Fields from Afar: Evidence of Heterogeneity in United States Corn Rotational Response from Remote Sensing Data

2021 ◽  
Author(s):  
Nicholas J. Pates ◽  
Nathan P. Hendricks
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Rotational Response

scholarly journals Evaluation of Remotely Sensed Snow Water Equivalent and Snow Cover Extent over the Contiguous United States

2018 ◽  
Vol 19 (11) ◽  
pp. 1777-1791 ◽  
Author(s):  
Nicholas Dawson ◽  
Patrick Broxton ◽  
Xubin Zeng
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Snow Cover ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Snow Cover Extent ◽  
Snow Water ◽  
The Mean

Abstract Global snow water equivalent (SWE) products derived at least in part from satellite remote sensing are widely used in weather, climate, and hydrometeorological studies. Here we evaluate three such products using our recently developed daily 4-km SWE dataset available from October 1981 to September 2017 over the conterminous United States. This SWE dataset is based on gridded precipitation and temperature data and thousands of in situ measurements of SWE and snow depth. It has a 0.98 correlation and 30% relative mean absolute deviation with Airborne Snow Observatory data and effectively bridges the gap between small-scale lidar surveys and large-scale remotely sensed data. We find that SWE products using remote sensing data have large differences (e.g., the mean absolute difference from our SWE data ranges from 45.8% to 59.3% of the mean SWE in our data), especially in forested areas (where this percentage increases up to 73.5%). Furthermore, they consistently underestimate average maximum SWE values and produce worse SWE (including spurious jumps) during snowmelt. Three additional higher-resolution satellite snow cover extent (SCE) products are used to compare the SCE values derived from these SWE products. There is an overall close agreement between these satellite SCE products and SCE generated from our SWE data, providing confidence in our consistent SWE, snow depth, and SCE products based on gridded climate and station data. This agreement is also stronger than that between satellite SCE and those derived from the three satellite SWE products, further confirming the deficiencies of the SWE products that utilize remote sensing data.

scholarly journals Evaluation of survey and remote sensing data products used to estimate land use change in the United States: Evolving issues and emerging opportunities

2022 ◽  
Vol 129 ◽  
pp. 68-78
Author(s):  
Minzi Wang ◽  
Michelle Wander ◽  
Steffen Mueller ◽  
Nico Martin ◽  
Jennifer B. Dunn
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Remote Sensing Data ◽  
The United States ◽  
Sensing Data ◽  
Data Products

Use of remote sensing data for estimation of winter wheat yield in the United States

2007 ◽  
Vol 28 (17) ◽  
pp. 3795-3811 ◽  
Author(s):  
L. Salazar ◽  
F. Kogan ◽  
L. Roytman
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Remote Sensing Data ◽  
The United States ◽  
Sensing Data ◽  
Winter Wheat Yield

scholarly journals Estimating Lightning from Microwave Remote Sensing Data

2016 ◽  
Vol 55 (9) ◽  
pp. 2021-2036
Author(s):  
Brian I. Magi ◽  
Thomas Winesett ◽  
Daniel. J. Cecil
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Brightness Temperature ◽  
Regional Differences ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
The United States ◽  
Lightning Flash ◽  
Sensing Data ◽  
Cg Lightning

AbstractThis study evaluates a method for estimating the cloud-to-ground (CG) lightning flash rate from microwave remote sensing data. Defense Meteorological Satellite Program satellites have been in operation since 1987 and include global-viewing microwave sensors that capture thunderstorms as brightness temperature depressions. The National Lightning Detection Network (NLDN) has monitored CG lightning in the United States since 1997. This study investigates the relationship between CG lightning and microwave brightness temperature fields for the contiguous United States from April to September for the years 2005–12. The findings suggest that an exponential function, empirically fit to the NLDN and SSM/I data, provides lightning count measurements that agree to within 60%–70% with NLDN lightning, but with substantial misses and false alarms in the predictions. The discrepancies seem to be attributable to regional differences in thunderstorm characteristics that require a detailed study at smaller spatial scales to truly resolve, but snow at higher elevations also produces some anomalous microwave temperature depressions similar to those of thunderstorms. The results for the contiguous United States in this study are a step toward potentially using SSM/I data to estimate CG lightning around the world, although the sensitivity of the results to regional differences related to meteorological regimes would need further study.

Sign in / Sign up

Export Citation Format

Share Document