Geology topics

John M. Vogel

Publications and source records attributed to John M. Vogel.

9 recordsLinked to original sources

USGS2016

Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C 4 ) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI 2 ) data from Landsat to develop the NDPI, and MSAVI 2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI 2 and summer maximum MSAVI 2 ), and two simple, conventional VI metrics (summer average MSAVI 2 , summer maximum MSAVI 2 ). The NDPI in a scaled form (NDPI s ) performed best in predicting variation in perennial C 4 grass cover as estimated from landscape photographs at 92 sites (R 2 = 0.76, p < 0.001), indicating improvement over the alternate DVP metric (R 2 = 0.73, p < 0.001) and substantial improvement over the two conventional VI metrics (R 2 = 0.62 and 0.56, p < 0.001). The results suggest DVP-based methods, and the NDPI in particular, can be effective for subpixel discrimination and mapping of exposed perennial C 4 grass cover within mixed-composition landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

Arizona↗

USGS2016

Vegetative response to water availability on the San Carlos Apache Reservation

On the San Carlos Apache Reservation in east-central Arizona, U.S.A., vegetation types such as ponderosa pine forests, pinyon-juniper woodlands, and grasslands have significant ecological, cultural, and economic value for the Tribe. This value extends beyond the tribal lands and across the Western United States. Vegetation across the Southwestern United States is susceptible to drought conditions and fluctuating water availability. Remotely sensed vegetation indices can be used to measure and monitor spatial and temporal vegetative response to fluctuating water availability conditions. We used the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Modified Soil Adjusted Vegetation Index II (MSAVI 2 ) to measure the condition of three dominant vegetation types (ponderosa pine forest, woodland, and grassland) in response to two fluctuating environmental variables: precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI). The study period covered 2002 through 2014 and focused on a region within the San Carlos Apache Reservation. We determined that grassland and woodland had a similar moderate to strong, year-round, positive relationship with precipitation as well as with summer SPEI. This suggests that these vegetation types respond negatively to drought conditions and are more susceptible to initial precipitation deficits. Ponderosa pine forest had a comparatively weaker relationship with monthly precipitation and summer SPEI, indicating that it is more buffered against short-term drought conditions. This research highlights the response of multiple, dominant vegetation types to seasonal and inter-annual water availability. This research demonstrates that multi-temporal remote sensing imagery can be an effective tool for the large scale detection of vegetation response to adverse impacts from climate change and support potential management practices such as increased monitoring and management of drought-affected areas. Different vegetation types displayed various responses to water availability, further highlighting the need for individual management plans for forest and woodland, especially considering the projected drier conditions in the Southwest U.S. and other arid or semi-arid regions around the world.

Arizona↗

USGS2016

Estimating forest and woodland aboveground biomass using active and passive remote sensing

Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R 2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14 Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1 . Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States.

Photogrammetric Engineering and Remote Sensing↗

USGS2016

Evaluating lidar point densities for effective estimation of aboveground biomass

The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m 2 , corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m 2 . Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m 2 , and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m 2 , our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

International Journal of Advanced Remote Sensing a↗

USGS2016

MODIS derived vegetation index for drought detection on the San Carlos Apache Reservation

A variety of vegetation indices derived from remotely sensed data have been used to assess vegetation conditions, enabling the identification of drought occurrences as well as the evaluation of drought impacts. Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite data were used to compute the Modified Soil Adjusted Vegetation Index II (MSAVI 2 ) of four dominant vegetation types over a 13-year period (2002 – 2014) on the San Carlos Apache Reservation in Arizona, US. MSAVI 2 anomalies were used to identify adverse impacts of drought on vegetation, characterized as mean MSAVI 2 below the 13-year average. In terms of interannual variability, we found similar responses between grassland and shrubland, and between woodland and forest vegetation types. We compared MSAVI 2 for specific vegetation types with precipitation data at the same time step, and found a lag time of roughly two months for the peak MSAVI 2 values following precipitation in a given year. All vegetation types responded to summer monsoon rainfall, while shrubland and annual herbaceous vegetation also displayed a brief spring growing season following winter snowmelt. MSAVI 2 values of shrublands corresponded well with precipitation variability both for summer rainfall and winter snowfall, and can be potentially used as a drought indicator on the San Carlos Apache Reservation given its wide geographic distribution. We demonstrated that moderate temporal frequency satellite-based MSAVI 2 can provide drought monitoring to inform land management decisions, especially on vegetated tribal land areas where in situ precipitation data are limited.

International Journal of Advanced Remote Sensing a↗

USGS2015

Field measurement and analysis of climatic factors affecting dune mobility near Grand Falls on the Navajo Nation, southwestern United States

Aeolian sand covers extensive areas of the Navajo Nation in the southwestern United States. Much of this sand is currently stabilized by vegetation, although many drier parts of these Native lands also have active and partly active dunes. Current prolonged drought conditions that started in the mid-1990s are producing significant changes in dune mobility. Reactivation of regional aeolian deposits due to drought or increasing aridity from rising temperatures resulting from climate change could have serious consequences for human and animal populations, agriculture, grazing, and infrastructure. To understand and document the current and future potential for mobility, seasonally repeated surveys were used to track the location of multiple active barchan dunes. By utilizing Real-Time Kinematic GPS field surveys and simultaneously collecting in-situ meteorological data, it is possible to examine climatic parameters and seasonal variations that affect dune mobility and their relative influences. Through analysis of the recorded data, we examined the fit of various climate parameters, and demonstrate that under the current prolonged drought, wind power is the dominant factor controlling dune mobility.

Arizona↗

USGS2015

Aeolian responses to climate variability during the past century on Mesquite Lake Playa, Mojave Desert

The erosion and deposition of sediments by wind from 1901 to 2013 have created large changes in surface features of Mesquite Lake playa in the Mojave Desert. The decadal scale recurrence of sand-sheet development, migration, and merging with older dunes appears related to decadal climatic changes of drought and wetness as recorded in the precipitation history of the Mojave Desert, complemented by modeled soil-moisture index values. Historical aerial photographs, repeat land photographs, and satellite images document the presence and northward migration of a mid-20th century sand sheet that formed during a severe regional drought that coincided with a multi-decadal cool phase of the Pacific Decadal Oscillation (PDO). The sand sheet slowly eroded during the wetter conditions of the subsequent PDO warm phase (1977–1998) due to a lack of added sediment. Sand cohesion gradually increased in the sand sheet by seasonal additions of salt and clay and by re-precipitation of gypsum, which resulted in the wind-carving of yardangs in the receding sand sheet. Smaller yardangs were aerodynamically shaped from coppice dunes with salt-clay crusts, and larger yardangs were carved along the walls and floor of trough blowouts. Evidence of a 19th century cycle of sand-sheet formation and erosion is indicated by remnants of yardangs, photographed in 1901 and 1916, that were found buried in the mid-20th century sand sheet. Three years of erosion measurements on the playa, yardangs, and sand sheets document relatively rapid wind erosion. The playa has lowered 20 to 40 cm since the mid-20th century and a shallow deflation basin has developed since 1999. Annually, 5–10 cm of surface sediment was removed from yardang flanks by a combination of wind abrasion, deflation, and mass movement. The most effective erosional processes are wind stripping of thin crusts that form on the yardang surfaces after rain events and the slumping of sediment blocks from yardang flanks. These wind-eroded landforms persist several decades to a century before eroding away or being buried by younger sands. On Mesquite Lake playa the climatic history of alternating PDO phases of multi-decadal drought and wetness is recorded twice by the presence of yardangs formed nearly a century apart.

Mesquite Lake, Mojave Desert↗

USGS2015

Vegetation burn severity mapping using Landsat-8 and WorldView-2

We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

Photogrammetric Engineering and Remote Sensing↗

USGS2011

Monitoring and analysis of sand dune movement and growth on the Navajo Nation, southwestern United States

Recurring drought and rising temperatures have caused reactivation and renewed growth of sand dunes on the lands of the Navajo Nation on the Colorado Plateau. Migrating dunes threaten health, housing, and transportation pathways. U.S. Geological Survey (USGS) scientists are conducting research to better understand the processes of dune growth and movement. This research will provide critical data to the Native peoples of the region in their response to the changing environment.

Colorado Plateau↗