Woody vegetation cover in Namibian savannahs: a modelling approach based on remote sensing

Erdkunde ◽  
2007 ◽  
Vol 61 (4) ◽  
pp. 325-334 ◽  
Author(s):  
Hendrik Wagenseil ◽  
Cyrus Samimi
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Woody Vegetation ◽  
Modelling Approach

scholarly journals Precipitation-Sensitive Dynamic Threshold: A New and Simple Method to Detect and Monitor Forest and Woody Vegetation Cover in Sub-Humid to Arid Areas

2020 ◽  
Vol 12 (8) ◽  
pp. 1231 ◽  
Author(s):  
Ron Drori ◽  
Harel Dan ◽  
Michael Sprintsin ◽  
Efrat Sheffer
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Lower Threshold ◽  
Woody Vegetation ◽  
Mean Annual Precipitation ◽  
Dynamic Threshold ◽  
Arid Areas ◽  
Simple Method ◽  
Area Index ◽  
Semi Arid

Remote-sensing tools and satellite data are often used to map and monitor changes in vegetation cover in forests and other perennial woody vegetation. Large-scale vegetation mapping from remote sensing is usually based on the classification of its spectral properties by means of spectral Vegetation Indices (VIs) and a set of rules that define the connection between them and vegetation cover. However, observations show that, across a gradient of precipitation, similar values of VI can be found for different levels of vegetation cover as a result of concurrent changes in the leaf density (Leaf Area Index—LAI) of plant canopies. Here we examine the three-way link between precipitation, vegetation cover, and LAI, with a focus on the dry range of precipitation in semi-arid to dry sub-humid zones, and propose a new and simple approach to delineate woody vegetation in these regions. By showing that the range of values of Normalized Difference Vegetation Index (NDVI) that represent woody vegetation changes along a gradient of precipitation, we propose a data-based dynamic lower threshold of NDVI that can be used to delineate woody vegetation from non-vegetated areas. This lower threshold changes with mean annual precipitation, ranging from less than 0.1 in semi-arid areas, to over 0.25 in mesic Mediterranean area. Validation results show that this precipitation-sensitive dynamic threshold provides a more accurate delineation of forests and other woody vegetation across the precipitation gradient, compared to the traditional constant threshold approach.

scholarly journals Woody Vegetation Cover, Attrition, and Patch Metrics over Eight Decades in Central Texas, United States

2021 ◽  
Vol 78 ◽  
pp. 54-66
Author(s):  
Edward C. Rhodes ◽  
Jay P. Angerer ◽  
William E. Fox ◽  
Jason R. McAlister
Keyword(s):  
United States ◽  
Vegetation Cover ◽  
Woody Vegetation ◽  
Central Texas

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.

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 Assessing the impact of climate variability on catchment water balance and vegetation cover

2011 ◽  
Vol 8 (3) ◽  
pp. 6291-6329 ◽  
Author(s):  
X. Xu ◽  
D. Yang ◽  
M. Sivapalan
Keyword(s):  
Statistical Analysis ◽  
Water Balance ◽  
Climate Variability ◽  
Vegetation Cover ◽  
Growing Season ◽  
Woody Vegetation ◽  
Elasticity Analysis ◽  
Total Runoff ◽  
Subsurface Runoff ◽  
Growing Season Precipitation

Abstract. Understanding the interactions among climate, vegetation cover and the water cycle lies at the heart of the study of watershed ecohydrology. Recently, considerable attention is being paid to the effect of climate variability (e.g., precipitation and temperature) on catchment water balance and also associated vegetation cover. In this paper, we investigate the general pattern of long-term water balance and vegetation cover (as reflected in fPAR) among 193 study catchments in Australia through statistical analysis. We then employ the elasticity analysis approach for quantifying the effects of climate variability on hydrologic partitioning (including total runoff, surface and subsurface runoff) and on vegetation cover (including total, woody and non-woody vegetation cover). Based on the results of statistical analysis, we conclude that annual runoff (R), evapotranspiration (E) and runoff coefficient (R/P) all increase with vegetation cover for catchments in which woody vegetation is dominant and annual precipitation is relatively high. Annual evapotranspiration (E) is mainly controlled by water availability rather than energy availability for catchments in relatively dry climates in which non-woody vegetation is dominant. The ratio of subsurface runoff to total runoff (Rg/R) also increases with woody vegetation cover. Through the elasticity analysis of catchment runoff, it is shown that precipitation (P) in the current year is the most important factor affecting the change in annual total runoff (R), surface runoff (Rs) and subsurface runoff (Rg). The significance of other controlling factors is in the order of the annual precipitation in the previous year (P−1 and P−2), which represent the net effect of soil moisture, and the annual mean temperature (T) in the current year. Change of P by +1 % causes a +3.35 % change of R, a +3.47 % change of Rs and a +2.89 % change of Rg, on average. Likewise a change of temperature of +1° causes a −0.05 % change of R, a −0.07 % change of Rs and a −0.10 % change of Rg, on average. Results of elasticity analysis on the maximum monthly vegetation cover indicate that incoming shortwave radiation during the growing season (Rsd,grow) is the most important factor affecting the change in vegetation cover. Change of Rsd,grow by +1 % produces a −1.08 % change of total vegetation cover (Ft) on average. The significance of other causative factors is in the order of the precipitation during growing season, mean temperature during growing season and precipitation during non-growing season. The growing season precipitation is more significant than the non-growing season precipitation to non-woody vegetation cover, but the both have equivalent effects to woody vegetation cover.

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.

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