Résumé : The slides were taken on collecting trips sponsored by the William L. Bryant Foundation, where books, music and art indigenous to the regions were gathered. The are organized by geographical location.
This image was taken in the mountains of Saint Ann, Jamaica with a view of a forest, clouds, and the Caribbean sea. Slide labeled Coast above St Ann.
Jamaica -- Caribbean region -- Saint Ann

Droits : All rights to images are held by the respective holding institution. This image is posted publicly for non-profit educational uses, excluding printed publication. For permission to reproduce images and/or for copyright information contact Special Collections & University Archives, University of Central Florida Libraries, Orlando, FL 32816 phone (407) 823-2576, email: speccoll@mail.ucf.edu
CFM1972_01a
http://ufdc.ufl.edu/AA00030975/00001

Éditeur(s) : HAL CCSD Elsevier
Résumé : Vegetation phenology is the study of the timing of seasonal events that are considered to be the result of adaptive responses to climate variations on short and long time scales. In the field of remote sensing of vegetation phenology, phenological metrics are derived from time series of optical data. For that purpose, considerable effort has been specifically focused on developing noise reduction and cloud-contaminated data removal techniques to improve the quality of remotely-sensed time series. Comparative studies between time series composed of satellite data acquired under clear and cloudy conditions and from radiometric data obtained with high accuracy from ground-based measurements constitute a direct and effective way to assess the operational use and limitations of remote sensing for predicting the main plant phenological events. In the present paper, we sought to explicitly evaluate the potential use of MODerate resolution Imaging Spectroradiometer (MODIS) remote sensing data for monitoring the seasonal dynamics of different types of vegetation cover that are representative of the major terrestrial biomes, including temperate deciduous forests, evergreen forests, African savannah, and crops. After cloud screening and filtering, we compared the temporal patterns and phenological metrics derived from in situ NDVI time series and from MODIS daily and 16-composite products. We also evaluated the effects of residual noise and the influence of data gaps in MODIS NDVI time series on the identification of the most relevant metrics for vegetation phenology monitoring. The results show that the inflexion points of a model fitted to a MODIS NDVI time series allow accurate estimates of the onset of greenness in the spring and the onset of yellowing in the autumn in deciduous forests (RMSE <= one week). Phenological metrics identical to those provided with the MODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately two weeks or more during the autumn phenological transitions. In the evergreen forests, in situ NDVI time series describe the phenology with high fidelity despite small temporal changes in the canopy foliage. However, MODIS is unable to provide consistent phenological patterns. In crops and savannah, MODIS NDVI time series reproduce the general temporal patterns of phenology, but significant discrepancies appear between MODIS and ground-based NDVI time series during very localized periods of time depending on the weather conditions and spatial heterogeneity within the MODIS pixel. In the rainforest, the temporal pattern exhibited by a MODIS 16-day composite NDVI time series is more likely due to a pattern of noise in the NDVI data structure according to both rainy and dry seasons rather than to phenological changes. More investigations are needed, but in all cases, this result leads us to conclude that MODIS time series in tropical rainforests should be interpreted with great caution. (C) 2013 Elsevier Inc. All rights reserved.
ISSN: 0034-4257

hal-01032407
https://hal.archives-ouvertes.fr/hal-01032407
DOI : 10.1016/j.rse.2013.01.010

Éditeur(s) : HAL CCSD Cambridge University Press (CUP)
Résumé : Devil's gardens are one of the most remarkable mutualistic associations between ants and plants. Myrmelachista ants eliminate all vegetation from around their host plants, resulting in wide forest clearings which have intrigued scientists from the start. Despite their noticeability, here we report the discovery of devil's gardens in remote highland cloud forests of the Eastern Amazon, more than 2000 km away from their nearest known analogues in Western Amazonia. We describe the ecological characteristics of these gardens and consider what factors could have produced the geographic isolation of Eastern Amazonian devil's gardens. Three hypotheses are investigated: (1) the host plant distribution restricts the distribution of the mutualism, (2) the ecological tolerances of Myrmelachista explain the isolation, and (3) the devil's gardens of the Eastern Amazon constitute relicts from ancient forest refugia. The distribution of the possible associated myrmecophytes and previously described ecological ranges of devil's gardens cannot explain their ecological restriction to cloud forests in Eastern Amazonia, but our discovery is consistent with the biogeographic refuge hypothesis (i.e. highlands along the Amazon Basin constitute refugia for humid forests that spread during the Cenozoic). Our finding opens exciting perspectives for comparative studies of the origin, ecology and evolutionary history of this ant-plant mutualism.
ISSN: 0266-4674

hal-01532640
https://hal.archives-ouvertes.fr/hal-01532640
DOI : 10.1017/S0266467416000195
PRODINRA : 384619

Éditeur(s) : HAL CCSD
Résumé : Co-encadrement assuré par le Groupement pour le Développement de la Télédétection Aérospatiale (GDTA) Diplôme : DESS
il s'agit d'un type de produit dont les métadonnées ne correspondent pas aux métadonnées attendues dans les autres types de produit : DISSERTATION
This document proposes a new map of the Eastern Guyana Shield, with the SPOT4-VEGETATION remotesensed datas of the year 2000. A new synthesis method, with the mean value, was applied and compared with the Maximum Value Method (WVC). To prepare this datas for the synthesis, a cloud filter was defined :BSC (BEST Sky Clear). With this results, an ISODATA classification was proceeded, and, produces 25 classes to detail the tropical maist forest with the 1 km low resolution. To valid this result, this document propose a method with the higthresolution datas Landsat 7 ETM+. This method aims to guide the ground truth and goes thoroughly into the description of the moist tropical forest classes. The sample, used to try this method, shows the boundaries and the constraints of this method. This points are debating in the discussion. Finally, the perspectives to develop the method are presented in the conclusion.
Ce document propose une nouvelle cartographie du Bouclier Oriental Guyanais à l'aide d'images satellites SPOT4-VEGETATION de l'année 2000. Une nouvelle méthode de synthèse annuelle, utilisant la valeur moyenne de la radiométrie, a été appliquée et comparée à la méthode du Maximum Value Composite (MVC). A cette occasion, un filtre de nuage a été défini pour préparer les données à cette synthèse : le filtre BSC (Best Sky Clear). Sur la base de ce résultat, une classification ISODATA a été réalisée, produisant 25 classes, et mettant en évidence les différents milieux forestiers des tropiques humides à une résolution spatiale de 1 km. Pour valider la classification, une méthode est proposée utilisant des images hautes résolutions Landsat 7 ETM+. Cette méthode permet de cadrer les vérifications sur le terrain et d'approfondir la définition des classes de forêt tropicale humide. L'échantillon utilisé pour tester la méthode met en évidence les limites et contraintes de la démarche proposée. Ces points sont exprimés dans la discussion. Enfin les perspectives de développements sont abordées dans la conclusion.
https://hal.archives-ouvertes.fr/hal-01189195

hal-01189195
https://hal.archives-ouvertes.fr/hal-01189195
PRODINRA : 13538

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
Within the framework of the international field campaign COPS (Convective and Orographically induced Precipitation Study), a large suite of state-of-the-art meteorological instrumentation was operated, partially combined for the first time. This includes networks of in situ and remote-sensing systems such as the Global Positioning System as well as a synergy of multi-wavelength passive and active remote-sensing instruments such as advanced radar and lidar systems. The COPS field phase was performed from 01 June to 31 August 2007 in a low-mountain area in southwestern Germany/eastern France covering the Vosges mountains, the Rhine valley and the Black Forest mountains. The collected dataset covers the entire evolution of convective precipitation events in complex terrain from their initiation, to their development and mature phase until their decay. Eighteen Intensive Observations Periods with 37 operation days and eight additional Special Observations Periods were performed, providing a comprehensive dataset covering different forcing conditions. In this article, an overview of the COPS scientific strategy, the field phase, and its first accomplishments is given. Highlights of the campaign are illustrated with several measurement examples. It is demonstrated that COPS research provides new insight into key processes leading to convection initiation and to the modification of precipitation by orography, in the improvement of quantitative precipitation forecasting by the assimilation of new observations, and in the performance of ensembles of convection-permitting models in complex terrain.
ISSN: 0035-9009

hal-00565513
https://hal.archives-ouvertes.fr/hal-00565513
DOI : 10.1002/qj.752

Éditeur(s) : HAL CCSD Elsevier Masson
Résumé : 14 pages
International audience
Central Africa hosts the world's second largest tropical forest after the Amazonian basin. However, as compared to its Amazonian counterpart, the Central Africa forests receive much less rain (∼1500 mm/year in mean spread over two rainy seasons in March-May and September-November, and two dry seasons). They also experience a slower deforestation rate, so that the main threat for the next decades might come from climate variations. Nonetheless, their response to the annual cycle of solar radiation and rainfall/clouds is still poorly known. Analysing high resolution remote sensing data of Enhanced Vegetation Index, rainfall, cloudiness, and solar radiation for a target region located between 0 and 5°N and 12–19°E, we explore the climatic drivers of the forests greenness mean annual cycle. Three main points emerge; first, the diurnal cycle is a key-scale for understanding the mean annual cycles of rainfall and incoming solar radiation at surface, then how climate shapes the greenness mean annual evolution; second, neither the two dry seasons nor the two rainy seasons resemble each other in terms of cloud cover, solar radiation and rainfall, and their links with greenness levels; third, whereas the first rainy season (March-May) appears optimal for greenness especially because of favorable light conditions, water availability is the main controlling factor during the main dry season and at the start of the first vegetative season (February). Regarding the little dry season (mid-June-mid-August) and the second rainy season (September-October), light availability might be the main limiting factor. These findings pave the way for further studies of the climate interannual variability and change impacts on the Central Africa forests, taking into account time-scale interactions.
ISSN: 0168-1923

hal-01309565
https://hal.archives-ouvertes.fr/hal-01309565
DOI : 10.1016/j.agrformet.2016.04.005