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首页> 外文会议>Asian conference on remote sensing;ACRS 2008 >LAND USE DISCRIMINATION IN THE TROPICAL HUMID CLIMATE REGION USING VARIATION OF LAND COVER CHARACTERISTICS DERIVED FROM REMOTE SENSING DATA
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LAND USE DISCRIMINATION IN THE TROPICAL HUMID CLIMATE REGION USING VARIATION OF LAND COVER CHARACTERISTICS DERIVED FROM REMOTE SENSING DATA

机译：利用来自遥感数据的土地覆被特征变化判别热带湿润气候地区的土地利用

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摘要

In the tropical humid climate region, high probability of cloud coverage is the major constraint to discriminate land use from satellite remote sensing data. Timing of cropping in this area tends to be flexibly changed and land surface condition for unique land use type could be complexly distributed even at the same time. In this study, a method was examined for the case study site located in the West Java, Indonesia to discriminate land use from multi-temporal Landsat data, which were obtained discretely in time. Three indices, which reflected the surface condition of soil, vegetation and water, respectively, were calculated and the maximum values of these indices were set as represented components at pixel. This procedure characterized the temporal variation of land surface condition, which could be associated with land use type. Classification results showed proper discrimination of urban or settlement area, which might be confused with bare land of agricultural area in case of classification using mono-temporal remote sensing data. Upland field and paddy field were also appropriately discriminated from other land use. In conclusion, this method would be promising to contribute to production of land use data with moderately high spatial resolution for areas in the tropical humid climate region, where land information is insufficiently provided.
机译：在热带湿润气候地区，云覆盖的高可能性是将土地利用与卫星遥感数据区分开的主要限制因素。该地区的种植时机往往会灵活变化，即使同时使用，独特土地利用类型的地表条件也可能会复杂地分布。在这项研究中，检查了位于印度尼西亚西爪哇的案例研究站点的一种方法，以区分土地和多时态Landsat数据中的土地用途，这些数据是在时间上离散获得的。计算了分别反映土壤，植被和水的表面状况的三个指标，并将这些指标的最大值设置为像素处的表示成分。该程序表征了土地表面状况的时间变化，这可能与土地利用类型有关。分类结果表明对城市或居民区进行了适当的区分，如果使用单时态遥感数据进行分类，则可能与农业区的裸地相混淆。旱田和水田也与其他土地用途适当区分开。总之，该方法将有望为热带湿润气候地区的土地信息不足的地区提供具有中等高空间分辨率的土地利用数据。

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