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Publications

Publications by Mário Cunha

2005

Airborne pollen of Olea in five regions of Portugal

Authors
Ribeiro, H; Cunha, M; Abreu, I;

Publication
ANNALS OF AGRICULTURAL AND ENVIRONMENTAL MEDICINE

Abstract
The aim of this work was to study spatial and temporal distribution of Olea europeae airborne pollen in different Portuguese regions: Reguengos de Monsaraz (south); Bairrada (west): Braga (northwest); Valenca do Douro and Foz Coa (northeast). Airborne pollen sampling was conducted from 1998-2003 using "Cour" type samplers located in each region. The main pollen season (NIPS) of Olea lasted on average 36 days and occurred from late April until middle-to-end of June. During the studied period, inter-annual variations among and within regions, concerning the total annual pollen counts and the beginning, peak and ending dates of the MPS. were reported. Reguengos de Monsaraz and Bairrada registered the earliest MPS starting date, followed by Valenca do Douro and Foz-Coa, and the latest date was verified in Braga that also had the shortest MPS. Reguengos de Monsaraz presented the longest MPS with the highest differences in the beginning and ending dates, but minimum differences in the dates of the maximum pollen peak. Our results showed an increase in the Olea annual pollen index, from north to south. and from the west to the east regions of the country.

2010

A Comparative Study of Satellite and Ground-Based Vineyard Phenology

Authors
Cunha, M; Marcal, ARS; Rodrigues, A;

Publication
IMAGIN [E,G] EUROPE

Abstract
Grapevine phenology observations are essential for ecological adaptability of grape varieties, crop management and crop modelling. Phenological events have traditionally been ground based, with observations mainly providing information concerning grape varieties over a limited spatial area and few in-season observations. Time-series of satellite imagery can rapidly provide a synoptic and objective view of grape vegetation dynamics that may be used for vineyard management. Ten-day VEGETATION image composites from 1999 to 2007 were used to examine temporal profile in the Normalized Difference Vegetation Index (NDVI) and their relationship with ground based observation of grapevine phenology. In Portugal is Douro wine region, 2 suitable tests sites with over 70% or more of their area occupied by grapevines were selected. A number of NDVI metrics were obtained for each year through logistic model adjusted to NDVI time series after noise reduction using a Savitzky-Golay filter. The comparison of ground-based vineyard phenology and satellite-derived flowering, show an average spread deviation of 3 days. The satellite derived full canopy date was significantly correlated to the veraison date (r=0.87; n=7; p<0.02). The data set provided by the VEGETATION sensor proved to be a valuable tool for vineyard monitoring, mainly for inter-annual comparisons on regional scale.

2009

Evaluation of data fusion methods for agricultural monitoring based on synthetic images

Authors
Rodrigues, AS; Marcal, ARS; Cunha, M;

Publication
REMOTE SENSING FOR A CHANGING EUROPE

Abstract
There are several data fusion methods widely used to produce a high resolution multi-spectral image from a pair of images - a panchromatic high resolution and a multi-spectral lower resolution image. Although the fused images can be visually satisfactory, it is not clear whether they provide additional information for quantitative measurements made from satellite images. A methodology to evaluate data fusion algorithms is proposed, based on the production of synthetic images that reproduce real satellite images. An experiment was conducted testing the performance of six data fusion methods in the production of NDVI values for land parcels from SPOT HRG and Landsat TM data. The fusion methods evaluated were: Brovey, IHS Hexcone, IHS Cylinder, PCA, Wavelet IHS and Wavelet Single Band. The best data fusion method overall was found to be Wavelet IHS, although better results were obtained by using directly the lower resolution multi-spectral data instead. The software tools developed and a number of test images datasets are freely available at the SITEF website (www.fc.up.pt/sitef).

2009

Remote sensing monitoring to preserve ancestral semi-natural mountain meadows landscapes

Authors
Pocas, I; Cunha, M; Marcal, ARS; Pereira, LS;

Publication
REMOTE SENSING FOR A CHANGING EUROPE

Abstract
"Lameiros" are ancestral semi-natural meadows, essential elements of mountain landscapes in Northern Portugal. In the "lameiros" a traditional irrigation system is used and water is applied all year around. They are mainly used for forage production for autochthonous bovine feeding, but they are also important for the water and nutrients cycle regulation, erosion control and as barrier to forest fires propagation. Although recognized for their economical, environmental, landscaping, cultural and genetic value, the perpetuation of these "lameiros" could be at risk, at medium term, due to human desertification in the mountain regions and to the announced constraints in use of water resources. To preserve these landscapes it is essential to know them better and to better characterize them. Therefore a monitoring program using remote sensing tools is now being developed to evaluate different patterns of "lameiros", and their spatial extent and evolution. Two important questions are determinant in this program: the selection of the most appropriate spatial resolution for monitoring "lameiros", and the availability of satellite historical data. In this context, NDVI were compared in two selected test sites, with and without full irrigation. Data were derived from several field campaigns with a spectroradiometer and using different sensors: i) Landsat 5 and Landsat 7 (30m pixel), ii) SPOT 4 and SPOT 2 (20m pixel), iii) SPOT 5 (10m pixel). The NDVI temporal series produced were evaluated considering "lameiros" management and weather data. Results obtained so far indicate that the SPOT images provide data at the most adequate scale.

2011

An evaluation of changes in a mountainous rural landscape of Northeast Portugal using remotely sensed data

Authors
Pocas, I; Cunha, M; Marcal, ARS; Pereira, LS;

Publication
LANDSCAPE AND URBAN PLANNING

Abstract
Image data from Earth Observation Satellites (EDS) were used to analyse mountain landscape changes in Northeast Portugal. Three Landsat images, from April 30th 1979, March 14th 1989 and May 29th 2002 were used. A supervised classification was performed for each image based on the radiometric information and the Normalised Difference Vegetation Index (NDVI). Eleven classes were selected considering the main land cover types in the region. The classification results showed high overall accuracy (above 92.5%) and kappa coefficient (above 0.91). Broadly, the range of dates of the Landsat images used allowed for the differentiation between classes. Nevertheless, some problems occurred in differentiating between classes of forest and shrub vegetation due to similar characteristics and vegetation conditions in some periods of the year, and also due to the effects of topographic shadows associated to mountain areas. Meadows and annual crops were the classes having greater changes from 1979 to 2002: meadows area increased 60% while annual crops decreased 43.5%. The increase in meadows area was likely due to policies supporting agroenvironmental conservation and autochthon bovine livestock production. Differently, the decrease in annual crops was likely due to the loss of economical competitiveness of main annual crops and to the rural population decrease and ageing, which favoured the replacement of arable lands by permanent meadows. These results may help developing policies and measures for sustainable management of traditional mountain rural landscapes.

2011

PhenoSat - A tool for vegetation temporal analysis from satellite image data

Authors
Rodrigues, A; Marcal, ARS; Cunha, M;

Publication
2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings

Abstract
The availability of temporal satellite image data has increased considerably in recent years. A number of satellite sensors currently observe the Earth with high temporal frequency thus providing a tool for monitoring/understanding the Earth-surface variability more precisely, for several applications such as the analysis of vegetation dynamics. However, the extraction of vegetation phenology information from Earth Observation Satellite (EOS) data is not easy, requiring efficient processing algorithms to properly handle the large amounts of data gathered. The purpose of this work is to present a new, easy-to-use software tool that produces phenology information from EOS vegetation temporal data - PhenoSat. This paper describes PhenoSat, focusing on two new features: the determination of the beginning and maximum of a double growth season, and the selection of a temporal sub-region of interest in order to reduce and control the data evaluated. © 2011 IEEE.

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