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From Global to Local: Testing the Potential of Cross-Scaling in Global Data Sets

机译:从全局到本地:在全局数据集中测试交叉扩展的潜力

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The present study investigates the potential of readily available and easily accessible global data sets to understand regional/local level interactions in wetland systems. The bio-geographical zones of India were used a base-frame to select three sites. The study well fits the interests of National Wetland Committee of India to investigate and document fundamental information on wetland extent/distribution. The national partnership with SACON represents this interest. SACON commenced the inland wetland inventory module at national scale using geospatial data, although the provincial scale analysis is underway. In addition, the global irrigated area mapping (GIAM-IWMI) project generated multi-scalar spatial outputs for irrigated/rain-fed areas. With the existing information base, a multi-level geospatial analysis using Arc GIS algorithmic modelling was used to derive comprehensive appraisal of wetland systems complementing the data from GIAM and SACON. It was observed that the overlap between the two layers was 58 percent for Gujarat and 10 percent in Tamil Nadu. In Krishna basin the wetland's cover 1.04 million hectare excluding the rice agro-ecosystem. The difference in the biogeography of the case sites governs the gradient of information derived from both data layers. Additionally, the global lakes and wetlands database (GLWD) database added thematic information on coastal wetlands. In summary we describe the cross-scaling the global data layers to compliment the regionalational level monitoring assignments.
机译:本研究调查了容易获得和易于获得的全球数据集的潜力,以了解湿地系统中区域/地方层面的相互作用。印度的生物地理区域被用作基础框架来选择三个地点。该研究非常符合印度国家湿地委员会的兴趣,以调查和记录有关湿地范围/分布的基本信息。与SACON的国家合作关系代表了这一利益。 SACON使用地理空间数据在全国范围内启动了内陆湿地清单模块,尽管正在进行省级规模分析。此外,全球灌溉面积制图(GIAM-IWMI)项目为灌溉/雨养地区产生了多尺度空间输出。在现有信息基础上,使用Arc GIS算法建模进行了多级地理空间分析,以补充GIAM和SACON的数据,对湿地系统进行综合评估。据观察,古吉拉特邦两层的重叠率为58%,泰米尔纳德邦为10%。在克里希纳盆地,不包括水稻农业生态系统,湿地总面积为104万公顷。案例地点的生物地理差异决定了从两个数据层得出的信息的梯度。此外,全球湖泊和湿地数据库(GLWD)数据库添加了有关沿海湿地的专题信息。总而言之,我们描述了交叉扩展全局数据层以补充区域/国家级别的监视任务。

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