Pub Date : 2019-06-27DOI: 10.5772/INTECHOPEN.86452
M. K. Mzuza, Weiguo Zhang, F. Kapute, Xiaodao Wei
Land use and land cover changes over a 26-year period for the middle Shire River catchment, Malawi, in southern Africa, were assessed using geographic information systems (GIS) and remote sensing techniques. The catchment area under study was divided into two sections, western and eastern sides of the Shire River. High rate of deforestation averaging 4.3% per annum was observed and more pronounced in the western side of the river. Rapid population growth and increase in gross domestic product (GDP) are identified as the major drivers of deforestation and forest degradation due to clearing of vast fields for agriculture, land expansion for urban settlement, and cutting down of trees for wood fuel energy. Deforestation in the middle Shire River catchment has resulted into increased soil loss through erosion causing huge accumulation of sediment at the Nkula B Hydroelectric Power Dam downstream and, consequently, causing serious problems with generation of hydroelectricity. Frequent droughts and floods in the area have drastically affected crop production forcing people into cutting down of trees for charcoal as a livelihood strategy. Combined techniques such as GIS, remote sensing, and socioeconomic factors used in this study could be applied in other places where similar challenges occur.
{"title":"The Impact of Land Use and Land Cover Changes on the Nkula Dam in the Middle Shire River Catchment, Malawi","authors":"M. K. Mzuza, Weiguo Zhang, F. Kapute, Xiaodao Wei","doi":"10.5772/INTECHOPEN.86452","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.86452","url":null,"abstract":"Land use and land cover changes over a 26-year period for the middle Shire River catchment, Malawi, in southern Africa, were assessed using geographic information systems (GIS) and remote sensing techniques. The catchment area under study was divided into two sections, western and eastern sides of the Shire River. High rate of deforestation averaging 4.3% per annum was observed and more pronounced in the western side of the river. Rapid population growth and increase in gross domestic product (GDP) are identified as the major drivers of deforestation and forest degradation due to clearing of vast fields for agriculture, land expansion for urban settlement, and cutting down of trees for wood fuel energy. Deforestation in the middle Shire River catchment has resulted into increased soil loss through erosion causing huge accumulation of sediment at the Nkula B Hydroelectric Power Dam downstream and, consequently, causing serious problems with generation of hydroelectricity. Frequent droughts and floods in the area have drastically affected crop production forcing people into cutting down of trees for charcoal as a livelihood strategy. Combined techniques such as GIS, remote sensing, and socioeconomic factors used in this study could be applied in other places where similar challenges occur.","PeriodicalId":11389,"journal":{"name":"Earth Observation and Geospatial Analyses [Working Title]","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83571622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-27DOI: 10.5772/INTECHOPEN.86596
C. Giardino, Kerttu-Liis Kõks, R. Bolpagni, G. Luciani, G. Candiani, M. Lehmann, H. J. Woerd, M. Bresciani
Lakes are inestimable renewable natural resources that are under significant pressure by human activities. Monitoring lakes regularly is necessary to understand their dynamics and the drivers of these dynamics to support effective management. Remote sensing by satellite sensors offers a significant opportunity to increase the spatiotemporal coverage of environmental monitoring programs for inland waters. Lake color is a water quality attribute that can be remotely sensed and is independent of the sensor specifications and water type. In this study we used the Multispectral Imager (MSI) on two Sentinel-2 satellites to determine the color of water of 170 Italian lakes during two periods in 2017. Overall, most of the lakes appeared blue in spring and green-yellow in late summer, and in particular, we confirm a blue-water status of the largest lakes in the subalpine ecoregion. The color and its seasonality are consistent with characteristics determined by geomorphology and primary drivers of water quality. This suggests that information about the color of the lakes can contribute to synoptic assessments of the trophic status of lakes. Further ongoing research efforts are focused to extend the mapping over multiple years.
{"title":"The Color of Water from Space: A Case Study for Italian Lakes from Sentinel-2","authors":"C. Giardino, Kerttu-Liis Kõks, R. Bolpagni, G. Luciani, G. Candiani, M. Lehmann, H. J. Woerd, M. Bresciani","doi":"10.5772/INTECHOPEN.86596","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.86596","url":null,"abstract":"Lakes are inestimable renewable natural resources that are under significant pressure by human activities. Monitoring lakes regularly is necessary to understand their dynamics and the drivers of these dynamics to support effective management. Remote sensing by satellite sensors offers a significant opportunity to increase the spatiotemporal coverage of environmental monitoring programs for inland waters. Lake color is a water quality attribute that can be remotely sensed and is independent of the sensor specifications and water type. In this study we used the Multispectral Imager (MSI) on two Sentinel-2 satellites to determine the color of water of 170 Italian lakes during two periods in 2017. Overall, most of the lakes appeared blue in spring and green-yellow in late summer, and in particular, we confirm a blue-water status of the largest lakes in the subalpine ecoregion. The color and its seasonality are consistent with characteristics determined by geomorphology and primary drivers of water quality. This suggests that information about the color of the lakes can contribute to synoptic assessments of the trophic status of lakes. Further ongoing research efforts are focused to extend the mapping over multiple years.","PeriodicalId":11389,"journal":{"name":"Earth Observation and Geospatial Analyses [Working Title]","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74355440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-11DOI: 10.5772/INTECHOPEN.86109
Xia Li, G. McCarty
Landscape topography is a key parameter impacting soil properties on the earth surface. Strong topographic controls on soil morphological, chemical, and physical properties have been reported. This chapter addressed applications of topographical information for mapping spatial patterns of soil properties in recent years. Objec-tives of this chapter are to provide an overview of (1) impacts of topographic heterogeneity on the spatial variability in soil properties and (2) commonly used topography-based models in soil science. A case study was provided to demonstrate the feasibility of applying topography-based models developed in field sites to predict soil property over a watershed scale. A large-scale soil property map can be obtained based on topographic information derived from high-resolution remotely sensed data, which would benefit studies in areas with limited data accesses or needed to extrapolate findings from representative sites to larger regions.
{"title":"Application of Topographic Analyses for Mapping Spatial Patterns of Soil Properties","authors":"Xia Li, G. McCarty","doi":"10.5772/INTECHOPEN.86109","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.86109","url":null,"abstract":"Landscape topography is a key parameter impacting soil properties on the earth surface. Strong topographic controls on soil morphological, chemical, and physical properties have been reported. This chapter addressed applications of topographical information for mapping spatial patterns of soil properties in recent years. Objec-tives of this chapter are to provide an overview of (1) impacts of topographic heterogeneity on the spatial variability in soil properties and (2) commonly used topography-based models in soil science. A case study was provided to demonstrate the feasibility of applying topography-based models developed in field sites to predict soil property over a watershed scale. A large-scale soil property map can be obtained based on topographic information derived from high-resolution remotely sensed data, which would benefit studies in areas with limited data accesses or needed to extrapolate findings from representative sites to larger regions.","PeriodicalId":11389,"journal":{"name":"Earth Observation and Geospatial Analyses [Working Title]","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74715938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-06DOI: 10.5772/INTECHOPEN.86132
Daniel A. Pickersgill, H. Müller, V. Després
Research on bioaerosol is still in its infancy. The dynamics and, therefore, the effects on atmospheric processes and the biosphere are often underestimated, or have not yet been sufficiently investigated. Atmospheric models such as FLEXPART and HYSPLIT enable researchers to simulate the transport of particles in the atmosphere and provide information on where air-parcels originate from. In the following, we present two methods for combining results of these models with spatial information, e.g., about vegetation. The first method shows how spatial CORINE land cover distribution can be analyzed within the boundaries of HYSPLIT trajectories. In a second method, FLEXPART simulations are used in combination with COSMO rain data and tree maps to generate maps that indicate the potential origin of bioaerosol for selected periods of time.
{"title":"Advanced Methods for Spatial Analysis of Bioaerosol Long-Range Transport Processes","authors":"Daniel A. Pickersgill, H. Müller, V. Després","doi":"10.5772/INTECHOPEN.86132","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.86132","url":null,"abstract":"Research on bioaerosol is still in its infancy. The dynamics and, therefore, the effects on atmospheric processes and the biosphere are often underestimated, or have not yet been sufficiently investigated. Atmospheric models such as FLEXPART and HYSPLIT enable researchers to simulate the transport of particles in the atmosphere and provide information on where air-parcels originate from. In the following, we present two methods for combining results of these models with spatial information, e.g., about vegetation. The first method shows how spatial CORINE land cover distribution can be analyzed within the boundaries of HYSPLIT trajectories. In a second method, FLEXPART simulations are used in combination with COSMO rain data and tree maps to generate maps that indicate the potential origin of bioaerosol for selected periods of time.","PeriodicalId":11389,"journal":{"name":"Earth Observation and Geospatial Analyses [Working Title]","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90071550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-06DOI: 10.5772/INTECHOPEN.86149
G. Grandjean, X. Briottet, K. Adeline, A. Bourguignon, A. Hohmann
Mapping subsurface clay minerals is an important issue because they have particular behaviors in terms of mechanics and hydrology that directly affects assets laid at the surface such as buildings, houses, etc. They have a direct impact in ground stability due to their swelling capacities, constraining infiltration processes during flooding, especially when moisture is important. So detecting and characterizing clay mineral in soils serve urban planning issues and improve the risk reduction by predicting impacts of subsidence on houses and infrastruc-tures. High-resolution clay maps are thus needed with accurate indications on mineral species and abundances. Clay minerals, known as phyllosilicates, are divided in three main species: smectite, illite, and kaolinite. The smectite group highly contributes to the swelling behavior of soils, and because geotechnical soil analyses are expensive and time-consuming, it is urgent to develop new approaches for mapping clays' spatial distribution by using new technologies, e.g., ground spectrometer or remote hyperspectral cameras [0.4-2.5 μm]. These technics constitute efficient alternatives to conventional methods. We present in this chapter some recent results we got for characterizing clay species and their abundances from spectrometry, used either from a ground spectrometer or from hyperspectral cameras.
{"title":"Clay Minerals Mapping from Imaging Spectroscopy","authors":"G. Grandjean, X. Briottet, K. Adeline, A. Bourguignon, A. Hohmann","doi":"10.5772/INTECHOPEN.86149","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.86149","url":null,"abstract":"Mapping subsurface clay minerals is an important issue because they have particular behaviors in terms of mechanics and hydrology that directly affects assets laid at the surface such as buildings, houses, etc. They have a direct impact in ground stability due to their swelling capacities, constraining infiltration processes during flooding, especially when moisture is important. So detecting and characterizing clay mineral in soils serve urban planning issues and improve the risk reduction by predicting impacts of subsidence on houses and infrastruc-tures. High-resolution clay maps are thus needed with accurate indications on mineral species and abundances. Clay minerals, known as phyllosilicates, are divided in three main species: smectite, illite, and kaolinite. The smectite group highly contributes to the swelling behavior of soils, and because geotechnical soil analyses are expensive and time-consuming, it is urgent to develop new approaches for mapping clays' spatial distribution by using new technologies, e.g., ground spectrometer or remote hyperspectral cameras [0.4-2.5 μm]. These technics constitute efficient alternatives to conventional methods. We present in this chapter some recent results we got for characterizing clay species and their abundances from spectrometry, used either from a ground spectrometer or from hyperspectral cameras.","PeriodicalId":11389,"journal":{"name":"Earth Observation and Geospatial Analyses [Working Title]","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90416361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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