Introduction

Data products from NASA's Land Processes Distributed Active Archive Center (LP DAAC) are used in many different applications. They play an important role in modeling, help to detect changes to the landscape, and are a way to assess ecosystem variables, among others. A few of these applications that have been published between October and December 2014 are highlighted below.

MODIS for Crop Yield Forecasting

In the study "Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale" published in Remote Sensing, Kouadio and others (2014) use Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices to improve spring wheat yield forecasts at ecodistrict-level scales in Western Canada.

Science Objectives

This study investigates the use of MODIS-derived vegetation indices (MOD13Q1) for forecasting spring wheat yield at the ecodistrict (ECD) scale in three provinces across western Canada with the Integrated Canadian Crop Yield Forecasters (ICCYF) for the 2000 to 2010 period. The study compares these forecasts and their accuracy to forecasts at the Census Agricultural Region (CAR) scale. An ECD is a subdivision of a single ecoregion and has specific climate, soil, landscape, and ecological aspects. CARs consist of neighboring census divisions.

Instruments Used

Agroclimate measurements (daily temperatures and precipitation, soil characteristics, and soil moisture) combined with MODIS derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) are used as inputs for the in-season yield forecasting of spring wheat from 2000 through 2010.

Major Findings

Results show that both inputs (agroclimate plus MODIS-NDVI and agroclimate plus MODIS-EVI) equally predict spring wheat yields at the ECD scale. The CARs or coarser statistical units had poorer ICCYF performance as reported in previous studies. Therefore, this study found that the model performance improved at the finer ECD scale.

References

Publication Reference

Kouadio, L., Newlands, N.K., Davidson, A., Zhang, Y., and Chipanshi, A., 2014, Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale: Remote Sensing, v. 6, no. 10, p. 10193–10214. doi:10.3390/Rs61010193.

Image References

Kouadio, L. et al., 2014; CC-BY-4.0

Tracking Elevation at a Coal Mine

In the study "Time-varying elevation change at the Centralia coal mine in Centralia, Washington (USA), constrained with InSAR, ASTER, and optical imagery" published in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Prush and others (2014) use Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and interferometric synthetic aperture radar (InSAR) instrument data to track elevation changes at the Centralia Coal Mine in Washington from 1971 to 2006.

Science Objectives

Digital elevation models (DEMs) are used to study elevation changes over a 30 year period at the Centralia Coal Mine in Centralia, Washington in this study. InSAR observations and other DEMs are used to create the time series.

Instruments Used

The other DEMs include the National Elevation Dataset (NED), the Shuttle Radar Topography Mission (SRTM), DEMs derived from individual scenes of ASTER imagery, and the ASTER Global Digital Elevation Model (GDEM). Elevation change was observed across all datasets relative to NED, which was used as the baseline.

Major Findings

There were several regions of significant positive and negative elevation changes. Negative values were areas that experienced a decrease in elevation due to the removal of materials. Positive values were areas that experienced an increase in elevation due to depressions being filled in and raised above their original elevation, or piling by transporting material from one place to another. This study demonstrated the ability to utilize time series DEM data to determine the elevation change patterns over time that were attributed to excavation and transport of materials at an operational coal mine between 1971 and 2006.

References

Publication Reference

Prush, V.B., and Lohman, R.B., 2014, Time-varying elevation change at the Centralia coal mine in Centralia, Washington (USA), constrained with InSAR, ASTER, and optical imagery: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. doi:10.1109/JSTARS.2014.2348412.

Land Cover and Urban Heat in Phoenix

In the study "Spatial configuration of anthropogenic land cover impacts on urban warming" published in Landscape and Urban Planning, Zheng and others (2014) use ASTER surface temperature data to analyze how clustered human-made surfaces influence Phoenix, Arizona's urban heat island effect.

Science Objectives

The urban heat island (UHI) effect refers to higher temperatures in urban areas relative to temperatures in surrounding rural areas. The goal of this study is to better understand how spatial patterns of anthropogenic land cover features influence land surface temperature (LST) within Phoenix, AZ. Anthropogenic land cover is created by human land use and in this study includes commercial, industrial, and residential buildings, grassland, unmanaged soils, and manmade water bodies.

Instruments Used

An urban classification map of Phoenix was derived from a high-resolution QuickBird image from May 24, 2007. Then summertime LST data were acquired from two ASTER images (AST_08), one daytime and the other nighttime. Local Moran’s I, a continuous spatial autocorrelation index, was used to measure the spatial pattern of land cover classes in Phoenix.

Major Findings

Results show that both random patterns and clusters of paved surfaces exhibit an increase in surface temperature at night, but are more obvious in the clustered paved areas. Weaker effects of spatial patterns of paved surface on LST are observed when the building fraction exceeds 50%. This weaker correlation could be due to cooling effects created by the shade of buildings. LST was observed to be higher for areas that are more than 50% paved and areas with more than 90% combined fraction of paved surfaces and soils. Since the results of this study indicate a strong influence of cluster patterns of paved surfaces on LST, urban planners could utilize this information to help minimize UHI effects.

References

Publication Reference

Zheng, B., Myint, S.W., and Fan, C., 2014, Spatial configuration of anthropogenic land cover impacts on urban warming: Landscape and Urban Planning, v. 130, no. 1, p. 104–111. doi:10.1016/j.landurbplan.2014.07.001.

Image Reference

NASA/GSFC/METI/Japan Space Systems, and U.S./Japan ASTER Science Team (ASTER Urban Land Cover and Spatial Structure, Phoenix, AZ)