Forest cover type and landuse mapping using landsat Thematic Mapper False colour Composite a case study for chakrata in western himalayas U.P.

1989 ◽  
Vol 17 (1) ◽  
pp. 33-40 ◽  
Author(s):  
M. C. Porwal ◽  
D. N. Pant
Keyword(s):  
Forest Cover ◽  
False Colour Composite ◽  
Thematic Mapper ◽  
Western Himalayas ◽  
Landsat Thematic Mapper ◽  
Forest Cover Type ◽  
Cover Type ◽  
Colour Composite ◽  
False Colour

Stratification approach for forest cover type and landuse mapping using IRS-1A LISS-II data — A case study

1994 ◽  
Vol 22 (1) ◽  
pp. 21-29 ◽  
Author(s):  
S. Sudhakar ◽  
R. K. Das ◽  
D. Chakraborty ◽  
B. K. Bardhan Roy ◽  
A. K. Raha ◽  
...  
Keyword(s):  
Forest Cover ◽  
Forest Cover Type ◽  
Cover Type

The forest resource of Labrador: Landsat Thematic Mapper imagery provides a unique and current perspective

1993 ◽  
Vol 69 (6) ◽  
pp. 667-671 ◽  
Author(s):  
John A. Drieman
Keyword(s):  
Forest Cover ◽  
Thematic Mapper ◽  
Landsat Thematic Mapper ◽  
Forest Resource ◽  
Visual Interpretation ◽  
Digital Format ◽  
Current Perspective ◽  
Colour Composite ◽  
Verification Process ◽  
Forest Cover Types

The need for a current, regional perspective of the forest of Labrador was identified. Mapping of forest cover types, peat-lands, recent burns and clearcut disturbances was accomplished through visual interpretation of 1:1,000,000 scale Landsat Thematic mapper colour composite transparencies and the transfer of interpreted polygons to a geographic information system. The mapping and verification process is described in this paper. The end product, a forest resource map, provides the most up-to-date and detailed information on Labrador's forest cover types and disturbances available on a single map. The digital format of the map facilities area summaries, viewing and printing.

scholarly journals ABOVE GROUND TREES BIOMASS OF LORE LINDU NATIONAL PARK-CENTRAL SULAWESI : A STUDY COMBINING FIELD MEASUREMENT AND REMOTE SENSING

Agromet ◽  
2010 ◽  
Vol 24 (1) ◽  
pp. 33
Author(s):  
Naimatu Solicha ◽  
Tania June ◽  
M. Ardiansyah ◽  
Antonius B. W.
Keyword(s):  
Remote Sensing ◽  
Carbon Stock ◽  
Field Data ◽  
Forest Cover ◽  
Satellite Image ◽  
Forest Biomass ◽  
Allometric Equation ◽  
Natural Forest ◽  
Forest Cover Type ◽  
Cover Type

Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.

scholarly journals Application of nonlinear colour enhancement on transparencies for interpretation of glacier surface characteristics

1992 ◽  
Vol 16 ◽  
pp. 190-192
Author(s):  
Cao Meisheng ◽  
Mi Desheng ◽  
Pu Yinbin ◽  
Liu Jinghaung
Keyword(s):  
Surface Characteristics ◽  
False Colour Composite ◽  
High Contrast ◽  
Glacier Surface ◽  
Ice Surface ◽  
Grey Scale ◽  
Scale Range ◽  
Colour Composite ◽  
Channel Image ◽  
False Colour

According to the analysis of grey scale range on MSS-4, -5, -6 and -7 channel image films for five snow-ice categories on glacier surface, the grey scale among snow, bare ice, ice pinnacle, moraine-covered ice surface and gully bed has been spread nonlinearly by using duplicative processing on high-contrast film. As a result of the rescaling of grey levels, the colour differences of morphological features of Rongbu Glacier in the Qpmolangma region have been increased on false colour composite photography. It is also shown that using MSS-6 to composite false colour images compared to MSS-5 will supply more information for the interpretation of the glacier area.

scholarly journals Estimates of Down Woody Materials on Fort A.P. Hill, Virginia

2008 ◽  
Vol 32 (2) ◽  
pp. 53-59 ◽  
Author(s):  
Jason R. Applegate
Keyword(s):  
Coarse Woody Debris ◽  
Forest Inventory ◽  
Forest Cover ◽  
Forest Type ◽  
Wildland Fire ◽  
Woody Debris ◽  
Forest Cover Type ◽  
Cover Type ◽  
Forest Cover Types ◽  
Structure Class

Abstract An inventory of down woody materials (DWM) was conducted on Fort A.P. Hill, Virginia, to develop a baseline of DWM abundance and distribution to assist in wildland fire management. Estimates of DWM are necessary to develop accurate assessments of wildfire hazard, model wildland fire behavior, and establish thresholds for retaining DWM, specifically CWD (coarse woody debris), as a structural component of forest ecosystems. DWM were sampled by forest type and structure class using US Forest Service, Forest Inventory and Analysis (FIA) field procedures. DWM averaged 12–16 tn/ac depending on forest cover type and structure class. Coarse woody debris (CWD) averaged 2.7–13.0 tn/ac depending on forest cover type and structure class. CWD comprised more than 70% of DWM across all forest cover types and structure classes. Fine woody debris (FWD) averaged 0.05–3.2 tn/ac depending on fuel hour class, forest cover type, and structure class. DWM was consistently higher in mature (sawtimber) forests than in young (poletimber) forests across all forest cover types, attributed to an increased CWD component of DWM. The variability associated with DWM suggests that obtaining robust estimates of CWD biomass will require a higher sampling intensity than FWD because of its nonuniform distribution in forest systems. FIA field procedures for tallying and quantifying DWM were practical, efficient, and, subsequently, included as permanent metrics in Fort A.P. Hill's Continuous Forest Inventory program.

scholarly journals Multitemporal Analysis Using Landsat Thematic Mapper (TM) Bands for Forest Cover Classification in East Texas

2008 ◽  
Vol 32 (1) ◽  
pp. 21-27
Author(s):  
Jason C. Raines ◽  
Jason Grogan ◽  
I-Kuai Hung ◽  
James Kroll
Keyword(s):  
Land Cover ◽  
Classification Accuracy ◽  
Forest Cover ◽  
Thematic Mapper ◽  
Landsat Thematic Mapper ◽  
Forest Types ◽  
Significant Difference ◽  
Potential Benefits ◽  
Land Cover Maps ◽  
Band Combinations

Abstract Land cover maps have been produced using satellite imagery to monitor forest resources since the launch of Landsat 1. Research has shown that stacking leaf-on and leaf-off imagery (combining two separate images into one image for processing) may improve classification accuracy. It is assumed that the combination of data will aid in differentiation between forest types. In this study we explored potential benefits of using multidate imagery versus single-date imagery for operational forest cover classification as part of an annual remote sensing forest inventory system. Landsat Thematic Mapper (TM) imagery was used to classify land cover into four classes. Six band combinations were tested to determine differences in classification accuracy and if any were significant enough to justify the extra cost and increased difficulty of image acquisition. The effects of inclusion/exclusion of the moisture band (TM band 5) also were examined. Results show overall accuracy ranged from 72 to 79% with no significant difference between single and multidate classifications. We feel the minimal increase (3.06%) in overall accuracy, coupled with the operational difficulties of obtaining multiple (two), useable images per year, does not support the use of multidate stacked imagery. Additional research should focus on fully utilizing data from a single scene by improving classification methodologies.

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