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On the application of remote sensing towards the estimation of cultivated land lost to urbanization
The Imaging Science Journal ( IF 0.871 ) Pub Date : 2019-06-04 , DOI: 10.1080/13682199.2019.1624442
Aftab Khan 1 , SherAfgan Khattak 1 , Muhammad Waleed 1 , Ashfaq Khan 2 , Umair Khan 1
Affiliation  

ABSTRACT In this research work, a 40-km2 SPOT-5 High-Resolution Imagery (HRI) of the Warsak locality in district Peshawar, Pakistan, was utilized to approximate the quantity of cultivated land lost to urbanization, due to the construction of new homes and buildings. The imagery from a period of 2005 to 2015 for wheat crop was taken, specifically during the months of March and June when the crop is rich green and golden ripe respectively. eCognition ® program’s Object-Oriented Classification Method (OOCM) was employed for recognition of land versus buildings. Nearest Neighbour (NN), Support Vector Machine (SVM), Decision Trees (DT) and Random Forests (RF) were utilized for the classification process. The results demonstrated that the urbanized area had increased by approximately 28 per cent in the area considered. Moreover, the efficacy of the proposed method is depicted by an accuracy of 97.9 per cent and a Kappa Statistics of 0.975 for the SVM classifier.

中文翻译:

遥感技术在城镇化耕地流失估算中的应用

摘要 在这项研究工作中,利用巴基斯坦白沙瓦地区 Warsak 地区的 40 平方公里 SPOT-5 高分辨率影像 (HRI) 来估算因建造新住宅而因城市化而损失的耕地数量和建筑物。拍摄了 2005 年至 2015 年期间小麦作物的图像,特别是在 3 月和 6 月期间,作物分别是丰富的绿色和金色成熟。eCognition ® 程序的面向对象分类方法(OOCM) 用于识别土地与建筑物。最近邻 (NN)、支持向量机 (SVM)、决策树 (DT) 和随机森林 (RF) 用于分类过程。结果表明,在所考虑的地区,城市化面积增加了约 28%。而且,
更新日期:2019-06-04
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