scholarly journals Linking vegetation cover and seasonal thaw depths in interior Alaska permafrost terrains using remote sensing

2019 ◽  
Vol 233 ◽  
pp. 111363 ◽  
Author(s):  
John E. Anderson ◽  
Thomas A. Douglas ◽  
Robyn A. Barbato ◽  
Stephanie Saari ◽  
Jarrod D. Edwards ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Interior Alaska

scholarly journals Rapid Evaluation and Validation Method of Above Ground Forest Biomass Estimation Using Optical Remote Sensing in Tundi Reserved Forest Area, India

2021 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Praveen Kumar ◽  
Akhouri P. Krishna ◽  
Thorkild M. Rasmussen ◽  
Mahendra K. Pal
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Test Site ◽  
Forest Area ◽  
Relational Model ◽  
Biomass Estimation ◽  
Optical Remote Sensing ◽  
Ground Sample ◽  
Sensing Data

Optical remote sensing data are freely available on a global scale. However, the satellite image processing and analysis for quick, accurate, and precise forest above ground biomass (AGB) evaluation are still challenging and difficult. This paper is aimed to develop a novel method for precise, accurate, and quick evaluation of the forest AGB from optical remote sensing data. Typically, the ground forest AGB was calculated using an empirical model from ground data for biophysical parameters such as tree density, height, and diameter at breast height (DBH) collected from the field at different elevation strata. The ground fraction of vegetation cover (FVC) in each ground sample location was calculated. Then, the fraction of vegetation cover (FVC) from optical remote sensing imagery was calculated. In the first stage of method implementation, the relation model between the ground FVC and ground forest AGB was developed. In the second stage, the relational model was established between image FVC and ground FVC. Finally, both models were fused to derive the relational model between image FVC and forest AGB. The validation of the developed method was demonstrated utilizing Sentinel-2 imagery as test data and the Tundi reserved forest area located in the Dhanbad district of Jharkhand state in eastern India was used as the test site. The result from the developed model was ground validated and also compared with the result from a previously developed crown projected area (CPA)-based forest AGB estimation approach. The results from the developed approach demonstrated superior capabilities in precision compared to the CPA-based method. The average forest AGB estimation of the test site obtained by this approach revealed 463 tons per hectare, which matches the previous estimate from this test site.

Using multilevel remote sensing and ground data to estimate forest biomass resources in remote regions: a case study in the boreal forests of interior Alaska

2011 ◽  
Vol 37 (6) ◽  
pp. 596-611 ◽  
Author(s):  
Hans-Erik Andersen ◽  
Jacob Strunk ◽  
Hailemariam Temesgen ◽  
Donald Atwood ◽  
Ken Winterberger
Keyword(s):  
Remote Sensing ◽  
Boreal Forests ◽  
Forest Biomass ◽  
Interior Alaska ◽  
Biomass Resources

Investigation of Ecosystem Restoration at Sites of Spent Coal Deposits in the Regions of the Urals Using Remote Sensing Resources

2021 ◽  
Vol 25 (1) ◽  
pp. 32-37
Author(s):  
I.V. Zenkov ◽  
Yu.P. Yuronen ◽  
G.I. Yurkovskaya ◽  
M.V. Safronov ◽  
P.M. Kondrashov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Monitoring ◽  
Vegetation Cover ◽  
Ecosystem Restoration ◽  
Ecological State ◽  
The Urals ◽  
Natural Processes ◽  
Coal Deposits

The results of assessing the ecological state of lands disturbed during the open-cut mining of four coal deposits in the Sverdlovsk and Chelyabinsk regions are presented. In the course of the studies carried out using the results of remote monitoring, it was found that ecologically acceptable restoration of vegetation cover on the territory of disturbed lands occurs as a result of reclamation work and natural processes of its self-restoration.

scholarly journals Spatial and temporal variation of vegetation cover in Al- Soudah area and its relationship to precipitation during the period (2014- 2018 AD) using remote sensing and geographic information systems: التباين المكاني والزمني للغطاء النباتي بمنطقة السودة وعلاقته بالتساقط خلال الفترة (2014- 2018م) باستخدام الاستشعار عن بعد ونظم المعلومات الجغرافية

2021 ◽  
Vol 5 (3) ◽  
pp. 107-87
Author(s):  
Fadi Abdullah alanazi, Yaser Rashed Alzannan, Faten Hamed Na Fadi Abdullah alanazi, Yaser Rashed Alzannan, Faten Hamed Na
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Geographic Information ◽  
Temporal Changes ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Changes ◽  
Modified Soil

Souda is one of the important regions in Saudi Arabia in terms of spatial and temporal changes in vegetation cover; It includes the National Park, which is a leading tourist destination and one of the most beautiful parks in it. by tracking the spatial and temporal changes of vegetation cover by integrating remote sensing and geographic information systems, through the application of the modified soil vegetation index MSAVI during the period (2014- 2018), it became clear the decrease in the quantity and density of vegetation cover in the area. Thus, the study concluded that this indicator is one of the best indicators that can be used to extract vegetation cover from satellite images.

scholarly journals Towards an integrated soil moisture drought monitor for East Africa

2012 ◽  
Vol 9 (4) ◽  
pp. 4587-4631 ◽  
Author(s):  
W. B. Anderson ◽  
B. F. Zaitchik ◽  
C. R. Hain ◽  
M. C. Anderson ◽  
M. T. Yilmaz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
East Africa ◽  
Remote Monitoring ◽  
Vegetation Cover ◽  
Land Surface ◽  
Microwave Remote Sensing ◽  
Surface Model ◽  
Monitoring Methods ◽  
Data Scarcity

Abstract. Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010–2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically-based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of anomaly estimates across independent methods. This approach holds potential as a remote soil moisture-based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa.

scholarly journals MONITORAMENTO DA COBERTURA VEGETAL POR SENSORIAMENTO REMOTO NO SEMIÁRIDO BRASILEIRO ATRAVÉS DE ÍNDICES DE VEGETAÇÃO

Nativa ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 708
Author(s):  
Caio Victor Santos Silva ◽  
Jhon Lennon Bezerra da Silva ◽  
Geber Barbosa De Albuquerque Moura ◽  
Pabrício Marcos Oliveira Lopes ◽  
Cristina Rodrigues Nascimento ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Environmental Changes ◽  
Spectral Response ◽  
Vegetation Indices ◽  
Digital Processing ◽  
Semiarid Region ◽  
Dry Period ◽  
Biophysical Parameters ◽  
Brazilian Semiarid

São necessárias medidas que visem à proteção e conservação dos recursos hídricos e naturais de forma rápida e eficiente. As técnicas de sensoriamento remoto são essenciais para o monitoramento ambiental dos recursos no semiárido no espaço e no tempo. Objetivou-se monitorar e analisar à dinâmica da cobertura vegetal através da variabilidade espaço-temporal do albedo da superfície e índices de vegetação em região de Caatinga do semiárido brasileiro por sensoriamento remoto. A área de estudo é o município de Arcoverde, localizado no semiárido de Pernambuco. O estudo foi desenvolvido através de seis imagens orbitais do Landsat-5 do sensor TM. O processamento digital dos parâmetros biofísicos foi realizado pelo algoritmo SEBAL. Os resultados foram analisados através da estatística descritiva e quanto a sua variabilidade. Áreas possivelmente degradadas foram identificadas pelos altos valores de albedo e índices de vegetação significativamente menores, localizadas à sudoeste e noroeste da região. Os índices apresentaram comportamento similares, principalmente no período seco, com baixos valores sendo próximos de zero, áreas afetadas pelo período de seca no semiárido. O SAVI apresentou maior precisão, destacando melhor resposta espectral da vegetação. O sensoriamento remoto promoveu monitoramento espaço-temporal adequado, destacando principalmente o período classificado como climaticamente seco através do albedo e índices de vegetação.Palavras-chave: Caatinga; NDVI; SAVI; mudanças ambientais; SEBAL. MONITORING OF VEGETATION COVER BY REMOTE SENSING IN BRAZILIAN SEMIARID THROUGH VEGETATION INDICES ABSTRACT: Measures are needed aimed at the protection and conservation of water and natural resources quickly and efficiently. Remote sensing techniques are essential for the environmental monitoring of resources in the semiarid region in space and time. Aimed to monitor and analyze the dynamics of vegetation cover through the spatial-temporal variability of the surface albedo and indices of vegetation in the Caatinga region of the Brazilian semiarid by remote sensing. The study area is the municipality of Arcoverde, located in the semiarid of Pernambuco. The study was developed through six orbital images of Landsat-5 of the TM sensor. The digital processing of the biophysical parameters was performed by the SEBAL algorithm. The results were analyzed through descriptive statistics and their variability. Possibly degraded areas were identified by high albedo values and significantly lower vegetation indices, located in the southwest and northwest of the region. The indexes showed similar behavior, mainly in the dry period, with low values being close to zero, areas affected by the dry period in the semiarid. The SAVI presented higher accuracy, highlighting better spectral response of the vegetation. Remote sensing promoted adequate space-time monitoring, highlighting mainly the period classified as climatically dry through the albedo and vegetation indexes.Keywords: Caatinga; NDVI; SAVI; environmental changes; SEBAL.

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