Earth Observation for Monitoring and Modeling Land Use

1st Edition - November 22, 2024
Imprint: Elsevier
Editors: Daniela Fernanda Da Silva Fuzzo, Dimitris Triantakonstantis, João Alberto Fischer Filho, Prashant K. Srivastava, Salim Lamine
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 5 1 9 3 - 7
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 5 1 9 4 - 4

Earth Observation for Monitoring and Modeling Land Use presents a practical guide and theoretical overview of the latest techniques and Earth observation technologies applie… Read more

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Earth Observation for Monitoring and Modeling Land Use presents a practical guide and theoretical overview of the latest techniques and Earth observation technologies applied to land use and land cover change through qualitative assessment of Earth observation technologies. The book's chapters include detailed case studies, Earth observation datasets, and detailed applications of the technologies covered that are presented in a way that each chapter is a self-contained guide on a specific application of Earth observation technologies to land use problems, ensuring all technical and background information is provided on each subject without the need for cross-referencing or searching for other sources.

The book spatializes the understanding of monitoring land cover and use, and quantifies the challenges faced, allowing analysis of the dynamics of the territory in terms of occupation processes, land use, and its transformations. It focuses on practical applications of using remote sensing and modeling that support new research in relation to monitoring of land use and spectral modelling, elucidating the importance of advanced methodologies in the coverage and use mappings of the Earth.

Title of Book
Cover image
Title page
Table of Contents
Copyright
Contributors
Chapter 1. Remote observation for predicting soil moisture in integrated crop/livestock areas
1 Introduction
2 Model formulation
3 Materials and methods
3.1 Area of analysis
4 Determining moisture in the field
5 Application of the simplified triangle method
6 Statistical analysis
7 Results and discussion
8 Conclusions
Chapter 2. Soil chemical properties estimation using hyperspectral remote sensing: A review
1 Introduction
2 Soil chemical properties
2.1 Hyperspectral remote sensing for soil chemical properties
2.1.1 HRS applications for SOC monitoring
2.1.2 HRS applications for nutrients (N, P, K) detection
2.1.3 HRS applications for soil salinity detection
2.1.4 HRS applications for soil pH analysis
2.1.5 HRS applications for soil cation exchange capacity monitoring
3 Challenges and opportunity
Chapter 3. Monitoring and modeling urban growth dynamics
1 Introduction
2 Material and methods
2.1 Study area
2.2 Data used
2.3 LULC classification
2.4 Shannon's entropy
2.5 Land use dynamics
2.6 The integrated dynamic index
2.7 Accuracy assessment
3 Results and discussion
3.1 LULC of PMC
3.1.1 LULC classification PCMC
3.1.2 LULC classification of PMC
3.1.3 LULC classification of PCMC
3.1.4 Urban growth
3.1.5 Measuring the urban growth of PMC, and PCMC
3.1.6 Shannon's entropy of PCMC
3.1.7 LULC dynamics of PMC and PCMC
4 Conclusion
Chapter 4. Drones in high resolution land use assessment using artificial intelligence
1 Introduction
2 Study area
3 Data used
4 Methodology
4.1 Random forest (RF) algorithm
4.2 Artificial neural network (ANN)
4.3 Support vector machine (SVM)
5 Results and discussions
6 Conclusions
Chapter 5. Mapping the soil organic carbon sequestration potential of Greek agricultural soils
1 Introduction
2 Methods
2.1 Study area
2.2 Datasets
2.2.1 Climatic data
2.2.2 Soil datasets
2.2.3 Land use and land use change data
2.2.4 Land management, C inputs and scenarios
2.3 RothC implementation
3 Results
3.1 Summary and spatial prediction of SOC sequestration potential in Greece
3.2 Absolute sequestration rate
3.3 Relative sequestration rate
3.4 Uncertainties for absolute and relative sequestration rates
4 Discussion and conclusions
Chapter 6. Mapping the Greek salt affected soils with the use of machine learning and remote sensing data
1 Introduction
2 Input data
2.1 Drivers of salt-affected soils
2.2 Soil data
3 Methodology
4 Results
4.1 Map of salt-affected soils in Greece
4.2 Proportions of salt-affected areas
4.3 Accuracy and uncertainty assessment
5 Discussion
6 Conclusions
Chapter 7. A view of biological invasions at the landscape scale: a case study of two Australian Acacia species in Portugal
1 Introduction
2 Regional settings
2.1 Study area and places investigated
2.2 Species characters description
3 Application of the methodology
3.1 Biological invasions at the landscape scale - theoretical approach
3.2 Using land-use cover changes to analyze plant invasion patterns
3.2.1 Land cover changes in the past and present—Historical routes of plant invasion spread
3.2.2 Habitat characteristics on the species community (distribution, density)—Species capacity to become invasive (implications to invasiveness)
3.2.3 Habitat characteristics on the physical attributes (soil, hydrography, topography)—Habitat vulnerability to invasion (implications to invasibility)
3.2.4 Impacts of land-use cover changes on plant invasions
4 Results and discussions
4.1 Maps showing the possible routes of spread, coming from historical analyses
4.2 Maps relating species distribution/abundance with environmental characteristics
4.3 Capacity to invasion: environmental characteristics (physical+species community) and invasive species attributes
4.4 Quantification of invasion impacts (by different means according to the species and related to environmental characteristics)
5 Conclusions
Chapter 8. Land use and socioeconomic interventions in the production of urban climate: Day and night thermal effects in a continental tropical city
1 Introduction
2 Area
3 Methodological procedures
4 Results and discussions
4.1 Atmospheric stability
4.2 Socioeconomic characteristics
4.3 The content perspective
5 Conclusion
Chapter 9. Landscape geoecology in the feasibility of creating linear parks in urban microbains
1 Introduction
2 The Municipal Plan of Ourinhos/SP/BR and the proposal of linear parks
3 Methods and techniques
3.1 Study area
3.2 Methodological path
4 Results and discussions
4.1 Map of use and land cover of the Furnas stream
4.2 Characterization map of the open spaces of Furnas stream
4.3 Map of measurement and characterization of the geoecological states of the stream
4.4 The linear park proposition in Furnas stream
4.5 Original area of the Furnas linear park and urban biological corridors proposal
5 Final considerations
Chapter 10. Hyperspectral remote sensing: Potential prospects in water quality monitoring and assessment
1 Introduction
1.1 Medical imaging
1.2 Agriculture
1.3 Food quality
1.4 Environmental monitoring
1.5 Forensic examinations
1.6 Defense applications
2 Hyperspectral data
3 Hyperspectral sensors
4 Water quality parameters
4.1 Suspended sediment concentration
4.2 Chlorophyll concentration
4.3 Algae
4.4 Temperature
5 Water quality using hyperspectral remote sensing
5.1 Identification of water quality parameters
5.2 Mapping of water quality parameters
5.3 Monitoring water quality changes
6 Hyperspectral imaging and water quality monitoring
7 Advantages of using remote sensing in water quality assessment
8 Challenges in water quality measurements
9 Conclusion
Chapter 11. Appraisal of spatial interpolation techniques in predicting soil organic carbon using earth observation datasets
1 Introduction
2 Spatial interpolation techniques
2.1 Inverse distance weighting (IDW)
2.2 Spline
2.3 Ordinary kriging
2.4 Kriging with external drift (KED)
2.5 Semi-variogram
3 Spatial interpolation technique applications for SOC monitoring
3.1 Case studies
4 Challenges and opportunity
5 Conclusions
Chapter 12. Conservation status of water and permanent preservation areas in the Cabaçal river basin, Mato Grosso state, Brazil
1 Introduction
2 Material and methods
2.1 Area under study
2.2 Methodologic procedures
3 Results and discussion
4 Conclusions
Chapter 13. Technological advances applied to spectral monitoring in agriculture
1 Introduction
2 Spectral behavior in vegetation
3 Remote sensing applications in agriculture
3.1 Orbital remote sensing
3.2 Aerial remote sensing
3.3 Proximal remote sensing
4 Use of vegetation index in agriculture
5 Integration between remote sensing and artificial intelligence
6 Final considerations
Chapter 14. Modeling and predicting future land use: Application of Dyna-CLUE and Cellular automata - Markov chain analysis (CA-Markov) models in a brazilian watershed
1 Introduction
2 Material and methods
2.1 Study area
2.2 Methodology
2.2.1 Markov chain transition estimator and cellular automata analysis model (CA-Markov)
2.2.2 Dyna-CLUE model
3 Results and discussion
3.1 Driving factors of LULC
3.2 Parameterization of CA-Markov model
3.3 Parameterization of Dyna-CLUE model
3.4 Sensitivity analysis of CA-Markov and Dyna-CLUE models
3.5 Scenarios simulation for 2030
4 Conclusions
Chapter 15. Interpretation of land use and land cover changes at different classification levels: The Paranapanema River Basin–Brazil case
1 Introduction
2 Study case
2.1 Paranapanema River Basin
2.2 Satellite imagery data
2.3 Land use and land cover classification
2.4 Data analysis
3 Results and discussion
3.1 Comparison between different classification levels provided by MapBiomas
3.2 Land use and cover change at HPU scale
3.3 Potentials and limitations of MapBiomas for LULC analysis at HPU scale
4 Conclusions
Index

Daniela Fernanda Da Silva Fuzzo

Daniela Fernanda da Silva Fuzzo graduated in Geography from Universidade Estadual Paulista Júlio de Mesquita Filho (2008) and obtained her master's degree in Agronomy (Tropical and subtropical agriculture - Management of agri-environmental resources) from Instituto Agronômico de Campinas (2011). She holds a PhD in Agricultural Engineering from the State University of Campinas (2015). She is currently a PhD Professor at the University of the State of Minas Gerais, with experience in orbital triangle methods, agrometeorological modeling, agricultural monitoring, crop estimation, land use analysis, precipitation, evapotranspiration, remote sensing, geoprocessing, cartography and geographic information systems (including ArcGis, QGis, Envi, and IDL) and is deputy coordinator of the research group CEDIAP-GEO (CNPq).

Affiliations and expertise

University of the State of Minas Gerais, Brazil

Dimitris Triantakonstantis

Dimitris Triantakonstantis is a researcher in the soil science department of the Institute of Soil and Water Resources, Hellenic Agricultural Organization DIMITRA, Greece. He is an agronomist-soil scientist and Geographical Information Systems/Remote Sensing expert, having completed postgraduate studies in Environmental Management (Agricultural University of Athens) and GIS with Remote Sensing (University of Greenwich, UK). In 2006, he received his PhD in the field of geographic information systems, spatial statistics, and land use change modelling from the Agricultural University of Athens, Greece. He has undertaken postdoctoral research at Newcastle University (UK); ESF State University of New York (USA); the Foundation for Research and Technology Hellas, University of Thessaly (Greece) and the National Hellenic Research Foundation (Greece). His research interests lie in GIS and remote sensing of soil science, natural resource management and climate change mitigation and adaptation.

Affiliations and expertise

Researcher, Soil Science Department, Institute of Soil and Water Resources, Hellenic Agricultural Organization DIMITRA, Greece

João Alberto Fischer Filho

João Alberto Fischer Filho graduated in Agronomic Engineering from the Faculty of Engineering of Ilha Solteira (2013), Master’s (2015) and Doctorate (2018) in Agronomy (Soil Science) from Universidade Estadual Paulista (UNESP). He is currently a professor at the State University of Minas Gerais, Brazil and at the Municipal Institute of Higher Education of Bebedouro Victório Cardassi, Brazil in the area of Agricultural Engineering. He is also an ad-hoc rapporteur for scientific journals, conference papers and scholarship-related processes, a member of the Brazilian Association of Agricultural Engineering (SBEA) and mainly works on the following areas: irrigated agriculture, irrigation management, and hydraulics for agricultural systems.

Affiliations and expertise

State University of Minas Gerais, Brazil

Prashant K. Srivastava

Prashant K. Srivastava is working at IESD, Banaras Hindu University, as a faculty and was affiliated with Hydrological Sciences, NASA Goddard Space Flight Center, as research scientist on SMAP satellite soil moisture retrieval algorithm development, instrumentation, and simulation for various applications. He received his PhD degree from the Department of Civil Engineering, University of Bristol, Bristol, United Kingdom. Prashant was the recipient of several awards such as NASA Fellowship, USA; University of Maryland Fellowship, USA; Commonwealth Fellowship, UK; Early Career Research Award (ECRA, DST, India), CSIR, as well as UGCJRF-NET (2005, 2006). He is leading a number of projects funded from reputed agencies in India as well as world. He was also a collaborator with NASA JPL on SMAP soil moisture calibration and validation as well as Scatsat-1, NISAR, AVIRIS-NG missions of India. Prashant made more than 200+ publications in peer-reviewed journals and published 14 books with reputed publishing house such as Springer, Taylor and Francis, AGU-Wiley, and Elsevier, and several book chapters with good citation index. He presented his work in several conferences and workshops and is acting as a convener for the last few years in EGU, Hydroinformatics (HIC), and other conferences. He is also acting as Regional Editor Asia-Geocarto International (T & F), Associate Editor-Journal of Hydrology (Elsevier), GIScience and Remote Sensing (T & F), Remote Sensing Applications: Society and Environment (Elsevier), Sustainable Environment (T & F), Water Resources Management (Springer), Frontiers Remote Sensing, Associate Editor- Remote Sensing-MDPI, Associate Editor- Environment, Development and Sustainability (Springer), Environmental Processes (Springer), Bull of Env and Sci Res.

Affiliations and expertise

Remote Sensing Laboratory, IESD, Banaras Hindu University, Varanasi, India

Salim Lamine

Salim Lamine is a distinguished scientist, serving as a professor and international consultant specializing in remote sensing and precision agriculture. He earned his PhD through a collaborative program between Aberystwyth University in the United Kingdom and the University of Sciences and Technology Houari Boumediene in Algeria. His academic pursuits further extended to the University of Nottingham in the UK, where he delved into GNSS applications, and he gained valuable research experience as an assistant researcher at the University of Aberystwyth. In 2017 Dr. Lamine was honored with the prestigious International Prize for the Environment, “ECOWORLD,” by the Russian Academy of Natural Sciences. He holds master’s degrees from both the Mediterranean Agronomic Institute of Bari in Italy and the Mediterranean Agronomic Institute of Chania in Greece. Currently, he is serving as a member of the editorial board for the prominent Taylor & Francis journal, Geocarto International. Additionally, he extends his expertise as a valued member of the Advisory Panel for several MDPI Journals. Dr. Lamine’s research portfolio encompasses a wide range of multidisciplinary areas, including remote sensing, precision agriculture, hyperspectral imaging, drone-based data analysis, crop yield prediction, field spectroradiometry, water and soil management, agri-biosystems engineering, gis and space mapping, machine learning and SVAT models. Dr. Lamine has made substantial contributions to the academic realm, evidenced by over 30 peer-reviewed publications in esteemed journals and participation in more than 150 international conferences. His scholarly influence also extends to the authorship of several book chapters. He authored a book entitled REMOTE SENSING: Multispectral & Hyperspectral Applications published in 2020.

Affiliations and expertise

Professor in Remote Sensing (RS) and Precision Agriculture (PA), Higher School of Saharan Agriculture Adrar, Adrar, Algeria

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Earth Observation for Monitoring and Modeling Land Use

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Daniela Fernanda Da Silva Fuzzo

Dimitris Triantakonstantis

João Alberto Fischer Filho

Prashant K. Srivastava

Salim Lamine

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