Theoretical Framework for Spatial Planning and Forest Management in Indonesia: Securing the Basic Rights for Adat People

Limited transparency, accountability, and participation in policy formulation as well as implementation mainly based on economic considerations, all lead to failure to attain sustainable forest management (SFM). Along with the reluctance of policy makers and lacking stakeholder capacity, less accurate data bases has also indicated a constraint in the development of appropriate action. The issues have been more complicated where they were correlated with economic imperatives, vested interest, ownership issues and the basic rights of indigenous communities living inside or adjacent the forest. Forest destruction will be no end without securing customary land and territorial rights. To cope with these issues, the concept of fair governance has been promoted as an alternative to the traditional pattern of administration. In this paper, we propose a theoretical framework for policy development in order to attain SFM while respecting the rights of the adat people. We show that adaptive governance, adaptive management, and participatory learning are strategic approaches in governance reform to achieve sustainable forest management securing the customary rights and traditional land use of forest dependent people

THEORETICAL FRAMEWORK FOR SPATIAL PLANNING AND FOREST MANAGEMENT IN INDONESIA: SECURING THE BASIC RIGHTS FOR ADAT PEOPLE

Limited transparency, accountability, and participation in policy formulation as well as implementation mainly based on economic considerations, all lead to failure to attain sustainable forest management (SFM). Along with the reluctance of policy makers and lacking stakeholder capacity, less accurate data bases has also indicated a constraint in the development of appropriate action. The issues have been more complicated where they were correlated with economic imperatives, vested interest, ownership issues and the basic rights of indigenous communities living inside or adjacent the forest. Forest destruction will be no end without securing customary land and territorial rights. To cope with these issues, the concept of fair governance has been promoted as an alternative to the traditional pattern of administration. In this paper, we propose a theoretical framework for policy development in order to attain SFM while respecting the rights of the adat people. We show that adaptive governance, adaptive management, and participatory learning are strategic approaches in governance reform to achieve sustainable forest management securing the customary rights and traditional land use of forest dependent people

THEORETICAL FRAMEWORK FOR SPATIAL PLANNING AND FOREST MANAGEMENT IN INDONESIA: SECURING THE BASIC RIGHTS FOR ADAT PEOPLE

Limited transparency, accountability, and participation in policy formulation as well as implementation mainly based on economic considerations, all lead to failure to attain sustainable forest management (SFM).  Along with the reluctance of policy makers and lacking stakeholder capacity, less accurate data bases has also indicated a constraint in the development of appropriate action. The issues have been more complicated where they were correlated with economic imperatives, vested interest, ownership issues and the basic rights of indigenous communities living inside or adjacent the forest.  Forest destruction will be no end without securing customary  land and territorial rights.  To cope with these issues, the concept of fair governance has been promoted as an alternative to the traditional pattern of administration. In this paper, we propose a theoretical framework for policy development in order to attain SFM while respecting the rights of the adat people.  We show that adaptive governance, adaptive management, and participatory learning are strategic approaches in  governance reform to achieve sustainable forest management securing the customary rights and traditional land use of forest dependent people

Integrating Airborne LiDAR and Terrestrial Laser Scanner forest parameters for accurate above-ground biomass/carbon estimation in Ayer Hitam tropical forest, Malaysia

Parameters of individual trees can be measured from LiDAR data provided that the laser points are dense enough to distinguish tree crowns. Retrieving tree parameters for above-ground biomass (AGB) valuation of the complex biophysical tropical forests using LiDAR technology is a major undertaking, and yet needs vital effort. Integration of Airborne LiDAR Scanner (ALS) and Terrestrial Laser Scanner (TLS) data for estimation of tree AGB at a single-tree level has been investigated in part of the tropical forest of Malaysia. According to the complete tree-crown detection potential of ALS and TLS, the forest canopy was cross-sectioned into upper and lower canopy layers. In a first step, multiresolution segmentation of the ALS canopy height model (CHM) was deployed to delineate upper canopy tree crowns. Results showed a 73% segmentation accuracy and permissible to detect 57% of field-measured trees. Two-way tree height validations were executed, viz. ALS-based upper and TLS-based lower canopy tree heights. The root mean square error (RMSE) for upper canopy trees height was 3.24 m (20.18%), and the bias was –1.20 m (–7.45%). For lower canopy trees height, RMSE of 1.45 m (14.77%) and bias of 0.42 m (4.29%) were obtained. In a second step, diameter at breast height (DBH) of individual tree stems detected from TLS data was measured. The RMSE obtained was 1.30 cm (6.52%), which was as nearly accurate as manually measured-DBH. In a third step, ALS-detected trees were co-registered and linked with the corresponding tree stems detected by TLS for DBH use. Lastly, an empirical regression model was developed for AGB estimated from a field-based method using an independent variable derived from ALS and TLS data. The result suggests that traditional field-methods underestimate AGB or carbon with the bias –0.289 (–3.53%) Mg, according for approximately 11%. Conversely, integrative use of ALS and TLS can enhance the capability of estimating more accurately AGB or carbon stock of the tropical forests

Forest inventory and aboveground biomass estimation with terrestrial LiDAR in the tropical forest of Malaysia

An accurate forest inventory is crucial for forest monitoring and quantifying forest aboveground biomass (AGB). This study aimed to investigate the feasibility of Terrestrial Laser Scanning (TLS) in forest inventory and AGB estimation in the tropical forest of Malaysia. Individual trees were detected using manual and automatic detection methods. An average tree detection rate of 99.55% and 93.75% were achieved using the manual and automatic detection method respectively. The accuracy of the diameter at breast height (DBH) of trees measured from TLS was validated using field DBH as reference. A root means square error (RMSE) of 1.37 cm (6.60%) and 2.36 cm (11.47%), respectively, were obtained for manually and automatically measured TLS DBH. Similarly, TLS based tree height was validated using Airborne Laser Scanner (ALS) height as a reference and resulted in RMSE of 1.74 m (9.30%) and 3.17 m (17.40%) with manual and automatic method respectively. Finally, AGB was calculated using the variables derived from the TLS data. Results show an R2 value of 0.98 and RMSE of 0.08 Mg. The results of this study confirmed that TLS as a nondestructive approach can provide a very good estimation of forest attributes and AGB in the dense tropical forest conditions

Quantification of carbon stock to understand two different forest management regimes in Kayar Khola watershed, Chitwan, Nepal

The impact of forest management activities on the ability of forest ecosystems to sequester and store atmospheric carbon is of increasing scientific and social concern. This is because a quantitative understanding of how forest management enhances carbon storage is lacking in most forest management regimes. In this paper two forest regimes, government and community-managed, in Kayar Khola watershed, Chitwan, Nepal were evaluated based on field data, very high resolution (VHR) GeoEye-1 satellite image and airborne LiDAR data. Individual tree crowns were generated using multi-resolution segmentation, which was followed by two tree species classification (Shorea robusta and Other species). Species allometric equations were used in both forest regimes for above ground biomass (AGB) estimation, mapping and comparison. The image objects generated were classified per species and resulted in 70 and 82 % accuracy for community and government forests, respectively. Development of the relationship between crown projection area (CPA), height, and AGB resulted in accuracies of R2 range from 0.62 to 0.81, and RMSE range from 10 to 25 % for Shorea robusta and other species respectively. The average carbon stock was found to be 244 and 140 tC/ha for community and government forests respectively. The synergistic use of optical and LiDAR data has been successful in this study in understanding the forest management system