Vision Goes Symbolic Without Loss of Information Within the Preattentive Vision Phase: The Need to Shift the Learning Paradigm from Machine-Learning (from Examples) to Machine-Teaching (by Rules) at the First Stage of a Two-Stage Hybrid Remote... Part I

Life sciences: general issue

Pre-processing, classification and semantic querying of large-scale Earth observation spaceborne/airborne/terrestrial image databases: Process and product innovations.

By definition of Wikipedia, “big data is the term adopted for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The big data challenges typically include capture, curation, storage, search, sharing, transfer, analysis and visualization”. Proposed by the intergovernmental Group on Earth Observations (GEO), the visionary goal of the Global Earth Observation System of Systems (GEOSS) implementation plan for years 2005-2015 is systematic transformation of multisource Earth Observation (EO) “big data” into timely, comprehensive and operational EO value-adding products and services, submitted to the GEO Quality Assurance Framework for Earth Observation (QA4EO) calibration/validation (Cal/Val) requirements. To date the GEOSS mission cannot be considered fulfilled by the remote sensing (RS) community. This is tantamount to saying that past and existing EO image understanding systems (EO-IUSs) have been outpaced by the rate of collection of EO sensory big data, whose quality and quantity are ever-increasing. This true-fact is supported by several observations. For example, no European Space Agency (ESA) EO Level 2 product has ever been systematically generated at the ground segment. By definition, an ESA EO Level 2 product comprises a single-date multi-spectral (MS) image radiometrically calibrated into surface reflectance (SURF) values corrected for geometric, atmospheric, adjacency and topographic effects, stacked with its data-derived scene classification map (SCM), whose thematic legend is general-purpose, user- and application-independent and includes quality layers, such as cloud and cloud-shadow. Since no GEOSS exists to date, present EO content-based image retrieval (CBIR) systems lack EO image understanding capabilities. Hence, no semantic CBIR (SCBIR) system exists to date either, where semantic querying is synonym of semantics-enabled knowledge/information discovery in multi-source big image databases. In set theory, if set A is a strict superset of (or strictly includes) set B, then A B. This doctoral project moved from the working hypothesis that SCBIR computer vision (CV), where vision is synonym of scene-from-image reconstruction and understanding EO image understanding (EO-IU) in operating mode, synonym of GEOSS ESA EO Level 2 product human vision. Meaning that necessary not sufficient pre-condition for SCBIR is CV in operating mode, this working hypothesis has two corollaries. First, human visual perception, encompassing well-known visual illusions such as Mach bands illusion, acts as lower bound of CV within the multi-disciplinary domain of cognitive science, i.e., CV is conditioned to include a computational model of human vision. Second, a necessary not sufficient pre-condition for a yet-unfulfilled GEOSS development is systematic generation at the ground segment of ESA EO Level 2 product. Starting from this working hypothesis the overarching goal of this doctoral project was to contribute in research and technical development (R&D) toward filling an analytic and pragmatic information gap from EO big sensory data to EO value-adding information products and services. This R&D objective was conceived to be twofold. First, to develop an original EO-IUS in operating mode, synonym of GEOSS, capable of systematic ESA EO Level 2 product generation from multi-source EO imagery. EO imaging sources vary in terms of: (i) platform, either spaceborne, airborne or terrestrial, (ii) imaging sensor, either: (a) optical, encompassing radiometrically calibrated or uncalibrated images, panchromatic or color images, either true- or false color red-green-blue (RGB), multi-spectral (MS), super-spectral (SS) or hyper-spectral (HS) images, featuring spatial resolution from low (> 1km) to very high (< 1m), or (b) synthetic aperture radar (SAR), specifically, bi-temporal RGB SAR imagery. The second R&D objective was to design and develop a prototypical implementation of an integrated closed-loop EO-IU for semantic querying (EO-IU4SQ) system as a GEOSS proof-of-concept in support of SCBIR. The proposed closed-loop EO-IU4SQ system prototype consists of two subsystems for incremental learning. A primary (dominant, necessary not sufficient) hybrid (combined deductive/top-down/physical model-based and inductive/bottom-up/statistical model-based) feedback EO-IU subsystem in operating mode requires no human-machine interaction to automatically transform in linear time a single-date MS image into an ESA EO Level 2 product as initial condition. A secondary (dependent) hybrid feedback EO Semantic Querying (EO-SQ) subsystem is provided with a graphic user interface (GUI) to streamline human-machine interaction in support of spatiotemporal EO big data analytics and SCBIR operations. EO information products generated as output by the closed-loop EO-IU4SQ system monotonically increase their value-added with closed-loop iterations

Earth resources: A continuing bibliography (issue 26)

This bibliography lists 480 reports, articles, and other documents introduced into the NASA scientific and technical information system between April 1, 1980 and June 30, 1980. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Validation of a simplified model to generate multispectral synthetic images

A new procedure to assess the quality of topographic correction (TOC) algorithms applied to remote sensing imagery was previously proposed by the authors. This procedure was based on a model that simulated synthetic scenes, representing the radiance an optical sensor would receive from an area under some specific conditions. TOC algorithms were then applied to synthetic scenes and the resulting corrected scenes were compared with a horizontal synthetic scene free of topographic effect. This comparison enabled an objective and quantitative evaluation of TOC algorithms. This approach showed promising results but had some shortcomings that are addressed herein. First, the model, originally built to simulate only broadband panchromatic scenes, is extended to multispectral scenes in the visible, near infrared (NIR), and short wave infrared (SWIR) bands. Next, the model is validated by comparing synthetic scenes with four Satellite pour l'Observation de la Terre 5 (SPOT5) real scenes acquired on different dates and different test areas along the Pyrenees mountain range (Spain). The results obtained show a successful simulation of all the spectral bands. Therefore, the model is deemed accurate enough for its purpose of evaluating TOC algorithms.The authors gratefully acknowledge the financial support provided by the Public University of Navarre (UPNA). Part of the research presented in this paper is funded by the Spanish Ministry of Economy and Competitiveness in the frame of the ESP2013-48458-C4-2-P project

Earth resources: A continuing bibliography with indexes (issue 61)

This bibliography lists 606 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1989. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors, and economic analysis

Mediterranean Forest Species Mapping Using Hyperspectral Imagery

2011/2012Advances in hyperspectral technology provides scientists the opportunity to investigate problems that were difficult if not impossible to approach using multispectral data; among those, species composition which is a very important and dynamic forest parameter, linked with many environmental qualities that we want to map and monitor. This study addresses the problem of Mediterranean forest species mapping using satellite EO-1 Hyperion imagery (30m, 196 bands). Two pixel based techniques were evaluated, namely Spectral Angle Mapper (SAM) and Support Vector Machines (SVM), as well as an object oriented approach (GEOBIA). These techniques were applied in two study areas with different species composition and pattern complexity, namely Thasos and Taksiarchis. Extensive field work provided reference data for the accuracy assessment of the produced maps. Image preprocessing included several steps of data corrections and the Minimum Noise Fraction transformation, as means for data dimensionality reduction. In the case of Thasos, where two conifer species are present, SAM technique resulted in an overall accuracy (OA) of 3.9%, SVM technique yielded OA of 89.0% and GEOBIA achieved an OA of 85.3%. In the case of Taksiarchis, where more species are present – both conifers and broadleaved- the respective OA was 80.0%, 82.6% and 74.1%. All three methodologies implemented to investigate the value of hyperspectral imagery in Mediterranean forest species mapping, achieved very accurate results; in some cases equivalent to forest inventory maps. SAM was the straightest forward to implement, only depending on the training samples. Implementation SVM involved the specification of several parameters as well as the use of custom software and was more successful in the challenging landscape of Taksiarchis. GEOBIA adapted to scale through segmentation and extended the exercise of classification, allowing for knowledge based refinement. Lower accuracies could be attributed to the assessment method, as research on alternative assessment methods better adapted to the nature of object space is ongoing. Two typical Mediterranean forests were studied. In Thasos, two conifer species of the same genus, namely Pinus brutia and Pinus nigra, dominate a big part of the island. Both of them were accurately mapped by all methodologies. In Taksiarchis primarily stands of Quercus frainetto mix with stands of Fagus sylvatica and the aforementioned pines. The two pines were again mapped with high accuracy. However, there was a notable confusion between the two broadleaved species, indicating the need for further research, possibly taking advantage of species phenology. The outcome of the proposed methodologies could confidently meet the current needs for vegetation geographical data in regional to national scale, and demonstrate the value of hyperspectral imagery in Mediterranean forest species mapping.XXIII Ciclo198

Multitemporal evaluation of topographic correction methods using multispectral synthetic images

Revista oficial de la Asociación Española de Teledetección[EN] This paper presents a multitemporal evaluation of topographic correction (TOC) methods based on synthetically generated images in order to evaluate the influence of solar angles on the performance of TOC methods. These synthetic images represent the radiance an optical sensor would receive for different periods of the year considering the real topography (SR image), and considering the relief completely horizontal (SH image). The comparison between the corrected image obtained applying a TOC method to a SR image and the SH image of the same area, i.e. considered the ideal correction, allows assessing the performance of each TOC algorithm, quantitatively measured through the Structural Similarity Index (SSIM).[ES] En este trabajo se presentan los resultados de la evaluación multitemporal de varios métodos de corrección topográfica (TOC), cuya bondad se determina de forma cuantitativa mediante el uso de imágenes sintéticas multiespectrales simuladas para diferentes fechas de adquisición a lo largo del año. Para cada fecha se generan dos imágenes sintéticas, una considerando el relieve real (imagen SR), y otra el relieve horizontal (imagen SH). Las imágenes SR se corrigen utilizando distintos TOC y estas imágenes corregidas se comparan con la corrección ideal (imagen SH) mediante el índice de similitud estructural (SSIM). Los valores de SSIM nos permiten evaluar la eficacia de cada corrección para distintas fechas, es decir, para distintos ángulos de elevación solar.Sola, I.; González-Audícana, M.; Álvarez-Mozos, J.; Torres, J. (2014). Evaluación multitemporal de métodos de corrección topográfica mediante el uso de imágenes sintéticas multiespectrales. Revista de Teledetección. (41):71-78. doi:10.4995/raet.2014.2246.SWORD717841Baraldi, A., Gironda, M., & Simonetti, D. (2010). Operational Two-Stage Stratified Topographic Correction of Spaceborne Multispectral Imagery Employing an Automatic Spectral-Rule-Based Decision-Tree Preliminary Classifier. IEEE Transactions on Geoscience and Remote Sensing, 48(1), 112-146. doi:10.1109/tgrs.2009.2028017Civco, D.L. 1989. Topographic Normalization of Landsat Thematic Mapper Digital Imagery. Photogramm. Eng. Remote S., 55: 1303-1309.Dumortier, D. 1998. The satellight model of turbidity variations in Europe. Report for the 6th Satel-Light meeting. Freiburg, Germany.Law, K.H., Nichol, J. 2004. Topographic correction for differential illumination effects on IKONOS satellite imagery. Int. Arch. Photogramm. Remote Sens. Spat. Inform. Sci., pp. 641-646.Page, J. 1996. Algorithms for the Satellight programme. Technical Report for the 2nd SATEL-LIGHT meeting. June, 1996, Bergen, Norway.Smith, J.A., Lin, T.L., Ranson, K.J. 1980. The Lambertian Assumption and Landsat Data. Photogrammetric Engineering & Remote Sensing, 46(9): 1183-1189Teillet, P. M., Guindon, B., & Goodenough, D. G. (1982). On the Slope-Aspect Correction of Multispectral Scanner Data. Canadian Journal of Remote Sensing, 8(2), 84-106. doi:10.1080/07038992.1982.10855028Twele, A., Kappas, M., Lauer, J., Erasmi, S. 2006. The effect of stratified topographic correction on land cover classificacion in tropical mountainous regions ISPRS Comm. VII Symp., 8-11 May, Enschede, The Netherlands, pp. 432-437

Earth Resources: A continuing bibliography with indexes, issue 17

This bibliography lists 775 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1978. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis