scholarly journals Surface Temperatures at the Continental Scale: Tracking Changes with Remote Sensing at Unprecedented Detail

2014 ◽  
Vol 6 (5) ◽  
pp. 3822-3840 ◽  
Author(s):  
Markus Metz ◽  
Duccio Rocchini ◽  
Markus Neteler
2021 ◽  
Vol 13 (7) ◽  
pp. 1247
Author(s):  
Bowen Zhu ◽  
Xianhong Xie ◽  
Chuiyu Lu ◽  
Tianjie Lei ◽  
Yibing Wang ◽  
...  

Extreme hydrologic events are getting more frequent under a changing climate, and a reliable hydrological modeling framework is important to understand their mechanism. However, existing hydrological modeling frameworks are mostly constrained to a relatively coarse resolution, unrealistic input information, and insufficient evaluations, especially for the large domain, and they are, therefore, unable to address and reconstruct many of the water-related issues (e.g., flooding and drought). In this study, a 0.0625-degree (~6 km) resolution variable infiltration capacity (VIC) model developed for China from 1970 to 2016 was extensively evaluated against remote sensing and ground-based observations. A unique feature in this modeling framework is the incorporation of new remotely sensed vegetation and soil parameter dataset. To our knowledge, this constitutes the first application of VIC with such a long-term and fine resolution over a large domain, and more importantly, with a holistic system-evaluation leveraging the best available earth data. The evaluations using in-situ observations of streamflow, evapotranspiration (ET), and soil moisture (SM) indicate a great improvement. The simulations are also consistent with satellite remote sensing products of ET and SM, because the mean differences between the VIC ET and the remote sensing ET range from −2 to 2 mm/day, and the differences for SM of the top thin layer range from −2 to 3 mm. Therefore, this continental-scale hydrological modeling framework is reliable and accurate, which can be used for various applications including extreme hydrological event detections.


2021 ◽  
Vol 58 (03) ◽  
pp. 274-285
Author(s):  
H. V. Parmar ◽  
N. K. Gontia

Remote sensing based various land surface and bio-physical variables like Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), surface albedo, transmittance and surface emissivity are useful for the estimation of spatio-temporal variations in evapotranspiration (ET) using Surface Energy Balance Algorithm for Land (SEBAL) method. These variables were estimated under the present study for Ozat-II canal command in Junagadh district, Gujarat, India, using Landsat-7 and Landsat-8 images of summer season of years 2014 and 2015. The derived parameters were used in SEBAL to estimate the Actual Evapotranspiration (AET) of groundnut and sesame crops. The lower values NDVI observed during initial (March) and end (May) stages of crop growth indicated low vegetation cover during these periods. With full canopy coverage of the crops, higher value of NDVI (0.90) was observed during the mid-crop growth stage. The remote sensing-based LST was lower for agricultural areas and the area near banks of the canal and Ozat River, while higher surface temperatures were observed for rural settlements, road and areas with exposed dry soil. The maximum surface temperatures in the cropland were observed as 311.0 K during March 25, 2014 and 315.8 K during May 31, 2015. The AET of summer groundnut increased from 3.75 to 7.38 mm.day-1, and then decreased to 3.99 mm.day-1 towards the end stage of crop growth. The daily AET of summer sesame ranged from 1.06 to 7.72 mm.day-1 over different crop growth stages. The seasonal AET of groundnut and sesame worked out to 358.19 mm and 346.31 mm, respectively. The estimated AET would be helpful to schedule irrigation in the large canal command.


2016 ◽  
Vol 13 (17) ◽  
pp. 5085-5102 ◽  
Author(s):  
Caitlin E. Moore ◽  
Tim Brown ◽  
Trevor F. Keenan ◽  
Remko A. Duursma ◽  
Albert I. J. M. van Dijk ◽  
...  

Abstract. Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia's vegetation phenology is a challenge due to its diverse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semi-arid scrublands, and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e. drought, flooding, cyclones, and fire) that can alter ecosystem composition, structure, and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology on the continental scale using the enhanced vegetation index (EVI), calculated from MODerate resolution Imaging Spectroradiometer (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e. tropical savannas) to regions where seasonal variation is minimal (i.e. tropical rainforests) or high but irregular (i.e. arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understorey, as well as strong seasonal dynamics of individual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that phenocams have the potential to greatly improve the current understanding of Australian ecosystems. To facilitate the sharing of this information, we have formed the Australian Phenocam Network (http://phenocam.org.au/).


Author(s):  
Nathalie Pettorelli

This chapter provides an overview of how satellite remote sensing can help map the occurrence, and risk of occurrence, of several environmental disturbances; assess the extent of the associated damages; and monitor the recovery of the areas impacted by these disturbances. It particularly focuses on floods, wild fires, droughts, frost, extreme winter warming events, infestations and blooms, and bleaching events, as these are all well-known natural disturbances likely to change in frequency of occurrence and intensity over the coming decades. Through the use of examples, this chapter demonstrates how the utility of satellite remote sensing resides in the ability it provides to separate and characterise (i.e. through form, intensity, and trajectory) disturbances and responses at various spatial and temporal scales, thereby facilitating ecological knowledge expansion and the identification of relevant management actions. In particular, this contribution shows how satellites offer multiple opportunities to gain accurate information on the location, spatial extent, and duration of disturbances at the continental scale, which is needed to evaluate the ecosystem impacts of land cover changes due to, for example, wild fire, insect epidemics, and flooding, thereby reducing uncertainties in our ability to model global carbon budgets.


2004 ◽  
Vol 25 (7-8) ◽  
pp. 1423-1435 ◽  
Author(s):  
Raghu Murtugudde ◽  
Liping Wang ◽  
Eric Hackert ◽  
James Beauchamp ◽  
James Christian ◽  
...  

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