A 3-yr study was conducted to determine the degree of aggregation of stink bugs and boll injury in cotton, Gossypium hirsutum L., and their spatial association with a multispectral vegetation index (normalized difference vegetation index [NDVI]). Using the spatial analysis by distance indices analyses, stink bugs were less frequently aggregated (17% for adults and 4% for nymphs) than boll injur...

A data assimilation method to produce complete temporal sequences of synthetic medium-resolution images is presented. The method implements a Kalman filter recursive algorithm that integrates medium and moderate resolution imagery. To demonstrate the approach, time series of 30-m spatial resolution NDVI images at 16-day time steps were generated using Landsat NDVI images and MODIS NDVI products...

The MODIS-NDVI data from 2000 to 2009 were used to analyze the temporal dynamics and spatial distribution of the vegetation cover in the Beijing metropolitan region before and after the 2008 Olympics. During the study period, the proportion of the significantly increased pixels of NDVI occupied 20.7% while that of the significantly decreased pixels only occupied 4.1% of the total, and the decre...

The spatial variabi]Lity and co-variability of two different types of remote sensing derivatives that portray vegetation and geomorphic patterns are analyzed in the context of estimating regional-scale CO 2 flux from land surfaces in the arctic tundra. For a study area encompassing the Kuparuk River watershed of the North Slope of Alaska, we compare satellite-derived maps of the normalized diff...

Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time...

NOAA/AVHRR satellite imagery has been widely used for vegetation studies at global and regional scales, to study for example the exchange of matter and energy between the ecosystem and the atmosphere or to generate land cover maps. PAL and LAC products are usually processed as maximum composite yielding an image every 10 days, with 8 and 1 km spatial resolution, respectively. However difference...

To evaluate the state of ecosystems in Mauritania, rainfall time series and a GIMMSNDVI (global inventory modeling and mapping study-normalized difference vegetation index) data set were used for analysis of rainfall and NDVI trends and their relationships in different ecological zones. Linear regression analysis and the non-parametric Mann-Kendall test were applied to detect NDVI and rainfall ...

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud ...

For estimation of grain yield in wheat, Normalized Difference Vegetation Index (NDVI) is considered as a potential screening tool. Field experiments were conducted to scrutinize the response of NDVI to yield behavior of different wheat cultivars and nitrogen fertilization at agronomic research area, University of Agriculture Faisalabad (UAF) during the two years 2008-09 and 2009-10. For recordi...

Sensors that estimate normalized difference vegetative index (NDVI) can increase nitrogen use efficiency and help meet the expected increased food demand; however, current devices are cost prohibitive to small farming operations. The objectives of this study were to determine the relationship of GreenSeeker (GS) sensor and HandHeld Crop Sensor (HHCS), manufactured by Trimble, when used to colle...