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Soil Temperature Variability in Complex Terrain Measured Using Fiber-Optic Distributed Temperature Sensing
摘要： Soil temperature (Ts) exerts critical controls on hydrologic and biogeochemical processes, but the magnitude and nature of Ts variability in a landscape setting are rarely documented. Fiber-optic distributed temperature sensing (DTS) systems potentially measure Ts at high density across a large extent. A fiber-optic cable 771 m long was installed at a depth of 10 cm in contrasting landscape units (LUs) defined by vegetative cover at Upper Sheep Creek in the Reynolds Creek Experimental Watershed (RCEW) and Critical Zone Observatory in Idaho. The purpose was to evaluate the applicability of DTS in remote settings and to characterize Ts variability in complex terrain. Measurement accuracy was similar to other field instruments (±0.4°C), and Ts changes of approximately 0.05°C at a monitoring spatial scale of 1 m were resolved with occasional calibration and an ambient temperature range of 50°C. Differences in solar inputs among LUs were strongly modified by surface conditions. During spatially continuous snow cover, Ts was practically homogeneous across LUs. In the absence of snow cover, daily average Ts was highly variable among LUs due to variations in vegetative cover, with a standard deviation (SD) greater than 5°C, and relatively uniform (SD < 1.5°C) within LUs. Mean annual soil temperature differences among LUs of 5.2°C was greater than those of 4.4°C associated with a 910-m elevation difference within the RCEW. In this environment, effective Ts simulation requires representation of relatively small-scale (<20 m) LUs due to the deterministic spatial variability of Ts.
关键词： landscape units,complex terrain,vegetative cover,fiber-optic cable,snow cover,spatial variability,Soil temperature,distributed temperature sensing
更新于2025-09-23 15:22:29
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Télédétection satellitaire des surfaces enneigées et englacées
摘要： This article presents an overview of recent advances in remote sensing applied to the study of snow and glacierized areas, in which the French scientific community has been involved. Whatever the type of satellite data, optical, radar, lidar or gravimetric, these works on seasonal or perennial snow cover, mountain glaciers, ice caps, sea ice, and lake or river ice, aim at documenting both the physical characteristics of these objects and their spatial and temporal variability at local, regional or global scales.
关键词： glaciers,remote sensing,snow,ice,spatial variability,satellite data,temporal variability
更新于2025-09-23 15:21:21
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Spectral data source effect on crop state estimation by vegetation indices
摘要： Spectral vegetation indices (VIs) are a well-known and widely used method for crop state estimation. The ability to monitor crop state by such indices is an important tool for agricultural management. Even though differences in imagery and point-based spectroscopy are obvious, their impact on crop state estimation by VIs is not well-studied. The aim of this study was to assess the performance level of the selected VIs calculated from spaceborne multispectral imagery and point-based field spectroscopy in application to crop state estimation. For this purpose, irrigated chickpea field was monitored by RapidEye satellite mission and additional measurements by field spectrometer were obtained. Estimated VIs average and coefficient of variation from each observation were compared with physical crop measurements: leaf water content, LAI and chlorophyll level. The results indicate that indices calculated from spaceborne spectral images regardless of the claimed response commonly react on phenology of the irrigated chickpea. This feature makes spaceborne spectral imagery an appropriate data source for monitoring crop development, crop water needs and yield prediction. VIs calculated from field spectrometer were sensitive for estimating pigment concentration and photosynthesis rate. Yet, a hypersensitivity of field spectral measures might lead to a very high variability (up to 69%) of the calculated values. Consequently, the high spatial variability of field spectral measurements depreciates the estimation agricultural field state by average mean only. Nevertheless, the spatial variability might have certain behavior trend, e.g., a significant increase in the active growth or stress and can be an independent feature for field state assessment.
关键词： Vegetation indices,Spatial variability,Agriculture management,Field spectroscopy,Spaceborne spectral imagery
更新于2025-09-11 14:15:04