Jeffrey C. Luvall

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

Thermal infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning.The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of landscape ecological processes.

Urban heat islands developing in coastal tropical cities

Beautiful and breezy cities on small tropical islands, it turns out, may not be exempt from the same local climate change effects and urban heat island effects seen in large continental cities such as Los Angeles or Mexico City. A surprising, recent discovery indicates that this is the case for San Juan, Puerto Rico, a relatively affluent coastal tropical city of about two million inhabitants that is spreading rapidly into the once-rural areas around it. A recent climatological analysis of the surface temperature of the city has revealed that the local temperature has been increasing over the neighboring vegetated areas at a rate of 0.06°C per year for the past 30 years. This is a trend that may be comparable to climate changes induced by global warming.

Climate Impacts of Land-Cover and Land-Use Changes in Tropical Islands under Conditions of Global Climate Change

AbstractLand-cover and land-use (LCLU) changes have significant climate impacts in tropical coastal regions with the added complexity of occurring within the context of a warming climate. The individual and combined effects of these two factors in tropical islands are investigated by use of an integrated mesoscale atmospheric modeling approach, taking the northeastern region of Puerto Rico as the test case. To achieve this goal, an ensemble of climate simulations is performed, combining two LCLU and global warming scenarios. Reconstructed agricultural maps and sea surface temperatures form the past (1955–59) scenario, while the present (2000–04) scenario is supported with high-resolution remote sensing LCLU data. Here, the authors show that LCLU changes produced the largest near-surface (2-m AGL) air temperature differences over heavily urbanized regions and that these changes do not penetrate the boundary layer. The influence of the global warming signal induces a positive inland gradient of maximum temp...

A Land–Atmospheric Interaction Study in the Coastal Tropical City of San Juan, Puerto Rico

Abstract This paper focuses on the surface–atmospheric interaction in a tropical coastal city including the validation of an atmospheric modeling and an impact study of land-cover and land-use (LCLU) changes. The Regional Atmospheric Modeling System (RAMS), driven with regional reanalysis data for a 10-day simulation, is used to perform the study in the San Juan metropolitan area (SJMA), one of the largest urban conglomerations in the Caribbean, which is located in the island of Puerto Rico and taken as the test case. The model’s surface characteristics were updated using airborne high-resolution remote sensing information to obtain a more accurate and detailed configuration of the SJMA. Surface and rawinsonde data from the San Juan Airborne Thermal and Land Applications Sensor (ATLAS) Mission are used to validate the modeling system, yielding satisfactory results in surface/canopy temperature, near-surface air temperatures, and vertical profiles. The impact analysis, performed with the updated SJMA confi...

BOUNDARY LAYER (ATMOSPHERIC) AND AIR POLLUTION | Urban Heat Islands

It is estimated that by the year 2025, 80% of the worlds population will live in cities. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. Research studies from many cities have documented that these effects range from decreases in air quality, increased energy consumption, and alteration of regional climate to direct effects on human health.

Intercomparison of Approaches to the Empirical Line Method for Vicarious Hyperspectral Reflectance Calibration

Analysis of visible remote sensing data research requires removing atmospheric effects by conversion from radiance to at-surface reflectance. This conversion can be achieved through theoretical radiative transfer models, which yield good results when well constrained by field observations, although these measurements are often lacking. Additionally, radiative transfer models often perform poorly in marine or lacustrine settings or when complex air masses with variable aerosols are present. The empirical line method (ELM) measures reference targets of known reflectance in the scene. ELM methods require minimal environmental observations and are conceptually simple. However, calibration coefficients are unique to the image containing the reflectance reference. Here we compare the conversion of hyperspectral radiance observations obtained with the NASA Glenn Research Center Hyperspectral Imager to at-surface reflectance factor using two reflectance reference targets. The first target employs spherical convex mirrors, deployed on the water surface to reflect ambient direct solar and hemispherical sky irradiance to the sensor. We calculate the mirror gain using near concurrent at-sensor reflectance, integrated mirror radiance, and in situ water reflectance. The second target is the Lambertian-like blacktop surface at Maumee Bay State Park, Oregon, OH, where reflectance was measured concurrently by a downward looking, spectroradiometer on the ground, the aerial hyperspectral imager and an upward looking spectroradiometer on the aircraft. These methods allows us to produce an independently calibrated at-surface water reflectance spectrum, when atmospheric conditions are consistent. We compare the mirror and blacktop-corrected spectra to the in situ water reflectance, and find good agreement between methods. The blacktop method can be applied to all scenes, while the mirror calibration method, based on direct observation of the light illuminating the scene validates the results. The two methods are complementary and a powerful evaluation of the quality of atmospheric correction over extended areas. We decompose the resulting spectra using varimax-rotated, principal component analysis, yielding information about the underlying color producing agents that contribute to the observed reflectance factor scene, identifying several spectrally and spatially distinct mixtures of algae, cyanobacteria, illite, haematite and goethite. These results have implications for future hyperspectral remote sensing missions, such as PACE, HyspIRI, and GeoCAPE.

The use of the Airborne Thermal/Visible Land Application Sensor (ATLAS) to Determine the Thermal Response Numbers for Urban Areas.

The additional heating of the air over the city is the result of the replacement of naturally vegetated surfaces with those composed of asphalt, concrete, rooftops and other man-made materials. The temperatures of these artificial surfaces can be 20 to 40degC higher than vegetated surfaces. This produces a dome of elevated air temperatures 5 to 8degC greater over the city, compared to the air temperatures over adjacent rural areas. Urban landscapes are a complex mixture of vegetated and non vegetated surfaces. It is difficult to take enough temperature measurements over a large city area to characterize the complexity of urban radiant surface temperature variability. The NASA Airborne Thermal and Land Applications Sensor (ATLAS) operates in the visual and IR bands was used in February 2004 to collect data from San Juan, Puerto Rico with the main objective of investigating the Urban Heat Island (UHI) in tropical cities. Ref. [1] developed the TRN (thermal response number) as a technique using aircraft remotely sensed surface temperatures to quantify the thermal response of urban surfaces. The TRN was used to quantify the thermal response of various urban surface types ranging from completely vegetated surfaces to asphalt pavements for San Juan, Puerto Rico.