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
Land ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 130
Author(s):  
Thanh Thi Nguyen ◽  
Melvin Lippe ◽  
Carsten Marohn ◽  
Tran Duc Vien ◽  
Georg Cadisch

The present study revealed how local socioecological knowledge elucidated during participatory rural appraisals and historical remote sensing data can be combined for analyzing land use change patterns from 1954 to 2007 in northwestern Vietnam. The developed approach integrated farmer decision rules on cropping preferences and location, visual and supervised classification methods, and qualitative information obtained during various forms of participatory appraisals. The integration of historical remote sensing data (aerial photo, Landsat, LISS III) with farmer decision rules showed the feasibility of the proposed method to explain crop distribution patterns for the assessment period of 53 years. Our approach is beneficial for data-limited environments, which is a prevalent situation for many developing regions. The derived land use and crop type dataset was used for understanding how anthropogenic activities altered the study area of the Chieng Khoi commune during the assessment period of five decades, and what potential impact this can have on the natural resource base. The newly developed approach offers a methodological pathway that can be easily transferred to local government authorities for a better understanding of cropping transitions and agricultural expansion trends in data-limited rural landscapes. The detected land use change patterns and upland cropping expansion of more than two hundred percent in 53 years not only revealed the consequences of the interactions and feedback between farmers and their land, but further highlighted the urgent need for implementing sustainable land management practices in the case study watershed of the Chieng Khoi commune and northwestern Vietnam in general.


2016 ◽  
Vol 55 (9) ◽  
pp. 2021-2036
Author(s):  
Brian I. Magi ◽  
Thomas Winesett ◽  
Daniel. J. Cecil

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.


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