AVHRR temporal analysis of a savanna site in Brazil

França, Helena; Setzer, Alberto

doi:10.1080/014311698214226

Cited by 23 publications

(8 citation statements)

References 13 publications

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“…Of particular relevance to animal ecologists is the normalized diVerence vegetation index (NDVI) (Pettorelli et al 2005b), which is calculated from near-infrared and red reXectance measurements [NDVI = (NIR ¡ RED)/ (NIR + RED), where NIR and RED are spectral reXectance of near-infrared and red light, respectively]. NDVI has so far been applied successfully to vegetation monitoring (Rasmussen 1998), primary production estimation (Ricotta and Avena 1998), environmental change detection (Franca and Setzer 1998) as well as studies of animal distributions (Verlinden and Masogo 1997;Serneels and Lambin 2001;Zinner et al 2001;Boone et al 2006;Mueller et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale

2008

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Lek-breeding species are characterized by a negative association between territorial resource availability and male mating success; however, the impact of resources on the overall distribution patterns of the two sexes in lek systems is not clear. The normalized difference vegetation index (NDVI) has recently emerged as a powerful proxy measure for primary productivity, allowing the links between the distributions of animals and resources to be explored. Using NDVI at four spatial resolutions, we here investigate how the distribution of the two sexes in a lek-breeding population of topi antelopes relates to resource abundance before and during the rut. We found that in the dry season preceding the rut, topi density correlated positively with NDVI at the large, but not the fine, scale. This suggests that before the rut, when resources were relatively scant, topi preferred pastures where green grass was widely abundant. The pattern was less pronounced in males, suggesting that the need for territorial attendance prevents males from tracking resources as freely as females do. During the rut, which occurs in the wet season, both male and female densities correlated negatively with NDVI at the fine scale. At this time, resources were generally plentiful and the results suggest that, rather than by resource maximization, distribution during the rut was determined by benefits of aggregating on relatively resource-poor leks for mating, and possibly antipredator, purposes. At the large scale, no correlation between density and NDVI was found during the rut in either sex, which can be explained by leks covering areas too small to be reflected at this resolution. The study illustrates that when investigating spatial organization, it is important: (1) to choose the appropriate analytic scale, and (2) to consider behavioural as well as strictly ecological factors.

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Section: Introductionmentioning

confidence: 99%

Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale

2008

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“…However, in the drier part of the year, the chances are considerably greater, especially during the months of June, July and August (90, Based on the strong and unique seasonality of the Cerrado (e.g. Franca andSetzer 1998, Ferreira et al 2003), we also analysed the feasibility of using Landsat-like dataset to monitor the seasonal variations in vegetation cover (figure 5). The months of July, August and September (peak of dry season) are excellent for obtaining Landsat imagery.…”

Section: Resultsmentioning

confidence: 99%

Spatial and temporal probabilities of obtaining cloud‐free Landsat images over the Brazilian tropical savanna

Sano

Ferreira

Asner

et al. 2007

International Journal of Remote Sensing

135

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Remotely sensed data are the best and perhaps the only possible way for monitoring large-scale, human-induced land occupation and biosphere-atmosphere processes in regions such as the Brazilian tropical savanna (Cerrado). Landsat imagery has been intensively employed for these studies because of their long-term data coverage (.30 years), suitable spatial and temporal resolutions, and ability to discriminate different land-use and land-cover classes. However, cloud cover is the most obvious constraint for obtaining optical remote sensing data in tropical regions, and cloud cover analysis of remotely sensed data is a requisite step needed for any optical remote sensing studies. This study addresses the extent to which cloudiness can restrict the monitoring of the Brazilian Cerrado from Landsat-like sensors. Percent cloud cover from more than 35 500 Landsat quick-looks were estimated by the K-means unsupervised classification technique. The data were examined by month, season, and El Niñ o Southern Oscillation event. Monthly observations of any part of the biome are highly unlikely during the wet season (October-March), but very possible during the dry season, especially in July and August. Research involving seasonality is feasible in some parts of the Cerrado at the temporal satellite sampling frequency of Landsat sensors. There are several limitations at the northern limit of the Cerrado, especially in the transitional area with the Amazon. During the 1997 El Niñ o event, the cloudiness over the Cerrado decreased to a measurable but small degree (5% less, on average). These results set the framework and limitations of future studies of land use/land cover and ecological dynamics using Landsat-like satellite sensors.

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“…Tieszen et al (1997) used NDVI to estimate potential production of grasslands in the Great Plains of North America. In addition, NDVI is often used to monitor forest degradation and interannual variability (Foody and Curran 1994;Franca and Setzer 1998;Paruelo and Lauenroth 1998;Helmer et al 2000;Awaya and Tanaka 2003;Sarkar and Kafatos 2004;Yamamoto et al 2004b;Patel et al 2004;Liu et al 2004). Wang et al (2004) demonstrated strong relations between NDVI and groundbased measurements of productivity of forest trees, represented by standardized tree ring width, diameter increase, seed production, and tree height growth.…”

Section: Introductionmentioning

confidence: 97%

Spatial identification by satellite imagery of the crop–fallow rotation cycle in northern Laos

Yamamoto

Oberthür

Lefroy

2007

Environ Dev Sustain

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In the mountainous regions of northern Laos, shifting cultivation, or slash-andburn agriculture, is widely practiced. However, the crop-fallow rotation cycle is becoming shorter owing to forest conservation policies and population pressure, causing loss of productivity that deleteriously affects farmers' livelihoods in the region. To investigate regional land use conditions, we have developed a method of identifying the crop-fallow rotation cycle from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper+ (ETM+) data. We assessed the impact of the identified cycle on plant production measured by Normalized Difference Vegetation Index (NDVI). The study site was an area in Luang Prabang Province. Using eight TM and ETM+ images acquired annually from 1995 to 2003, except for 1998, when cloud-free data were not collected, we classified land use in each year as crop or fallow by the presence of vegetation in the late dry season. Conformity with fallow age determined by field investigation was 69.1%. The cultivation frequency from 1995 to 2002 showed that 77,000 ha (17.3% of the study site) had not been used for cropping during the period, but 41,000 ha (9.2%) had been used every year. Of the study site, 129,000 ha (29.1%) was cultivated one or two times, 83,000 ha (18.7%) was three or four times, and 54,000 ha (12.2%) was five or six times. The NDVI of crops in November did not provide sufficient evidence to prove the assumption that a longer fallow period would result in better crop yields. Instead, the regeneration of fallow vegetation was Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue. evidenced by the higher NDVI values after longer fallow. More than 8 years would be needed to reach the same NDVI as forest. From the produced maps indicating fallow age and cultivation frequency, we found that areas with high potential for regeneration decreased as cultivation frequency increased. Areas near rivers were intensively used, and fallow length was accordingly short. Low-potential areas were found in the western basin of the Mekong River. This spatial information can be used to detect areas where biomass productivity is at high risk of deteriorating.

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AVHRR temporal analysis of a savanna site in Brazil

Cited by 23 publications

References 13 publications

Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale

Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale

Spatial and temporal probabilities of obtaining cloud‐free Landsat images over the Brazilian tropical savanna

Spatial identification by satellite imagery of the crop–fallow rotation cycle in northern Laos

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