LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa

Accurate mapping and monitoring of tropical forests aboveground biomass (AGB) is crucial to design effective carbon emission reduction strategies and improving our understanding of Earth’s carbon cycle. However, existing large-scale maps of tropical forest AGB generated through combinations of Earth Observation (EO) and forest inventory data show markedly divergent estimates, even after accounting for reported uncertainties. To address this, a network of high-quality reference data is needed to calibrate and validate mapping algorithms. This study aims to generate reference AGB datasets using field inventory plots and airborne LiDAR data for eight sites in Central Africa and five sites in South Asia, two regions largely underrepresented in global reference AGB datasets. The study provides access to these reference AGB maps, including uncertainty maps, at 100 m and 40 m spatial resolutions covering a total LiDAR footprint of 1,11,650 ha [ranging from 150 to 40,000 ha at site level]. These maps serve as calibration/validation datasets to improve the accuracy and reliability of AGB mapping for current and upcoming EO missions (viz., GEDI, BIOMASS, and NISAR)

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Not AvailableA geospatial analysis of agricultural carbon pools (crop biomass and soil organic matter) of Madhya Pradesh, India for the year 2005-06 is reported. Remote sensing data, district boundaries, and the agro-ecological sub-regions (AESR) were integrated in GIS with land cover and an FAO-UNESCO soil map. District-wise crop production statistics of agricultural crops of M.P. for the year 2005-06 were used to estimate crop biomass by using conversion factors. Point-based data of soil organic carbon (0-30 cm) was regionalized for all five AESR, and total soil carbon density and stock were estimated. Total crop and soil C stocks of the study area were 34.94 and 790.61 Tg, respectively. Malwa plateau and Narmada valley with hot dry sub-humid condition (AESR III) recorded the maximum crop biomass carbon (14.12 Tg) while Satpura range and Wainganga Valley with hot moist sub-humid condition (AESR V) reflected the minimum crop biomass carbon (2.71 Tg). Maximum (3.95 Mg C ha-1) and minimum (0.50 Mg C ha-1) crop biomass C densities were recorded in Indore and Shahdol districts, respectively. AESR-wise soil organic carbon stocks varied from 74.7 Tg (AESR V) to 263.23 Tg (AESR III). The estimates were found to be positively correlated (R2=0.65) with the remotesensing derived max. NDVI. Positive correlation was also seen with the cropping intensity, net irrigated area, and per capita N consumption.Not Availabl

Land use change and net C flux in Indian forests

This paper reports on the net carbon flux caused by deforestation and afforestation in India over the period from 1982 to 2002, separately for two time periods, 1982¿1992 (PI) and 1992¿2002 (PII), using the IPCC 2006 guidelines for greenhouse gas inventories. The approach accounts for forest and soil C pool changes for (a) forest areas remaining as forests, (b) afforested areas and (c) deforested areas. The data set used were remote sensing based forest cover for three time periods (1982, 1992, 2002), biomass increments, biomass expansion factors and wood density. In addition a number of required coefficients and parameters from published literature were adopted. In the 1982¿2002 period, the forest cover changed from 64.20 Mha in 1982 to 63.96 and 67.83 Mha in 1992 and 2002 respectively. During the PI and PII periods, plantations were also established of 0.2 and 0.5 Mha yr¿1, while the annual deforestation rate was about 0.22 and 0.07 Mha in these periods, respectively. The average net flux of carbon attributable to land use change decreased from a source level of 5.65 Tg C yr¿1 (or 0.09 Mg C ha¿1 yr¿1) during PI (1982¿1992) to a sink level of 1.09 Tg C yr¿1 (or 0.02 Mg C ha¿1 yr¿1) during PII (1992¿2002). Over recent years, Indian forests have acted as a small carbon sink. The results indicate that the conversion of land to forest (regeneration/afforestation) led to a net uptake of 0.86 and 1.85 Tg C yr¿1 in PI and PII, respectively. By contrast, the net C emissions from the forest land conversion to another land use (deforestation) resulted in annual emissions of 9.9 and 3.2 Tg C during PI and PII, respectively. The cumulative net carbon flux from Indian forests due to land use change between 1982 and 2002 was estimated as 45.9 Tg C. The largest fluxes result from the conversion of forest land to cropland and waste lands, and since there are uncertainties in input variables (due to very large spatial heterogeneity) that affect net C flux from land use change, there is an urgent need for more reliable district-based data to facilitate accurate and refined estimates in future. This study was intended to improve consistency and completeness in the estimation and reporting of greenhouse gas emissions and removal

Evaluation of digital elevation models for delineation of hydrological response units in a Himalayan watershed

This study reports results from evaluation of the quality of digital elevation model (DEM) from four sources viz. topographic map (1: 50,000), Shuttle Radar Topographic Mission (SRTM) (90 m), optical stereo pair from ASTER (15 m) and CARTOSAT (2.5 m) and their use in derivation of hydrological response units (HRUs) in Sitla Rao watershed (North India). The HRUs were derived using water storage capacity and slope to produce surface runoff zones. The DEMs were evaluated on elevation accuracy and representation of morphometric features. The DEM derived from optical stereo pairs (ASTER and CARTOSAT) provided higher vertical accuracies than the SRTM and topographic map-based DEM. The SRTM with a coarse resolution of 90 m provided vertical accuracy but better morphometry compared to topographic map. The HRU maps derived from the fine resolution DEM (ASTER and CARTOSAT) were more detailed but did not provide much advantage for hydrological studies at the scale of Sitla Rao watershed (5800 ha)

Potential of ASAR-ENVISAT for estimating near surface soil moisture in a sloping terrain of a Himalayan watershed

Soil moisture estimation is considered to be one of the important parameters in hydrological studies. The extraction of information on near surface soil moisture from the synthetic aperture radar is well established. The available Advanced Synthetic Aperture Radar (ASAR) data onboard ENVISAT with multi-incidence and multi-polarization mode for soil moisture estimation on sloping terrain was investigated. Empirical models were developed to estimate near surface soil moisture in the fallow agricultural fields by incorporating the effects of surface roughness using multi-incidence angle ASAR data. Medium incidence angle (IS-4) with VV polarization of ASAR data had higher correlation coefficient to volumetric soil moisture content. The ratio of medium (IS-4) to high incidence (IS-6) angle could further reduce the effect of surface roughness. The effect of topography on the radar data is taken care by calculating local incidence angle derived from ASTER DEM data. The VV polarization in the sloping terrain provided better results in comparison to VH polarization