Multi-Decadal Remote-Sensing Analysis of Irrigated Areas in the Lower Rio Grande Valley, New Mexico

被引:1
作者
Jordan, David L. [1 ]
Barroll, Peggy [2 ]
机构
[1] INTERA Inc, Albuquerque, NM 87110 USA
[2] New Mexico Off State Engineer, Santa Fe, NM 87501 USA
来源
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION | 2013年 / 49卷 / 03期
关键词
remote sensing; monitoring; land-use change; land cover change; irrigation; water allocation; water supply; TIME-SERIES; LANDSAT; VEGETATION; EVAPOTRANSPIRATION; LANDSCAPE; IMAGES;
D O I
10.1111/jawr.12052
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A time series of estimates of irrigated area was developed for the Lower Rio Grande valley (LRG) in New Mexico from the 1970s to present day. The objective of the project was to develop an independent, accurate, and scientifically justifiable evaluation of irrigated area in the region for the period spanning from the mid-1970s to the present. These area estimates were used in support of groundwater modeling of the LRG region, as well as for other analyses. This study used a remote-sensing-based methodology to evaluate overall irrigated area within the LRG. We applied a methodology that involved the normalization of vegetation indices derived from satellite imagery to get a more accurate estimation of irrigated area across multiple time periods and multiple Landsat platforms. The normalization allows more accurate evaluation of vegetation index data that span several decades. An accuracy assessment of the methodology and results from this study was performed using field-collected crop data from the 2008 growing season. The comparisons with field data indicate that the accuracy of the remote-sensing-based estimates of historical irrigated area is very good, with rates of false positives (areas identified as irrigated that are not truly irrigated) of only about 4%, and rates of false negatives (areas identified as not irrigated that are truly irrigated) in the range of 0.6-2.0%.
引用
收藏
页码:484 / 497
页数:14
相关论文
共 22 条
[1]   Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources [J].
Anderson, Martha C. ;
Allen, Richard G. ;
Morse, Anthony ;
Kustas, William P. .
REMOTE SENSING OF ENVIRONMENT, 2012, 122 :50-65
[2]  
[Anonymous], 1986, INTRO DIGITAL IMAGE
[3]  
[Anonymous], 1999, ERDAS FIELD GUID, VFifth
[4]   Development of a Landsat time series for application in forest status assessment in the Inland Northwest United States [J].
Beck, Russell N. ;
Gessler, Paul E. .
WESTERN JOURNAL OF APPLIED FORESTRY, 2008, 23 (01) :53-62
[5]   A simple and effective radiometric correction method to improve landscape change detection across sensors and across time [J].
Chen, XX ;
Vierling, L ;
Deering, D .
REMOTE SENSING OF ENVIRONMENT, 2005, 98 (01) :63-79
[6]   Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems [J].
Glenn, Edward P. ;
Neale, Christopher M. U. ;
Hunsaker, Doug J. ;
Nagler, Pamela L. .
HYDROLOGICAL PROCESSES, 2011, 25 (26) :4050-4062
[7]   Estimation of insect infestation dynamics using a temporal sequence of Landsat data [J].
Goodwin, Nicholas R. ;
Coops, Nicholas C. ;
Wulder, Michael A. ;
Gillanders, Steve ;
Schroeder, Todd A. ;
Nelson, Trisalyn .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (09) :3680-3689
[8]  
JENSEN JR, 1995, PHOTOGRAMM ENG REM S, V61, P199
[9]  
Jordan D., 2006, US COMM IRR DRAIN C
[10]  
Melesse A.M., 2003, Journal of Spatial Hydrology, V3, P1