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Accueil du site → Doctorat → États-Unis → 2011 → Quantifying vegetation response to grazing intensity and precipitation on Chihuahuan Desert rangeland using remote sensing and GIS

New Mexico State University (2011)

Quantifying vegetation response to grazing intensity and precipitation on Chihuahuan Desert rangeland using remote sensing and GIS

Mohamed Ahmed H

Titre : Quantifying vegetation response to grazing intensity and precipitation on Chihuahuan Desert rangeland using remote sensing and GIS

Auteur : Ahmed H Mohamed

Université de soutenance : New Mexico State University

Grade : Doctor of Philosophy (PhD) 2011

Résumé
High spatial resolution satellite imagery is a promising data source for studying vegetation dynamics. The overall goal for this study was to use QuickBird high spatial resolution satellite imagery to develop methods for vegetation analysis and tracking livestock distribution. I hypothesized that using these technologies would create appropriate new management tool that provides spatial, temporal, and current information for extensive rangeland pastures. This research was conducted on four large scale pastures at the Chihuahuan Desert Rangeland Research Center (CDRRC) in south central New Mexico. Two QuickBird ortho-ready standard satellite images (DigitalGlobe Inc., Longmont, Colorado, USA) were acquired for the study area in May of 2006 and 2009. The image covered an area of 4381 ha and had a 60 cm panchromatic resolution and 2.4 m multispectral resolution. A 4-band pan-sharpened image with spatial resolution of 60 cm was produced for each QuickBird image. Per-pixel spectral based classification algorithms were used to classify the two images and map the primary vegetation types in the study area. Post-classification change detection was conducted between the May 2006 image and the May 2009 image. GPS collars were used to track 2 cows in each pasture for 10 weeks during the winter of 2010. Forage production for the primary perennial grasses was estimated from 40 permanent vegetation plots across the study area in May 2009. Spectral-based classification techniques were very effective in classifying QuickBird satellite imagery. Overall accuracy of the classified map ranged from 89 to 95 %. Increasing honey mesquite (Prosopis glandulosa Torr.) canopy cover corresponded to lower perennial grass forage production. Improvement in range condition in terms of declining shrub cover and bare ground and increased grass-mix vegetation was noted in conservatively grazed (35% utilization) pastures. However, only slight changes were observed in lightly grazed pastures. Grazing patterns of cattle in conservatively grazed pasture appeared to be more uniform than those in the lightly grazed pasture. Combining GPS collar data with high spatial resolution vegetation maps and GIS assessment was very effective in tracking cattle grazing distribution in the Chihuahuan Desert rangelands.

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Page publiée le 7 janvier 2012, mise à jour le 11 novembre 2018