scholarly journals Tropical montane forests are a larger than expected global carbon store

2014 ◽  
Vol 11 (10) ◽  
pp. 2741-2754 ◽  
Author(s):  
D. V. Spracklen ◽  
R. Righelato
Keyword(s):  
Land Surface ◽  
Forest Cover ◽  
Slope Angle ◽  
Remotely Sensed ◽  
Data Sets ◽  
Remotely Sensed Data ◽  
Montane Forests ◽  
Tropical Montane Forests ◽  
Global Land ◽  
Steep Slopes

Abstract. Tropical montane forests (TMFs) are recognized for the provision of hydrological services and the protection of biodiversity, but their role in carbon storage is not well understood. We synthesized published observations (n = 94) of above-ground biomass (AGB) from forest inventory plots in TMFs (defined here as forests between 23.5° N and 23.5° S with elevations ≥ 1000 m a.s.l.). We found that mean (median) AGB in TMFs is 271 (254) t per hectare of land surface. We demonstrate that AGB declines moderately with both elevation and slope angle but that TMFs store substantial amounts of biomass, both at high elevations (up to 3500 m) and on steep slopes (slope angles of up to 40°). We combined remotely sensed data sets of forest cover with high resolution data of elevation to show that 75% of the global planimetric (horizontal) area of TMF are on steep slopes (slope angles greater than 27°). We used our remote sensed data sets to demonstrate that this prevalence of steep slopes results in the global land surface area of TMF (1.22 million km2) being 40% greater than the planimetric area that is the usual basis for reporting global land surface areas and remotely sensed data. Our study suggests that TMFs are likely to be a greater store of carbon than previously thought, highlighting the need for conservation of the remaining montane forests.

scholarly journals Tropical montane forests are a larger than expected global carbon store

2013 ◽  
Vol 10 (12) ◽  
pp. 18893-18924 ◽  
Author(s):  
D. V. Spracklen ◽  
R. Righelato
Keyword(s):  
Land Surface ◽  
Forest Cover ◽  
Slope Angle ◽  
Remotely Sensed Data ◽  
Montane Forests ◽  
High Resolution Data ◽  
Tropical Montane Forests ◽  
Global Land ◽  
Carbon Store ◽  
Steep Slopes

Abstract. Tropical montane forests (TMFs) are recognised for the provision of hydrological services and the protection of biodiversity, but their role in carbon storage is not well understood. We synthesized published observations (n=89) of above-ground biomass (AGB) from forest inventory plots in TMFs (defined here as forests between 23.5° N and 23.5° S with elevations ≥ 1000 m a.s.l.). We found that mean (median) AGB in TMF is 257 (239) t per hectare of Earth's surface. We demonstrate that AGB declines moderately with both elevation and slope angle but that TMF store substantial amounts of biomass, both at high elevations (up to 3500 m) and on steep slopes (slope angles of up to 40°). We combined remote sensed datasets of forest cover with high resolution data of elevation to show that seventy five percent of the planimetric global area of TMF are on steep slopes (slope angles greater than 27°). We used our remote sensed datasets to demonstrate that this prevalence of steep slopes results in the global land-surface area of TMF (1.22 million km2) being 40% greater than the planimetric (horizontal) area that is the usual basis for reporting global land surface areas and remotely sensed data. Our study suggests that TMF are likely to be a greater store of carbon than previously thought, highlighting the need for conservation of remaining montane forests.

scholarly journals Assessing the relationship between environmental factors and malaria vector breeding sites in Swaziland using multi-scale remotely sensed data

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Sabelo Nick Dlamini ◽  
Jonas Franke ◽  
Penelope Vounatsou
Keyword(s):  
Environmental Factors ◽  
Spatial Resolution ◽  
Malaria Vector ◽  
Land Surface ◽  
High Spatial Resolution ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Breeding Sites ◽  
Multi Scale ◽  
The Relationship

Many entomological studies have analyzed remotely sensed data to assess the relationship between malaria vector distribution and the associated environmental factors. However, the high cost of remotely sensed products with high spatial resolution has often resulted in analyses being conducted at coarse scales using open-source, archived remotely sensed data. In the present study, spatial prediction of potential breeding sites based on multi-scale remotely sensed information in conjunction with entomological data with special reference to presence or absence of larvae was realized. Selected water bodies were tested for mosquito larvae using the larva scooping method, and the results were compared with data on land cover, rainfall, land surface temperature (LST) and altitude presented with high spatial resolution. To assess which environmental factors best predict larval presence or absence, Decision Tree methodology and logistic regression techniques were applied. Both approaches showed that some environmental predictors can reliably distinguish between the two alternatives (existence and non-existence of larvae). For example, the results suggest that larvae are mainly present in very small water pools related to human activities, such as subsistence farming that were also found to be the major determinant for vector breeding. Rainfall, LST and altitude, on the other hand, were less useful as a basis for mapping the distribution of breeding sites. In conclusion, we found that models linking presence of larvae with high-resolution land use have good predictive ability of identifying potential breeding sites.

scholarly journals Combining remotely sensed data using aggregation algorithms

1998 ◽  
Vol 2 (2/3) ◽  
pp. 149-158 ◽  
Author(s):  
W. J. Shuttleworth
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Remotely Sensed ◽  
Surface Radiation ◽  
Control Surface ◽  
Future Research ◽  
Practical Implementation ◽  
Remotely Sensed Data ◽  
Theoretical Concepts ◽  
Average Value

Abstract. This paper describes a strategic approach for providing documentation of the surface energy exchange for heterogeneous land surfaces via the simultaneous, four-dimensional assimilation of several streams of remotely sensed data into a coupled land surface-atmosphere model. The basic concepts and underlying theory behind this proposed approach are presented with the intent that this will guide, facilitate, and stimulate future research focused on its practical implementation when appropriate data from the Earth Observing System (EOS) become available. The theoretical concepts that underlie the approach are derived from relationships between the values of parameters which control surface exchanges at pixel (or patch) scale and the area-average value of equivalent parameters applicable at larger, grid scale. A three-step implementation method is proposed which involves (a) estimating grid-average surface radiation fluxes from appropriate remotely sensed data; (b) absorbing these radiation flux estimates into a four-dimensional data assimilation model in which grid-average values of vegetation-related parameters are calculated from pertinent remotely sensed data using the equations that link pixel and grid scales; and (c) improving the resulting estimate of the surface energy balance-again using scale-linking equations by estimating the effect of soil-moisture availability, perhaps assuming that cloud-free pixels are an unbiased subsample of all the pixels in the grid square.

scholarly journals GIS and Remote Sensing Application in Water Management in Agriculture Field

2020 ◽  
Author(s):  
Sassi Mohamed Taher
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Resources ◽  
Land Surface ◽  
Remotely Sensed ◽  
Irrigated Agriculture ◽  
Accurate Information ◽  
Remotely Sensed Data ◽  
Gis And Remote Sensing ◽  
Practical Applications

This document is meant to demonstrate the potential uses of remote sensing in managing water resources for irrigated agriculture and to create awareness among potential users. Researchers in various international programs have studied the potential use of remotely sensed data to obtain accurate information on land surface processes and conditions. These studies have demonstrated that quantitative assessment of the soil-vegetation-atmosphere transfer processes can lead to a better understanding of the relationships between crop growth and water management. Remote sensing and GIS was used to map the agriculture area and for detect the change. This was very useful for mapping availability and need of water resources but the problem was concentrating in data collection and analysis because this kind of information and expertise are not available in all country in the world mainly in the developing and under developed country or third world country. However, even though considerable progress has been made over the past 20 years in research applications, remotely sensed data remain underutilized by practicing water resource managers. This paper seeks to bridge the gap between researchers and practitioners first, by illustrating where research tools and techniques have practical applications and, second, by identifying real problems that remote sensing could solve. An important challenge in the field of water resources is to utilize the timely, objective and accurate information provided by remote sensing.

Using Remotely Sensed Data To Monitor Land Surface Climatology Variations In A Semi-arid Grassland

2005 ◽  
Author(s):  
L.F. Johnson ◽  
N.A. Bryant ◽  
A.J. BrazeI ◽  
C.F. Hutchinson ◽  
R.C. Balling
Keyword(s):  
Land Surface ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Semi Arid

scholarly journals Uncertainty and Variation of Remotely Sensed Lake Ice Phenology across the Tibetan Plateau

2018 ◽  
Vol 10 (10) ◽  
pp. 1534 ◽  
Author(s):  
Linan Guo ◽  
Yanhong Wu ◽  
Hongxing Zheng ◽  
Bing Zhang ◽  
Junsheng Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Regional Climate ◽  
Local Environment ◽  
Remotely Sensed ◽  
The Tibetan Plateau ◽  
Remotely Sensed Data ◽  
Lake Ice ◽  
Reflectance Data ◽  
Ice Phenology

In the Tibetan Plateau (TP), the changes of lake ice phenology not only reflect regional climate change, but also impose substantial ecohydrological impacts on the local environment. Due to the limitation of ground observation, remote sensing has been used as an alternative tool to investigate recent changes of lake ice phenology. However, uncertainties exist in the remotely sensed lake ice phenology owing to both the data and methods used. In this paper, three different remotely sensed datasets are used to investigate the lake ice phenology variation in the past decade across the Tibetan Plateau, with the consideration of the underlying uncertainties. The remotely sensed data used include reflectance data, snow product, and land surface temperature (LST) data of moderate resolution imaging spectroradiometer (MODIS). The uncertainties of the three methods based on the corresponding data are assessed using the triple collocation approach. Comparatively, it is found that the method based on reflectance data outperforms the other two methods. The three methods are more consistent in determining the thawing dates rather than the freezing dates of lake ice. It is consistently shown by the three methods that the ice-covering duration in the northern part of the TP lasts longer than that in the south. Though there is no general trend of lake ice phenology across the TP for the period of 2000–2015, the warmer climate and stronger wind have led to the earlier break-up of lake ice.

Landscape fragmentation

2010 ◽  
Author(s):  
Ned Horning ◽  
Julie A. Robinson ◽  
Eleanor J. Sterling ◽  
Woody Turner ◽  
Sacha Spector
Keyword(s):  
Forest Fragmentation ◽  
Landscape Metrics ◽  
Forest Cover ◽  
Remotely Sensed ◽  
Clear Understanding ◽  
Remotely Sensed Data ◽  
Deforestation Rates ◽  
Habitat Conversion ◽  
Conservation Organizations ◽  
Total Core Area

The country of Vietnam has long been recognized as an important region for biodiversity (Sterling et al. 2006). High-profile discoveries in the 1990s of many species new to science including large ones such as the Saola (Pseudoryx nghetinhensis), an 85 kg basal member of the cattle subfamily Bovinae and the first new genus of large land-dwelling mammal described since the okapi (Okapia johnstoni) in 1901, have focused the attention of national and international conservation organizations on Vietnam and surrounding countries in mainland Southeast Asia (Hurley et al. in prep.). Conservation action for these endemic, endangered species relies on a clear understanding of trends in habitat conversion. To track deforestation rates through time in Vietnam, Meyfroidt and Lambin (2008) combined remotely sensed data with landscape metrics such as number of patches, mean patch size, mean proximity index, and total core area index. They tested their analyses across a variety of land cover studies including those using Advanced Very High Resolution Radiometer (AVHRR), Landsat, SPOT, and MODIS data sources. They found that forest cover decreased nationally from the 1980s to the 1990s and then showed an increase between 1990 and 2000, due to plantation forests as well as natural forest regeneration. However, the effects of this forest transition on fragmentation metrics noted above differed across the country. For instance, in some places, such as central Vietnam where forest cover is relatively large and well connected, reforestation led to a decrease in forest fragmentation and secondary forests recovered rapidly. However in others, such as areas in the north where forest fragmentation dates back centuries and forests have therefore long been isolated, reforestation did not seem to have an impact on continued fragmentation and habitat loss. In this chapter we detail the importance of fragmentation and landscape metrics to ecology and conservation, outlining when and where remotely sensed data can help in these analyses. We then discuss a subset of fragmentation metrics and point to some challenges in processing fragmentation data. We provide examples of composition and connectivity metrics illuminated with examples from the remote sensing literature.

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