additionally, we also design an algorithm for prioritizing GBR and non-GBR bearers from different QoS Class Identifiers (QCIs) following 3GPP QoS rules. We compare the proposed framework with two reference schedulers by means of network-level simulations. The results will show the ability of the proposed framework to address the QoS requirements from 3GPP specifications while providing an interesting performance from a spectral efficiency viewpoint.This work is partially supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (project TIN2013-46223-P)

Optimizing multiresolution segmentation for extracting plastic greenhouses from WorldView-3 imagery

Multiresolution segmentation (MRS) has been pointed out as one of the most successful image segmentation algorithms within the object-based image analysis (OBIA) framework. The performance of this algorithm depends on the selection of three tuning parameters (scale, shape and compactness) and the bands combination and weighting considered. In this work, we tested MRS on a WorldView-3 bundle imagery in order to extract plastic green-house polygons. A recently published command line tool created to assess the quality of segmented digital images (AssesSeg), which implements a modified version of the supervised discrepancy measure named Euclidean Distance 2 (ED2), was used to select both the best aforementioned MRS pa-rameters and the optimum image data source derived from WorldView-3 (i.e., panchromatic, multispectral and atmospherically corrected multispectral orthoimages). The best segmentation results were always attained from the atmospherically corrected multispectral WorldView-3 orthoimage

Shift work and colorectal cancer risk in the MCC-Spain case-control study

Objectives Shift work that involves circadian disruption has been associated with a higher cancer risk. Most epidemiological studies to date have focused on breast cancer risk and evidence for other common tumors is limited. We evaluated the risk for colorectal cancer (CRC) in relation to shift work history in a population-based case-control study in Spain. Methods This analysis included 1626 incident CRC cases and 3378 randomly selected population controls of both sexes, enrolled in 11 regions of Spain. Sociodemographic and lifestyle information was assessed in face-to-face interviews. Shift work was assessed in detail throughout lifetime occupational history. We estimated the risk of colon and rectal cancer associated with rotating and permanent shift work (ever, cumulative duration, age of first exposure) using unconditional logistic regression analysis adjusting for potential confounders. Results Having ever performed rotating shift work (morning, evening and/or night) was associated with an increased risk for CRC [odds ratio (OR) 1.22, 95% confidence interval (95% CI) 1.04-1.43], as compared to day workers. Having ever worked permanent night shifts (?3 nights/month) was not associated with CRC risk (OR 0.79, 95% CI 0.62-1.00). OR increased with increasing lifetime cumulative duration of rotating shift work (P-value for trend 0.005) and were highest among subjects in the top quartiles of exposure (3 rdquartile, 20-34 years, OR 1.38, 95%CI 1.06-1.81; 4 thquartile, ?35 years, OR 1.36, 95% CI 1.02-1.79). Conclusions These data suggest that rotating shift work may increase the risk of CRC especially after long-term exposures