Wim Van Leeuwen | University of Arizona (original) (raw)

Papers by Wim Van Leeuwen

S OF PRESENTED PAPERS (LISTED ALPHABETICALLY BY FIRST AUTHOR) 25 YEARS ON A MOUNTAIN TRAIL: A FLO... more S OF PRESENTED PAPERS (LISTED ALPHABETICALLY BY FIRST AUTHOR) 25 YEARS ON A MOUNTAIN TRAIL: A FLORISTIC STUDY OF AN ARIZONA CANYON BERTELSEN, DAVID University of Arizona Herbarium, University of Arizona, Tucson, AZ, dbertelsen1@cox.net Since 1984 I have recorded all flowering plant taxa along a five-mile trail that climbs 4158 ft into the Santa Catalina Mountains. With a primary focus on an area 30 ft on either side of the trail, a “transect” of about 1.6 million ft2, I amassed 111,012 records along five trail segments during 1024 hikes in the first 20 years. I also compiled a flora of 596 specific and infraspecific taxa. The flora and its phenology are extremely variable, both temporally and spatially. Although taxa were added each year, decreasing annual rainfall and increasing average annual temperature have been accompanied by a decreasing proportion of know taxa seen in bloom. Annually, a strongly bimodal distribution, with spring and summer peaks, was seen for the flora as a w...

iEXECUTIVE SUMMARY One of the primary interests of the Earth Observing System (EOS) program is to... more iEXECUTIVE SUMMARY One of the primary interests of the Earth Observing System (EOS) program is to study the role of terrestrial vegetation in large-scale global processes with the goal of understanding how the Earth functions as a system. This requires an understanding of the global distribution of vegetation types as well as their biophysical and structural properties and spatial/temporal variations. Vegetation Indices (VI) are robust, empirical measures of vegetation activity at the land surface. They are designed to enhance the vegetation signal from measured spectral responses by combining two (or more) different wavebands, often in the red (0.6-0.7 mm) and NIR wavelengths (0.7-1.1 mm). The MODIS vegetation index (VI) products will provide consistent, spatial and temporal comparisons of global vegetation conditions which will be used to monitor the Earth's terrestrial photosynthetic vegetation activity in support of phenologic, change detection, and biophysical interpretati...

diometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a... more diometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research. The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring. These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assess-ment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations. The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard

International Journal of Remote Sensing, 2011

Riparian systems have become increasingly susceptible to both natural and human disturbances as c... more Riparian systems have become increasingly susceptible to both natural and human disturbances as cumulative pressures from changing land use and climate alter the hydrological regimes. This article introduces a landscape dynamics monitoring protocol that incorporates riparian structural classes into the land-cover classification scheme and examines riparian change within the context of surrounding land-cover change. We tested whether Landsat Thematic Mapper

PLOS ONE, 2015

Spatial variation in resources is a fundamental driver of habitat quality but the realized value ... more Spatial variation in resources is a fundamental driver of habitat quality but the realized value of resources at any point in space may depend on the effects of conspecifics and stochastic factors, such as weather, which vary through time. We evaluated the relative and combined effects of habitat resources, weather, and conspecifics on habitat quality for ferruginous pygmy-owls (Glaucidium brasilianum) in the Sonoran Desert of northwest Mexico by monitoring reproductive output and conspecific abundance over 10 years in and around 107 territory patches. Variation in reproductive output was much greater across space than time, and although habitat resources explained a much greater proportion of that variation (0.70) than weather (0.17) or conspecifics (0.13), evidence for interactions among each of these components of the environment was strong. Relative to habitat that was persistently low in quality, high-quality habitat buffered the negative effects of conspecifics and amplified the benefits of favorable weather, but did not buffer the disadvantages of harsh weather. Moreover, the positive effects of favorable weather at low conspecific densities were offset by intraspecific competition at high densities. Although realized habitat quality declined with increasing conspecific density suggesting interference mechanisms associated with an Ideal Free Distribution, broad spatial heterogeneity in habitat quality persisted. Factors linked to food resources had positive effects on reproductive output but only where nest cavities were sufficiently abundant to mitigate the negative effects of heterospecific enemies. Annual precipitation and brooding-season temperature had strong multiplicative effects on reproductive output, which declined at increasing rates as drought and temperature increased, reflecting conditions predicted to become more frequent with climate change. Because the collective environment influences habitat quality in complex ways, integrated approaches that consider habitat resources, stochastic factors, and conspecifics are necessary to accurately assess habitat quality.

Remote Sensing, 2011

Remotely sensed multi-spectral and-spatial data facilitates the study of mosquito-borne disease v... more Remotely sensed multi-spectral and-spatial data facilitates the study of mosquito-borne disease vectors and their response to land use and cover composition in the urban environment. In this study we assess the feasibility of integrating remotely sensed multispectral reflectance data and LiDAR (Light Detection and Ranging)-derived height information to improve land use and land cover classification. Classification and Regression Tree (CART) analyses were used to compare and contrast the enhancements and accuracy of the multi-sensor urban land cover classifications. Eight urban land-cover classes were developed for the city of Tucson, Arizona, USA. These land cover classes focus on pervious and impervious surfaces and microclimate landscape attributes that impact mosquito habitat such as water ponds, residential structures, irrigated lawns, shrubs and trees, shade, and humidity. Results show that synergistic use of LiDAR, multispectral and the Normalized Difference Vegetation Index data produced the most accurate urban land cover classification with a Kappa value of 0.88. Fusion of multi-sensor data leads to a better land cover product that is suitable for a variety of urban applications such as exploring the relationship between neighborhood composition and adult mosquito abundance data to inform public health issues.

Remote Sensing, 2013

Increasing water use and droughts, along with climate variability and land use change, have serio... more Increasing water use and droughts, along with climate variability and land use change, have seriously altered vegetation growth patterns and ecosystem response in several regions alongside the Andes Mountains. Thirty years of the new generation biweekly normalized difference vegetation index (NDVI3g) time series data show significant land cover specific trends and variability in annual productivity and land surface phenological response. Productivity is represented by the growing season mean NDVI values (July to June). Arid and semi-arid and sub humid vegetation types (Atacama desert, Chaco and Patagonia) across Argentina, northern Chile, northwest Uruguay and southeast Bolivia show negative trends in productivity, while some temperate forest and agricultural areas in Chile and sub humid and humid areas in Brazil, Bolivia and Peru show positive trends in productivity. The start (SOS) and length (LOS) of the growing season results show large variability and regional hot spots where later SOS often coincides with reduced productivity. A longer growing season is generally found for some locations in the south of Chile (sub-antarctic forest) and Argentina (Patagonia steppe), while central Argentina (Pampa-mixed grasslands and agriculture) has a shorter LOS. Some of the areas have significant shifts in SOS and LOS of one to several months. The seasonal Multivariate ENSO Indicator (MEI) and the Antarctic Oscillation (AAO) index have a significant

... three important fisheries, because rains that followed the wildfire caused a significant incr... more ... three important fisheries, because rains that followed the wildfire caused a significant increase ... modeling and GIS The geo-spatial land degradation modeling and GIS integration (ARC ... The first stage involves the static geospatial database integration and analysis of slope length ...

In situ radiometric field data and data simulated with a radiative transfer model were used to ev... more In situ radiometric field data and data simulated with a radiative transfer model were used to evaluate the performance and biophysical interpretation of spectral indices. Concurrently with remotely sensed measurements, temporal biophysical measurements for different ...

To improve the ability to observe, understand, and predict climate and its response to changes in... more To improve the ability to observe, understand, and predict climate and its response to changes in global environment, accurate albedo observations are of vital importance. This investigation evaluated the uncertainties in short-wave (300-4000nm) albedo, visible (400-700nm) albedo and near-infrared (NIR: 700-4000nm) albedo derived from geo-stationary (Meteosat Second Generation - MSG) and polar orbiting (Advanced Very High Resolution Radiometer-3 - AVHRR-3)

IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), 2001

This investigation evaluated the uncertainties in albedo derived from geostationary and polar orb... more This investigation evaluated the uncertainties in albedo derived from geostationary and polar orbiting optical sensors with emphasis on the spectral characteristics, angular sampling and atmospheric correction issues. Albedo simulations were achieved by using satellite orbital models and the SAIL code to produce synthetic bidirectional reflectance data sets for a range of vegetation canopies. Among the list of BRDF model candidates

Background/Question/Methods Much of the Earth’s vegetation communities can be seen as existing al... more Background/Question/Methods Much of the Earth’s vegetation communities can be seen as existing along a continuum of woody plant cover; grasslands, shrublands and forests are examples of these. The degree of woody cover at a site or landscape can influence nutrient and hydrological cycles as well as phenological variability and overall productivity. Woody cover continuums are exemplified over elevation gradients such as the Sky Islands of southwestern USA; along these gradients, biogeography is compressed and sensitivity to disturbances like drought and wildfire is high. Methods are needed to detect and quantify vegetation change along such gradients. Numerous studies have highlighted trends in vegetation and associated ecosystem properties along vegetation gradients such as Sky Islands. Additionally, many remote sensing-based studies have assessed site- to global-scale vegetation phenology, often using greenness metrics such as the Normalized Difference Vegetation Index. However, st...

Sensors, 2008

This study examines how satellite based time-series vegetation greenness data and phenological me... more This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer -Normalized Difference Vegetation Index) data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre-and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR) and examine burn severity at the selected sites. The phenological metrics (pheno-metrics) included the timing and greenness (i.e. NDVI) for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation cover dynamics and successional Sensors 2008, 8 2018 changes in response to drought, wildfire disturbances, and forest restoration treatments in fire-suppressed forests.

Remote Sensing of Environment, 2002

This investigation aims at quantifying the various sources of uncertainties in the derivation of ... more This investigation aims at quantifying the various sources of uncertainties in the derivation of albedo products from geo-stationary and polar orbiting optical systems with emphasis on the sensor and surface type (soil, snow, vegetation) spectral characteristics, atmospheric condition, and angular sampling issues. This research specifically takes into account the uncertainties in albedo that we can expect due to the synergistic use of the European Polar System (EPS)/Advanced Very High Resolution Radiometer (AVHRR) and Meteosat Second Generation (MSG)/Scanning Enhanced Visible and Infrared Imager (SEVIRI) instruments data. Satellite orbital models and a Scattering by Arbitrarily Inclined Leaves (SAIL)-hotspot canopy radiative transfer model were used to simulate synthetic bidirectional reflectance data sets for a broad range of vegetation canopies. The surface bidirectional reflectance distribution function (BRDF) database derived from the Polarization and Directionality of Earth Reflectance (POLDER) data was used in support of the simulations. Spectral atmospheric effects were generated using the 6S atmospheric radiative transfer code. Linear BRDF models, which are candidates for operational use, were inverted with the synthetic reflectance data sets of MSG, AVHRR and MSG -AVHRR combined. The BRDF parameters were then used to derive albedo by hemispherical angular integration. The retrieved model coefficients are discussed with regard to angular sampling and the implications these yield on spectral and broadband albedo determinations. It appears that the sampling problem is better conditioned thanks to the synergistic nature of MSG and AVHRR data. This synergy contributed to enhanced albedo retrievals, but can introduce larger uncertainties due to issues related to the differences in spectral bands and atmospheric state. Hence, the quality of the operational albedo products derived from one or more sources of satellite data will depend to a large extent on sensor characteristics (spectral, radiometric, and geometric), cloud detection, atmospheric correction, the angular distribution of the observations, and finally, the narrow-to-broadband albedo conversion. D

Journal of Vector Ecology, 2012

It is currently unclear what role microhabitat land cover plays in determining the seasonal spati... more It is currently unclear what role microhabitat land cover plays in determining the seasonal spatial distribution of Aedes aegypti and Culex quinquefasciatus, disease vectors of dengue and West Nile Virus, respectively, in Tucson, AZ. We compared mosquito abundance to sixteen land cover variables derived from 2010 NAIP multispectral data and 2008 LiDAR height data. Mosquitoes were trapped with 30-49 traps from May to October of 2010 and 2011. Variables were extracted for five buffer zones (10-50 m radii at 10 m intervals) around trapping sites. Stepwise regression was performed to determine the best scale for observation and the influential land cover variables. The 30 m radius buffer was determined to be the best for observing the land cover-mosquito abundance relationship. Ae. aegypti presence was positively associated with structure and medium height trees and negatively associated with bare earth; Cx. quinquefasciatus presence was positively associated with pavement and medium height trees and negatively associated with shrubs. These findings emphasize vegetation, impervious surfaces, and soil influences on mosquito presence in an urban setting. Lastly, the land cover-mosquito abundance relationships were used to produce risk maps of seasonal presence that highlight high risk areas in Tucson, which may be useful for focusing mosquito control program actions. Journal of Vector Ecology 37 (2): 407-418. 2012.

Journal of Arid Environments, 2014

This research investigates the human impact on land-cover dynamics in arid agro-ecosystems. Our s... more This research investigates the human impact on land-cover dynamics in arid agro-ecosystems. Our study area was La Costa de Hermosillo (northwestern Mexico), where the unregulated use of water resources has resulted in the abandonment of irrigated agricultural fields and a shift to new economic activities. Using remote sensing and ancillary datasets combined with classification and regression tree (CART) models, we mapped land-cover class distributions over 22 years (1988e2009) to characterize agricultural changes following management decisions. Our land-cover classification maps had an overall accuracy of over 80%. Using these maps, we were able to show the decrease in agriculture from approximately 115,066 to 66,044 ha between 1988 and 2009 and the conversion to alternative economic activities, with aquaculture increasing from 0 to 10,083 ha during the same period. Our analyses also show the temporalespatial dynamics of land-use management practices, which suggest that implementation of the remote sensing methods developed in this manuscript may contribute to bridging the gap of knowledge between ecological effects and unsustainable management practices and decrease the time required to inform and make policy decisions in arid agro-ecosystems.

International Journal of Remote Sensing, 2012