Search results for "Vegetation index"
showing 10 items of 170 documents
Intraspecific Differences in Spectral Reflectance Curves as Indicators of Reduced Vitality in High-Arctic Plants
2017
Remote sensing is a suitable candidate for monitoring rapid changes in Polar regions, offering high-resolution spectral, spatial and radiometric data. This paper focuses on the spectral properties of dominant plant species acquired during the first week of August 2015. Twenty-eight plots were selected, which could easily be identified in the field as well as on RapidEye satellite imagery. Spectral measurements of individual species were acquired, and heavy metal contamination stress factors were measured contemporaneously. As a result, a unique spectral library of dominant plant species, heavy metal concentrations and damage ratios were achieved with an indication that species-specific chan…
Evaluation of the MOD16A2 evapotranspiration product in an agricultural area of Argentina, the Pampas region
2021
The Pampas Region is a big plain of approximately 520,000 km2 in Argentina. It is essential to estimate evapotranspiration (ET) in this region since the primary productivity is directly linked to water availability. Information provided by satellite missions allows monitoring the spatial and temporal variability of ET. In the current study, we evaluated the version 006 of MOD16A2 product (MOD16A2.006) of Potential Evapotranspiration (ETp) and Actual Evapotranspiration (ETa) in Argentinian Pampas Region (APR). MOD16A2.006 product was compared with Crop Evapotranspiration (ETc), calculated with local measurements from the Oficina de Riesgo Agropecuario (ORA), and Crop Coefficient (Kc) data (f…
A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data
2001
Abstract A comparative study has been carried out on the most recent algorithms for the estimation of land surface emissivity (ϵ) using Advanced Very High Resolution Radiometer (AVHRR) data. Three of the algorithms are based on the Temperature-Independent Spectral Indices (TISI) concept using atmospherically corrected channels 3, 4, and/or 5, namely: (1) TISI BL , (2) TS-RAM, and (3) Δ day. The fourth is a simplified method based on the estimation of ϵ using atmospherically corrected data in the visible and near-infrared channels, called Normalized Difference Vegetation Index (NDVI) Thresholds Method (NDVI THM ). This method integrates a wide spectral data set of bare soil reflectivity meas…
Brown and green LAI mapping through spectral indices
2015
Abstract When crops senescence, leaves remain until they fall off or are harvested. Hence, leaf area index (LAI) stays high even when chlorophyll content degrades to zero. Current LAI approaches from remote sensing techniques are not optimized for estimating LAI of senescent vegetation. In this paper a two-step approach has been proposed to realize simultaneous LAI mapping over green and senescent croplands. The first step separates green from brown LAI by means of a newly proposed index, ‘Green Brown Vegetation Index (GBVI)’. This index exploits two shortwave infrared (SWIR) spectral bands centred at 2100 and 2000 nm, which fall right in the dry matter absorption regions, thereby providing…
Multitemporal fusion of Landsat and MERIS images
2011
Monitoring Earth dynamics from current and future observation satellites is one of the most important objectives for the remote sensing community. In this regard, the exploitation of image time series from sensors with different characteristics provides an opportunity to increase the knowledge about environmental changes, which are needed in many operational applications, such as monitoring vegetation dynamics and land cover/use changes. Many studies in the literature have proven that high spatial resolution sensors like Landsat are very useful for monitoring land cover changes. However, the cloud cover probability of many areas and the 15-days temporal resolution restrict its use to monito…
Vegetation dynamics from NDVI time series analysis using the wavelet transform
2009
A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to study NDVI time series. These series, which are non-stationary and present short-term, seasonal and long-term variations, can be decomposed using this MRA as a sum of series associated with different temporal scales. The main focus of the paper is to check the potential of this MRA to capture and describe both intra- and inter-annual changes in the data, i.e., to discuss the ability of the proposed procedure to monitor vegetation dynamics at regional scale. Our approach concentrates on what wavelet analysis can tell us about a NDVI time series. On the one hand, the intra-annual series, linked to th…
Impact of climate change and man-made irrigation systems on the transmission risk, long-term trend and seasonality of human and animal fascioliasis i…
2014
Large areas of the province of Punjab, Pakistan are endemic for fascioliasis, resulting in high economic losses due to livestock infection but also affecting humans directly. The prevalence in livestock varies pronouncedly in space and time (1-70%). Climatic factors influencing fascioliasis presence and potential spread were analysed based on data from five mete- orological stations during 1990-2010. Variables such as wet days (Mt), water-budget-based system (Wb-bs) indices and the normalized difference vegetation index (NDVI), were obtained and correlated with geographical distribution, seasonality patterns and the two-decade evolution of fascioliasis in livestock throughout the province. …
Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data
2019
Abstract NDVI (Normalized Difference Vegetation Index) time series usually suffer from remaining cloud presence, even after data pre-processing. To address this issue, numerous gap-filling (or reconstruction) techniques have been developed in the literature, although their comparison has mainly been local to regional, with only two global studies to date, and has led to sometimes contradictory results. This study builds on these different comparisons, by testing different parameterizations for five NDVI temporal profile reconstruction techniques, namely HANTS (Harmonic Analysis of Time Series), IDR (iterative Interpolation for Data Reconstruction), Savitzky-Golay, Asymmetric Gaussian and Do…
Deep Learning Models Performance For NDVI Time Series Prediction: A Case Study On North West Tunisia
2020
The main goal of this paper is to analyze the performance of two deep learning models Long Short-Term Memory (LSTM) and bidirectional LSTM (BiLSTM) network for non-stationary Normalized Difference Vegetation Index (NDVI) time-series prediction. Both methods have provided good performances in the different time series. The BiLSTM has shown the best agreement with the lowest root mean square error (RMSE) and the highest Pearson correlation coefficient (R) of 0.034 and 0.93, respectively.
How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment
2016
This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spanning 4 continents and covering 15 crop types with corresponding Landsat satellite images. Best-fit functions for the LAI-VI relationships were generated and assessed in terms of crop type, vegetation index, level of radiometric/atmospheric processing, method of LAI measurement, as well as the time difference between LAI measurements and satellite overpass. These global LAI-VI relationships were evalu…