2009
DOI: 10.1111/j.1749-8198.2009.00243.x
|View full text |Cite
|
Sign up to set email alerts
|

Observing Forest Change to Enhance Border Sustainability in Chihuahua, Mexico

Abstract: The US–Mexico border is a place of great social and economic contrasts. Environmental systems straddle the border without regard for social or economic differences, and degradation is rarely confined to a single side of the border. Of major concern to the border region is the quantity and quality of water resources in the Rio Grande and its tributaries. The forests of the Sierra Madre Occidental in Chihuahua State are the source of much of this water and are an ideal place to study the impact of distant border… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2019
2019
2020
2020

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 38 publications
(46 reference statements)
0
1
0
Order By: Relevance
“…One of the main reasons for the lack of attention on the driving forces of vegetation cover change was the availability of precise spatial data measuring land covers. The rise of remotesensing data in the recent decades has provided the opportunities for researchers worldwide to investigate the change of vegetation cover at much finer resolutions and much larger scales (Townshend et al 1991, Currit 2009). The high-resolution remote-sensing data have seen widespread applications in many industries, especially in agricultural and environmental management.…”
Section: Introductionmentioning
confidence: 99%
“…One of the main reasons for the lack of attention on the driving forces of vegetation cover change was the availability of precise spatial data measuring land covers. The rise of remotesensing data in the recent decades has provided the opportunities for researchers worldwide to investigate the change of vegetation cover at much finer resolutions and much larger scales (Townshend et al 1991, Currit 2009). The high-resolution remote-sensing data have seen widespread applications in many industries, especially in agricultural and environmental management.…”
Section: Introductionmentioning
confidence: 99%