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首页> 外文会议>Agriculture and Hydrology Applications of Remote Sensing; Proceedings of SPIE-The International Society for Optical Engineering; vol.6411 >Performance of different vegetation indices in assessing degradation of community grazinglands in Indian Arid Zone
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Performance of different vegetation indices in assessing degradation of community grazinglands in Indian Arid Zone

机译：不同植被指数在印度干旱区草地放牧退化评估中的表现

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Vegetation in arid community grazinglands shows monsoonal growth. Its matching phenology with crops makes its detection difficult during July to September. While crops are harvested during September-October, using satellite data thereafter for the natural vegetation seems most appropriate but by then it turns dry. An index capable of sensing dry vegetation was needed since conventional NDVI is sensitive to greenness of vegetation. Performance of NDVI vis-a-vis another index, PD54, based on cover was therefore compared in assessing degradation of grazinglands. The PD54 was used to isolate anthropogenic impacts from environmental induced degradation by analyzing satellite images from dry and wet seasons. Substantial absence of appreciable vegetation response indicated poor resilience and severe degradation.rnFive grazinglands in Shergarh tehsil of Jodhpur district in Rajasthan were studied following above approach. Ground radiometric observations were recorded. Satellite data of IRS 1C/1D/P6 with LISS 3 sensor for both pre and post monsoon season were acquired for three contrasting wet-dry season events.rnThese were geometrically registered and radiometrically calibrated to calculate an index of vegetation cover PD54 as well as NDVI. PD54 is a perpendicular vegetation index based on the green and red spectral band width. The PD54 and NDVI calculated from spectro-radiometer were related to vegetation cover measured on ground in permanent plots. This confirmed that PD54 was superior index for estimating cover in arid dry grasslands.rnThese ground vegetation trends in a good rainfall year (2001) with drought year (2002) were related with satellite data for a protected and four unprotected grazinglands. NDVI failed to detect any vegetation in protected areas supporting excellent grass cover which was succinctly brought out by PD54. Successful validation of PD54 in detecting degradation of 13 additional sites confirmed its efficacy. These findings have implication in forage availability assessments, forage forecasting, drought preparedness, pastoralism and transhumance.
机译：干旱社区牧场的植被显示季风性增长。其与作物相匹配的物候特征使其在7月至9月难以检测。虽然在9月至10月期间收割农作物，但此后使用卫星数据获取自然植被似乎是最合适的方法，但随后转为干燥状态。由于常规的NDVI对植被的绿色敏感，因此需要一种能够感应干燥植被的指标。因此，在评估放牧地退化时，比较了基于覆盖的NDVI与另一指标PD54的性能。通过分析干旱和潮湿季节的卫星图像，PD54可用于隔离人为因素与环境导致的退化。上面的方法研究了拉贾斯坦邦乔德普尔地区的Shergarh tehsil的五个草场。记录了地面辐射观测。在三个对比鲜明的干湿季事件中，获取了季风前后前后具有LISS 3传感器的IRS 1C / 1D / P6的卫星数据，对它们进行了几何配准和放射线校准，以计算出植被覆盖指数PD54和NDVI 。 PD54是基于绿色和红色光谱带宽的垂直植被指数。由分光辐射计计算出的PD54和NDVI与永久性地块在地面上测得的植被覆盖率有关。这证实了PD54是评估干旱干旱草原覆盖率的优良指标。rn在良好的降雨年（2001年）和干旱年（2002年）中，这些地面植被的趋势与保护区和四个非保护区的卫星数据有关。 NDVI无法在保护区域内的任何植被上找到任何植被，这些植被支持PD54简洁地带来的出色草皮。 PD54在检测另外13个位点降解中的成功验证证实了其功效。这些发现对牧草可利用量评估，牧草预报，干旱准备，牧民和超人类现象都有影响。

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