Using SAR Remote Sensing, Field Observations, and Models to Better Understand Coastal Flows in the Gulf of Alaska

Circular 1514, a 47-page illustrated report by Joaquin Casanova, Fei Yan, Mi-young Jang, Juan Fernandez, Jasmeet Judge, Clint Slatton, Kai-Jen Calvin Tien, Tzu-yun Lin, Orlando Lanni, and Larry Miller, presents the results of experiments using microwave remote sensing to determine root-zone soil moisture at UF/IFAS PSREU. Published by the UF Department of Agricultural and Biological Engineering, May 2007. CIR1514/AE407: Field Observations During the Fifth Microwave Water and Energy Balance Experiment: from March 9 through May 26, 2006 (ufl.edu)

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GEOMETRIC ANALYSIS OF SINGLE SAR REMOTE SENSING IMAGE POSITIONING

JOURNAL OF INFRARED AND MILLIMETER WAVES ◽

10.3724/sp.j.1010.2009.00461 ◽

2010 ◽

Vol 28 (6) ◽

pp. 461-465

Author(s):

Shuai XING ◽

Qing XU ◽

Yu HE ◽

Chao-Zhen LAN

Keyword(s):

Remote Sensing ◽

Geometric Analysis ◽

Remote Sensing Image ◽

Sar Remote Sensing

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Beyond Bioproductivity: Engaging Local Perspectives in Land Degradation Monitoring and Assessment

10.20944/preprints201805.0399.v1 ◽

2018 ◽

Author(s):

Stefanie Herrmann ◽

Abdoul Aziz Diouf ◽

Ibrahima Sall

Keyword(s):

Remote Sensing ◽

Land Degradation ◽

Vegetation Indices ◽

Temporal Trends ◽

Photo Elicitation ◽

Field Observations ◽

Crowd Sourcing ◽

Vegetative Cover ◽

Degradation Monitoring ◽

Land Condition

Land degradation monitoring and assessment in the Sahel zone takes advantage of and relies substantially on temporal trends of remote sensing-based vegetation indices, which are proxies for the bioproductivity of the land. However, prior studies have shown that negative or positive trends in bioproductivity are not necessarily associated with degradation or improvement of land condition. We argue that remote sensing-based indices, while having contributed much to dismantling an outdated desertification narrative, are themselves falling short of capturing the whole picture and need to be accompanied by field observations that are relevant to local land users. We used the participatory photo elicitation method in three sites in order to elicit local pastoralists’ perspectives on land degradation and identify the indicators that they use to characterize pasture quality, while empowering them to lead the discussion. The discussion revealed indicators far beyond bioproductivity, including livestock performance as well as composition and quality of the herbaceous and woody vegetative cover, invasive species, soil quality and water availability. We found that the pastoralists’ interest, knowledge and field observations could potentially be harnessed using a crowd-sourcing approach in order to produce a geospatially explicit dataset of land degradation, which would be complementary to the remote sensing-based maps of trends in bioproductivity and could serve as a reference for the development of more targeted remote sensing-based indicators of land degradation

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