scholarly journals Evapotranspiration estimation using a normalized difference vegetation index transformation of satellite data

1994 ◽  
Vol 39 (4) ◽  
pp. 333-345 ◽  
Author(s):  
P. M. SEEVERS ◽  
R. W. OTTMANN
Keyword(s):  
Satellite Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Evapotranspiration Estimation

scholarly journals Relative Contribution of the Topographic Influence on the Triangle Approach for Evapotranspiration Estimation over Mountainous Areas

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaosong Zhao ◽  
Yuanbo Liu
Keyword(s):  
Complex Terrain ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Surface Air Temperature ◽  
Temperature Correction ◽  
Topographic Effects ◽  
Topographic Correction ◽  
Relative Contribution ◽  
Triangle Method ◽  
Evapotranspiration Estimation

Evapotranspiration (ET) is an important component of the water budget. Estimation ET through remote sensing over a mountainous terrain is typically obstructed by topographic effects. In this paper, topographic corrections were applied to ET estimates using the surface-air temperature difference-Normalized Difference Vegetation Index ((Ts-Ta)-NDVI) triangle method with MODIS data for the Taihu Basin in China. The effect of topography on ET was evaluated over an area with a complex terrain. After applying the topographic correction, the results indicate that the ET decreased with elevation and slope. The slope had a stronger impact on ET than the elevation, which caused the corrected ET to decrease by 90% from 6.8 mm day−1to 0.6 mm day−1for slopes over 50°. On average, the corrected ET decreased by 10.4% and 32.1% for north- and south-facing slopes, respectively. The ET corrected using the triangle method strongly depended on the evaporative fraction correction, which can mainly be attributed to the surface temperature correction. We conclude that a topographic correction is necessary when the triangle method is applied to areas with a complex terrain.

scholarly journals Active-layer thickness estimation from X-band SAR backscatter intensity

2017 ◽  
Vol 11 (1) ◽  
pp. 483-496 ◽  
Author(s):  
Barbara Widhalm ◽  
Annett Bartsch ◽  
Marina Leibman ◽  
Artem Khomutov
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Satellite Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Active Layer Thickness ◽  
Backscatter Intensity ◽  
X Band ◽  
Spatial Coverage ◽  
Microwave Backscatter

Abstract. The active layer above the permafrost, which seasonally thaws during summer, is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally, but a range of methods which utilize information from satellite data exist. Mostly, the normalized difference vegetation index (NDVI) obtained from optical satellite data is used as a proxy. The applicability has been demonstrated mostly for shallow depths of active-layer thickness (ALT) below approximately 70 cm. Some permafrost areas including central Yamal are, however, characterized by larger ALT. Surface properties including vegetation structure are also represented by microwave backscatter intensity. So far, the potential of such data for estimating ALT has not been explored. We therefore investigated the relationship between ALT and X-band synthetic aperture radar (SAR) backscatter of TerraSAR-X (averages for 10  ×  10 m window) in order to examine the possibility of delineating ALT with continuous and larger spatial coverage in this area and compare it to the already-established method of using NDVI from Landsat (30 m). Our results show that the mutual dependency of ALT and TerraSAR-X backscatter on land cover types suggests a connection of both parameters. A range of 5 dB can be observed for an ALT range of 100 cm (40–140 cm), and an R2 of 0.66 has been determined over the calibration sites. An increase of ALT with increasing backscatter can be determined. The root mean square error (RMSE) over a comparably heterogeneous validation site with maximum ALT of  >  150 cm is 20 cm. Deviations are larger for measurement locations with mixed vegetation types (especially partial coverage by cryptogam crust) with respect to the spatial resolution of the satellite data.

scholarly journals Mapping and Monitoring the Canopy Cover and Greenness of Southern Yellow Pines (Loblolly, Shortleaf, and Virginia Pines) in Central-Eastern Tennessee Using Multi-Temporal Landsat Satellite Data

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 499
Author(s):  
Clement Akumu ◽  
Raphael Smith ◽  
Solomon Haile
Keyword(s):  
Satellite Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Canopy Cover ◽  
Forest Products ◽  
The United States ◽  
Pinus Echinata ◽  
Random Forest Classification ◽  
Central Eastern ◽  
Landsat Satellite

Southern yellow pines such as loblolly, Virginia and shortleaf pines constitute forest products and contribute significantly to the economy of the United States (U.S.). However, little is understood about the temporal change in canopy cover and greenness of southern yellow pines, especially in Tennessee where they are used for timber and pulpwood. This study aims to map and monitor the canopy cover and greenness of southern yellow pines i.e., loblolly (Pinus taeda), shortleaf (Pinus echinata), and Virginia (Pinus Virginiana) pines in the years 1988, 1999 and 2016 in central-eastern Tennessee. Landsat time-series satellite data acquired in December 1988, November 1999 and February 2016 were used to map and monitor the canopy cover and greenness of loblolly, shortleaf and Virginia pines. The classification and mapping of the canopy cover of southern yellow pines were performed using a machine-learning random forest classification algorithm. Normalized Difference Vegetation Index (NDVI) was used to monitor the temporal variation in canopy greenness. In total, the canopy cover of southern yellow pines decreased by about 35% between December 1988 and February 2016. This information could be used by foresters and forest managers to support forest inventory and management.

scholarly journals Normalized Difference Vegetation Index in the Integration of Conservation Education

2018 ◽  
Vol 3 (1) ◽  
pp. 47 ◽  
Author(s):  
Ali Rahmat ◽  
Mustofa Abi Hamid ◽  
Muhammad Khoiru Zaki ◽  
Abdul Mutolib
Keyword(s):  
Developing Countries ◽  
Satellite Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forest Degradation ◽  
Conservation Education ◽  
Global Environment ◽  
Vegetation Monitoring ◽  
June July ◽  
Status Data

Forest plays an important role to support a global environment. Currently, forest degradation occurs in developing countries. Therefore, the excellent strategies to against the forest degradation must be found. One of the best solutions is understanding the information of vegetation condition. Here, the objective of this paper was to apply a method as the assessment of vegetation monitoring using satellite data in the integration of conservation education forest at great forest Wan Abdul Rachman in Lampung Province, Indonesia. In this study, normalized difference vegetation index (NDVI) was used, completed with satellite data (namely MODIS). This technique helps in monitoring vegetation status. Data NDVI from MODIS satellite data showed that forest area decrease very small from 2000-2017. The data was obtained for June, July, and the end of September.

scholarly journals Assessment of the impact of ungoverned spaces on insurgency in Borno State, Nigeria

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Sylvanus Helda Bernard ◽  
Mwanret Gideon Daful
Keyword(s):  
Population Density ◽  
Satellite Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Population Data ◽  
Information Criterion ◽  
The State ◽  
High Incidence ◽  
The Impact ◽  
Vegetal Cover

This study examines the relationship between ungoverned spaces and insurgency in the Borno State, Nigeria. The aim is to understand the influence of geographical variables on the activities of insurgence. The study used satellite data, population data and data on insurgency attack in the study area. Normalized Difference Vegetation Index, percentage rise in slope analysis and reclassification were used for the satellite data processing.  Geographically Weighted Regression (GWR) models was employed for data analysis. The findings revealed that LGAs in the central and the southern parts of the state recorded the highest number of insurgency attacks. The central and far northern part of the state has more vegetal cover, which has influenced the high incidence of insurgency attack observed. In addition, the very high incidence of insurgency attack (145) observed in Gwoza LGA, is largely attributed to the presence of the Gwoza Mountain, which is one of the main strong holds of the insurgents in Borno State. The GWR analysis reveals that the performance of the model with the population density was much better than the other variables with a corrected Akaike Information Criterion (AICc) value of 273.15, R-Squared values of 0.0323, 0.0224, 0.0203 and 0.8901 for the undulating terrain, vegetation, combination of vegetation and undulating terrain, and population density respectively. Thus, the study concludes that vegetal cover and population density have more influence on insurgency attack in the study area. Hence, the need for policy makers and security establishments to properly monitor the forested areas.

scholarly journals DURANKULAK LAKE ACTUAL STATE AND MONITORING USING SENTINEL 2 SATELLITE DATA

2019 ◽  
pp. 53-58
Author(s):  
Iva Ivanova ◽  
Iliyana Gigova ◽  
Temenuzhka Spassova ◽  
Nataliya Stankova
Keyword(s):  
Satellite Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Orthogonal Transformation ◽  
Transformation Model ◽  
Actual State ◽  
The European Union ◽  
Ramsar Convention ◽  
Natural Habitats ◽  
Sentinel 2

Durankulak Lake is one of the most important wetlands in Bulgaria and Europe. It is included in the Ramsar Convention and is recognized as an important bird area of world importance. The subject of protection within the protected zone is the condition of the natural habitats and the habitats of the species, including the natural species composition, the typical species and the conditions of the environment. Remote sensing methods provide opportunities for characterization and monitoring of the wetland on various scales that have not been done so far. In the present study satellite multispectral images from the European Union Copernicus Satellite Program, Sentinel 2 are used for assessment and monitoring of the actual state of the lake. Based on these satellite images, the boundaries of the protected wetland are derived. An index classification of the wetland was made. Normalized Difference Vegetation Index (NDVI) is used to classify sites within the protected area. Sentinel-2 satellite data to implement the orthogonal transformation model called Tasseled Cap Transformation (TCT) has also been used. The model is an effective method for classifying and analyzing of the processes related to the dynamics of changes, affecting the main components of the earth's surface: soil, water and vegetation. The spring survey of 2019 was selected for the present study. The results will show successful mapping and monitoring of the wetland, which will give a real idea of the state of the Durankulak Lake and the need to take conservation measures to protect it. Key words: monitoring, satellite data, wetlands, habitats

scholarly journals Spatial Upscaling of Tree-Ring-Based Forest Response to Drought with Satellite Data

2019 ◽  
Vol 11 (20) ◽  
pp. 2344 ◽  
Author(s):  
Peipei Xu ◽  
Wei Fang ◽  
Tao Zhou ◽  
Xiang Zhao ◽  
Hui Luo ◽  
...  
Keyword(s):  
Tree Ring ◽  
Satellite Data ◽  
Large Scale ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Windows ◽  
Ring Width ◽  
Continuous Measure ◽  
Tree Ring Data ◽  
Moderate Resolution Imaging Spectroradiometer

We have integrated the observational capability of satellite remote sensing with plot-scale tree-ring data to upscale the evaluation of forest responses to drought. Satellite data, such as the normalized difference vegetation index (NDVI), can provide a spatially continuous measure with limited temporal coverage, while tree-ring width index (RWI) provides an accurate assessment with a much longer time series at local scales. Here, we explored the relationship between RWI and NDVI of three dominant species in the Southwestern United States (SWUS) and predicted RWI spatial distribution from 2001 to 2017 based on Moderate Resolution Imaging Spectroradiometer (MODIS) 1-km resolution NDVI data with stringent quality control. We detected the optimum time windows (around June–August) during which the RWI and NDVI were most closely correlated for each species, when the canopy growth had the greatest effect on growth of tree trunks. Then, using our upscaling algorithm of NDVI-based RWI, we were able to detect the significant impact of droughts in 2002 and in 2011–2014, which supported the validity of this algorithm in quantifying forest response to drought on a large scale.

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