Assessing Landsat Images Availability and Its Effects on Phenological Metrics

Forests

Francisca Soares de Araújo¹  Jean-François Mas² 

[1] Centro de Ciências, Departamento de Biologia, Universidade Federal do Ceará, Fortaleza 60440-900, Brazil;Laboratorio de análisis espacial, Centro de Investigaciones en Geografía Ambiental, Universidad Nacional Autónoma de México (UNAM), Morelia, 58090 Michoacán, Mexico;

关键词: Landsat;    dynamics of land cover;    time series;    monitoring;    phenology;   

DOI  :  10.3390/f12050574

来源: DOAJ

【 摘 要 】

Landsat imagery offers the most extended continuous land surface observation at 30 m spatial resolution and is widely used in land change studies. On the other hand, the recent developments on big data, such as cloud computing, give new opportunities for carrying out satellite-based continuous land cover monitoring including land use/cover change and more subtle changes as forest degradation, agriculture intensification and vegetation phenological patterns alterations. However, in the range 0–10${}^{\circ }$ south latitude, especially in the summer and autumn, there is a high rainfall and high clouds presence. We hypothesise that it will be challenging to characterise vegetation phenology in regions where the number of valid (cloud-free) remotely-sensed observation is low or when the observations are unevenly distributed over the year. This paper aims to evaluate whether there is sufficient availability of Landsat 7 and 8 images over Brazil to support the analysis of phenodynamics of vegetation. We used Google Earth Engine to assess Landsat data availability during the last decades over the Brazilian territory. The valid observations (excluding clouds and shadow areas) from Landsat 4/5/7/8 during the period 1984–2017 were determined at pixel level. The results show a lower intensity of Landsat observations in the northern and northeastern parts of Brazil compared to the southern region, mainly due to clouds’ presence. Taking advantage of the overlapping areas between satellite paths where the number of observations is larger, we modelled the loss of information caused by a lower number of valid (cloud free) observations. We showed that, in the deciduous woody formations of the Caatinga dominium, the scarcity of valid observations has an adverse effect on indices’ performance aimed at describing vegetation phenology. However, the combination of Landsat data with satellite constellation such as Sentinel will likely permit to overcome many of these limitations.

【 授权许可】

Unknown