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NASA NTRS2019

A Crop Yield Change Emulator for Use in GCAM and Similar Models: Persephone v1.0

Future changes in Earth system state will impact agricultural yields and, through these changed yields, can have profound impacts on the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields but are often too computationally intensive to dynamically couple into global multisector economic models, such as the Global Change Assessment Model (GCAM) and other similar-in-scale models. Yet, generalizing a faster site-specific crop model’s results to be used globally will introduce inaccuracies, and the question of which model to use is unclear given the wide variation in yield response across crop models. To examine the feedback loop among socioeconomics, Earth system changes, and crop yield changes, rapidly generated yield responses with some quantification of crop response uncertainty are desirable. The Persephone v1.0 response functions presented in this work are based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Climate-Crop Modeling Project (C3MP) sensitivity test data set and are focused on providing GCAM and similar models with a tractable number of rapid to evaluate dynamic yield response functions corresponding to a range of the yield response sensitivities seen in the C3MP data set. With the Persephone response functions, a new variety of agricultural impact experiments will be open to GCAM and other economic models: for example, examining the economic impacts of a multi-year drought in a key agricultural region and how economic changes in response to the drought can, in turn, impact the drought.

Snyder, Abigail↗

NASA NTRS2017

The Past and Future Changes in Climate of the Rice-Wheat Cropping Zone in Punjab, Pakistan

Agriculture is ranked top among Pakistan economic sectors vulnerable to the potential impacts of climate change. The agricultural production system is directly affected by weather inputs (temperature, solar radiation, and rainfall) that are projected to change in future (following increases in carbon dioxide and other greenhouse gasses). Although Climatic extremes such as drought, floods and heat waves, are expected to increase with detrimental consequences for agriculture and livestock production, yet changes in mean climates also pose challenges to sustainable development. This study presents climate change results for five districts within the major rice-wheat productivity zone of Punjab province in Pakistan. The results are focused on RCP8.5 mid-century (2040-2069) scenarios derived from five global climate models (GCMs) output and the Kharif (June-October) and Rabi (November-April) seasons. Analysis of recent historical weather data of Sialkot and Sheikhupura districts shows an increase in minimum temperatures and maximum temperatures and a large variation in rainfall. This temperature change and variability in rainfall are expected to enhance further as we approach 2050s. The mean maximum temperature is projected to increase by 2-2.5 ºC during the rice growing (Kharif) season and 2.4-2.7ºC during the wheat growing (Rabi) season. Rainfall during the rice growing season is more uncertain, with projections indicating an increase of 25%-35 % in the study region, while a minimal change is expected during the Rabi season. Climax of the rice growing season corresponds with the projected increase in monsoon intensity, leaving no doubt about the crop water demand satisfaction. However, a simultaneous increase in the day and night temperature may affect the growth and development of some critical phenological stages and thus could impact final yield.

Climate Change↗

NASA NTRS1994

Spectral composition of light and growing of plants in controlled environments

The main conclusions of many investigations about general requirements of plants for spectral composition of PAR (photosynthetically active radiation) are based on phylogenetic aspects of plant growth. We think that these aspects are not the main criteria in choosing the spectral composition required for growing plants in controlled conditions. Our approach to this problem is based on plant and crop reaction under long duration growth with specific spectra and intensity. Only in this way can we determine correctly the role of light characteristics for developing crops.

Tikhomirov, Alexander A.↗

NASA NTRS2006

Chlorophyll Fluorescence Emissions of Vegetation Canopies From High Resolution Field Reflectance Spectra

A two-year experiment was performed on corn (Zea mays L.) crops under nitrogen (N) fertilization regimes to examine the use of hyperspectral canopy reflectance information for estimating chlorophyll fluorescence (ChlF) and vegetation production. Fluorescence of foliage in the laboratory has proven more rigorous than reflectance for correlation to plant physiology. Especially useful are emissions produced from two stable red and far-red chlorophyll ChlF peaks centered at 685V10 nm and 735V5 nm. Methods have been developed elsewhere to extract steady state solar induced fluorescence (SF) from apparent reflectance of vegetation canopies/landscapes using the Fraunhofer Line Depth (FLD) principal. Our study utilized these methods in conjunction with field-acquired high spectral resolution canopy reflectance spectra obtained in 2004 and 2005 over corn crops, as part of an ongoing multi-year experiment at the USDA/Agriculture Research Service in Beltsville, MD. A spectroradiometer (ASD-FR Fieldspec Pro, Analytical Spectral Devices, Inc., Boulder, CO) was used to measure canopy radiances 1 m above plant canopies with a 22deg field of view and a 0deg nadir view zenith angle. Canopy and plant measurements were made at the R3 grain fill reproductive stage on 3-4 replicate N application plots provided seasonal inputs of 280, 140, 70, and 28 kg N/ha. Leaf level measurements were also made which included ChlF, photosynthesis, and leaf constituents (photosynthetic pigment, carbon (C), and N contents). Crop yields were determined at harvest. SIF intensities for ChlF were derived directly from canopy reflectance spectra in specific narrowband regions associated with atmospheric oxygen absorption features centered at 688 and 760 nm. The red/far-red S F ratio derived from these field reflectance spectra successfully discriminated foliar pigment levels (e.g., total chlorophyll, Chl) associated with N application rates in both corn crops. This canopy-level spectral ratio was also positively correlated to the foliar C/N ratio (r = 0.89, n = go), as was a leaf-level steady state fluorescence ratio (Fs/Chl, r = 0.92). The latter ratio was inversely correlated with crop grain yield (Kg 1 ha) (r = 0.9). This study has relevance to future passive satellite remote sensing approaches to monitoring C dynamics from space.

Middleton, E. M.↗

NASA NTRS2022

Global Gridded Crop Models Underestimate Yield Responses to Droughts and Heatwaves

Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.

extreme events↗

NASA NTRSDate not supplied

Bhutan Agriculture II: Creating a Graphical User Interface, Crop Mask, and Data Collection Protocol for Analysis of Rice Crop in Bhutan Using Remotely Sensed Data

Agriculture is an important sector in Bhutan, accounting for 19.63% of Bhutan’s GDP in 2020 (World Bank) while also providing livelihoods for approximately 57% of the population (World Bank, 2017). The Department of Agriculture (DoA) in Bhutan still relies on in-field reporting for crop monitoring, which is time-consuming and labour intensive. To promote efficiency in these efforts, the team partnered with the DoA, the Bhutan Foundation, and the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER). The team, with the help of the science advisors from NASA SERVIR, expanded the crop mask created in the previous term to the whole country of Bhutan and streamlined the sampling protocols for applicability to any available crop data. The team also created a graphical user interface (GUI) which provided a visual representation of current trends and rice distribution across Bhutan. The team utilized NASA Earth observations, including Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Shuttle Radar Topography Mission (SRTM), as well as other Earth observations including Sentinel-1 C-band Synthetic Aperture Radar (C-SAR). This project refined the previous term’s methodology to help supplement crop monitoring and increase the frequency of data collected to aid decision-making processes with the use of remote sensing data.

Wangdrak Dorji↗

NASA NTRS2000

A Passive Method for Detecting Vegetation Stress from Orbit: Chlorophyll Fluorescence Spectra from Fraunhofer Lines

Solar-stimulated chlorophyll fluorescence measured with the Fraunhofer line depth method has correlated well with vegetation stress in previous studies. However, the instruments used in those studies were limited to a single solar absorption line (e.g. 656.3 nm), obviating the red/far-red ratio (R/FR) method. Optics and detector technology have reached the level whereby multiple, very narrow Fraunhofer lines are resolvable. Thirteen such lines span the visible spectrum in the red to far-red region where chlorophyll fluorescence occurs. Fluorescence intensities at the 13 Fraunhofer line wavelengths were used to model emission spectra. The source data were collected for summer and fall bean crops (Phaseolus vulgaris L.) subjected to various levels of nitrogen fertilization. The intensities were adjusted to account for Fraunhofer line depth and atmospheric transmittance. Multiple R/FR fluorescence ratios, calculated from the modeled fluorescence spectra, correlated strongly with leaf chlorophyll concentration and well with applied nitrogen. The ratio yielding the best correlation with chlorophyll utilized red fluorescence at the 694.5 nm Fraunhofer line and farred fluorescence at the 755.6 nm Fraunhofer line. Twenty R/FR ratios, each evaluated for the maximum differential between low and high (optimal) nitrogen treatments, ranked higher in some cases and lower in others, possibly related to the time of year the crops were grown and the stage of growth of the crops. Ratios with 728.9 nm and 738.9 nm in the denominator consistently ranked in the lowest and next lowest quartile, respectively. Ratios of the 656.3 nm Fraunhofer line and the 755.6 nm line consistently ranked highest for the summer crop. Ratios with 755.6 nm in the denominator ranked in the upper quartile for 10 out of 12 measurement dates. Differences in ratio ranking indicate that physiological conditions may be estimated using selected ratios of Fraunhofer lines within the context of R/FR analysis. A passive instrument designed to monitor R/FR chlorophyll fluorescence (i.e. vegetation stress) from orbit could be built today.

Theisen, Arnold F.↗

NASA NTRSDate not supplied

Harvesting Microgreens in Microgravity: Analysis of Six Different Methods

In long duration space missions, crops will be used to supplement the astronaut diet. One such proposed crop type is microgreens, the young seedlings of edible plants that are known for their high nutritional levels, intense flavors, colorful appearance, and variety of textures. While these characteristics make microgreens a great candidate for space crop production, their small size presents a unique challenge within the microgravity environment. To ensure that astronauts will be able to harvest microgreens in microgravity with ease while avoiding the introduction of debris to the spacecraft cabin, multiple harvesting methods were developed by the Space Crop Production Team at NASA’s Kennedy Space Center. Three parabolic flights were conducted in November and December of 2021 and during those flights three different microgreen cutting methods (guillotine, pepper grinder, scissors) as well as two different bagging methods (attached and manual) were tested. In each flight, the microgreens were contained inside of a glovebox and footage of all the microgreen harvests was recorded. The cutting and bagging method combination that introduced the lowest average number of particulates into the glovebox was the scissors with attached bagging, closely followed by the pepper grinder with attached bagging. However, the scissors with attached bagging may had introduced fewer particulates into the glovebox because on average, 27% of the microgreens were never cut using the scissors method, so there were fewer free-floating particulates generated. The cutting and bagging method combination that left the lowest average percentage of microgreens remaining on the hardware post-harvest was the pepper grinder with an attached bag. Future directions include involving microgreen harvests in analog environments and further development of the different microgreen cutting and bagging methods. This research was funded by multiple NASA grants at the Kennedy Space Center.

Haley O Boles↗

NASA NTRS2020

Delineation of vulnerable areas to water erosion in a mountain region using SDR-InVEST model: A case study of the Ourika watershed, Morocco

The Ourika watershed is characterized by higher than average flood flows, a rugged topography, a sparse vegetation cover and a friable substrate that makes it vulnerable to soil erosion. Soil is an important non-renewable asset capital, providing several ecosystem services that sustain life through physical and biological regulation processes. The loss, or otherwise, redistribution of biota by soil erosion in the Ourika watershed has received little attention and thus constitutes a key knowledge gap that needs to be addressed. This study quantifies the level of erosion and maps its spatial distribution in the watershed using the Sediment Delivery Ratio (SDR) of the Integrated Valuation of Ecosystem Services and Tradeoffs model (InVEST3.6.0). The SDR maps the overland sediment generation and delivery to the stream at the watershed level using rainfall, soil properties, topography, cover management and cropping practices as predefined set of input variables. Recommended internal model calibration was used and results were compared to similar studies carried out in different parts of Morocco for validation. The results reveal that 93% of the watershed is subject to a strong rainfall aggressiveness greater than 50 MJ mm ha–1 h–1 yr1 under an average rainfall intensity of 541 mm/year, rainfall capacity to initiate the detachment and transport of soil particles by runoff, and only 11.5% of the watershed area is protected with vegetative cover. We find that overall, the Ourika watershed is losing its soil to erosion at an alarming average rate of 258.48 ton.ha–1.yr–1, a rate well above the tolerable threshold of 7ton.ha–1.yr–1. The spatial distribution of this loss shows areas that need to be urgently remedied. The primary factors for soil erosion in the Ourika watershed appear to be related to the aggressive nature of local rainfall and the inherent susceptibility of soils, which can be costly to this cash-crop region. Because rainfall intensity, soil properties, and topography are intrinsic characteristics of the watershed, we suggest that seasonally adapted cropping rotations that maintains conservative practices with a high cover management may reduce soil erosion in the Ourika watershed.

Erosion↗

NASA NTRS1973

Vegetation analysis in the Laramie Basin, Wyoming from ERTS-1 imagery

The author has identified the following significant results. The application of ERTS-1 imagery to vegetation mapping and identification was tested and confirmed by field checking. ERTS-1 imagery interpretation and density contour mapping allows definition of minute vegetation features and estimation of vegetative biomass and species composition. Large- and small-scale vegetation maps were constructed for test areas in the Laramie Basin and Laramie mountains of Wyoming. Vegetative features reflecting grazing intensity, moisture availability, changes within the growing season, cutting of hay crops, and plant community constituents in forest and grassland are discussed and illustrated. Theoretical considerations of scattering, sun angle, slope, and instrument aperture upon image and map resolution were investigated. Future suggestions for applications of ERTS-1 data to vegetative analysis are included.

Evans, M. A.↗

NASA NTRS1994

Comparisons of luminaires: Efficacies and system design

Lighting designs for architectural (aesthetic) purposes, vision and safety, and plant growth have many features in common but several crucial ones that are not. The human eye is very sensitive to the color (wavelength) of light, whereas plants are less so. There are morphological reactions, particularly to the red and blue portions of the light spectrum but, in general, plants appear to accept and use light for photosynthesis everywhere over the PAR region of the spectrum. In contrast, the human eye interprets light intensity on a logarithmic scale, making people insensitive to significant differences of light intensity. As a rough rule, light intensity must change by 30 to 50% for the human eye to recognize the difference. Plants respond much more linearly to light energy, at least at intensities below photosynthetic saturation. Thus, intensity differences not noticeable to the human eye can have significant effects on total plant growth and yield, and crop timing. These factors make luminaire selection and lighting system design particularly important when designing supplemental lighting systems for plant growth. Supplemental lighting for plant growth on the scale of commercial greenhouses is a relatively expensive undertaking. Light intensities are often much higher than required for task (vision) lighting, which increases both installation and operating costs. However, and especially in the northern regions of the United States (and Canada, Europe, etc.), supplemental lighting during winter may be necessary to produce certain crops (e.g., tomatoes) and very useful to achieve full plant growth potential and crop timing with most other greenhouse crops. Operating costs over the life of a luminaire typically will exceed the initial investment, making lighting efficacy a major consideration. This report reviews tests completed to evaluate the efficiencies of various commercially-available High-Pressure Sodium luminaires, and then describes the results of using a commercial lighting design computer program, Lumen-Micro, to explore how to place luminaires within greenhouses and plant growth chambers to achieve light (PAR) uniformity and relatively high lighting efficacies. Several suggestions are presented which could encourage systematic design of plant lighting systems.

Albright, L. D.↗

NASA NTRS1973

The results of an agricultural analysis of the ERTS-1 MSS data at the Johnson Space Center

The initial analysis of the ERTS-1 multispectral scanner (MSS) data at the Johnson Space Center (JSC), Houston, Texas is discussed. The primary data set utilized was the scene over Monterey Bay, California, on July 25, 1972, NASA ERTS ID No. 1002-18134. It was submitted to both computerized and image interpretative processing. An area in the San Joaquin Valley was submitted to an intensive evaluation of the ability of the data to (1) discriminate between crop types and (2) to provide a reasonably accurate area measurement of agricultural features of interest. The results indicate that the ERTS-1 MSS data is capable of providing the identifications and area extent of agricultural lands and field crop types.

Bizzell, R. M.↗

NASA NTRS2026

Timing the Flames: Geostationary Satellite Detection of Diurnally Shifting Stubble Burning in Northwestern India

Post-monsoon open-field stubble burning in northwestern (NW) India—a key agricultural region known as the “breadbasket”—is a longstanding practice used to clear fields. Satellite observations spanning over two decades have revealed significant upward trends in crop production, vegetative greenness, and the frequency of post-harvest fires, with this last contributing to hazardous air quality during the peak burning season (mid-October to mid-November). Since 2022, thermal anomaly data from Aqua-MODIS and SNPP-VIIRS sensors have shown a sharp decline in reported fire events—an observation that contrasts starkly with the concurrent rise in regional aerosol loading detected from space. This apparent discrepancy became particularly pronounced in 2024–2025, prompting a closer examination using high-temporal-resolution imagery from the Advanced Meteorological Imager (AMI) on the geostationary satellite GEO-KOMPSAT-2A. These observations revealed a clear spike in fire-related signals occurring around and after 4:00 p.m. local time, i.e., outside the typical noon to 2:00 p.m. detection window of the MODIS and VIIRS. A fire detection algorithm exploiting the fire-sensitive shortwave-infrared 3.8 μm signal and its contrast to 11.2 μm infrared observations is designed to adopt AMI observations and applied to its multi-year observations (2019–2025). The resulting fire dataset unambiguously shows a gradual shift in stubble burning activity toward the late afternoon hours beginning in 2022 which is underreported by polar-orbiting satellites. The orbital drift of NASA’s MODIS sensor on the Aqua platform allows detection of some of the gradually shifting fires during afternoon hours, but the MODIS still misses a large number of fires occurring around and after 4 p.m. The AMI’s relatively coarse spatial resolution (~4 km), a consequence of its slant viewing geometry over NW India, imposes inherent limitations on quantifying the full extent of fire occurrences. The operational air quality forecasting models currently assimilate satellite fire detections predominantly captured during early afternoon overpasses of the MODIS and VIIRS. The temporal shift in fire activity complicates such forecast, leading to a substantial underestimation of emissions. Intense stubble burning and the resulting air pollution highlight the need for effective crop residue management practices for mitigating the frequency of open biomass burning and thereby reducing episodic degradation of air quality and its associated public health and economic impacts.

post-monsoon stubble burning; northwestern India;↗

NASA NTRS2002

Effects of Interannual Climate Variability on Water Availability and Productivity in Capoeira and Crops Under Traditional and Alternative Shifting Cultivation

Regenerating forests play an important role in long-term carbon sequestration and sustainable landuse as they act as potentially important carbon and nutrient sinks during the shifting agriculture fallow period. The long-term functioning of capoeira. is increasingly threatened by a shortening fallow period during shifting cultivation due to demographic pressures and associated increased vulnerability to severe climatic events. Declining productivity and functioning of fallow forests of shifting cultivation combined with progressive loss of nutrients by successive burning and cropping activities has resulted in declining agricultural productivity. In addition to the effects of intense land use practices, droughts associated with El Nino events are becoming more frequent and severe in moist tropical forests and negative effects on capoeira productivity could be considerable. In Igarape-Acu (near Belem, Para), we hypothesize that experimental alternative landuse/clearing practices (mulching and fallow vegetation improvement by planting with fast-growing leguminous tree species) may make capoeira and agriculture more resilient to the effects of agricultural pressures and drought through (1) increased biomass, soil organic matter and associated increase in soil water storage, and nutrient retention and (2) greater rooting depth of trees planted for fallow improvement. This experimental practice (moto mechanized chop-and-mulch with fallow improvement) has resulted increased soil moisture during the cropping phase, reduced loss of nutrients and organic matter, and higher rates of secondary-forest biomass accumulation. We present preliminary data on water relations during the dry season of 2001 in capoeira and crops for both traditional slash-and-burn and alternative chop-and-mulch practices. These data will be used to test IKONOS data for the detection of moisture status differences. The principal goal of the research is to determine the extent to which capoeira and agricultural fields are susceptible to extreme climate events (drought) under contrasting landuse/clearing practices.

Guild, Liane S.↗

NASA NTRS1985

Vegetation canopy discrimination and biomass assessment using multipolarized airborne SAR

Multipolarized airborne Synthetic Aperture Radar (SAR) data were acquired over a largely agricultural test site near Macomb, Illinois, in conjunction with the Shuttle Imaging Radar (SIR-B) experiment in October 1984. The NASA/JPL L-band SAR operating at 1.225 GHz made a series of daily overflights with azimuth view angles both parallel and orthogonal to those of SIR-B. The SAR data was digitally recorded in the quadpolarization configuration. An extensive set of ground measurements were obtained throughout the test site and include biophysical and soil measurements of approximately 400 agricultural fields. Preliminary evaluation of some of the airborne SAR imagery indicates a great potential for crop discrimination and assessment of canopy condition. False color composites constructed from the combination of three linear polarizations (HH, VV, and HV) were found to be clearly superior to any single polarization for purposes of crop classification. In addition, an image constructed using the HH return to modulate intensity and the phase difference between HH and VV returns to modulate chroma indicates a clear capability for assessment of canopy height and/or biomass. In particular, corn fields heavily damaged by infestations of corn borer are readily distinguished from noninfested fields.

Ulaby, F. T.↗

NASA NTRS2006

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗

NASA NTRS1983

Remote sensing investigations of wetland biomass and productivity for global biosystems research

Monitoring biomass of wetlands ecosystems can provide information on net primary production and on the chemical and physical status of wetland soils relative to anaerobic microbial transformation of key elements. Multispectral remote sensing techniques successfully estimated macrophytic biomass in wetlands systems. Regression models developed from ground spectral data for predicting Spartina alterniflora biomass over an entire growing season include seasonal variations in biomass density and illumination intensity. An independent set of biomass and spectral data were collected and the standing crop biomass and net primary productivity were estimated. The improved spatial, radiometric and spectral resolution of th LANDSAT-4 Thematic Mapper over the LANDSAT MSS can greatly enhance multispectral techniques for estimating wetlands biomass over large areas. These techniques can provide the biomass data necessary for global ecology studies.

Harkisky, M.↗

NASA NTRS2020

Developing a Customized Composite Drought Index for Pakistan

Pakistan experiences frequent and intense agricultural drought, varying spatially and temporally. Prolonged dry conditions often result in failed crop production. Using multiple variables, different components of drought can be captured across a multitude of climatic zones and throughout different seasons. Developing a composite drought index (CDI), specific for each district, will provide a more complete view of agricultural drought and enhance early warning systems.

Schwartz, Caily↗