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Advances in remote sensing for forest monitoring / / Paul Arellano and Prem C. Pandey
| Advances in remote sensing for forest monitoring / / Paul Arellano and Prem C. Pandey |
| Autore | Arellano Paul <1967-> |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (400 pages) |
| Disciplina | 634.9 |
| Soggetto topico |
Forests and forestry - Remote sensing
Forest monitoring |
| ISBN |
1-119-78815-3
1-119-78813-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- List of Contributors -- Foreword -- Preface -- List of Abbreviations -- Editors -- Section I General Introduction to Forest Monitoring -- Chapter 1 Introduction to Forest Monitoring Using Advanced Remote Sensing Technology - An Editorial Message -- 1.1 Introduction -- 1.2 Forest Monitoring: Importance and Trends -- 1.3 Advances in Remote Sensing Technology for Forest Monitoring -- 1.4 Summary -- References -- Chapter 2 Geospatial Perspectives of Sustainable Forest Management to Enhance Ecosystem Services and Livelihood Security -- 2.1 Introduction and Background -- 2.2 Major Ecological Disturbances of Forests -- 2.2.1 Livelihood Dependencies -- 2.3 Forest Fires -- 2.4 Invasive Plant Species (IPS) -- 2.5 Climate Change -- 2.6 Forest Ecosystem Services (FESs) -- 2.7 Sustainable Uses of Forests and Their Contributions to Livelihood Security -- 2.8 Landscape Based Approach (LbA) and Ecosystem-Based Approach (EbA) of Sustainable Forests Management (SFM) -- 2.9 Conclusions -- References -- Section II Forest Parameters - Biochemical and Biophysical Parameters -- Chapter 3 Distinguishing Carotene and Xanthophyll Contents in the Leaves of Riparian Forest Species by Applying Machine Learning Algorithms to Field Reflectance Data -- 3.1 Introduction -- 3.1.1 Chapter Overview -- 3.1.2 Threats to Riparian Forests -- 3.1.3 Remote Sensing of Riparian Forests -- 3.1.4 Implication of Carotenoids in Plant Stress -- 3.1.5 Advances in Carotenoid Retrieval Using Reflectance Spectroscopy -- 3.1.6 Applying Machine Learning to Reflectance Spectroscopy -- 3.2 Study Area -- 3.3 Data -- 3.3.1 Leaf Sampling and Analysis -- 3.3.2 Reflectance Measurements -- 3.4 Methodology -- 3.4.1 Preprocessing of Reflectance Data -- 3.4.2 ML Algorithms -- 3.4.3 Carotenoid Prediction -- 3.5 Results -- 3.5.1 Leaf Carotenoid Contents.
3.5.2 Predictions of Carotenoid Contents Using ML Algorithms -- 3.6 Discussion -- 3.6.1 Sources of Variability in the Carotenoid Pool among Species -- 3.6.2 Toward a Broad-Scale Monitoring of Carotenoids? -- 3.6.3 Sensitivity Analysis -- 3.7 Conclusion -- Acknowledgments -- Funding -- References -- Supporting Information -- Chapter 4 Modeling of Abiotic Stress of Conifers with Remote Sensing Data -- 4.1 Introduction -- 4.2 Natural Factors -- 4.2.1 Soils -- 4.3 Anthropogenic Factors -- 4.3.1 Atmospheric Pollution -- 4.3.2 Soil and Groundwater Pollution -- 4.4 Thresholds and Critical Loads -- 4.4.1 Satellite Multi-Band Remote Methods for Detecting Abiotic Stress -- 4.4.2 Satellite Infrared Remote Sensing Methods for Detecting Abiotic Stress -- 4.4.3 Hyperspectral Satellite Remote Sensing Methods for Detecting Abiotic Stress -- 4.4.4 Fluorescent Satellite Remote Sensing Methods for Detecting Vegetation Stress -- 4.4.5 Modeling in Geoscience -- 4.4.6 Models of Geosystems and Abiotic Stress in Ecology and Radioecology -- 4.5 Conclusions -- References -- Chapter 5 Retrieval of Mangrove Forest Properties Using Synthetic Aperture Radar -- 5.1 Introduction -- 5.2 Microwave Remote Sensing -- 5.2.1 Polarization -- 5.2.2 Interaction Mechanism of SAR -- 5.2.3 SAR Based Mangroves Studies -- 5.2.4 SAR Image of the Mangroves -- 5.2.5 Mapping the Mangrove Area -- 5.2.6 Identification of Mangrove Degraded Area Using SAR -- 5.2.7 Mangrove Forest Structure Parameters and SAR -- 5.2.8 Mangrove Biomass and SAR -- 5.3 Conclusions -- References -- Chapter 6 Photosynthetic Variables Estimation in a Mangrove Forest -- 6.1 Introduction -- 6.1.1 Mangroves -- 6.1.2 Photosynthesis/Carbon Sequestration -- 6.1.3 Leaf Area Index -- 6.1.4 Chlorophyll Concentration -- 6.1.5 Solar Induced Fluorescence -- 6.1.6 Gross Primary Productivity (GPP) -- 6.1.7 Vegetation Indices (VIs). 6.2 Materials and Methodology -- 6.2.1 Dataset -- 6.2.2 Methods -- 6.3 Results -- 6.3.1 Seasonal Variation of LAI, SIF, and GPP -- 6.3.2 Landsat-8 Predicted LAI -- 6.3.3 Landsat-8 Predicted Canopy Chlorophyll Content (CCC) -- 6.4 Discussion -- 6.4.1 Seasonal Behavior -- 6.4.2 Random Forest-based LAI and LCC estimation -- 6.5 Conclusions -- References -- Chapter 7 Quantifying Carbon Stock Variability of Species Within a Reforested Urban Landscape Using Texture Measures Derived from Remotely Sensed Imagery -- 7.1 Introduction -- 7.2 Materials and Methods -- 7.2.1 The Study Site -- 7.2.2 Field Survey and Data Collection -- 7.2.3 Allometric Modeling of Above Ground Biomass and Carbon Stock -- 7.2.4 Image Acquisition and Pre-processing -- 7.2.5 Sentinel-2 MSI Texture Metrics Derivation -- 7.2.6 Statistical Analysis -- 7.2.7 Model Accuracy Assessment -- 7.3 Results -- 7.3.1 Carbon Stock of Reforested Tree Species -- 7.3.2 Prediction Performance of Carbon Stock Using Remotely Sensed Data and the Random Forest Model -- 7.3.3 Carbon Stock Estimates and Variability Between Reforested Tree Species -- 7.4 Discussion -- 7.4.1 Carbon Stock Variability Between Reforested Tree Species -- 7.5 Conclusion -- Acknowledgments -- References -- Chapter 8 Mapping Oil Palm Plantations in the Fringe of Sebangau National Park, Central Kalimantan, Indonesia -- 8.1 Introduction -- 8.2 Methodology -- 8.2.1 Test Site and Datasets -- 8.2.2 Data Processing and Analysis -- 8.3 Results and Discussion -- 8.3.1 Identifying Oil Palm -- 8.3.2 Classification Accuracies -- 8.4 Conclusion -- Acknowledgments -- References -- Section III Remote Sensing Technology for Forest Fire Monitoring -- Chapter 9 Forest Fire Susceptibility Mapping by Integrating Remote Sensing and Machine Learning Algorithms -- 9.1 Introduction -- 9.2 Study Area -- 9.3 Materials and Methods -- 9.3.1 Materials. 9.3.2 Forest Fire Inventory -- 9.3.3 Ignition Factors for Forest Fire Modeling -- 9.3.4 Method for the Multicollinearity Analysis -- 9.3.5 Methods for Forest Fire Susceptibility Modeling -- 9.3.6 Validation of the Models -- 9.4 Results -- 9.4.1 Multicollinearity Analysis -- 9.4.2 Forest Fire Susceptibility Modeling -- 9.4.3 Validation Analysis of the Models -- 9.5 Discussion -- 9.6 Conclusion -- Acknowledgements -- References -- Chapter 10 Leveraging Google Earth Engine (GEE) and Landsat Images to Assess Bushfire Severity and Postfire Short-Term Vegetation Recovery: A Case Study of Victoria, Australia -- 10.1 Introduction -- 10.2 Materials and Methods -- 10.2.1 Study Area -- 10.2.2 Conceptual Workflow and Vegetation Recovery Predictors -- 10.2.3 Dataset -- 10.2.4 Processing in GEE -- 10.2.5 Fire Severity Characterization -- 10.2.6 Post-Fire Recovery Indices Calculation -- 10.2.7 Bushfire Severity Accuracy Assessment -- 10.3 Results -- 10.3.1 Bushfire Severity Assessment -- 10.3.2 Bushfire Severity Accuracy Assessment Results -- 10.3.3 Post-Fire Recovery Assessment -- 10.3.4 Correlation Among Climatic, Topographic, and Post-fire Recovery Variables -- 10.3.5 Relative Variable Importance in Post-Fire Recovery -- 10.4 Discussion -- 10.4.1 Bushfire Severity Assessment -- 10.4.2 Post-Fire Recovery Assessment -- 10.4.3 Climatic and Topographic Influence of Bushfire Recovery Assessment -- 10.4.4 Limitations of this Study -- 10.5 Conclusions -- Acknowledgements -- References -- Section IV Advancement in RS-Drones and Multi-Sensors Multi-Source for Forest Monitoring -- Chapter 11 Recent Advancement and Role of Drones in Forest Monitoring: Research and Practices -- 11.1 Introduction -- 11.2 Field Sampling Methods in Forest Application: Traditional to Present -- 11.3 Biophysical Parameters Assessment Using Remote Sensing -- 11.3.1 Above Ground Biomass (AGB). 11.3.2 Tree Height and Diameter at Breast Height (DBH) -- 11.3.3 Leaf Area Index (LAI) -- 11.4 Biochemical Parameter Assessment Using Remote Sensing -- 11.4.1 Canopy Chlorophyll Content (CCC) -- 11.4.2 Canopy Water Content (CWC) -- 11.5 UAV-Based Remote Sensing -- 11.6 Other Important Forest Research Applications and Practices -- 11.7 Conclusions -- References -- Chapter 12 Applications of Multi-Source and Multi-Sensor Data Fusion of Remote Sensing for Forest Species Mapping -- 12.1 Introduction -- 12.2 Forest Mapping Process -- 12.2.1 Image Acquisition -- 12.2.2 Image Pre-processing -- 12.2.3 Image Enhancement -- 12.2.4 Image Classification -- 12.2.5 Accuracy Assessments -- 12.2.6 Vegetation Indices -- 12.3 Data Fusion -- 12.3.1 Fusion of Satellite and UAV/Drone -- 12.4 Discussion -- 12.5 Conclusion and Future Trends -- Acknowledgments -- References -- Section V Opportunities, Challenges, and Future Aspects in Forest Monitoring -- Chapter 13 Challenges and Monitoring Methods of Forest Management Through Geospatial Application: A Review -- 13.1 Introduction -- 13.2 Importance of Forest Cover -- 13.2.1 Biogeochemical Cycle -- 13.2.2 Climate Change -- 13.2.3 Soil and Nutrients -- 13.2.4 Soil Conservation -- 13.2.5 Microbes -- 13.3 Challenges in the Sustainability of Forest Management -- 13.3.1 Challenges Due to Anthropogenic Activities -- 13.3.2 Application of Geospatial Technology in Monitoring of the Forests -- 13.3.3 Types of Forest Data -- 13.4 Summary -- References -- Chapter 14 Challenges and Future Possibilities Toward Himalayan Forest Monitoring -- 14.1 Introduction -- 14.2 Component of Forest Monitoring -- 14.2.1 Satellite Monitoring -- 14.2.2 Ground Station Monitoring -- 14.2.3 Ground Survey and Inventory -- 14.3 Challenges in Satellite Monitoring -- 14.3.1 Forest Fire Monitoring -- 14.3.2 Challenges in Land-Use Change Monitoring. 14.3.3 Challenges in Species Distribution Monitoring. |
| Record Nr. | UNINA-9910677971903321 |
Arellano Paul <1967->
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| Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Complex sample survey estimation in static state-space [[electronic resource] /] / Raymond L. Czaplewski
| Complex sample survey estimation in static state-space [[electronic resource] /] / Raymond L. Czaplewski |
| Autore | Czaplewski Raymond L |
| Pubbl/distr/stampa | Ft. Collins, CO : , : U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, , 2010 |
| Descrizione fisica | 1 online resource (124 pages) : illustrations |
| Collana | General technical report RMRS |
| Soggetto topico |
Forests and forestry - Sampling
Forest surveys - Methodology Forests and forestry - Measurement - Mathematical models Forests and forestry - Remote sensing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910700332503321 |
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Czaplewski Raymond L
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| Ft. Collins, CO : , : U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Concepts and applications of remote sensing in forestry / / Mohd Nazip Suratman, editor
| Concepts and applications of remote sensing in forestry / / Mohd Nazip Suratman, editor |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (454 pages) |
| Disciplina | 634.9 |
| Soggetto topico |
Forests and forestry - Remote sensing
Forests and forestry - Research |
| ISBN |
9789811942006
9789811941993 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Remote Sensing for Forest Inventory and Resources Assessment -- 2. Multiple Sensors and Platforms for Biophysical and Biochemical Characterizations of Various Ecosystem Types of Tropical Forests in Malaysia: Advance, Limitation and Opportunity -- 3. A Review on the Use of LiDAR Remote Sensing for Forest Landscape Restoration -- 4. Assessment and Modeling of Forest Biomass and Carbon Stock and Sequestration using Various Remote Sensing Sensor Systems -- 5. Spatial Modeling of Transport and Resources Accessibility for Protecting Forest Ecosystems Against Forest Fires -- 6. Assessment of Forest Aboveground Biomass Estimation from Superview-1 Satellite Image using Machine Learning Approaches -- 7. Floristic Distribution Modelling for Resource Partitioning of Four Native Tree Species in Azad Jammu and Kashmir (AJK), Pakistan using Maxent -- 8. Application of Remote Sensing Vegetation Indices for Forest Cover Assessments -- 9. Rainforest Assessment in Brunei Darussalam through Application of Remote Sensing -- 10. Rubber Trees and Biomass Estimation Using Remote Sensing Technology -- 11. The Use of Landsat TM Imagery for the Application of Rubber Tree Area and Stand Volume Predictive Models in Rubber Plantations in Selangor, Malaysia -- 12. Using Historical Disturbance Identified with LandTrendr in Google Earth Engine for Land Cover Mapping of Oil Palm Landscapes -- 13. Geospatial Technology - Unlocking the Management and Monitoring in Malaysian Mangrove Forests -- 14. Effect of Tidal Regime, Relative Sea Level and Wind Intensity on Changes of Mangrove Area using Remote Sensing Approach -- 15. Spatio-temporal Distribution of Mangrove at Kuala Sepetang Forest Reserve, Malaysia using Remotely-sensed Data -- 16. Determination of The Effect of Urban Forests and Other Green Areas on Surface Temperature in Antalya -- 17. Conceptualising the Citizen-Driven Urban Forest Framework to Improve Local Climate Condition: Geospatial Data Fusion and Numerical Simulation -- 18. State-of-the-Art on Airborne LiDAR Applications in the Field of Forest Engineering -- 19. Restoration of Damaged Forest and Roles of Remote Sensing -- 20. Recent Advances in UAV-based Structure-from-motion Photogrammetry for Aboveground Biomass and Carbon Storage Estimations in Forestry -- 21. Hyperspectral Identification of Selected Dipterocarp Montane at the Species Level -- 22. Tree Biophysical Parameters Retrieval from Multi-source Remote Sensing Data Fusion. |
| Record Nr. | UNINA-9910640383903321 |
| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Geo-Spatial Analysis of Forest Landscape for Wildlife Management / / Mrinmay Mandal and Nilanjana Das Chatterjee
| Geo-Spatial Analysis of Forest Landscape for Wildlife Management / / Mrinmay Mandal and Nilanjana Das Chatterjee |
| Autore | Mandal Mrinmay |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (191 pages) |
| Disciplina | 910.5 |
| Collana | GIScience and Geo-Environmental Modelling Series |
| Soggetto topico |
Forests and forestry - Remote sensing
Landscape ecology |
| ISBN | 3-031-33606-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Landscape Background Study Area and Wildlife History -- 2. Conceptual Framework of Landscape Spatial Character and Ecological Interaction -- 3. Quantification of Forest Landscape Pattern for Habitat Quality Assessment -- 4. Quality Assessments Through Analysis of Forest Habitat Configuration and Composition -- 5. Assessment of Habitat Structural Connectivity and Corridors from Ecological Point of View -- 6. Species Specific Habitat Quality Assessment– Asian Elephant (Elephas Maximus) -- 7. Effective Landscape Management Methods to Improve Ecological Quality of Forest Habitat: Case Studies in the Fragmented Habitats -- 8. Landscape Management Methods to Enhance Habitat Quality for Wild Life Conservation in General And Elephants in Specific. |
| Record Nr. | UNINA-9910760290803321 |
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Mandal Mrinmay
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| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Global forest monitoring from earth observation / / edited by Frederic Achard, Matthew C. Hansen
| Global forest monitoring from earth observation / / edited by Frederic Achard, Matthew C. Hansen |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press LLC, , [2013] |
| Descrizione fisica | 1 online resource (xiv, 316 p. ) : ill. (some color), maps |
| Disciplina | 333.75 |
| Collana | Earth observation of global changes |
| Soggetto topico |
Forests and forestry - Remote sensing
Forest monitoring |
| ISBN |
1-000-21865-1
0-429-08646-6 1-4665-5202-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Why forest monitoring matters for people and the planet / Ruth DeFries -- 2. Role of forests and impact of deforestation in the global carbon cycle / Richard A. Houghton -- 3. Use of earth observation technology to monitor forests across the globe / Frederic Achard and Matthew C. Hansen -- 4. Global data availability from U.S. satellites : Landsat and MODIS / Thomas R. Loveland and Matthew C. Hansen -- 5. Sampling strategies for forest monitoring from global to national levels / Stephen V. Stehman -- 6. Use of coarse-resolution imagery to identify hot spots of forest loss at the global scale / Matthew C. Hansen, Peter Potapov, and Svetlana Turubanova -- 7. Use of a systematic statistical sample with moderate-resolution imagery to assess forest cover changes at tropical to global scale / Frederic Achard. [et al.] -- 8. Monitoring forest loss and degradation at national to global scales using Landsat data / Peter Potapov. [et al.] -- 9. The Brazilian Amazon monitoring program : PRODES and DETER projects / Yosio Edemir Shimabukuro. [et al.] -- 10. Monitoring of forest degradation : a review of methods in the Amazon Basin / Carlos Souza, Jr. -- 11. Use of wall-to-wall moderate- and high-resolution satellite imagery to monitor forest cover across Europe / Jesus San-Miguel-Ayanz. [et al.] -- 12. Monitoring U.S. forest dynamics with Landsat / Jeffrey G. Masek and Sean P. Healey -- 13. Long-term monitoring of Australian land cover change using Landsat data : development, implementation, and operation / Peter Caccetta. [et al.] -- 14. Assessment of burned forest areas over the Russian Federation from MODIS and Landsat-TM/ETM+ imagery / Sergey Bartalev. [et al.] -- 15. Global forest monitoring with synthetic aperture radar (SAR) data / Richard Lucas. [et al.] -- 16. Future perspectives (way forward) / Alan Belward. [et al.]. |
| Record Nr. | UNINA-9910416126803321 |
| Boca Raton, FL : , : CRC Press LLC, , [2013] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Highlights of satellite-based forest change recognition and tracking using the Forwarn system / / Steven P. Norman [and four others]
| Highlights of satellite-based forest change recognition and tracking using the Forwarn system / / Steven P. Norman [and four others] |
| Autore | Norman Steven P. |
| Pubbl/distr/stampa | Asheville, NC : , : United States Department of Agriculture, Forest Service, Research & Development, Southern Research Station, , August 2013 |
| Descrizione fisica | 1 online resource (ii, 30 pages) : color illustrations, color maps |
| Collana | General technical report SRS |
| Soggetto topico |
Forests and forestry - Remote sensing
Forest monitoring |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910703911703321 |
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Norman Steven P.
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| Asheville, NC : , : United States Department of Agriculture, Forest Service, Research & Development, Southern Research Station, , August 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Landsat eyes help guard the world's forests / / by Jon Campbell
| Landsat eyes help guard the world's forests / / by Jon Campbell |
| Autore | Campbell Jon C. |
| Pubbl/distr/stampa | [Reston, Va.] : , : U.S. Department of the Interior, U.S. Geological Survey, , 2017 |
| Descrizione fisica | 1 online resource (2 unnumbered pages) : color illustrations |
| Collana | Fact sheet |
| Soggetto topico |
Forests and forestry - Remote sensing
Forest biodiversity - Monitoring Deforestation - Control Landsat satellites Forest protection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910713841803321 |
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Campbell Jon C.
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| [Reston, Va.] : , : U.S. Department of the Interior, U.S. Geological Survey, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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QGIS and applications in agriculture and forest / / edited by Nicolas Baghdadi, Clément Mallet, Mehrez Zribi
| QGIS and applications in agriculture and forest / / edited by Nicolas Baghdadi, Clément Mallet, Mehrez Zribi |
| Pubbl/distr/stampa | London, England ; ; Hoboken, New Jersey : , : iSTE : , : Wiley, , 2018 |
| Descrizione fisica | 1 online resource (371 pages) |
| Disciplina | 910.285 |
| Collana | Earth System - Environmental Sciences Series. QGIS in Remote Sensing |
| Soggetto topico |
Geographic information systems
Forests and forestry - Remote sensing |
| ISBN |
1-119-49094-4
1-119-45710-6 1-119-49089-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910270944703321 |
| London, England ; ; Hoboken, New Jersey : , : iSTE : , : Wiley, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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QGIS and applications in agriculture and forest / / edited by Nicolas Baghdadi, Clément Mallet, Mehrez Zribi
| QGIS and applications in agriculture and forest / / edited by Nicolas Baghdadi, Clément Mallet, Mehrez Zribi |
| Pubbl/distr/stampa | London, England ; ; Hoboken, New Jersey : , : iSTE : , : Wiley, , 2018 |
| Descrizione fisica | 1 online resource (371 pages) |
| Disciplina | 910.285 |
| Collana | Earth System - Environmental Sciences Series. QGIS in Remote Sensing |
| Soggetto topico |
Geographic information systems
Forests and forestry - Remote sensing |
| ISBN |
1-119-49094-4
1-119-45710-6 1-119-49089-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910820435803321 |
| London, England ; ; Hoboken, New Jersey : , : iSTE : , : Wiley, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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