Estimation of Tropical Forest Extent and Regenerative Stage Using Remotely Sensed Data

1994 ◽  
Vol 21 (3) ◽  
pp. 223 ◽  
Author(s):  
Giles M. Foody ◽  
Paul J. Curran
Keyword(s):  
Tropical Forest ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Regenerative Stage

scholarly journals Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data

2008 ◽  
Vol 105 (27) ◽  
pp. 9439-9444 ◽  
Author(s):  
M. C. Hansen ◽  
S. V. Stehman ◽  
P. V. Potapov ◽  
T. R. Loveland ◽  
J. R. G. Townshend ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Forest Clearing ◽  
Humid Tropical Forest

Ecosystem process models at multiple scales for mapping tropical forest productivity

2004 ◽  
Vol 28 (2) ◽  
pp. 241-281 ◽  
Author(s):  
J. M. Nightingale ◽  
S. R. Phinn ◽  
A. A. Held
Keyword(s):  
Tropical Forest ◽  
Tropical Forests ◽  
Remotely Sensed ◽  
Process Models ◽  
Carbon Accounting ◽  
Spatial Extent ◽  
Ecosystem Process ◽  
Remotely Sensed Data ◽  
Time Step ◽  
Forest Models

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Understanding the dynamic of a tropical forest located in Southern Mexico using remotely sensed data

2016 ◽  
Author(s):  
Alejandro Monsivais-Huertero ◽  
Jose Carlos Jimenez-Escalona ◽  
Jose Mauricio Galeana-Pizana ◽  
Aura Citlalli Torres-Gomez ◽  
Ramata Magagi ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Southern Mexico

THE ROLE OF REMOTE SENSING DATA FOR COASTAL ZONE MONITIORING AND MANAGEMENT (CASE STUDY FOR THE EAST PART OF GULF OF FINLAND)

2017 ◽  
Author(s):  
Nikifor Ostanin ◽  
Nikifor Ostanin
Keyword(s):  
Remote Sensing ◽  
Coastal Zone ◽  
Environmental Changes ◽  
Rapid Development ◽  
Water Environment ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Gulf Of Finland ◽  
Coastal Protection ◽  
Remotely Sensed Data

Coastal zone of the Eastern Gulf of Finland is subjected to essential natural and anthropogenic impact. The processes of abrasion and accumulation are predominant. While some coastal protection structures are old and ruined the problem of monitoring and coastal management is actual. Remotely sensed data is important component of geospatial information for coastal environment research. Rapid development of modern satellite remote sensing techniques and data processing algorithms made this data essential for monitoring and management. Multispectral imagers of modern high resolution satellites make it possible to produce advanced image processing, such as relative water depths estimation, sea-bottom classification and detection of changes in shallow water environment. In the framework of the project of development of new coast protection plan for the Kurortny District of St.-Petersburg a series of archival and modern satellite images were collected and analyzed. As a result several schemes of underwater parts of coastal zone and schemes of relative bathymetry for the key areas were produced. The comparative analysis of multi-temporal images allow us to reveal trends of environmental changes in the study areas. This information, compared with field observations, shows that remotely sensed data is useful and efficient for geospatial planning and development of new coast protection scheme.

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