MAPPING AND MODELLING ABOVEGROUND WOODY BIOMASS AND CARBON STOCK IN SAL (SHOREA ROBUSTA GAERTN. F.) FORESTS OF DOON VALLEY USING GEOSPATIAL TECHNIQUES

Abstract. Information on the quantitative and qualitative distribution of forest biomass is helpful for effective forest management. Besides its quantitative use, Biomass plays a twin role by acting as a carbon source and sinks but its long-term carbon-storing ability is of considerable importance which is helpful in lessening global warming and climate change impacts. The present study was done for mapping aboveground woody biomass (Bole) (AGWB) of Shorea robusta (Gaertn.f.) forests in Doon valley by establishing relationships between field measured data, satellite data derived variables and geostatistical techniques. Landsat 8 Operational Land Imager (OLI) data was used in preparing the forest homogeneity map (forest type and density). 55 sampling plots of 0.1ha were laid across the Doon Valley using stratified random sampling. Correlations were established between Landsat 8 OLI derived variables and field measured data and were evaluated. Field measured biomass has got the maximum correlation with NDVI (0.7553) and it was further used for carrying out multivariate kriging (Cok) for biomass prediction map. Prediction errors for the AGWB were lowest for exponential model with RMSE=66.445Mg/ha, Average Standard Error=71.07694Mg/ha and RMSS=0.95097. Carbon is calculated as 47% of the biomass value.AGWB was ranged from 163.381 to 750.025 Mg/ha and Carbon from 76.789 to 352.512Mg/ha. Cokriging was found as a better alternative as compared to direct radiometric relationships for the spatial distribution of the AGWB of Shorea robusta (Gaertn.f.) forests and this study would be helpful in better forest management planning and research purposes.

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Sawtimber Yield Tables for Pennsylvania Forest Management Planning

Northern Journal of Applied Forestry ◽

10.1093/njaf/27.4.140 ◽

2010 ◽

Vol 27 (4) ◽

pp. 140-150

Author(s):

Horacio Gilabert ◽

Phillip J. Manning ◽

Marc E. McDill ◽

Steve Sterner

Keyword(s):

Forest Management ◽

Forest Type ◽

Site Class ◽

Management Planning ◽

Forest Management Planning ◽

Ecological Regions ◽

Continuous Forest ◽

Planning Project ◽

Species Groups ◽

The 1960S

Abstract Models to predict gross and net sawtimber volume per acre for even-aged stands were calibrated for Pennsylvania forests as part of a continuing forest management planning project for Pennsylvania's 2.1 million acres of state forestland. Because of the requirements of the models and limitations of the planning data, the main variable driving the yield models was age. Binary variables were used to shift the sawtimber volume predictions up or down to differentiate yields for 3 site classes, 2 stocking classes, 7 forest types, and 10 ecological regions within the state. The models were fitted using plot-level observations from a continuous forest inventory that has been carried out by the Pennsylvania Department of Conservation and Natural Resources Bureau of Forestry since the 1960s. To apportion the total volume into species groups, proportions were derived of the total sawtimber volume per acre for seven different species groups by forest type and site class for four macro-regions aggregated from the ecological regions within Pennsylvania.

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Forest type mapping using object-based classification method in Kapilvastu district, Nepal

Banko Janakari ◽

10.3126/banko.v26i1.15500 ◽

2016 ◽

Vol 26 (1) ◽

pp. 38-44

Author(s):

A. K. Chaudhary ◽

A. K. Acharya ◽

S. Khanal

Keyword(s):

Nearest Neighbor ◽

Forest Type ◽

Accuracy Assessment ◽

Regression Tree ◽

Classification And Regression Tree ◽

Systematic Sampling ◽

Landsat 8 ◽

Forest Types ◽

Shorea Robusta ◽

Object Based

In the recent years, object-based image analysis (OBIA) approach has emerged with an attempt to overcome limitations inherited in conventional pixel-based approaches. OBIA was performed using Landsat 8 image to map the forest types in Kapilvastu district of Nepal. Systematic sampling design was adopted to establish sample points in the field, and 70% samples were used for classification and 30% samples for accuracy assessment. Landsat image was pre-processed, and the slope and aspect derived from the ASTER DEM were used as additional predictors for classification. Segmentation was done using eCognition v8.0 with the scale parameter of 20, ratios of 0.1 and 0.9 for shape and color, respectively. Classification and Regression Tree (CART) and nearest neighbor classifier (k-NN) methods were used for object-based classification. The major forest types observed in the district were KS (Acacia catechu/ Dalbergia sissoo), Sal (Shorea robusta) and Tropical Mixed Hardwood. The k-NN classification technique showed higher overall accuracy than the CART method. The classification approach used in this study can also be applied to classify forest types in other districts. Improvement in classification accuracy can be potentially obtained through inclusion of sufficient samples from all classes.Banko JanakariA Journal of Forestry Information for NepalVol. 26, No. 1, Page: 38-44, 2016

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Classification and Observed Seasonal Phenology of Broadleaf Deciduous Forests in a Tropical Region by Using Multitemporal Sentinel-1A and Landsat 8 Data

Forests ◽

10.3390/f12020235 ◽

2021 ◽

Vol 12 (2) ◽

pp. 235

Author(s):

Anh Tuan Tran ◽

Kim Anh Nguyen ◽

Yuei An Liou ◽

Minh Hang Le ◽

Van Truong Vu ◽

...

Keyword(s):

Forest Management ◽

Large Scale ◽

Vegetation Index ◽

Deciduous Forest ◽

Forest Type ◽

Deciduous Forests ◽

Tropical Region ◽

Landsat 8 ◽

Tropical Regions ◽

Dipterocarp Forests

Broadleaf deciduous forests (BDFs) or dry dipterocarp forests play an important role in biodiversity conservation in tropical regions. Observations and classification of forest phenology provide valuable inputs for ecosystem models regarding its responses to climate change to assist forest management. Remotely sensed observations are often used to derive the parameters corresponding to seasonal vegetation dynamics. Data acquired from the Sentinel-1A satellite holds a great potential to improve forest type classification at a medium-large scale. This article presents an integrated object-based classification method by using Sentinel-1A and Landsat 8 OLI data acquired during different phenological periods (rainy and dry seasons). The deciduous forest and nondeciduous forest areas are classified by using NDVI (normalized difference vegetation index) from Landsat 8 cloud-free composite images taken during dry (from February to April) and rainy (from June to October) seasons. Shorea siamensis Miq. (S. siamensis), Shorea obtusa Wall. ex Blume (S. obtusa), and Dipterocarpus tuberculatus Roxb. (D. tuberculatus) in the deciduous forest area are classified based on the correlation between phenology of BDFs in Yok Don National Park and backscatter values of time-series Sentinel-1A imagery in deciduous forest areas. One hundred and five plots were selected during the field survey in the study area, consisting of dominant deciduous species, tree height, and canopy diameter. Thirty-nine plots were used for training to decide the broadleaf deciduous forest areas of the classified BDFs by the proposed method, and the other sixty-six plots were used for validation. Our proposed approach used the changes of backscatter in multitemporal SAR images to implement BDF classification mapping with acceptable accuracy. The overall accuracy of classification is about 79%, with a kappa coefficient of 0.7. Accurate classification and mapping of the BDFs using the proposed method can help authorities implement forest management in the future.

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Development of the Statistical Model for Monitoring Salinization in the Mekong Delta of Vietnam Using Remote Sensing Data and In-Situ Measurements

Proceedings ◽

10.3390/iecg_2018-05362 ◽

2018 ◽

Vol 2 (10) ◽

pp. 565

Author(s):

Nguyen Nguyen Vu ◽

Le Van Trung ◽

Tran Thi Van

Keyword(s):

Statistical Model ◽

Mekong Delta ◽

Remote Sensing Data ◽

Principal Component ◽

Measured Data ◽

In Situ Measurements ◽

Landsat 8 ◽

Spectral Bands ◽

Component Band

This article presents the methodology for developing a statistical model for monitoring salinity intrusion in the Mekong Delta based on the integration of satellite imagery and in-situ measurements. We used Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat- 8 OLI and TIRS) satellite data to establish the relationship between the planetary reflectance and the ground measured data in the dry season during 2014. The three spectral bands (blue, green, red) and the principal component band were used to obtain the most suitable models. The selected model showed a good correlation with the exponential function of the principal component band and the ground measured data (R2 > 0.8). Simulation of the salinity distribution along the river shows the intrusion of a 4 g/L salt boundary from the estuary to the inner field of more than 50 km. The developed model will be an active contribution, providing managers with adaptation and response solutions suitable for intrusion in the estuary as well as the inner field of the Mekong Delta.

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Do Review Papers on Bird–Vegetation Relationships Provide Actionable Information to Forest Managers in the Eastern United States?

Forests ◽

10.3390/f12080990 ◽

2021 ◽

Vol 12 (8) ◽

pp. 990

Author(s):

Casey A. Lott ◽

Michael E. Akresh ◽

Bridgett E. Costanzo ◽

Anthony W. D’Amato ◽

Shengwu Duan ◽

...

Keyword(s):

Forest Management ◽

Information Needs ◽

Online Survey ◽

Forest Type ◽

Grey Literature ◽

Natural Disturbance ◽

Eastern United States ◽

Ecological Processes ◽

Desired Future Conditions ◽

Forest Managers

Forest management planning requires the specification of measurable objectives as desired future conditions at spatial extents ranging from stands to landscapes and temporal extents ranging from a single growing season to several centuries. Effective implementation of forest management requires understanding current conditions and constraints well enough to apply the appropriate silvicultural strategies to produce desired future conditions, often for multiple objectives, at varying spatial and temporal extents. We administered an online survey to forest managers in the eastern US to better understand how wildlife scientists could best provide information to help meet wildlife-related habitat objectives. We then examined more than 1000 review papers on bird–vegetation relationships in the eastern US compiled during a systematic review of the primary literature to see how well this evidence-base meets the information needs of forest managers. We identified two main areas where wildlife scientists could increase the relevance and applicability of their research. First, forest managers want descriptions of wildlife species–vegetation relationships using the operational metrics of forest management (forest type, tree species composition, basal area, tree density, stocking rates, etc.) summarized at the operational spatial units of forest management (stands, compartments, and forests). Second, forest managers want information about how to provide wildlife habitats for many different species with varied habitat needs across temporal extents related to the ecological processes of succession after harvest or natural disturbance (1–2 decades) or even longer periods of stand development. We provide examples of review papers that meet these information needs of forest managers and topic-specific bibliographies of additional review papers that may contain actionable information for foresters who wish to meet wildlife management objectives. We suggest that wildlife scientists become more familiar with the extensive grey literature on forest bird–vegetation relationships and forest management that is available in natural resource management agency reports. We also suggest that wildlife scientists could reconsider everything from the questions they ask, the metrics they report on, and the way they allocate samples in time and space, to provide more relevant and actionable information to forest managers.

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Challenges in developing and implementing a decision support systems (ETÇAP) in forest management planning: a case study in Honaz and Ibradı, Turkey

Scandinavian Journal of Forest Research ◽

10.1080/02827581.2013.822543 ◽

2013 ◽

Vol 29 (sup1) ◽

pp. 121-131 ◽

Cited By ~ 6

Author(s):

Emin Zeki Başkent ◽

Sedat Keleş ◽

Ali İhsan Kadıoğulları

Keyword(s):

Decision Support ◽

Forest Management ◽

Decision Support Systems ◽

Support Systems ◽

Management Planning ◽

Forest Management Planning

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Forest management strategies for dealing with fire-related uncertainty when managing two forest seral stages

Canadian Journal of Forest Research ◽

10.1139/x10-212 ◽

2011 ◽

Vol 41 (2) ◽

pp. 309-320 ◽

Cited By ~ 12

Author(s):

David W. Savage ◽

David L. Martell ◽

B. Mike Wotton

Keyword(s):

Forest Management ◽

Simulation Model ◽

Sustainable Forest Management ◽

Management Strategies ◽

Fire Regimes ◽

Analysis Tool ◽

Planning Model ◽

Minimum Area ◽

Forest Management Planning ◽

Planning Models

Ecological values are an important aspect of sustainable forest management, but little attention has been paid to maintaining these values when using traditional linear programming (LP) forest management planning models in uncertain planning environments. We embedded an LP planning model that specifies when and how much to harvest in a simulation model of a “managed” flammable forest landscape. The simulation model was used to evaluate two strategies for dealing with fire-related uncertainty when managing mature and old forest areas. The two seral stage areas were constrained in the LP planning model to a minimum of 10% of the total forest area and the strategies were evaluated under four representative fire regimes. We also developed a risk analysis tool that can be used by forest managers that wish to incorporate fire-related uncertainty in their decision-making. We found that use of the LP model would reduce the areas of the mature and old forest to their lower bound and fire would further reduce the seral areas below those levels, particularly when the mean annual burn fraction exceeds 0.45% per annum. Increasing the minimum area required (i.e., the right-hand side of the constraint) would increase the likelihood of satisfying the minimum area requirements.

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