Insights Into the Aerodynamic Versus Radiometric Surface Temperature Debate in Thermal-Based Evaporation Modeling

Global evaporation monitoring from Earth observation thermal infrared satellite missions is historically challenged due to the unavailability of any direct measurements of aerodynamic temperature. State-of-the-art one-source evaporation models use remotely sensed radiometric surface temperature as a substitute for the aerodynamic temperature and apply empirical corrections to accommodate for their inequality. This introduces substantial uncertainty in operational drought mapping over complex landscapes. By employing a non-parametric model, we show that evaporation can be directly retrieved from thermal satellite data without the need of any empirical correction. Independent evaluation of evaporation in a broad spectrum of biome and aridity yielded statistically significant results when compared with eddy covariance observations. While our simplified model provides a new perspective to advance spatio-temporal evaporation mapping from any thermal remote sensing mission, the direct retrieval of aerodynamic temperature also generates the highly required insight on the critical role of biophysical interactions in global evaporation research

Insights into the aerodynamic versus radiometric surface temperature debate in thermal-based evaporation modeling

Global evaporation monitoring from Earth observation thermal infrared satellite missions is historically challenged due to the unavailability of any direct measurements of aerodynamic temperature. State-of-the-art one-source evaporation models use remotely sensed radiometric surface temperature as a substitute for the aerodynamic temperature and apply empirical corrections to accommodate for their inequality. This introduces substantial uncertainty in operational drought mapping over complex landscapes. By employing a non-parametric model, we show that evaporation can be directly retrieved from thermal satellite data without the need of any empirical correction. Independent evaluation of evaporation in a broad spectrum of biome and aridity yielded statistically significant results when compared with eddy covariance observations. While our simplified model provides a new perspective to advance spatio-temporal evaporation mapping from any thermal remote sensing mission, the direct retrieval of aerodynamic temperature also generates the highly required insight on the critical role of biophysical interactions in global evaporation research

UAS-based multi-angular remote sensing of the effects of soil management strategies on grapevine

Aims: The present investigation in a Luxembourgish vineyard aimed at evaluating the potential of multispectral, multi-angular UAS (unmanned aerial system) imagery to separate four soil management strategies, to predict physiological variables (chlorophyll, nitrogen, yield etc.) and to follow seasonal changes in grapevine physiology in relation to soil management. Methods and results: Multi-angular (nadir and 45° off-nadir) multispectral imageries (530-900 nm) were taken in the years 2011 and 2012. Image grey values and reflectance-derived vegetation indices were computed and canopy and vigour properties were monitored in the field. All four soil management strategies could be significantly discriminated (box-plots, linear discriminant analysis) and vegetation properties estimated (linear regression) in 2011. For 2012, global models predicted chlorophyll contents and nitrogen balance index values with a R²cv of 0.65 and 0.76, respectively. Conclusions: Soil management strategies strongly affect plant vigour and reflectance. Differences were best detectable by oblique visible/near-infrared (Vis/nIR) UAS data of illuminated canopies. Significance and impact of the study: UAS imaging is a flexible tool for applications in precision viticulture

Retrieving the Bioenergy Potential from Maize Crops Using Hyperspectral Remote Sensing

Biogas production from energy crops by anaerobic digestion is becoming increasingly important. The amount of biogas that can be produced per unit of biomass is referred to as the biomethane potential (BMP). For energy crops, the BMP varies among varieties and with crop state during the vegetation period. Traditional ways of analytical BMP determination are based on fermentation trials and require a minimum of 30 days. Here, we present a faster method for BMP retrievals using near infrared spectroscopy and partial least square regression (PLSR). PLSR prediction models were developed based on two different sets of spectral reflectance data: (i) laboratory spectra of silage samples and (ii) airborne imaging spectra (HyMap) of maize canopies under field (in situ) conditions. Biomass was sampled from 35 plots covering different maize varieties and the BMP was determined as BMP per mass (BMPFM, Nm3 biogas/t fresh matter (Nm3/t FM)) and BMP per area (BMParea, Nm3 biogas/ha (Nm3/ha)). We found that BMPFM significantly differs among maize varieties; it could be well retrieved from silage samples in the laboratory approach (Rcv2 = 0.82, n = 35), especially at levels >190 Nm3/t. In the in situ approach PLSR prediction quality declined (Rcv2 = 0.50, n = 20). BMParea, on the other hand, was found to be strongly correlated with total biomass, but could not be satisfactorily predicted using airborne HyMap imaging data and PLSR

UAS-based multi-angular remote sensing of the effects of soil management strategies on grapevine

Aims: The present investigation in a Luxembourgish vineyard aimed at evaluating the potential of multispectral, multi-angular UAS (unmanned aerial system) imagery to separate four soil management strategies, to predict physiological variables (chlorophyll, nitrogen, yield etc.) and to follow seasonal changes in grapevine physiology in relation to soil management. Methods and results: Multi-angular (nadir and 45° off-nadir) multispectral imageries (530-900 nm) were taken in the years 2011 and 2012. Image grey values and reflectance-derived vegetation indices were computed and canopy and vigour properties were monitored in the field. All four soil management strategies could be significantly discriminated (box-plots, linear discriminant analysis) and vegetation properties estimated (linear regression) in 2011. For 2012, global models predicted chlorophyll contents and nitrogen balance index values with a R²cv of 0.65 and 0.76, respectively. Conclusions: Soil management strategies strongly affect plant vigour and reflectance. Differences were best detectable by oblique visible/near-infrared (Vis/nIR) UAS data of illuminated canopies. Significance and impact of the study: UAS imaging is a flexible tool for applications in precision viticulture

A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing

This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1–5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2–12.5 µm (instrument NEDT 0.05 K–0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0–10.25 µm and 10.25–12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1–3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval

High Resolution Temperature and Spectral Emissivity Mapping (HITESEM)

The “High resolution temperature and spectral emissivity mapping” (HiTeSEM) initiative aims at developing a conceptual instrument design for a hyperspectral thermal satellite to find answers for the most pressing research and data requirements within the scope of Food Security and Human Health. The satellite is proposed to consist of two long-wave infrared (LWIR) sensors, (1) a hyperspectral system with ~ 75 bands at 7.2 - 12.5 μm (NEΔT of <; 0.05 K) and a ground sampling distance (GSD) of 60 m and (2) a panchromatic (PAN) LWIR high resolution imager with two bands (8.0 - 10.25 μm and 10.25 - 12.5 μm, NEΔT of ~0.06 K) but a three times higher GSD of 20 m to extend the system to regional applications where higher spatial accuracy is required. For an accurate water vapor content (CWV) estimation, which is needed for accurate atmospheric correction and temperature-emissivity separation (TES), three wavelengths within the range 7.2-7.3 μm are used. Based on the science case, key regions of interest were identified in India, Asia, Andes mountains, Mediterranean ecosystems and densely-populated as well as growing regions

HiTeSEM: A Satellite sensor concept for Hyperspectral Thermal Remote Sensing

HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping) is a preparatory study, funded by the German Aerospace Center (DLR) that aims preparing the floor for a future spaceborn hyperspectral thermal mission. Thermal remote sensing is poised to become a major source of information on land surface processes. HiTeSEM aims at closing the research gap still hampering utilization of the thermal infrared data at reasonable spectral and spatial resolution and focusses on surface-solid Earth interactions to assess natural and human-induced changes. Land surface temperature (LST) and spectral emissivity (LSE) of the Earth are the basis for the extraction of sensitive variables in geology, pedology, and vegetation monitoring. Towards this end, HiTeSEM will enable the research community to evaluate the potential of emissive spectroscopy methodologies in Earth observation to answer a series of key science questions related to global change, human health, and food security. Relevant target variables include soil mineral composition, soil organic matter (SOM), surface moisture availability, evapotranspiration and stomatal/surface conductance. These are key indicators for soil productivity and plant stress in sensitive regions and can be used to govern and adapt land use practices under challenging ecological and climatic conditions. In urban remote sensing HiTeSEM is expected to furnish important information to define thermal models, which implies knowledge of the surface material composition by means of spectral emissivity retrieval. The methodological challenge of HiTeSEM lies in the development of a robust high performance temperature emissivity separation (TES) technique to allow optimum pre-processing of the measured thermal radiance signal at the sensor level. From these scientific goals a series of mission and instrument requirements has been derived that can be summarized as follows

High-resolution temperature and emissivity mapping (HiTeSEM): A satellite sensor concept for hyperspectral thermal remote sensing

HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping) is a preparatory study, funded by the German Aerospace Center (DLR) that aims at preparing the floor for a future spaceborne hyperspectral thermal mission. Up to now this spectral region in Earth observation is mainly used to measure surface temperature. Nevertheless, the spectrally dispersed signal between 8μm and 12 μm can provide information about abundances of key rock and soil forming minerals as well as the status of vegetation. HiTeSEM aims at closing the research gap still hampering utilization of the thermal infrared data at reasonable spectral and spatial resolution and focusses on surface-solid Earth interactions to assess natural and human-induced changes. Land surface temperature (LST) and spectral emissivity (LSE) of the Earth are the basis for the extraction of sensitive variables in geology, pedology, vegetation monitoring, and biosphere-pedosphere interaction. Towards this end, HiTeSEM will enable the research community to evaluate the potential of emissive spectroscopy methodologies in Earth observation to answer a series of key science questions related to global change, human health, and food security. Relevant target variables include soil mineral composition, soil organic matter (SOM), surface moisture availability, evapotranspiration and stomatal/surface conductance. These are key indicators for soil productivity and plant stress in sensitive regions and can be used to govern and adapt land use practices under challenging ecological and climatic conditions. In urban remote sensing HiTeSEM is expected to furnish important information to define thermal models, which implies knowledge of the surface material composition by means of spectral emissivity retrieval. The methodological challenge of HiTeSEM lies in the development of a robust high performance temperature emissivity separation (TES) technique to allow optimum pre-processing of the measured thermal radiance signal at the sensor level. The above science goals define the technical baseline for the proposed mission, namely a system composed of a thermal infrared spectrometer covering the spectral region of 8 – 12.5 µm with ~75 spectral channels, a swath width of 50 km - 100 km, and a ground IFOV of 60 x 60 m2 (TIR, hyperspectral) and 20 x20 m2 (TIR, broadband). The retrieval of emissivity spectra requires low noise equivalent temperatures, in the order of 0.05 K @ 300 K