Physical and Environmental Geography Commons^™

Distinguishing Land Change From Natural Variability And Uncertainty In Central Mexico With Modis Evi, Trmm Precipitation, And Modis Lst Data, Zachary Christman, John Rogan, J. Ronald Eastman, B. L. Turner Ii

Zachary Christman

Precipitation and temperature enact variable influences on vegetation, impacting the type and condition of land cover, as well as the assessment of change over broad landscapes. Separating the influence of vegetative variability independent and discrete land cover change remains a major challenge to landscape change assessments. The heterogeneous Lerma-Chapala-Santiago watershed of central Mexico exemplifies both natural and anthropogenic forces enacting variability and change on the landscape. This study employed a time series of Enhanced Vegetation Index (EVI) composites from the Moderate Resolution Imaging Spectoradiometer (MODIS) for 2001–2007 and per-pixel multiple linear regressions in order to model changes in EVI as …

Land Surface Phenologies And Seasonalities Using Cool Earthlight In Mid-Latitude Croplands, W. G. Alemu, G. M. Henebry

Geoffrey Henebry

Phenology deals with timing of biotic phenomena and seasonality concerns temporal patterns of abiotic variables. Studies of land surface phenology (LSP) and land surface seasonality (LSS) have long been limited to visible to near infrared (VNIR) wavelengths, despite degradation by atmospheric effects and solar illumination constraints. Enhanced land surface parameters derived from passive microwave data enable improved temporal monitoring of agricultural land surface dynamics compared to the vegetation index data available from VNIR data. LSPs and LSSs in grain growing regions of the Volga River Basin of Russia and the spring wheat belts of the USA and Canada were characterized …

Remote Sensing-Based Time Series Models For Malaria Early Warning In The Highlands Of Ethiopia, A. Midekisa, G. Senay, G. M. Henebry, P. Semuniguse, M. C. Wimberly

Geoffrey Henebry

Background

Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. …

Change And Persistence In Land Surface Phenologies Of The Don And Dnieper River Basins, V. Kovalskyy, G. M. Henebry

Geoffrey Henebry

The formal collapse of the Soviet Union at the end of 1991 produced major socio-economic and institutional dislocations across the agricultural sector. The picture of broad scale patterns produced by these transformations continues to be discovered. We examine here the patterns of land surface phenology (LSP) within two key river basins—Don and Dnieper—using AVHRR (Advanced Very High Resolution Radiometer) data from 1982 to 2000 and MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2001 to 2007. We report on the temporal persistence and change of LSPs as summarized by seasonal integration of NDVI (normalized difference vegetation index) time series using accumulated …

Dual Scale Trend Analysis Distinguishes Climatic From Anthropogenic Effects On The Vegetated Land Surface, K. M. De Beurs, C. K. Wright, G. M. Henebry

Geoffrey Henebry

We present a dual scale trend analysis for characterizing and comparing two contrasting areas of change in Russia and Kazakhstan that lie less than 800 km apart. We selected a global NASA MODIS (moderate resolution imaging spectroradiometer) product (MCD43C4 and MCD43A4) at a 0.05◦ (∼5.6 km) and 500 m spatial resolution and a 16-day temporal resolution from 2000 to 2008. We applied a refinement of the seasonal Kendall trend method to the normalized difference vegetation index (NDVI) image series at both scales. We only incorporated composites during the vegetative growing season which was delineated by start of season and end …

Evaluation Of A Coupled Event-Driven Phenology And Evapotranspiration Model For Croplands In The United States Northern Great Plains, V. Kovalskyy, G. M. Henebry, D. P. Roy, B. Adusei, M. Hansen, G. Senay, D. M. Mocko

Geoffrey Henebry

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme consists of the VegET, a model to estimate ET from meteorological and water balance data, and an Event Driven Phenology Model (EDPM), an empirical crop specific model trained on multiple years of flux tower data transformed into six types of environmental forcings that are called “events” to emphasize their temporally discrete character, which has advantages for modeling multiple contingent influences. The EDPM in prognostic mode supplies seasonal trajectories of normalized difference vegetation index (NDVI); whereas in diagnostic mode, it …

A New Approach For The Analysis Of Hyperspectral Data: Theory And Sensitivity Analysis Of The Moment Distance Method, E.A. L. Salas, G. M. Henebry

Geoffrey Henebry

We present the Moment Distance (MD) method to advance spectral analysis in vegetation studies. It was developed to take advantage of the information latent in the shape of the reflectance curve that is not available from other spectral indices. Being mathematically simple but powerful, the approach does not require any curve transformation, such as smoothing or derivatives. Here, we show the formulation of the MD index (MDI) and demonstrate its potential for vegetation studies. We simulated leaf and canopy reflectance samples derived from the combination of the PROSPECT and SAIL models to understand the sensitivity of the new method to …

Interannual Variations And Trends In Global Land Surface Phenology Derived From Enhanced Vegetation Index During 1982–2010, Xiaoyang Zhang, Bin Tan, Yunyue Yu

Xiaoyang Zhang

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel …

Daily Modis 500 M Reflectance Anisotropy Direct Broadcast (Db) Products For Monitoring Vegetation Phenology Dynamics, Yanmin Shuai, Crystal Schaaf, Xiaoyang Zhang, Alan Strahler, David P. Roy, Jeffery Morisette, Zhuosen Wang, Joanne Nightingale, Jaime Nickerson, Andrew D. Richardson, Donghui Xie, Jindi Wang, Xiaowen Li, Kathleen Strabala, James E. Davies

Xiaoyang Zhang

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on …

A Cross Comparison Of Spatiotemporally Enhanced Springtime Phenological Measurements From Satellites And Ground In A Northern U.S. Mixed Forest, Liang Liang, Mark D. Schwartz, Zhuosen Wang, Feng Gao, Crystal B. Schaaf, Bin Tan, Jeffrey T. Morisette, Xiaoyang Zhang

Xiaoyang Zhang

Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed …

Reconstruction Of Daily 30 M Data From Hj Ccd, Gf-1 Wfv, Landsat, And Modis Data For Crop Monitoring, Mingquan Wu, Xiaoyang Zhang, Wenjiang Huang, Zheng Niu, Changyao Wang, Wang Li, Pengyu Hao

Xiaoyang Zhang

With the recent launch of new satellites and the developments of spatiotemporal data fusion methods, we are entering an era of high spatiotemporal resolution remote-sensing analysis. This study proposed a method to reconstruct daily 30 m remote-sensing data for monitoring crop types and phenology in two study areas located in Xinjiang Province, China. First, the Spatial and Temporal Data Fusion Approach (STDFA) was used to reconstruct the time series high spatiotemporal resolution data from the Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field-of-view camera (GF-1 WFV), Landsat, and Moderate Resolution Imaging Spectroradiometer (MODIS) data. Then, …

Proceedings Of The Workshop On Spatio-Temporal Data Models Of Biogeophysical Fields For Ecological Forecasting, Geoffrey Henebry, Jan Chomicki, Tony Fountain

Geoffrey Henebry