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Stratified sampling of satellite images with a systematic grid of points / F.J. Gallego in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 6 (November 2005)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 59 n° 6 (November 2005) . - pp 369 - 376 Titre : Stratified sampling of satellite images with a systematic grid of points Type de document : Article/Communication Auteurs : F.J. Gallego, Auteur Année de publication : 2005 Article en page(s) : pp 369 - 376 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] distribution spatiale [Termes IGN] échantillonnage d'image [Termes IGN] erreur systématique [Termes IGN] grille régulière [Termes IGN] image Landsat-ETM+ [Termes IGN] mosaïque d'images [Termes IGN] polygone de Thiessen Résumé : (Auteur) Sampling satellite images presents some specific characteristics : images overlap and many of them fall partially outside the studied region. A careless sampling may introduce an important bias. This paper illustrates the risk of bias and the efficiency improvements of systematic, pps (probability proportional to size) and stratified sampling. A sampling method is proposed with the following criteria: (a) unbiased estimators are easy to compute; (b) it can be combined with stratification; (c) within each stratum, sampling probability is proportional to the area of the sampling unit; and (d) the geographic distribution of the sample is reasonably homogeneous. Thiessen polygons computed on image centres are sampled through a systematic grid of points. The sampling rates in different strata are tuned by dividing the systematic grid into subgrids or replicates and taking for each stratum a certain number of replicates. The approach is illustrated with an application to the estimation of the geometric accuracy of Image2000, a Landsat ETM+ mosaic of the European Union. Copyright ISPRS Numéro de notice : A2005-492 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.10.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.10.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27628 [article]

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Regional crop inventories in Europe assisted by remote sensing, 1988-1993 / C. Taylor (1997)

Public Titre : Regional crop inventories in Europe assisted by remote sensing, 1988-1993 : Synthesis report of the Mars project, action 1 Type de document : Rapport Auteurs : C. Taylor, Auteur ; C. Sannier, Auteur ; J. Delince, Auteur ; F.J. Gallego, Auteur Editeur : Luxembourg : Office des Publications de l'Union Européenne Année de publication : 1997 Collection : Space Applications Institute Importance : 71 p. Format : 16 x 23 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Agriculture [Termes IGN] classification [Termes IGN] Communauté Européenne [Termes IGN] correction géométrique [Termes IGN] cultures [Termes IGN] image Landsat-TM [Termes IGN] image SPOT XS [Termes IGN] image SPOT-HRV [Termes IGN] inventaire [Termes IGN] télédétection spatiale Résumé : (Auteur) This report is a synthesis of the work, the results and an assessment of the achievements of Action I of the MARS Project. The report consist of this stand-alone executive summary and five additional sections. The first three enlarge on the main elements of the methodology : ground survey, remote sensing and the combination of these using regression. These sections also present a synthesis of the results and comments on their accuracy. Note de contenu : 1. CROP INVENTORY BY GROUND SURVEY 1.1 General Statistical Methodology 1.1.1 Summary of approach at each study site 1.1.2 Sample selection 1.1.3 Direct expansion estimates 1.1.4 Stratification 1.1.5 Example of stratified sample design 1.1.6 Efficiency of stratification 1.2 Application and variations. 1.2.1 Survey design 1.2.2 Field work 1.2.3 Data processing 1.3 Results and Conclusions 1.3.1 Accuracy of area estimates. 1.3.2 Timeliness of results 1.3.3 Efficiency of stratification 1.3.4 Yield estimates 2. SATELLITE REMOTE SENSING 2.1 Achievement of satellite image coverage 2.1.1 Satellite images used for regional inventories 2.1.2 Acquisition of satellite images 2.2 Remote sensing methodology 2.2.1 Fundamental concepts 2.2.2 Technical principles of geometric correction 2.2.3 Estimating the accuracy of geometric transformation 2.2.4 Technical principles of digital classification 2.2.5 Assessing the accuracy of digital classification 2.3 Application and results 2.3.1 Geometric correction 2.3.2 Classification of satellite imagery 2.3.3 Classification accuracy assessment 2.3.4 Timeliness 2.3.5 Yield estimation by remote sensing 3. CROP INVENTORY WITH REMOTE SENSING . 3.1 Methodology 3.1.1 Introduction 3.1.2 Relationship between ground survey and digital classification 3.1.3 The regression estimator 3.1.4 Neostratification imposed by satellite imagery. 3.1.5 Cost benefit of remote sensing 3.1.6 Implementation of the methodology 3.2 Results.. 3.2.1 Improvement of estimates of main crop areas 3.2.2 Variation of results across test sites 3.2.3 Improved accuracy of crop area estimates vs. class area 3.2.4 Cost-effectiveness 3.2.5 Comparison with national statistics 3.2.6 Timeliness 3.2.7 Comparison with USDA-NASS results 4. TECHNICAL FACTORS INFLUENCING RESULTS. 4.1 Accuracy of ground surveys 4.2 Success of image coverage 4.3 Quality of geometric correction 4.4 Quality of regression relationships 4.5 Comments on Neostratification 4.6 Relationship between classification accuracy and improvement in precision . 4.7 Effect of different digital classification rules Numéro de notice : 16739 Affiliation des auteurs : non IGN Nature : Rapport d'étude technique Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=41311

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Sampling frames of square segments / F.J. Gallego (1995)

Public Titre : Sampling frames of square segments Type de document : Rapport Auteurs : F.J. Gallego, Auteur Editeur : Luxembourg : Office des Publications de l'Union Européenne Année de publication : 1995 Collection : Un système d'information agronomique pour la Communauté Européenne Importance : 68 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-92-827-5106-0 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Agriculture [Termes IGN] Communauté Européenne [Termes IGN] image à basse résolution [Termes IGN] image à haute résolution [Termes IGN] inventaire [Termes IGN] parcelle agricole Résumé : (Auteur) This report describes the area frame sampling methodology developed or assessed in the frame of the "Action 1" (Regional Inventories) of the MARS Project, launched by the European Community in 1988. This Project was initiated by the Directorate General for Agriculture in co-operation with Eurostat. The Institute for Remote Sensing Applications (IRSA) of the Joint Research Centre (JRC) of the EC is responsible for implementing the programme in close co-operation with national laboratories and organisations. Note de contenu : 1. Some approaches to agricultural statistics. 1.1 Village Statistics 1.2 Census of Farms 1.3 Sampling Surveys 2. Sampling frames in agriculture 2.1 Finite and Infinite Sampling Frames 2.2 Sampling Farms from a List Frame 2.3 Area Frame Sampling with Direct Observation 2.4 Sampling Farms in an Area Frame 2.5 Sampling Errors and Non-Sampling Errors 3. Sampling frames of cadastral segments 3.1 Defining Cadastral Segments 4. Area frames of segments without physical limits 4.1 Why Use Segments without Physical Boundaries ? 4.2 Area Frame Based on Square Segments 4.3 Segment Location and Shape Errors in an Area Sampling Frame on a square grid 5. Sampling in an area frame based on square segments 5.1 Simple random sampling 5.2 Sampling with a distance threshold 5.3 Sampling Square Segments by Square Blocks 6. Practical choices to set up an area frame of square segments 6.1 Some Restrictions of Ground Survey Material 6.2 Segment size 7. Stratification of an area frame 7.1 Classical Stratification Tools for Area Frames 7.2 Examples of Stratification in Different Countries 7.3 Other Stratification Tools 7.4 Systematic Sampling with a Distance Threshold in a Stratified Area Sampling on a Frame Square Grid 7.5 Estimators for Stratified Sampling and their Precision 7.6 Efficiency of the Stratification 7.7 Dealing with Segments that Straddle Boundaries 8. Expected precision of area estimates from a ground survey with square segments 9. Planning a ground survey based on square segment sampling 9.1 Photographs and Maps 9.2 Crop Calendar and Dates for the Ground Survey 9.3 Surveyors 9.4 Stratification 9.5 Digitising Equipment and Software for Calculation of Estimates 9.6 Approximate Time Schedule 10. Sampling points clustered by square segments 10.1 Cost Efficiency of Point and Segment Surveys. 11. Segment survey and farm survey 12. Some conclusions on area frames of segments without physical boundaries Numéro de notice : 16704 Affiliation des auteurs : non IGN Nature : Rapport d'étude technique Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=41294

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