The ability to regionally monitor crop progress and condition through the growing season benefits both crop management and yield estimation. In the United States, these metrics are reported weekly at ...state or district (multiple counties) levels by the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) using field observations provided by trained local reporters. However, the ground data collection process supporting this effort is time consuming and subjective. Furthermore, operational crop management and yield estimation efforts require information with more granularity than at the state or district level. This paper evaluates remote sensing approaches for mapping crop phenology using vegetation index time-series generated by fusing Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) surface reflectance imagery to improve temporal sampling over that provided by Landsat alone. The case study focuses on an agricultural region in central Iowa from 2001 to 2014. Our objectives are 1) to assess Landsat-MODIS data fusion results over cropland; 2) to map crop phenology at 30m resolution using fused surface reflectance data; and 3) to identify the relationships between remotely sensed crop phenology metrics and the crop progress stages reported by NASS. The results show that detailed spatial and temporal variability in vegetation development across this landscape can be identified using the fused Landsat-MODIS data. The mean difference (bias) in Normalized Difference Vegetation Index (NDVI) between actual Landsat observations and the fused Landsat-MODIS data, generated for Landsat overpass dates, is in the range of −0.011 to 0.028 for every year. The derived phenological metrics show distinct features for different crops and natural vegetation at field scales. Strong correlations are observed between remotely sensed phenological stages, based on NDVI curve inflection points, and the observed crop physiological growth stages from the NASS Crop Progress (CP) reports. The green-up dates detected from remote sensing data typically occurred during crop vegetative stages when 2–4 leaves were developed for both corn and soybeans, or about 1–3weeks after the reported emergence dates when the plant were first visible to ground-based observers. Despite being a lagging indicator, remotely sensed green-up can be used effectively to backcast emergence, e.g. as input to spatially distributed crop models. The differences in green-up date between corn and soybean were 8–10days, consistent with the offset in emergence dates reported by NASS at district level. The reported harvest dates were typically about 2–3weeks after the dormancy stage was detected via remote sensing for corn and about 1–2weeks for soybeans. This suggests that probable harvest times for individual fields may be predicted 1–3weeks ahead using remote sensing data. The results suggest that crop phenology and certain growth stages at field scales (30m spatial resolution) can be linked and mapped by integrating imagery from multiple remote sensing platforms.
•Remote sensing approaches for mapping crop phenology at field scale are developed.•Spatial details and seasonal variability are captured from data fusion approach.•30-m crop phenological metrics are generated using the fused Landsat-MODIS data.•Crop phenology from remote sensing are correlated to crop physiological stages.
Freshwater resources are becoming increasingly limited in many parts of the world, and decision makers are demanding new tools for monitoring water availability and rates of consumption. Remotely ...sensed thermal-infrared imagery collected by Landsat provides estimates of land-surface temperature that allow mapping of evapotranspiration (ET) at the spatial scales at which water is being used. This paper explores the utility of moderate-resolution thermal satellite imagery in water resource management. General modeling techniques for using land-surface temperature in mapping the surface energy balance are described, including methods developed to safeguard ET estimates from expected errors in the remote sensing inputs. Examples are provided of how remotely sensed maps of ET derived from Landsat thermal imagery are being used operationally by water managers today: in monitoring water rights, negotiating interstate compacts, estimating water-use by invasive species, and in determining allocations for agriculture, urban use, and endangered species protection. Other applications include monitoring drought and food insecurity, and evaluation of large-scale land-surface and climate models. To better address user requirements for high-resolution, time-continuous ET data, novel techniques have been developed to improve the spatial resolution of Landsat thermal-band imagery and temporal resolution between Landsat overpasses by fusing information from other wavebands and satellites. Finally, a strategy for future modification to the Landsat program is suggested, improving our ability to track changes in water use due to changing climate and growing population. The long archive of global, moderate resolution TIR imagery collected by the Landsat series is unmatched by any other satellite program, and will continue to be an invaluable asset to better management of our earth's water resources.
► Thermal satellite data provide valuable information for water resource management. ► We summarize applications for moderate resolution thermal data from Landsat. ► Uses include monitoring water consumption, ecosystem health, and food security. ► Synergistic fusion with data from other satellite platforms improves utility. ► An optimal satellite system configuration for global water management is outlined.
Daily continuous evapotranspiration (ET) estimates of 1 km spatial resolution can benefit agricultural water resources management at regional scales. Thermal infrared remote sensing-derived land ...surface temperature (LST) is a critical variable for ET estimation using energy balance-based models. However, missing LST information under cloudy conditions remains a long-standing barrier for spatiotemporally continuous monitoring of daily ET at regional scales. In this study, LST data of 1 km spatial resolution at 11:00 local solar time under all-weather conditions across the North China Plain (NCP) were first generated using a data fusion approach developed previously. Second, combined with the generated LST data, MODIS products, and meteorological forcing from the China Land Data Assimilation System, the Two-Source Energy Balance model (TSEB) and a temporal upscaling method were jointly used to estimate daily ET at 1 km spatial resolution across the NCP for a decade from 2008 to 2017. In particular, to better incorporate the impact of crop phenology on ET and improve the ET estimation, the fraction of greenness in TSEB was determined in terms of a leaf area index threshold during the crop growth period. Compared with observed instantaneous latent heat flux (LE) corrected for energy balance closure, the estimated LE reasonably captures inter- and intra-annual variations in LE measured at the Huailai, Daxing, Weishan, and Guantao flux towers, with R2 of 0.63–0.79. Estimated daily ET against in situ ET measurements with energy balance closure at the Huailai, Daxing, and Guantao sites showed good performance in terms of R2 greater than 0.70 and RMSE below 0.91 mm/d. These accuracies are comparable with published results, with our ET data set validated by many more observations than previous studies and featuring spatiotemporal continuity and high spatial resolution across the entire NCP for a decade. Furthermore, seasonal ET variations reflected by our product outperform two widely used global products in capturing water consumption characteristics in the winter wheat-summer maize rotation system. In terms of temporal trends, annual ET estimates across the NCP show a decreasing and then increasing trend over the past decade, which is attributed to the increased cropping intensity over the recent years reflected by an increase in leaf area index.
•TSEB and LST fusion were jointly used to obtain daily ET with an improved fg characterization.•ET maps of high accuracy, spatiotemporal continuity and fine spatial resolution were generated.•Performance of the ET estimates at multiple temporal scales was systematically evaluated.•Trends of decadal ET estimates across the NCP over a decade were triggered by agricultural intensification.
Operational application of a remote sensing-based two source energy balance model (TSEB) to estimate evaportranspiration (ET) and the components evaporation (E), transpiration (T) at a range of space ...and time scales is very useful for managing water resources in arid and semiarid watersheds. The TSEB model uses composite land surface temperature as input and applies a simplified Priestley–Taylor formulation to partition this temperature into soil and vegetation component temperatures and then computes subsequent component energy fluxes. The remote sensing-based TSEB model using component temperatures of the soil and canopy has not been adequately evaluated due to a dearth of reliable observations. In this study, soil and vegetation component temperatures partitioned from visible and near infrared and thermal remote sensing data supplied by advanced scanning thermal emission and reflection radiometer (ASTER) are applied as model inputs (TSEBCT) to assess and refine the subsequent component energy fluxes estimation in TSEB scheme under heterogeneous land surface conditions in an advective environment. The model outputs including sensible heat flux (H), latent heat flux (LE), component LE from soil and canopy from the TSEBCT and original model (TSEBPT) are compared with ground measurements from eddy covariance (EC) and larger aperture scintillometers (LAS) technique, and stable isotopic method. Both model versions yield errors of about 10% with LE observations. However, the TSEBCT model output of H and LE are in closer agreement with the observations and is found to be generally more robust in component flux estimation compared to the TSEBPT using the ASTER data in this heterogeneous advective environment. Thus given accurate soil and canopy temperatures, TSEBCT may provide more reliable estimates of plant water use and values of water use efficiency at large scales for water resource management in arid and semiarid landscapes.
Land-surface temperature retrieved from thermal infrared (TIR) remote sensing has proven to be a valuable constraint in surface energy balance models for estimating evapotranspiration (ET). For ...optimal utility in agricultural water management applications, frequent thermal imaging (<4-day revisit) at sub-field (100 m or less) spatial resolution is desired. While, the current suite of Landsat satellites (7 and 8) provides the required spatial resolution, the 8-day combined revisit can be inadequate to capture rapid changes in surface moisture status or crop phenology, particularly in areas of persistent cloud cover. The new ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission, with an average 4-day revisit interval and nominal 70-m resolution, provides a valuable research platform for augmenting Landsat TIR sampling and for investigating TIR-based ET mapping mission requirements more broadly. This study investigates the interoperability of Landsat and ECOSTRESS imaging for developing ET image timeseries with high spatial (30-m) and temporal (daily) resolution. A data fusion algorithm is used to fuse Landsat and ECOSTRESS ET retrievals at 30 m with daily 500-m retrievals using TIR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) over target agricultural sites spanning the United States.The added value of the combined multi-source dataset is quantified in comparison with daily flux tower observations collected within these target domains. In addition, we investigate ET model performance as a function of ECOSTRESS view angle, overpass time, and time separation between TIR and Landsat visible to shortwave infrared (VSWIR) data acquisitions used to generate land-surface temperature, leaf area index, and albedo inputs to the surface energy balance model. The results demonstrate the value of the higher temporal sampling provided by ECOSTRESS, especially in areas that are frequently impacted by cloud cover. Limiting usage to ECOSTRESS scenes collected between 9:00 a.m. to 5:00 p.m. and nadir viewing angles <20° yielded daily (24-h) ET retrievals of comparable quality to the well-tested Landsat baseline. We also discuss challenges in using land-surface temperature from a thermal free-flyer system for ET retrieval, which may have ramifications for future TIR water-use mapping missions.
•Landsat thermal infrared constrains field-scale evapotranspiration (ET) retrievals.•ECOSTRESS thermal imaging effectively augments Landsat sampling.•Extra sampling improves ET timeseries in areas of high cloud cover frequency.•Lack of shortwave bands on ECOSTRESS limits accuracy of ET retrievals.•These findings have ramifications for design of future water use mapping missions.
Land cover has a strong effect on the evapotranspiration (ET) and the hydrologic cycle. Urbanization alters the land cover affecting the surface energy balance and ET by, for example, urban ...encroachment in agricultural areas. This study investigates the potential utility of high resolution ET in determining more accurately the impact of land cover on water use for an agricultural area. The approach was to apply the physically based two-source energy balance (TSEB) model to very high resolution (~8 m) aircraft thermal data and compare the ET pattern and distribution to TSEB output using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired on 2 August 2012. Modeled flux components were validated using measurements collected from a network of 16 eddy covariance (EC) towers at the study site. The modeled ET using the aircraft data agreed satisfactorily with the flux tower measurements and had better performance than the TSEB model applied to the ASTER data. The percent errors between ET closed by the Bowen ratio (BR) and residual (RE) approaches were 3 and 1%, respectively. It is shown that the high resolution aircraft ET can more accurately determine the change in ET magnitude by having pure pixels of the main land cover types, namely urban, agriculture, and natural vegetation. As a result, the ET histogram exhibits a significant bi-modal distribution which can be used to accurately distinguish the impact on ET from urban versus agricultural land cover areas and potentially monitor the effect on ET over a landscape due to small changes in land cover. At the coarser 90 m resolution of ASTER, the TSEB ET estimates are more often a combination of urban and agricultural land cover ET near the urban-agriculture land cover boundaries. As a result, the bi-modal distribution in ET is almost nonexistent. This study demonstrates the potential utility of high resolution ET mapping for more accurately determining the magnitude of the ET differences between cropland and urban land cover. It also suggests that, with high resolution thermal imagery, TSEB is a potential tool for monitoring the impact on ET due to relatively small changes in land cover as a result of urban expansion. Such a tool would be useful for watershed management.
Partitioning of eddy covariance flux measurements is routinely done to quantify the contributions of separate processes to the overall fluxes. Measurements of carbon dioxide fluxes represent the ...difference between gross ecosystem photosynthesis and total respiration, while measurements of water vapor fluxes represent the sum of transpiration and direct evaporation. Existing flux partitioning procedures typically require additional instrumentation and/or invoke scaling assumptions that may or may not be appropriate. Here, we present a novel flux partitioning procedure that relies upon the simple assumption that contributions to the measured high-frequency time series of carbon dioxide and water vapor concentrations derived from stomatal processes (i.e., photosynthesis and transpiration) and non-stomatal processes (i.e., respiration and direct evaporation) separately conform to flux-variance similarity. Vegetation water use efficiency is the only parameter needed to perform the partitioning. We apply this technique to eddy covariance data collected over the course of a growing season above a maize field. Results yielded by the correlation-based partitioning approach are consistent with expected trends throughout the growing season, as photosynthesis and transpiration fluxes increase in parallel with observed increases in maize leaf area. Magnitudes of the derived fluxes compare well with literature-based values, and short-term, transient features are also detected as both respiration and direct evaporation fluxes are found to respond to wetting events. These results support the validity of the theory-based partitioning approach, which has the benefit of being simultaneously applied to both carbon dioxide and water vapor fluxes, while relying solely upon standard eddy covariance instrumentation.
Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for ...monitoring crop conditions of individual fields or the impacts of land cover changes that are at significantly finer spatial scales. Consequently, thermal sharpening techniques have been developed to sharpen TIR imagery to shortwave band pixel resolutions, which are often fine enough for field-scale applications. A classic thermal sharpening technique, TsHARP, uses a relationship between land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) developed empirically at the TIR pixel resolution and applied at the NDVI pixel resolution. However, recent studies show that unique relationships between temperature and NDVI may only exist for a limited class of landscapes, with mostly green vegetation and homogeneous air and soil conditions. To extend application of thermal sharpening to more complex conditions, a new data mining sharpener (DMS) technique is developed. The DMS approach builds regression trees between TIR band brightness temperatures and shortwave spectral reflectances based on intrinsic sample characteristics. A comparison of sharpening techniques applied over a rainfed agricultural area in central Iowa, an irrigated agricultural region in the Texas High Plains, and a heterogeneous naturally vegetated landscape in Alaska indicates that the DMS outperformed TsHARP in all cases. The artificial box-like patterns in LST generated by the TsHARP approach are greatly reduced using the DMS scheme, especially for areas containing irrigated crops, water bodies, thin clouds or terrain. While the DMS technique can provide fine resolution TIR imagery, there are limits to the sharpening ratios that can be reasonably implemented. Consequently, sharpening techniques cannot replace actual thermal band imagery at fine resolutions or missions that provide high quality thermal band imagery at high temporal and spatial resolution critical for many agricultural, land use and water resource management applications.
A spatially distributed land surface temperature is important for many studies. The recent launch of the Sentinel satellite programs paves the way for an abundance of opportunities for both large ...area and long-term investigations. However, the spatial resolution of Sentinel-3 thermal images is not suitable for monitoring small fragmented fields. Thermal sharpening is one of the primary methods used to obtain thermal images at finer spatial resolution at a daily revisit time. In the current study, the utility of the TsHARP method to sharpen the low resolution of Sentinel-3 thermal data was examined using Sentinel-2 visible-near infrared imagery. Compared to Landsat 8 fine thermal images, the sharpening resulted in mean absolute errors of ~1 °C, with errors increasing as the difference between the native and the target resolutions increases. Part of the error is attributed to the discrepancy between the thermal images acquired by the two platforms. Further research is due to test additional sites and conditions, and potentially additional sharpening methods, applied to the Sentinel platforms.
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