Yapay Zeka Hızlı Bakış & Çıkarımlar
AI InsightFurther studies are advisable to determine whether the object-based or the pixel-based classification is more suitable toevaluate LULC changes in our study area.
📌 3 Maddede Bu Makale
Abstract
Understanding the current and past state of land use and land cover (LULC) changes in a region is possible through multitemporalremote sensing studies in order to identify patterns of long-term changes. This study was conducted to evaluate the shorelinedynamics of the Valencia lake and the magnitude of LULC changes in Zamora Municipality, Venezuela from 1986 to 2016. Landsat(5/7/8) images were processed and classified through the object-based approach. The image classification assessment was performedthrough the stratified random sampling and the unbiased accuracy assessment methods over 397 sampling units. We used GIS(Geographical Information System) analysis to estimate the magnitude of LULC changes, ascertain the evolution of the shoreline,and identify areas in conflict with the potential for agricultural use. Our image classification accuracy was 69%. We found thatscrublands and farmlands experienced reductions, 13029 ha, and 818 ha respectively, whereas forest, built-up, and water bodiesshowed increments, 11792 ha, 1482 ha, and 634 ha correspondingly. The lake shoreline underwent more than 50% of its raisingduring the last two study years (2003-2016). It was also observed during these two years that LULC changes prompted conflicts withother land uses, 82% of the lands affected by the shoreline increment were farmlands with high potential for crop yields, and built-upareas grew at a rate of 81 ha /yr. wherein more than one third were lands with high or moderate potential for agricultural use. Ourresults show that scrublands and/or grasslands experienced important reductions and to a lesser degree farmlands. On the other hand,other classes experienced remarkable increments: forest, and built-up. An upward trend of the Valencia lake shoreline wasdetermined. Further studies are advisable to determine whether the object-based or the pixel-based classification is more suitable toevaluate LULC changes in our study area.