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Books on the topic 'High spatial and spectral remote sensing'

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Published: 11 March 2023

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1

He, Yuhong, and Qihao Weng, eds. High Spatial Resolution Remote Sensing. Boca Raton, FL : Taylor & Francis, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9780429470196.

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2

Pedram, Ghamisi, ed. Spectral-spatial classififcation of hyperspectral remote sensing images. Boston: Artech House, 2015.

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3

Chedin, Alain, Moustafa T. Chahine, and Noëlle A. Scott, eds. High Spectral Resolution Infrared Remote Sensing for Earth’s Weather and Climate Studies. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84599-4.

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4

Alain, Chedin, Chahine Moustafa T, Scott Noëlle A. 1941-, North Atlantic Treaty Organization. Scientific Affairs Division., and NATO Advanced Research Workshop on High Spectral Resolution Infrared Remote Sensing for Earth's Weather and Climate Studies (1992 : Paris, France), eds. High spectral resolution infrared remote sensing for earth's weather and climate studies. Berlin: Springer, 1993.

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5

S, Carlson G., and George C. Marshall Space Flight Center., eds. Inter-comparison of wildfire and high-resolution interferometer sounder (HIS) data from STORM-FEST: An investigation of wildfire spectral channel discrepancies. [Marshall Space Flight Center, Ala.]: National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1994.

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6

S, Carlson G., and George C. Marshall Space Flight Center., eds. Inter-comparison of wildfire and high-resolution interferometer sounder (HIS) data from STORM-FEST: An investigation of wildfire spectral channel discrepancies. [Marshall Space Flight Center, Ala.]: National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1994.

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7

S, Carlson G., and George C. Marshall Space Flight Center., eds. Inter-comparison of wildfire and high-resolution interferometer sounder (HIS) data from STORM-FEST: An investigation of wildfire spectral channel discrepancies. [Marshall Space Flight Center, Ala.]: National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1994.

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8

Joanne, White, Mountain Pine Beetle Initiative (Canada), and Pacific Forestry Centre, eds. Detection of red attack stage mountain pine beetle infestation with high spatial resolution satellite imagery. Victoria, B.C: Canadian Forest Service, Pacific Forestry Centre, 2005.

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9

J, Tucker Compton, Dye Dennis G, and Goddard Space Flight Center, eds. North American vegetation patterns observed with the NOAA-7 Advanced Very High Resolution Radiometer. [Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1985.

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10

Hlavka, Christine A. Unmixing AVHRR imagery to assess clearcuts and forest regrowth in Oregon. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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11

Hlavka, Christine A. Unmixing AVHRR imagery to assess clearcuts and forest regrowth in Oregon. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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12

United States. National Aeronautics and Space Administration., ed. Applications of GOES-8/9 data to hurricane analysis. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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13

United States. National Aeronautics and Space Administration., ed. Applications of GOES-8/9 data to hurricane analysis. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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14

Smith, William L. Analysis of cirrus optical properties with data from the NASA ER2 high-resolution interferometer sounder (HIS): Final report on NASA research grant NAG-1-1015. Madison, Wis: University of Wisconsin-Madison, 1990.

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15

L, Barker John, and United States. National Aeronautics and Space Administration., eds. Landsat-4 science characterization early results. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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16

L, Barker John, and United States. National Aeronautics and Space Administration., eds. Landsat-4 science characterization early results. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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17

L, Barker John, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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18

L, Barker John, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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19

L, Barker John, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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20

L, Barker John, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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21

L, Barker John, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch, eds. Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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22

Landsat-4 Science Characterization Early Results Symposium (1983 Greenbelt, Md.). Landsat-4 science characterization early results: Proceedings of the Landsat-4 Science Characterization Early Results Symposium, February 22-24, 1983, held at NASA Goddard Space Flight Center, Greenbelt, Maryland. Edited by Barker John L, United States. National Aeronautics and Space Administration, and Landsat-4 Early Results Symposium (1983 : Greenbelt, Md.). Washington, D.C: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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23

Landsat-4 Science Characterization Early Results Symposium (1983 Greenbelt, Md.). Landsat-4 science characterization early results: Proceedings of the Landsat-4 Science Characterization Early Results Symposium, February 22-24, 1983, held at NASA Goddard Space Flight Center, Greenbelt, Maryland. Edited by Barker John L, United States. National Aeronautics and Space Administration, and Landsat-4 Early Results Symposium (1983 : Greenbelt, Md.). Washington, D.C: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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24

L, Barker John, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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25

Erasmi, Stefan, and Martin Kappas. High Resolution Remote Sensing: Precise Spectral, Spatial and Temporal Satellite Data for Environmental Applications. Springer, 2007.

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26

High Spatial Resolution Remote Sensing. Taylor & Francis Group, 2018.

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27

Weng, Qihao, and Yuhong He. High Spatial Resolution Remote Sensing: Data, Analysis, and Applications. Taylor & Francis Group, 2018.

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28

Weng, Qihao, and Yuhong He. High Spatial Resolution Remote Sensing: Data, Analysis, and Applications. Taylor & Francis Group, 2018.

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29

Weng, Qihao, and Yuhong He. High Spatial Resolution Remote Sensing: Data, Analysis, and Applications. Taylor & Francis Group, 2018.

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30

Weng, Qihao, and Yuhong He. High Spatial Resolution Remote Sensing: Data, Analysis, and Applications. Taylor & Francis Group, 2018.

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31

Buddhiraju, Krishna Mohan. Analysis of High Spatial Resolution Remote Sensing Imagery: An Object Based Approach. Taylor & Francis Group, 2019.

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32

Buddhiraju, Krishna Mohan. Analysis of High Spatial Resolution Remote Sensing Imagery: An Object Based Approach. Taylor & Francis Group, 2019.

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33

Buddhiraju, Krishna Mohan, and Biplab Banerjee. Analysis of High Spatial Resolution Remote Sensing Imagery: An Object Based Approach. Taylor & Francis Group, 2021.

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34

Buddhiraju, Krishna Mohan. Analysis of High Spatial Resolution Remote Sensing Imagery: An Object Based Approach. Taylor & Francis Group, 2019.

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35

Buddhiraju, Krishna Mohan. Analysis of High Spatial Resolution Remote Sensing Imagery: An Object Based Approach. Taylor & Francis Group, 2019.

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36

Chahine, Moustafa T., Alain Chedin, and Noelle A. Scott. High Spectral Resolution Infrared Remote Sensing for Earth’s Weather and Climate Studies. Springer, 2012.

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37

Chahine, Moustafa T., Alain Chedin, and Noelle A. Scott. High Spectral Resolution Infrared Remote Sensing for Earth's Weather and Climate Studies. Springer London, Limited, 2013.

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38

Bishop, Gary, Gary Kamerman, John Gonglewski, Ainsley Killey, and Ove Steinvall. Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II. SPIE, 2014.

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39

Applications of GOES-8/9 data to hurricane analysis. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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40

Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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41

Landsat-4 science characterization early results. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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42

Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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43

Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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44

Landsat-4 science characterization early results. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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45

Gao, Yanhong, and Deliang Chen. Modeling of Regional Climate over the Tibetan Plateau. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.591.

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Abstract:
The modeling of climate over the Tibetan Plateau (TP) started with the introduction of Global Climate Models (GCMs) in the 1950s. Since then, GCMs have been developed to simulate atmospheric dynamics and eventually the climate system. As the highest and widest international plateau, the strong orographic forcing caused by the TP and its impact on general circulation rather than regional climate was initially the focus. Later, with growing awareness of the incapability of GCMs to depict regional or local-scale atmospheric processes over the heterogeneous ground, coupled with the importance of this information for local decision-making, regional climate models (RCMs) were established in the 1970s. Dynamic and thermodynamic influences of the TP on the East and South Asia summer monsoon have since been widely investigated by model. Besides the heterogeneity in topography, impacts of land cover heterogeneity and change on regional climate were widely modeled through sensitivity experiments.In recent decades, the TP has experienced a greater warming than the global average and those for similar latitudes. GCMs project a global pattern where the wet gets wetter and the dry gets drier. The climate regime over the TP covers the extreme arid regions from the northwest to the semi-humid region in the southeast. The increased warming over the TP compared to the global average raises a number of questions. What are the regional dryness/wetness changes over the TP? What is the mechanism of the responses of regional changes to global warming? To answer these questions, several dynamical downscaling models (DDMs) using RCMs focusing on the TP have recently been conducted and high-resolution data sets generated. All DDM studies demonstrated that this process-based approach, despite its limitations, can improve understandings of the processes that lead to precipitation on the TP. Observation and global land data assimilation systems both present more wetting in the northwestern arid/semi-arid regions than the southeastern humid/semi-humid regions. The DDM was found to better capture the observed elevation dependent warming over the TP. In addition, the long-term high-resolution climate simulation was found to better capture the spatial pattern of precipitation and P-E (precipitation minus evapotranspiration) changes than the best available global reanalysis. This facilitates new and substantial findings regarding the role of dynamical, thermodynamics, and transient eddies in P-E changes reflected in observed changes in major river basins fed by runoff from the TP. The DDM was found to add value regarding snowfall retrieval, precipitation frequency, and orographic precipitation.Although these advantages in the DDM over the TP are evidenced, there are unavoidable facts to be aware of. Firstly, there are still many discrepancies that exist in the up-to-date models. Any uncertainty in the model’s physics or in the land information from remote sensing and the forcing could result in uncertainties in simulation results. Secondly, the question remains of what is the appropriate resolution for resolving the TP’s heterogeneity. Thirdly, it is a challenge to include human activities in the climate models, although this is deemed necessary for future earth science. All-embracing further efforts are expected to improve regional climate models over the TP.
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