Pub Date : 2019-11-28DOI: 10.1017/9781316888872.003
G. Rossman, B. Ehlmann
Many of the spectral features ofminerals in the visible to near-infrared region (VNIR; defined here as ~0.4–2.5 μm) arise from electronic transitions within and between transition elements and the anions chemically bound to them. Thousands of minerals have color or wavelengthvariable properties in this portion of the spectrum.Metal ions including vanadium, chromium, manganese, iron, cobalt, nickel, and copper, usually in either the 2+ or 3+ oxidation state, are responsible for the color of many minerals. However, only a few of these elements, typically iron, titanium, and oxygen, are important in most remote sensing applications of rocky bodies. Many features arise from electronic transitions of electrons between the d orbitals of a metal ion, while some spectroscopic features arise from interactions between atoms.
{"title":"Electronic Spectra of Minerals in the Visible and Near-Infrared Regions","authors":"G. Rossman, B. Ehlmann","doi":"10.1017/9781316888872.003","DOIUrl":"https://doi.org/10.1017/9781316888872.003","url":null,"abstract":"Many of the spectral features ofminerals in the visible to near-infrared region (VNIR; defined here as ~0.4–2.5 μm) arise from electronic transitions within and between transition elements and the anions chemically bound to them. Thousands of minerals have color or wavelengthvariable properties in this portion of the spectrum.Metal ions including vanadium, chromium, manganese, iron, cobalt, nickel, and copper, usually in either the 2+ or 3+ oxidation state, are responsible for the color of many minerals. However, only a few of these elements, typically iron, titanium, and oxygen, are important in most remote sensing applications of rocky bodies. Many features arise from electronic transitions of electrons between the d orbitals of a metal ion, while some spectroscopic features arise from interactions between atoms.","PeriodicalId":375917,"journal":{"name":"Remote Compositional Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132740040","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 : 2019-11-28DOI: 10.1017/9781316888872.014
P. Sobrón, A. Misra, F. Rull, A. Sansano
{"title":"Raman Spectroscopy","authors":"P. Sobrón, A. Misra, F. Rull, A. Sansano","doi":"10.1017/9781316888872.014","DOIUrl":"https://doi.org/10.1017/9781316888872.014","url":null,"abstract":"","PeriodicalId":375917,"journal":{"name":"Remote Compositional Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116590765","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 : 2019-11-28DOI: 10.1017/9781316888872.008
Shiv k. Sharma, M. Egan
{"title":"Raman Spectroscopy","authors":"Shiv k. Sharma, M. Egan","doi":"10.1017/9781316888872.008","DOIUrl":"https://doi.org/10.1017/9781316888872.008","url":null,"abstract":"","PeriodicalId":375917,"journal":{"name":"Remote Compositional Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132564269","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 : 2005-04-15DOI: 10.1002/0471654507.EME379
J. V. Zyl, Yunjin Kim
In this article, we present the basic principles of how remote sensing radars work. These include SARs (synthetic aperture radar), scatterometers, altimeters, sounders, cloud radars, and rain radars. Radars are active sensors; they provide their own illumination and therefore can be operated during day or night. An additional advantage of particularly lower-frequency radars is their ability to penetrate clouds, rain, tree canopies, and even dry soil surfaces. We start the discussion by defining the basic concepts of resolution, the radar equation, signal fading, and the geometric distortions associated with the radar imaging geometry. We also include a description of advanced SAR techniques (polarimetry, interferometry, and polarimetric interferometry) and their applications. We complete the chapter by briefly examining nonimaging radars such as scatterometers, altimeters, radar sounders, and meteorological radars. An extensive list of references is provided for each radar for readers who need an in-depth description of a particular radar. Keywords: remote sensing; radar; SAR; polarimetric SAR; interferometric SAR; polarimetric interferometry; scatterometer; altimeter; sounder; cloud radar; rain radar
{"title":"Radar Remote Sensing","authors":"J. V. Zyl, Yunjin Kim","doi":"10.1002/0471654507.EME379","DOIUrl":"https://doi.org/10.1002/0471654507.EME379","url":null,"abstract":"In this article, we present the basic principles of how remote sensing radars work. These include SARs (synthetic aperture radar), scatterometers, altimeters, sounders, cloud radars, and rain radars. Radars are active sensors; they provide their own illumination and therefore can be operated during day or night. An additional advantage of particularly lower-frequency radars is their ability to penetrate clouds, rain, tree canopies, and even dry soil surfaces. We start the discussion by defining the basic concepts of resolution, the radar equation, signal fading, and the geometric distortions associated with the radar imaging geometry. We also include a description of advanced SAR techniques (polarimetry, interferometry, and polarimetric interferometry) and their applications. We complete the chapter by briefly examining nonimaging radars such as scatterometers, altimeters, radar sounders, and meteorological radars. An extensive list of references is provided for each radar for readers who need an in-depth description of a particular radar. \u0000 \u0000 \u0000Keywords: \u0000 \u0000remote sensing; \u0000radar; \u0000SAR; \u0000polarimetric SAR; \u0000interferometric SAR; \u0000polarimetric interferometry; \u0000scatterometer; \u0000altimeter; \u0000sounder; \u0000cloud radar; \u0000rain radar","PeriodicalId":375917,"journal":{"name":"Remote Compositional Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115872937","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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