scholarly journals A Brief Analysis of the Triangle Method and a Proposal for its Operational Implementation

2020 ◽  
Vol 12 (22) ◽  
pp. 3832
Author(s):  
Toby N. Carlson
Keyword(s):  
Remote Sensing ◽  
Moisture Index ◽  
Thermal Remote Sensing ◽  
Crop Moisture Index ◽  
Triangle Method

The well-known triangle method in optical/thermal remote sensing, its construction, uncertainties, and the significance of its products are first discussed. These topics are then followed by an outline of how the method can be implemented operationally for practical use, including a suggestion for constructing a dynamic crop moisture index.

scholarly journals An Assessment of Drought Stress in Tea Estates Using Optical and Thermal Remote Sensing

2021 ◽  
Vol 13 (14) ◽  
pp. 2730
Author(s):  
Animesh Chandra Das ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Drought Stress ◽  
Land Surface ◽  
Climatic Factors ◽  
Standardized Precipitation Index ◽  
Landsat 8 ◽  
Drought Frequency ◽  
Moisture Index ◽  
Area Index ◽  
Drought Period

Drought is one of the detrimental climatic factors that affects the productivity and quality of tea by limiting the growth and development of the plants. The aim of this research was to determine drought stress in tea estates using a remote sensing technique with the standardized precipitation index (SPI). Landsat 8 OLI/TIRS images were processed to measure the land surface temperature (LST) and soil moisture index (SMI). Maps for the normalized difference moisture index (NDMI), normalized difference vegetation index (NDVI), and leaf area index (LAI), as well as yield maps, were developed from Sentinel-2 satellite images. The drought frequency was calculated from the classification of droughts utilizing the SPI. The results of this study show that the drought frequency for the Sylhet station was 38.46% for near-normal, 35.90% for normal, and 25.64% for moderately dry months. In contrast, the Sreemangal station demonstrated frequencies of 28.21%, 41.02%, and 30.77% for near-normal, normal, and moderately dry months, respectively. The correlation coefficients between the SMI and NDMI were 0.84, 0.77, and 0.79 for the drought periods of 2018–2019, 2019–2020 and 2020–2021, respectively, indicating a strong relationship between soil and plant canopy moisture. The results of yield prediction with respect to drought stress in tea estates demonstrate that 61%, 60%, and 60% of estates in the study area had lower yields than the actual yield during the drought period, which accounted for 7.72%, 11.92%, and 12.52% yield losses in 2018, 2019, and 2020, respectively. This research suggests that satellite remote sensing with the SPI could be a valuable tool for land use planners, policy makers, and scientists to measure drought stress in tea estates.

scholarly journals Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

2021 ◽  
Vol 13 (7) ◽  
pp. 1340
Author(s):  
Shuailong Feng ◽  
Shuguang Liu ◽  
Lei Jing ◽  
Yu Zhu ◽  
Wende Yan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Environmental Impacts ◽  
Land Surface ◽  
Vegetation Index ◽  
Highway Construction ◽  
Temporal Changes ◽  
Moisture Index ◽  
Buffer Zones ◽  
Wide Range ◽  
Spatial And Temporal Changes

Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.

scholarly journals A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing

Sensors ◽  
2017 ◽  
Vol 17 (7) ◽  
pp. 1542 ◽  
Author(s):  
Thomas Udelhoven ◽  
Martin Schlerf ◽  
Karl Segl ◽  
Kaniska Mallick ◽  
Christian Bossung ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Thermal Remote Sensing

Thermal remote sensing of snow cover to identify the extent of hydrothermal areas in Yellowstone National Park

2012 ◽  
Author(s):  
Christopher M. U. Neale ◽  
S. Sivarajan ◽  
A. Masih ◽  
C. Jaworowski ◽  
H. Heasler
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Yellowstone National Park ◽  
National Park ◽  
Thermal Remote Sensing

scholarly journals Utilization of Thermal Remote Sensing in Water Resource Management

2014 ◽  
Vol 7 (1) ◽  
Author(s):  
Morris Scherer Warren ◽  
Antônio Heriberto de Castro Teixeira ◽  
Lineu Neiva Rodrigues ◽  
Fernando Braz Tangerino Hernandez
Keyword(s):  
Remote Sensing ◽  
Resource Management ◽  
Water Resource ◽  
Water Resource Management ◽  
Thermal Remote Sensing
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