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1.
PLoS One ; 11(12): e0166592, 2016.
Artículo en Inglés | MEDLINE | ID: mdl-27977685

RESUMEN

Remote sensing has been widely used for mapping land cover and is considered key to monitoring changes in forest areas in the REDD+ Measurement, Reporting and Verification (MRV) system. But Remote Sensing as a desk study cannot capture the whole picture; it also requires ground checking. Therefore, complementing remote sensing analysis using participatory mapping can help provide information for an initial forest cover assessment, gain better understanding of how local land use might affect changes, and provide a way to engage local communities in REDD+. Our study looked at the potential of participatory mapping in providing complementary information for remotely sensed maps. The research sites were located in different ecological and socio-economic contexts in the provinces of Papua, West Kalimantan and Central Java, Indonesia. Twenty-one maps of land cover and land use were drawn with local community participation during focus group discussions in seven villages. These maps, covering a total of 270,000ha, were used to add information to maps developed using remote sensing, adding 39 land covers to the eight from our initial desk assessment. They also provided additional information on drivers of land use and land cover change, resource areas, territory claims and land status, which we were able to correlate to understand changes in forest cover. Incorporating participatory mapping in the REDD+ MRV protocol would help with initial remotely sensed land classifications, stratify an area for ground checks and measurement plots, and add other valuable social data not visible at the RS scale. Ultimately, it would provide a forum for local communities to discuss REDD+ activities and develop a better understanding of REDD+.


Asunto(s)
Conservación de los Recursos Naturales/métodos , Ecosistema , Monitoreo del Ambiente/métodos , Bosques , Sistemas de Información Geográfica , Indonesia
2.
Glob Chang Biol ; 22(4): 1406-20, 2016 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-26499288

RESUMEN

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.


Asunto(s)
Biomasa , Mapas como Asunto , Conjuntos de Datos como Asunto , Modelos Teóricos , Árboles , Clima Tropical
3.
PLoS One ; 8(8): e69887, 2013.
Artículo en Inglés | MEDLINE | ID: mdl-23967062

RESUMEN

Combining protected areas with natural forest timber concessions may sustain larger forest landscapes than is possible via protected areas alone. However, the role of timber concessions in maintaining natural forest remains poorly characterized. An estimated 57% (303,525 km²) of Kalimantan's land area (532,100 km²) was covered by natural forest in 2000. About 14,212 km² (4.7%) had been cleared by 2010. Forests in oil palm concessions had been reduced by 5,600 km² (14.1%), while the figures for timber concessions are 1,336 km² (1.5%), and for protected forests are 1,122 km² (1.2%). These deforestation rates explain little about the relative performance of the different land use categories under equivalent conversion risks due to the confounding effects of location. An estimated 25% of lands allocated for timber harvesting in 2000 had their status changed to industrial plantation concessions in 2010. Based on a sample of 3,391 forest plots (1×1 km; 100 ha), and matching statistical analyses, 2000-2010 deforestation was on average 17.6 ha lower (95% C.I.: -22.3 ha- -12.9 ha) in timber concession plots than in oil palm concession plots. When location effects were accounted for, deforestation rates in timber concessions and protected areas were not significantly different (Mean difference: 0.35 ha; 95% C.I.: -0.002 ha-0.7 ha). Natural forest timber concessions in Kalimantan had similar ability as protected areas to maintain forest cover during 2000-2010, provided the former were not reclassified to industrial plantation concessions. Our study indicates the desirability of the Government of Indonesia designating its natural forest timber concessions as protected areas under the IUCN Protected Area Category VI to protect them from reclassification.


Asunto(s)
Conservación de los Recursos Naturales/estadística & datos numéricos , Árboles , Borneo , Toma de Decisiones , Indonesia
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