Suchergebnisse

Abstract. The growing number and effectiveness of Earth observation satellite systems, along with the increasing reliability of remote sensing methodologies and techniques, present a wide range of new capabilities in monitoring and assessing droughts. A number of drought indices have been developed based on NOAA-AVHRR data exploiting the remote sensing potential at different temporal scales. In this paper, the remotely sensed Reconnaissance Drought Index (RDI) is employed for the quantification of drought. RDI enables the assessment of hydro-meteorological drought, since it uses hydrometeorological parameters, such as precipitation and potential evapotranspiration. The study area is Thessaly, central Greece, which is a drought-prone agricultural region characterized by vulnerable agriculture. Several drought features are analyzed and assessed by using monthly RDI images over the period 1981–2001: severity, areal extent, duration, periodicity, onset and end time. The results show an increase in the areal extent during each drought episode and that droughts are classified into two classes, namely small areal extent drought and large areal extent drought, respectively, lasting 12 or 13 months coinciding closely with the hydrological year. The onset of large droughts coincides with the beginning of the hydrological year, whereas the onset of small droughts is in spring. During each drought episode, the maximum occurs usually in the summer and they all last until the end of the hydrological year. This finding could justify an empirical prognostic potential of drought assessment.

Abstract. Wildfire can become a catastrophic natural hazard, especially during dry summer seasons in Australia. Severity is influenced by various meteorological, geographical, and fuel characteristics. Modified Mark 4 McArthur's Grassland Fire Danger Index (GFDI) is a commonly used approach to determine the fire danger level in grassland ecosystems. The degree of curing (DOC, i.e. proportion of dead material) of the grass is one key ingredient in determining the fire danger. It is difficult to collect accurate DOC information in the field, and therefore ground-observed measurements are rather limited. In this study, we explore the possibility of whether adding satellite-observed data responding to vegetation water content (vegetation optical depth, VOD) will improve DOC prediction when compared with the existing satellite-observed data responding to DOC prediction models based on vegetation greenness (normalised difference vegetation index, NDVI). First, statistically significant relationships are established between selected ground-observed DOC and satellite-observed vegetation datasets (NDVI and VOD) with an r2 up to 0.67. DOC levels estimated using satellite observations were then evaluated using field measurements with an r2 of 0.44 to 0.55. Results suggest that VOD-based DOC estimation can reasonably reproduce ground-based observations in space and time and is comparable to the existing NDVI-based DOC estimation models.

Urban trees and forests provide multiple ecosystem services (ES), including temperature regulation, carbon sequestration, and biodiversity. Interest in ES has increased amongst policymakers, scientists, and citizens given the extent and growth of urbanized areas globally. However, the methods and techniques used to properly assess biodiversity and ES provided by vegetation in urban environments, at large scales, are insufficient. Individual tree identification and characterization are some of the most critical issues used to evaluate urban biodiversity and ES, given the complex spatial distribution of vegetation in urban areas and the scarcity or complete lack of systematized urban tree inventories at large scales, e.g., at the regional or national levels. This often limits our knowledge on their contributions toward shaping biodiversity and ES in urban areas worldwide. This paper provides an analysis of the state-of-the-art studies and was carried out based on a systematic review of 48 scientific papers published during the last five years (2016–2020), related to urban tree and greenery characterization, remote sensing techniques for tree identification, processing methods, and data analysis to classify and segment trees. In particular, we focused on urban tree and forest characterization using remotely sensed data and identified frontiers in scientific knowledge that may be expanded with new developments in the near future. We found advantages and limitations associated with both data sources and processing methods, from which we drew recommendations for further development of tree inventory and characterization in urban forestry science. Finally, a critical discussion on the current state of the methods, as well as on the challenges and directions for future research, is presented. ; This work was financially supported by the Catalan Government through the fundinggrant ACCIÓ-Eurecat.

Voluntarily or not, women are moved in great numbers from Manila to Nigeria, from Burma to Thailand, and from post-socialist countries to Western Europe: female geobodies in the flow of global capitalism. The recently released 53-minute video essay Remote Sensing by the Swiss artist and video director Ursula Biemann traces the routes and reasons of women who migrate into the global sex industry. Taking a geographical approach to trafficking, the video develops a particular visual language generated by new media and satellite technologies, which traces the migration of women in the age of digital images. All stills are taken from the video that was shot in the Philippines, Thailand, California, and the German–Czech border.