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首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >Aboveground biomass and leaf area index (LAI) mapping for Niassa Reserve, northern Mozambique
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Aboveground biomass and leaf area index (LAI) mapping for Niassa Reserve, northern Mozambique

机译：莫桑比克北部尼亚萨保护区的地上生物量和叶面积指数（LAI）图

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摘要

Estimations of biomass are critical in miombo woodlands because they represent the primary source of goods and services for over 80% of the population in southern Africa. This study was carried out in Niassa Reserve, northern Mozambique. The main objectives were first to estimate woody biomass and Leaf Area Index (LAI) using remotely sensed data [RADARSAT (C-band, λ = 5.7-cm)] and Landsat ETM+ derived Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR) calibrated by field measurements and, second to determine, at both landscape and plot scales, the environmental controls (precipitation, woody cover density, fire and elephants) of biomass and LAI. A land-cover map (72% overall accuracy) was derived from the June 2004 ETM+ mosaic. Field biomass and LAI were correlated with RADARSAT backscatter (r biomass = 0.65, r LAI = 0.57, p < 0.0001) from July 2004, NDVI (r biomass = 0.30, r LAI = 0.35; p < 0.0001) and SR (r biomass = 0.36, r LAI = 0.40, p < 0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = ?5.19 + 0.074 * radarsat + 1.56 * SR, r 2 = 0.55) and LAI (LAI = ?0.66 + 0.01 * radarsat + 0.22 * SR, r 2 = 0.45). Biomass and LAI maps were produced with an estimated peak of 18 kg m?2 and 2.80 m2 m?2, respectively. On the landscape-scale, both biomass and LAI were strongly determined by mean annual precipitation (F = 13.91, p = 0.0002). On the plot spatial scale, woody biomass was significantly determined by fire frequency, and LAI by vegetation type.
机译：对生物多样性的估计在密欧博林地至关重要，因为它们代表了南部非洲80％以上人口的商品和服务的主要来源。这项研究是在莫桑比克北部的尼亚萨保护区进行的。主要目标是首先使用遥感数据[RADARSAT（C带，λ= 5.7-cm）]和Landsat ETM +得出的归一化植被指数（NDVI）和简单比率（SR）估算木质生物量和叶面积指数（LAI）。 ），并通过野外测量进行校准，其次是在景观和样地尺度上确定生物量和LAI的环境控制（降水，木质覆盖密度，火和大象）。从2004年6月的ETM +马赛克获得了一张土地覆盖图（总精度为72％）。从2004年7月开始，田间生物量和LAI与RADARSAT背向散射（r生物量= 0.65，r LAI = 0.57，p <0.0001），NDVI（r生物量= 0.30，r LAI = 0.35; p <0.0001）和SR（r生物量= 0.36，r LAI = 0.40，p <0.0001）。使用折刀逐步回归技术为生物量（生物量= 5.19 + 0.074 *雷达卫星+ 1.56 * SR，r 2 = 0.55）和LAI（LAI =≤0.66+ 0.01 *雷达卫星+ 0.22 * SR）建立最佳预测模型， r 2 = 0.45）。产生的生物量和LAI图谱的峰值分别为18 kg m？2和2.80 m2 m？2。在景观尺度上，生物量和LAI均由年平均降水量强烈决定（F = 13.91，p = 0.0002）。在样地空间尺度上，木质生物量由火频率显着决定，LAI由植被类型决定。

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