Showing posts with label Forests. Show all posts
Showing posts with label Forests. Show all posts

Monday, September 21, 2020

Landsat 7 captures active fires in SE Wyoming (Sep 19, 2020)

Last Saturday (Sep 19), Landsat 7 satellite passed over the Mullen Fire in Medicine Bow National Forest (Wyo.) and captured the active fires. Images captured in spectral regions that are invisible to humans shows active fires.

The stripes in the Landsat 7 image correspond to missing data due to scan line corrector malfunction developed in 2003. Despite this limitation, images continued to provide valuable information about forests, croplands, water bodies and many more.  Landsat 9, the next satellite in the series, is scheduled to launch in 2021. For more information about Landsat, please visit https://landsat.usgs.gov.

Mullen Fire started on Sep 17, and as of Monday (Sep 21) has burned more than 13,835 acres.  Please visit the InciWeb site for more information about this fire.

Wednesday, May 14, 2014

WyomingView interns describe how satellite data can be used for monitoring past environmental changes

Emily Richardson (BS Botany) monitored aspen tree growth in normal, wet, and dry years along an elevation gradient in the Sierra Madre Mountains. She computed a vegetation index from Moderate Resolution Imaging Spectrometer (MODIS) data acquired in 3 years and analyzed tree growth based on their phenology curves. Aspen stands growing at lower elevations exhibited major changes during these three years, whereas their growth patterns at higher elevations did not show such variations.



Ryan Lermon (BS Rangeland Ecology & Watershed Management) mapped the burn severity at a prescribed fire site north of Rawlins, WY. Prescribed fires are part of forest management methods aimed at reducing fuel load, and improving overall habitat quality. Following a prescribed fire event, land management agencies are required to map how fire moved through the landscape but lack the necessary resources to generate it. Using a Landsat 8 image acquired after the fire, Ryan mapped the impact of this prescribed fire as high, medium, low and no-burn classes. This map will be used by agencies to establish field sampling plots for monitor vegetation regrowth.


Emily and Ryan presented their work in the Wyoming Undergraduate Research Day on 26 April 2014.


Following newspapers published a short description of Emily's work:


Laramie Boomerang - May 10, 2014 - Link to article

Casper Star Tribune - May 12, 2014 - Link to article

Washington Times - May 10, 2014 - Link to article

Monday, May 21, 2012

UW Students Research Value of Satellite Images for Monitoring Wyoming Resources

Source: UW Extension Service's press release
By: Steven L. Miller, Senior Editor
Date: 21 May 2012


Students at the University of Wyoming found that aspen had budded earlier in a drought year, and that surface area estimates from satellite images matched well with corresponding water levels in Woodruff Narrows Reservoir near Evanston. Other students used information derived from remotely sensed images to monitor crop growth on a southeast Wyoming wheat farm and the effects of the 2004 Basin Draw fire in northeast Wyoming. The research taught students how to use satellite images and its effectiveness.

Every spring semester, three to five students -- in the Department of Ecosystem Science and Management in the UW College of Agriculture and Natural Resources -- conduct research using remotely sensed data on a topic of their interest, says Ramesh Sivanpillai, research scientist in the Wyoming Geographic Information Science Center. He teaches the college's digital image processing for natural resources management course.

"Most of these students select the farms or ranches owned by family members or forests and public land they have worked on during summer months," he says. "Familiarity about their study areas provides them a unique advantage when analyzing and interpreting satellite images, and for conveying the findings of their study to the landowners or agencies."

Matthew Thoman of Riverton worked on a dryland winter wheat farm east of Cheyenne and was familiar with the fields. By processing Landsat images from the growing seasons of 2007 and 2009, he found growth variations within fields -- despite higher soil moisture levels in 2009 than 2007.

He will share the information with the producer, who could devise plans to correct the deficiencies, Sivanpillai says.

Brandt Schiche of Buffalo used Landsat images to glean information about surface area changes on Woodruff Narrows Reservoir. Water from the reservoir is used for irrigation, recreation and industry, and is shared between Utah and Wyoming.

"He found a significant relationship between the surface area estimates derived from Landsat images and the corresponding water levels in the reservoir," Sivanpillai says.

Jason Pindell of Wheatland used MODIS (Moderate Resolution Imaging Spectroradiometer) data to assess differences in the growing pattern of aspen stands in the Medicine Bow National Forest. His research showed aspen put out leaves relatively earlier (bud-burst) in a drought year (2002) in comparison to the bud-burst in a normal year (2009).



Orin Hutchinson of Newcastle (pictured above) had worked with the U.S. Forest Service managing wildfires. He evaluated indices derived from Landsat images that highlighted burned (immediately) and revegetated (few years later) areas after the 2004 Basin Draw fire northwest of Aladdin in Crook County. The fire burned more than 4,500 acres in three days, but its impact and severity varied throughout the landscape.

"His results pointed out that burn severity index values were in good agreement with the data collected in the field," Sivanpillai says. "However, extraneous factors, such as precipitation and management practices, influenced the vegetation regrowth, limiting the effectiveness of satellite data for monitoring regrowth after several years."

Students presented their findings during UW's recent Undergraduate Research Day.

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Thursday, September 16, 2010

WyomingView interns present their research findings in the 2010 GIS in the Rockies Conference

WyomingView interns (spring 2010 semester) Paul Arendt and William (Bill) Gray presented their research findings in the 23rd annual GIS in the Rockies Conference in Loveland, CO.


Using Landsat images Paul Arendt (BA Geography) analyzed the spectral reflectance patterns of areas impacted by the Mountain pine beetle in the Medicine Bow National Forest, Wyoming.  He combined Landsat observations with aerial survey data collected by the US Forest Service to identify differences in the reflectance patterns of beetle infected (n=77) and non-infected (n=50) areas. He calculated Normalized Difference Vegetation Index (NDVI) and Tasseled Cap Wetness Index for these sites and found that both indices had lower values at affected sites and these differences were statistically significant (p < 0.01). Within the 77 beetle infected sites, the mean NDVI and Tasseled Cap wetness values were higher (p < 0.01) in the patchy lower forest (< 2567 m) in comparison to the subalpine lodgepole pine (>2568 m) forest.  Describing the value of this research, Paul commented "...this project served as an excellent introduction to the process of scientific research".

Bill Gray (MA Planning) used Landsat images acquired from 1984 through 2009 to map changes in the surface area of Ocean Lake in Freemont County, Wyoming. Using images acquired in spring and fall for 27 years, he mapped changes in the surface area and compared the within- and between-year variations.  His findings revealed that the lake's surface area in spring (2442 hectares) was less in comparison to the surface area in fall or autumn (2457 hectares).  The overall area showed a declining trend from 2536 ha (fall 1986) to 2392 ha (fall 2009).

Both studies were possible due to the availability of no-cost Landsat data.  Prior to the no-cost Landsat data era, purchasing 54 images that Bill Gray used in his study, would have cost him US$ 35,000 which would be beyond the reach of any graduate student.  "A unique aspect of this study is that it offers the end-user a technique to use the free archive of LandSat images in a time series for analysis..." said Bill Gray.

Every semester WyomingView offers internships to UW undergraduate and graduate students to work on projects that use remotely sensed data for addressing natural resource management issues in Wyoming.

Tuesday, June 1, 2010

Enhanced learning through student selected agricultural remote sensing projects

Article originally published in Reflections a publication of the UW College of Agriculture and Natural Resources (Publication date: June 2010; pages 56-58)

Access the issue online at: http://www.uwyo.edu/uwexpstn/publications/reflections/2010/reflections_2010.pdf (5.3 MB)

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Enhanced learning through student selected agricultural remote sensing projects

Students utilize high-tech opportunities to examine Wyoming crop, ranch, and forest areas 


Carla Grefroh of Douglas, WY compares vegetation on her family’s ranch during drought and wet years

Images from earth observation satellites provide valuable information for students and researchers interested in monitoring natural resources. These remotely sensed images provide a bird-eye’s view of the earth’s surface and enable monitoring of rangelands, shrublands, and forests.

Many remote sensing satellites collect images at regular intervals, giving researchers an opportunity to monitor changes on the earth’s surface.  They can also be used to characterize variability in vegetation conditions within an agricultural field, ranch, or forest.  Vegetation growth stage (emergent vs. full canopy) and condition (healthy vs. stressed) can be determined by examining reflected infrared light, which is measured by many remote sensing satellites.

In general, remotely sensed images contain a wealth of information about the earth’s surface and are valuable for a wide range of users.

Remotely sensed satellites divide the earth surface into a uniform grid comprised of pixels and record the amount of reflected visible and infrared light coming to the satellite from each pixel.  Analysts examine the pattern of reflected light across a range of wavelengths to extract information about places in an image.  For example, a farmer can monitor changes in crop growth during the growing season using a series of Landsat images (Box 1).  A rancher can map forage conditions on a ranch and also identify areas of poor or no vegetation growth.

Box 1: Landsat images
Landsat images have been collected by a series of remote sensing satellites operated by the U.S. government since early 1970s (http://landsat.usgs.gov) and represent an extensive civilian archive in terms of duration (more than 36 years) and geographic coverage. Landsat collects a new image every 16 days for every place on earth.  Each image covers a relatively large geographic area (approximately 90 miles x 90 miles). Landsat records information from the visible region and the infrared regions of the spectrum, which is useful for monitoring vegetation condition and for a wide variety of other applications. Countless studies have demonstrated the value of Landsat data for monitoring changes in croplands, rangelands and forests. Landsat images are useful when monitoring rangelands and croplands through conventional field surveys is not feasible due to cost or access issues.

Increasing student employment potential

Changes introduced by natural disturbances, such as wildfires and droughts, and anthropogenic activities, such as land conversion, are creating new applications of remotely sensed imagery.  Because the imagery is so valuable, several countries have launched remotely sensed satellites to collect earth observation data.  In the U.S., federal and state government agencies, as well as private companies, are launching and operating remote sensing satellites. Students who learn image processing and interpretation skills as part of their academic training often increase their employment potential.

Ag remote sensing projects

UW students are learning to implement many of the applications described above in the Applied Remote Sensing for Agricultural Management (BOT/RNEW 4130/5130 and AECL4130) course.  One requirement of this course is that students complete a class project using imagery to answer questions about a real-world agricultural issue. For example, some students use images of their parent’s farm or ranch to obtain a better understanding of crop growth patterns by comparing the images to conditions observed on the ground.

Students associate areas of poor growth (often characterized by low infrared reflectance) identified in the image to problems such as soil alkalinity or poor water drainage.  Similarly, several students obtained images acquired in normal and drought years for rangelands and mapped changes in vegetation condition.  Students enhanced their learning experience by selecting images for areas of interest to them rather than working on pre-defined laboratory exercises.

Mapping crop growth in the Big Horn River Basin

Garret Klein and Laramie Wiginton (rangeland ecology majors), Chris Heil (agroecology major) and Travis Yeik (geography major) used Landsat images for monitoring crop growth in agricultural fields in Freemont and Washakie counties.

Klein and Wiginton mapped crop growth by computing a vegetation index derived from the amount of reflected red and infrared light.  Based on their research, they concluded Landsat images could be used to accurately identify areas of poor and medium growth for different crops; however, they noticed some weed infested areas also had high infrared reflectance due to dense canopy, thereby reducing the utility of Landsat data under these circumstances.

Yeik analyzed growth patterns in sugar beets and alfalfa crops in Worland using Landsat images acquired from 2006, 2007, and 2008.  This multi-year analysis of crop growth patterns was necessary for identifying areas of poor and high growth and for devising appropriate management plans to help improve crop yields.

Assessing wildfire damage to forest vegetation

Using Landsat images, Cody Tully estimated wildfire burn severity of a fire in Medicine Bow National Forest, Brice Stanton and Adam Stephens for a fire in the Black Hills National Forest, and Anne Morabito for a fire in Southern California. Stanton and Tully worked on firefighting teams and had firsthand knowledge of the impacts of fire on forest vegetation.  This knowledge was valuable for interpreting the information derived from Landsat images about burn severity patterns.

Cody Tully of Sinclair, WY helped fight the 2006 Isabelle Fire that burned near
Lake Owen in Southeast Wyoming. He is examining satellite images of the burn

Tully fought the 2006 Isabelle Fire that burned 1 mile south of Lake Owen in southeast Wyoming.  Burn Ratio Indices derived from the Landsat images acquired before and after the wildfire enabled him to distinctly classify the burned areas and also group them by severity classes.

Using the same method, Morabito (a California native) generated burn severity maps depicting various levels of damage caused by the Station Fire near Los Angeles in Southern California during August 2009.   Methodology used by these students is identical to the methods used by federal and state land management agencies tasked with fighting wildfires and monitoring vegetation establishment in burned areas.

Monitoring Wyoming Rangelands

Most students used Landsat images for monitoring rangelands throughout Wyoming.  Students compared vegetation condition during drought years to normal years and estimated the differences in spectral reflectance in different regions of the electromagnetic spectrum.  For example, Carla Gefroh (rangeland ecology major) compared the vegetation condition for her family ranch using images acquired in June 2002 and 2009, representing drought and wet years, respectively.  Landsat images highlighted changes in vegetation condition during the drought and wet years.

Monitoring vegetation response to drought was one topic in the class.  Other projects included monitoring vegetation condition in a growing season for estimating forage availability and areas of overgrazing.  The synoptic view provided by Landsat images was invaluable for gaining insights about vegetation condition in rangelands, and repeat coverage helped students to map those changes.

USGS Offers Landsat Satellite Images for Free

In December 2008, the entire Landsat satellite image archive was made available for free through the U.S. Geological Survey.  Previously, images had to be purchased (terrain corrected images could cost as much as $800) unless they were archived by programs like AmericaView (http://www.americaview.org) or on dedicated public Web sites like that of the Global Land Cover Facility (http://glcf.umiacs.umd.edu).

The recent availability of no-cost Landsat images has created opportunities and enhanced learning experiences for students. When fewer no-cost Landsat images were available, students had to modify the scope of their projects to match data availability.  Now, students can download any number of images for anywhere on earth.

UW students enrolled in the Applied Remote Sensing for Agricultural Management course are taking advantage of this valuable opportunity and are using these images for monitoring and mapping Wyoming croplands, rangelands, and forests.

Saturday, May 2, 2009

UW Range students present wildfire damage assessment research in the 2009 Undergraduate Research Day


Adam Stephens and Brice Stanton (BS Rangeland Ecology & Watershed Management major) presented their research on mapping burn severity near Deadwood, SD using Landsat images acquired prior and after the Grizzly Gulch Fire.  Brice had first hand knowledge of the burn severity at these sites from his work with the US Forest Service.  They determined burn severity classes, based on the changes in the Normalized Burn Ratio Index (NBRI) values in pre- and post-fire images.

Sites that burned the most (high severity) witnessed a large drop in their NBRI values between the pre- and post-fire images, while the unburned sites had no change.  They were able to associate remaining burn categories to the magnitude of change in the NBRI values.

Post-fire Landsat infrared image
Post-fire NBRI image
Burn severity map derived from pre- and post-fire Landsat images

Describing the value of this project in terms of his career, Brice said "I learned how to use remote sensing and apply it to the forest, by either grass management, or by being able to map a fire, and by learning how to do this I will be able to use what I have learned to be able to make decisions on the forest that I work."

This presentation was the second presentation by the WyomingView interns in annual Undergraduate Research Day event.

Title:  Mapping Burn Severity within the Grizzly Gulch Fire Using Remote Sensing Techniques.
Their presentation can be viewed at UW Digital Library.