Physical Sciences and Mathematics Commons^™

Detecting Spatiotemporal Changes Of Corn Developmental Stages In The U.S. Corn Belt Using Modis Wdrvi Data, Toshihiro Sakamoto, Brian D. Wardlow, Anatoly A. Gitelson

School of Natural Resources: Faculty Publications

The dates of crop developmental stages are important variables for many applications including assessment of the impact of abnormal weather on crop yield. Time-series 250-m vegetation-index (VI) data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide valuable information for monitoring the spatiotemporal changes of corn growth across large geographic areas. The goal of this study is to evaluate the performance of a new crop phenology detection method, namely, two-step filtering (TSF), for revealing the spatiotemporal pattern of specific corn developmental stages (early vegetative: V2.5; silking: R1; dent: R5; mature: R6) over an eight-year period (2001–2008) across Iowa, Illinois, and …

Slides: Arctic Ecosystem Services Measurement And Modeling Project, Eric Biltonen

Best Management Practices (BMPs): What? How? And Why? (May 26)

Presenter: Eric Biltonen, PhD, Environment Economist, Houston Advanced Research Center

8 slides

Nir-Red Reflectance-Based Algorithms For Chlorophyll-A Estimation In Mesotrophic Inland And Coastal Waters: Lake Kinneret Case Study, Yosef Z. Yacobi, Wesley Moses, Semion Kaganovsky, Benayahu Sulimani, Bryan Leavitt, Anatoly A. Gitelson

School of Natural Resources: Faculty Publications

A variety of models have been developed for estimating chlorophyll-a (Chl-a) concentration in turbid and productive waters. All are based on optical information in a few spectral bands in the red and near-infra-red regions of the electromagnetic spectrum. The wavelength locations in the models used were meticulously tuned to provide the highest sensitivity to the presence of Chl-a and minimal sensitivity to other constituents in water. But the caveat in these models is the need for recurrent parameterization and calibration due to changes in the biophysical characteristics of water based on the location and/or time of the year. In this …

Comparison And Analysis Of Empirical Equations For Soil Heat Flux For Different Cropping Systems And Irrigation Methods, Ayse Kilic, R. K. Singh, Elizabeth A. Walter-Shea, Shashi Verma, Andrew E. Suyker

School of Natural Resources: Faculty Publications

We evaluated the performance of four models for estimating soil heat flux density (G) in maize (Zea mays L.) and soybean (Glycine max L.) fields under different irrigation methods (center‐pivot irrigated fields at Mead, Nebraska, and subsurface drip irrigated field at Clay Center, Nebraska) and rainfed conditions at Mead. The model estimates were compared against measurements made during growing seasons of 2003, 2004, and 2005 at Mead and during 2005, 2006, and 2007 at Clay Center. We observed a strong relationship between the G and net radiation (R_n) ratio (G/R_n) and the normalized difference …

Spectral Data-Based Estimation Of Soil Heat Flux, Ramesh K. Singh, Ayse Kilic, Elizabeth Walter-Shea, Shashi B. Verma, Andrew E. Suyker

School of Natural Resources: Faculty Publications

Numerous existing spectral‐based soil heat flux (G) models have shown wide variation in performance for maize and soybean cropping systems in Nebraska, indicating the need for localized calibration and model development. The objectives of this article are to develop a semi‐empirical model to estimate G from a normalized difference vegetation index (NDVI) and net radiation (R_n) for maize (Zea mays L.) and soybean (Glycine max L.) fields in the Great Plains, and present the suitability of the developed model to estimate G under similar and different soil and management conditions. Soil heat fluxes measured in both …