Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure

Reducing the Uncertainties in Direct Aerosol Radiative Forcing

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction

The plankton, aerosol, cloud, ocean ecosystem mission status, science, advances

The Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) mission represents the National Aeronautics and Space Administration\u27s (NASA) next investment in satellite ocean color and the study of Earth\u27s ocean-atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth\u27s changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food-web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave-infrared wavelengths, with a ground sample distance of 1 km at nadir. This payload is complemented by two multiangle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022 to early 2023, the PACE observatory will enable significant advances in the study of Earth\u27s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean-atmosphere-land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products

Applications of Remote Sensing to Alien Invasive Plant Studies

Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions. Therefore, it is often important to systematically monitor the spread of species over a broad region. Remote sensing has been an important tool for large-scale ecological studies in the past three decades, but it was not commonly used to study alien invasive plants until the mid 1990s. We synthesize previous research efforts on remote sensing of invasive plants from spatial, temporal and spectral perspectives. We also highlight a recently developed state-of-the-art image fusion technique that integrates passive and active energies concurrently collected by an imaging spectrometer and a scanning-waveform light detection and ranging (LiDAR) system, respectively. This approach provides a means to detect the structure and functional properties of invasive plants of different canopy levels. Finally, we summarize regional studies of biological invasions using remote sensing, discuss the limitations of remote sensing approaches, and highlight current research needs and future directions

Simulation of multiangular remote sensing products using small satellite formations

To completely capture the multiangular reflectance of an opaque surface, one must estimate the bidirectional reflectance distribution function (BRDF), which seeks to represent variations in surface reflectance as a function of measurement and illumination angles at any time instant. The gap in angular sampling abilities of existing single satellites in Earth observation missions can be complemented by small satellites in formation flight. The formation would have intercalibrated spectrometer payloads making reflectance measurements, at many zenith and azimuthal angles simultaneously. We use a systems engineering tool coupled with a science evaluation tool to demonstrate the performance impact and mission feasibility. Formation designs are generated and compared to each other and multisensor single spacecraft, in terms of estimation error of BRDF and its dependent products such as albedo, light use efficiency (LUE), and normalized difference vegetation index (NDVI). Performance is benchmarked with respect to data from previous airborne campaigns (NASA's Cloud Absorption Radiometer), and tower measurements (AMSPEC II), and assuming known BRDF models. Simulations show that a formation of six small satellites produces lesser average error (21.82%) than larger single spacecraft (23.2%), purely in terms of angular sampling benefits. The average monolithic albedo error of 3.6% is outperformed by a formation of three satellites (1.86%), when arranged optimally and by a formation of seven to eight satellites when arranged in any way. An eight-satellite formation reduces albedo errors to 0.67% and LUE errors from 89.77% (monolithic) to 78.69%. The average NDVI for an eight satellite, nominally maintained formation is better than the monolithic 0.038

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying “photosynthetic phenology” from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a “chlorophyll/carotenoid index” (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA’s Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying “photosynthetic phenology” from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a “chlorophyll/carotenoid index” (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA’s Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology

Aerosol characteristics over different regions of southern Africa : using sunphotometer and satellite measurements.

Ph. D. University of KwaZulu-Natal, Durban 2015.Aerosols and cloud play a major role in understanding and interpreting the varying earth’s energy budget. It is necessary to characterize these atmospheric particles by their sizes, chemical composition, water content etc. Aerosols can both cause heating and cooling depending on what they are made of; dust will generally tend to scatter leading to cooling effect while some species of black carbon will absorb sunlight thereby causing a heating effect. In order to assess their impact on global climate, a multiple measurement approach is necessary and specifically, we need long and short term ground-based measurements in clean and polluted environment and long term satellite measurements. In this thesis, we have used aerosol measurements from CIMEL Sunphotometer (part of the world-wide network; Aerosol Robotic Network: AERONET) over, Pretoria (25.75º S, 28.28º E) and Skukuza (24.9º S, 31.5º E) in South Africa, and satellite data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). Pretoria is situated in industrial region with adequate influence of urban/industrial aerosols while Skukuza is an agricultural based region with frequent burning of agricultural waste to clear the harvest during the late winter, spring and summer seasons. Thus, the study over industrial and agricultural regions explores more understanding about the regional radiative forcing in relation to aerosol loading and meteorology. MODIS satellite data was utilized for addressing long term trend in aerosol loading and cloud interaction studies over different locations of South Africa where no ground based sunphotometer data are available. Using six months sunphotometer data (July–December 2012), aerosol characteristics over Gorongosa were studied with particular attention to how aerosol loading evolves during the biomass burning season (spring) including pre- and post-months. The results revealed that the monthly mean aerosol optical depth (AOD₅₀₀) was at maximum in September and minimum in November. The study also investigated biomass burning and forest fire occurrences in Mozambique using MODIS active fire data. Using a year sunphotometer data (January – December 2012) obtained from Pretoria’s (CSIR_DPPS) AERONET site, aerosol was characterized by its optical, microphysical and radiative properties. The study explored meteorological effects on aerosol loading and aerosol direct radiative forcing over Pretoria. Maximum value of aerosol optical depth (AOD₅₀₀) was found during February (summer) and August (winter) while the atmospheric forcing was found to be independent of seasonal variation in AOD. Besides, AOD, Angstrom exponent (AE; α440-870), columnar water vapor (CWV), volume size distribution (VSD), single scattering albedo (SSA) and aerosol radiative forcing (ARF) were computed and their variations with their climatic implications were studied. Using the ground-based instrument of AERONET at Skukuza, we performed validation of MISR and MODIS (Terra and Aqua) level 3 AOD products using the data retrieved for the year 2010. We also carried out regression analysis on these satellite products using 10 years of dataset (2004-2013) to evaluate their performance at a hinterland and coastland stations with two distinct environments in SA. The validation showed that MISR was better correlated with sunphotometer having a coefficient of determination (R²=0.94), Aqua MODIS (R²=0.77) and Terra MODIS (R²=0.68). The long term regression analysis at the two selected locations showed MODIS products underestimating MISR. At the hinterland, MISR showed an increasing trend while MODIS products showed a decreasing trend over the study period but at the coastland MISR and Terra MODIS showed a negative trend while Aqua MODIS showed a positive trend. When the two MODIS products were compared, they were better correlated at the coastland (R²=0.66) than hinterland (R²=0.59) and when compared based on seasonal variation, they were better correlated in the winter season in both locations than any other season. The Ozone Monitoring Instrument (OMI) Ultra-Violet Aerosol Index (UVAI) which was used to monitor the absorption aerosol index showed an increasing trend over the two locations with 0.0089/yr hinterland and 0.0022/yr at coastland. In the present thesis, we also used data obtained from the Terra satellite onboard of the MODIS to investigate the spatial and temporal relationship between AOD and cloud parameters namely, water vapor (WV), cloud optical depth (COD), cloud fraction (CF), cloud top pressure (CTP) and cloud top temperature (CTT) based on 5 years (January 2008 -December 2012) of dataset over six locations in South Africa. AOD has high values during spring (September to November) but low values in winter (June to August) in all locations. In terms of temporal variation AOD was lowest at Bloemfontein 0.06±0.04 followed by Cape Town 0.08±0.02, then Potchefstroom 0.09±0.05, Pretoria and Skukuza had 0.11±0.05 each and Durban 0.13±0.05. The mean AE values for each location show a general prevalence of fine particles for most parts of the year. Our analysis of AOD and WV showed both quantities only co-vary at the beginning of the year but later in the year they tend to have opposite trend over all the locations. AOD and CF showed negative correlation for most of the locations while AOD and COD were positive over three of the locations. AOD and CTT, CTP showed similar variations in almost all the locations. The co-variation of CTT and CTP may be due to large scale meteorological variation