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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Determining the potential productivity of food crops in controlled environments

The quest to determine the maximum potential productivity of food crops is greatly benefitted by crop growth models. Many models have been developed to analyze and predict crop growth in the field, but it is difficult to predict biological responses to stress conditions. Crop growth models for the optimal environments of a Controlled Environment Life Support System (CELSS) can be highly predictive. This paper discusses the application of a crop growth model to CELSS; the model is used to evaluate factors limiting growth. The model separately evaluates the following four physiological processes: absorption of PPF by photosynthetic tissue, carbon fixation (photosynthesis), carbon use (respiration), and carbon partitioning (harvest index). These constituent processes determine potentially achievable productivity. An analysis of each process suggests that low harvest index is the factor most limiting to yield. PPF absorption by plant canopies and respiration efficiency are also of major importance. Research concerning productivity in a CELSS should emphasize: (1) the development of gas exchange techniques to continuously monitor plant growth rates and (2) environmental techniques to reduce plant height in communities.

Bugbee, Bruce↗
NASA NTRS1996

Recycle of Inorganic Nutrients for Hydroponic Crop Production Following Incineration of Inedible Biomass

Recovery of resources from waste streams is essential for future implementation and reliance on a regenerative life support system. The major waste streams of concern are from human activities and plant wastes. Carbon, water and inorganics are the primary desired raw materials of interest. The goal of resource recovery is maintenance of product quality to insure support of reliable and predictable levels of life support function performance by the crop plant component. Further, these systems must be maintained over extended periods of time, requiring maintenance of nutrient solutions to avoid toxicity and deficiencies. Today, reagent grade nutrients are used to make nutrient solutions for hydroponic culture and these solutions are frequently changed during the life cycle or sometimes managed for only one crop life cycle. The focus of this study was to determine the suitability of the ash product following incineration of inedible biomass as a source of inorganic nutrients for hydroponic crop production. Inedible wheat biomass was incinerated and ash quality characterized. The incinerator ash was dissolved in adequate nitric acid to establish a consistent nitrogen concentration in all nutrient solution treatments. Four experimental nutrient treatments were included: control, ash only, ash supplemented to match control, and ash only quality formulated with reagent grade chemicals. When nutrient solutions are formulated using only ash following-incineration of inedible biomass, a balance in solution is established representing elemental retention following incineration and nutrient proportions present in the original biomass. The resulting solution is not identical to the control. This imbalance resulted in suppression of crop growth. When the ash is supplemented with nutrients to establish the same balance as in the control, growth is identical to the control. The ash appears to carry no phytotoxic materials. Growth in solution formulated with reagent grade chemicals but matching the quality of the ash only treatment resulted in growth similar to that of the ash only treatment. The ash product resulting from incineration of inedible biomass appears to be a suitable form for recycle of inorganic nutrients to crop production.

Bubenheim, David L.↗
NASA NTRS2000

A multiple chamber, semicontinuous, crop carbon dioxide exchange system: design, calibration, and data interpretation

Long-term, whole crop CO2 exchange measurements can be used to study factors affecting crop growth. These factors include daily carbon gain, cumulative carbon gain, and carbon use efficiency, which cannot be determined from short-term measurements. We describe a system that measures semicontinuously crop CO2 exchange in 10 chambers over a period of weeks or months. Exchange of CO2 in every chamber can be measured at 5 min intervals. The system was designed to be placed inside a growth chamber, with additional environmental control provided by the individual gas exchange chambers. The system was calibrated by generating CO2 from NaHCO3 inside the chambers, which indicated that accuracy of the measurements was good (102% and 98% recovery for two separate photosynthesis systems). Since the systems measure net photosynthesis (P-net, positive) and dark respiration(R-dark, negative), the data can be used to estimate gross photosynthesis, daily carbon gain, cumulative carbon gain, and carbon use efficiency. Continuous whole-crop measurements are a valuable tool that complements leaf photosynthesis measurements. Multiple chambers allow for replication and comparison among several environmental or cultural treatments that may affect crop growth. Example data from a 2 week study with petunia (Petunia x hybrida Hort. Vilm.-Andr.) are presented to illustrate some of the capabilities of this system.

NASA Discipline Life Support Systems↗
NASA NTRS2007

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage.

Lewis, David↗
NASA NTRS2004

Handling Procedures of Vegetable Crops

The National Aeronautics and Space Administration (NASA) is working towards future long duration manned space flights beyond low earth orbit. The duration of these missions may be as long as 2.5 years and will likely include a stay on a lunar or planetary surface. The primary goal of the Advanced Food System in these long duration exploratory missions is to provide the crew with a palatable, nutritious, and safe food system while minimizing volume, mass, and waste. Vegetable crops can provide the crew with added nutrition and variety. These crops do not require any cooking or food processing prior to consumption. The vegetable crops, unlike prepackaged foods, will provide bright colors, textures (crispy), and fresh aromas. Ten vegetable crops have been identified for possible use in long duration missions. They are lettuce, spinach, carrot, tomato, green onion, radish, bell pepper, strawberries, fresh herbs, and cabbage. Whether these crops are grown on a transit vehicle (e.g., International Space Station) or on the lunar or planetary surface, it will be necessary to determine how to safely handle the vegetables while maintaining acceptability. Since hydrogen peroxide degrades into water and oxygen and is generally recognized as safe (GRAS), hydrogen peroxide has been recommended as the sanitizer. The objective of th is research is to determine the required effective concentration of hydrogen peroxide. In addition, it will be determined whether the use of hydrogen peroxide, although a viable sanitizer, adversely affects the quality of the vegetables. Vegetables will be dipped in 1 % hydrogen peroxide, 3% hydrogen peroxide, or 5% hydrogen peroxide. Treated produce and controls will be stored in plastic bags at 5 C for up to 14 days. Sensory, color, texture, and total plate count will be measured. The effect on several vegetables including lettuce, radish, tomato and strawberries has been completed. Although each vegetable reacts to hydrogen peroxide differently, the data suggest that 5% hydrogen peroxide reduces the shelf life of the vegetable. A dip of either 1 % or 3% hydrogen peroxide helps reduce the microbial total count while not adversely affecting the quality of the vegetable.

Perchonok, Michele↗
NASA NTRS2011

Crop and Substrate Tests with Single Use Rooting "Pillows" for the VEGGIE Plant Growth Hardware

VEGGIE is a small plant production chamber built by ORBITEC. This chamber can be collapsed for easy stowage and deployed in orbit. It is designed for gravity independent operation, and provides 0.17 square m of crop growth area with three primary subsystems: an LED light panel, extendable transparent Teflon bellows to enclose the plants, and a wicking reservoir. VEGGIE would provide the capability for astronauts to grow fresh foods for dietary supplementation. Initial planting concepts tested with the VEGGIE included direct seeding or plug placement on the reservoir surface. These options had issues of salt accumulation and eventual toxicity if the reservoir was filled with nutrient solution, and hardware reuse was limited due to sanitation. In response a rooting packet or "pillow" concept was developed: single-use bags of media containing time release fertilizer with a wicking surface contacting the VEGGIE reservoir. Pillows being tested are small electrostatic bags with a Nitex nylon mesh side, each holding 100 mL of dry media. Six pillows fit in one VEGGIE unit; however pillow size could vary depending on crop selected. Seeds can be planted directly in pillows and planted pillows can be hydrated in space as desired. Our goals were to define optimal media and crops for an ISS mission scenario. Plant tests in pillows were performed in a controlled environment chamber set to habitat-relevant conditions, and capillary reservoir analogs were utilized. Media tested within pillows included: a commercial peat-based potting mix, arcillite (calcined clay), perlite: vermiculite, and peat-based: arcillite blends. Testing included 15 types of leafy greens, snow pea, radish, and herbs. Media performance was crop dependent, but generally plants showed the greatest growth in the peat-based: arcillite mixes. Crops with the best performance in pillows were identified, and testing is underway with select leafy greens examining plant and microbial load response to repeated harvest. We plan to use findings from previous flight testing with media to evaluate the effects of capillary flow from the reservoir to pillows in microgravity.

Massa, Gioia↗
NASA NTRS2011

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Zhang, Ping↗
NASA NTRS2014

Estimation of Crop Gross Primary Production (GPP): I. Impact of MODIS Observation Footprint and Impact of Vegetation BRDF Characteristics

Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) ≤ 35◦ to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA ≤ 35◦. The fourth experiment included only backscatter observations with VZA ≤ 35◦. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation footprint impact whereas comparison of experiment 4 vs. experiment 3 was used to examine the BRDF impact. Changes in R2, RMSE,CV and changes in model coefficients "a" and "b" (experiment 2 vs. experiment 1; and experiment 4 vs. experiment 3) were indicators of the impacts. The second experiment produced better performance than the first experiment, increasing R2 (↑0.13) and reducing RMSE (↓0.68 g C m−2 d−1) and CV (↓9%). For each VI, the slope of GPP = a × VI × PAR in the second experiment for each crop type changed little while the slope and intercept of GPP = a × VI × PAR + b varied field by field. The CIgreen was least affected by the MODIS observation footprint in estimating crop daily GPP (R2, ↑0.08; RMSE, ↓0.42 g C m−2 d−1; and CV, ↓7%). Footprint most affected the NDVI (R2, ↑0.15; CV, ↓10%) and the EVI (RMSE, ↓0.84 g C m−2 d−1). The vegetation BRDF impact also caused variation of model performance and change of model coefficients. Significantly different slopes were obtained for forward vs. backscatter observations, especially for the CIgreen and the NDVI. Both the footprint impact and the BRDF impact varied with crop types, irrigation options, model options and VI options.

Chlorophyll↗
NASA NTRS2016

Pick-and-Eat Salad-Crop Productivity, Nutritional Value, and Acceptability to Supplement the ISS Food System

The capability to grow nutritious, palatable food for crew consumption during spaceflight has the potential to provide health-promoting, bioavailable nutrients, enhance the dietary experience, and reduce launch mass as we move toward longer-duration missions. However, studies of edible produce during spaceflight have been limited, leaving a significant knowledge gap in the methods required to grow safe, acceptable, nutritious crops for consumption in space. Researchers from Kennedy Space Center, Johnson Space Center, Purdue University and ORBITEC have teamed up to explore the potential for plant growth and food production on the International Space Station (ISS) and future exploration missions. KSC, Purdue, and ORBITEC bring a history of plant and plant-microbial interaction research for ISS and for future bioregenerative life support systems. JSC brings expertise in Advanced Food Technology (AFT), Behavioral Health and Performance (BHP), and statistics. The Veggie vegetable-production system on the ISS offers an opportunity to develop a pick-and-eat fresh vegetable component to the ISS food system as a first step to bioregenerative supplemental food production. We propose growing salad plants in the Veggie unit during spaceflight, focusing on the impact of light quality and fertilizer formulation on crop morphology, edible biomass yield, microbial food safety, organoleptic acceptability, nutritional value, and behavioral health benefits of the fresh produce. The first phase of the project will involve flight tests using leafy greens, with a small Chinese cabbage variety, Tokyo bekana, previously down selected through a series of research tests as a suitable candidate. The second phase will focus on dwarf tomato. Down selection of candidate varieties have been performed, and the dwarf cultivar Red Robin has been selected as the test crop. Four light treatments and three fertilizer treatments will be tested for each crop on the ground, to down select to two light treatments and one fertilizer treatment to test on ISS. Our work will help define light colors, levels, and horticultural best practices to achieve high yields of safe, nutritious leafy greens and tomatoes to supplement a space diet of prepackaged food. Our final deliverable will be the development of growth protocols for these crops in a spaceflight vegetable production system. With this work, and potentially with other pending joint projects, we will continue the synergistic research to help close gaps in the human research roadmap, and enable humans to venture to Mars and beyond. This research was co-funded by the Human Research Program and Space Biology (MTL1075) in the ILSRA 2015 NRA call.

Behavioral Health↗
NASA NTRS2017

The Uncertainty of Crop Yield Projections Is Reduced by Improved Temperature Response Functions

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for is greater than 50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 C to 33 C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

Wang, Enli↗
NASA NTRS2018

Using Reanalysis in Crop Monitoring and Forecasting Systems

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980-2010 under potential and water-imited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.

Reanalysis↗
NASA NTRS2016

Developing a Crop Mask for Agricultural Assessments in Kenya

Kenya relies on agricultural production for supporting local consumption and other processing value chains. The role of agriculture in supporting Kenya's economy is critical, with its contribution to the Gross Domestic product (GDP) estimated at over 277,000 Million in 2016. With changing climate in a rain-fed dependent agricultural production system, cropping zones are shifting and proper decision making will require updated data for proper delineation of cropping areas and extent; especially in agriculture and food security assessments. Where up-to-date data is not available it is important that it is generated and passed over to relevant stakeholders to inform their decision making processes. It is important that government agencies, non-governmental agencies and other agricultural stakeholders access updated tools and information to assist in their assessments. To support agricultural decision making, SERVIR E&SA will develop an updated agricultural crop mask. Due to intercropping especially in small holder farming, the mask will cover all crops to provide an overall map of cropped areas.

environment↗
NASA NTRS2019

How Does Water Delivery System Design Impact the Microbial Load of Salad Crops?

In a microgravity setting, such as the environment aboard the International Space Station (ISS), an ideal plant water delivery system is one that can grow edible crops with minimal resource consumption and minimal risk to crew members. There are also concerns associated with the ability to control fluid escape and biofilm formation resulting in potential dangers to systems, crops, or crewmembers. To identify an appropriate system, candidate systems were assembled and operated under simulated ISS environmental conditions (T,CO2,and RH) with red romaine lettuce (Lactuca sativa cultivar 'Outredgeous') as a model crop. Fluid reservoirs and randomly selected planting sites were sampled every seven days until maturity at which point edible plant biomass and root samples were also taken. Heterotrophic bacteria and fungi growth patterns throughout each planting cycle were determined by plate counts on appropriate agar media. The candidate systems were compared to a classic hydroponics system as a control and harvested crops were compared to controls as well as Veggie-grown and market produce. Plants harvested from candidate systems yielded lower average heterotrophic bacteria and fungi per gram of plant mass levels when compared to market and Veggie samples as well as those from the control system. Additional studies to evaluate the system sanitation regimen as well as testing additional crops should be considered to aid in the selection of an ideal system.

Curry, Aaron B.↗
NASA NTRS2019

Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation

Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas.

Minoli, Sara↗
NASA NTRS2019

Connecting Crop Productivity, Residue Fires, and Air Quality over Northern India

Northwestern India is known as the “breadbasket” of the country producing two-thirds of food grains, with wheat and rice as the principal crops grown under the crop rotation system. Agricultural data from India indicates a 25% increase in the post-monsoon rice crop production in Punjab during 2002–2016. NASA’s A-train satellite sensors detect a consistent increase in the vegetation index (net 21%) and post-harvest agricultural fire activity (net ~60%) leading to nearly 43% increase in aerosol loading over the populous Indo-Gangetic Plain in northern India. The ground-level particulate matter (PM2.5) downwind over New Delhi shows a concurrent uptrend of net 60%. The effectiveness of a robust satellite-based relationship between vegetation index—a proxy for crop amounts, and post-harvest fires—a precursor of extreme air pollution events, has been further demonstrated in predicting the seasonal agricultural burning. An efficient crop residue management system is critically needed towards eliminating open field burning to mitigate episodic hazardous air quality over northern India.

Hiren Jethva↗
NASA NTRS2021

Argentina Food Security & Agriculture: Crop Monitoring and Forecasting for Argentina using NASA Satellite Observations

Early harvest information helps guide agricultural commodity assessments in Argentina, providing valuable planning information to identify potentially food-insecure regions, anticipate transportation and storage demands, predict price fluctuations, and project commodity trends. However, crop yield estimates are currently subjective, based on interviews with qualified informants (i.e., farmers, agribusiness actors). In partnership with the Buenos Aires Grain Exchange, we leveraged Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Soil Moisture Active Passive (SMAP), and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM IMERG) NASA Earth observations to develop a Google Earth Engine (GEE) toolset to monitor vegetation growth. The first component of the toolset produces spatial and temporal maps of temperature, precipitation, soil moisture, and the Normalized Difference Vegetation Index (NDVI), allowing users to visualize the influence of the region’s climate and weather. Next, we developed an autoregressive model to predict NDVI several months in advance. Lastly, we created a linear regression model of crop yield and NDVI for soybeans, corn, and wheat, and input the forecasted NDVI to generate a predicted crop yield output. The NDVI forecasting model produced accurate predictions at two, four, and six months when examining the most recent growing season. In the crop yield model, soybeans exhibited moderately strong correlation, wheat had consistent weak correlation, and corn varied from weak to strong correlation depending on zone. This information is vital for vegetation growth monitoring by identifying areas of high growth and allocating resources to areas of lower growth to efficiently maximize crop yields.

DEVELOP Tech Paper↗
NASA NTRS2021

Crop-CASMA - A Web GIS Tool for Cropland Soil Moisture Monitoring and Assessment Based on SMAP Data

Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA- a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.

Zhengwei Yang↗
NASA NTRSDate not supplied

Maipo River Valley Agriculture: Determining Crop Coefficients Using Remote Sensing for the Maipo River Valley Basin in Chile

Agriculture is the primary use of water in the Maipo River basin of Central Chile, accounting for ~ 75% of the total demand. Assessment of irrigation needs for agricultural production has commonly relied on reference crop coefficients (Kc) derived from geographic and climatic conditions that differ from those of Chile. In partnership with the Centro de Información de Recursos Naturales (CIREN), this work focused on calculating site-specific crop coefficients tailored to crop production in the water-stressed Maipo River Valley. Two distinct approaches were implemented, each relying on remotely-sensed Earth observation datasets from NASA over consecutive growing seasons from 2019 to 2022. The first method estimated Kc values based on their linear relationship with the Normalized Difference Vegetation Index (NDVI) obtained from either Terra Moderate Resolution Imaging Spectroradiometer (MODIS) or Landsat 8 Operational Land Imager (OLI) surface reflectance. The second technique leveraged information from the ISS Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) by computing the ratio between actual crop evapotranspiration (ET) and potential evapotranspiration (PET). Both procedures showed promising results that can build on one another. The former approach best captured vegetation signals of annual crops while the latter appeared suited for perennials. Overall, this study provides a strong basis and novel way to accurately estimate Kc using remote sensing, with the potential for improved irrigation management and reduction in water consumption.

Benjamin Goffin↗