Contrastive Analysis on Soil Alkalinization Predicting Models Based on Measured Reflectance and TM Image Reflectance
ZHANG Fang1, 3, XIONG Hei-gang2, 3*, LONG Tao1, 3, LU Wen-juan1, 3
1. College of Resources & Environment Science, Xinjiang University, Urumqi 830046, China 2. Urban Department of College of Art & Science, Beijing Union University, Beijing 100083, China 3. Key Laboratory of Oasis Ecology(Xinjiang University)Ministry of Education, Urumqi 830046, China
Abstract：Based on the monitored data of soil pH and measured Vis-NIR reflectance on spot in Qitai oasis alkalinized area in Xinjiang, as well as comparison of the relationship between measured reflectance and soil pH and the relationship between TM reflectance and soil pH, both of the reflectance multivariate linear regression models were built to evaluate soil alkalinization level, and the model accuracy of pH fitting was discussed with error inspection of post-sample. The results showed that there is a significant positive correlation between soil pH and reflectance. With pH rising the reflectance increased concurrently. So the alkalinization soil characterized by hardening had good spectral response characteristics. Both measured reflectance and TM image reflectance had good potential ability for change detection of the alkalinization soil. The pH predicting model of measured reflectance had higher accuracy and the major error was from different hardening state. If building model by TM reflectance directly, the accuracy of fitting was lower because of the vegetation information in image spectrum. With the vegetation factor removed with NDVI, the accuracy of TM predicting model was near the accuracy of measured reflectance predicting model, and both of the model levels were good.
[1] WANG Zun-qin(王遵亲). Soil Salinization in China(中国盐渍土). Beijing: Science Press(北京: 科学出版社), 1993. [2] Amezketa E. Journal of Arid Environments, 2006, 67: 594. [3] XI Jin-biao, ZHANG Fu-suo, TIAN Chang-yan, et al( 郗金标，张福锁，田长彦，等). Salt Plant in Xinjiang(新疆盐生植物). Beijing: Science Press(北京： 科学出版社)，2006. [4] GUAN Yuan-xiu，LIU Gao-huan, LIU Qing-sheng, et al(关元秀, 刘高焕, 刘庆生, 等). Journal of Remote Sensing(遥感学报), 2001，5(1): 46. [5] García P Rodríguez, Ma E Pérez González, Guerra A Zaballos. International Journal of Remote Sensing, 2007, 28(12): 2713. [6] Haubrock S N, Chabrillat S, Lemmnitz C, et al. International Journal of Remote Sensing, 2008, 29(1): 3. [7] WU Jia-min, YAO Jian-hua, ZHANG Yong-ting, et al(吴加敏, 姚建华, 张永庭, 等). Journal of Remote Sensing(遥感学报), 2007, 11(3): 414. [8] HUANG Ming-xiang，CHENG Jie-liang，WANG Ke，et al(黄明祥，程街亮，王 珂，等). Acta Pedologica Sinica(土壤学报)，2009，46(5)： 932. [9] HUANG Ming-xiang, SHI Zhou, LI Yan, et al(黄明祥, 史 舟, 李 艳, 等). Journal of Remote Sensing(遥感学报), 2004, 8(4)： 378. [10] Farifteh J, Van der F Meer, Van der M Meijde, et al. Geoderma, 2008, 145: 196. [11] Ignacio Melendez-Pastor, Jose Navarro-Pedreno, Ignacio Gómez, et al. Geoderma, 2008, 147(3): 126. [12] Daniel Kassahun, Nitin K Tripathi, Kiyoshi Honda. International Journal of Remote Sensing, 2006, 27(19): 4213. [13] Houssa R, Pion J C, Yesou H. Photogrammetry & Remote Sensing, 1996, 51: 284. [14] FU Qing-hua，NI Shao-xiang，WANG Shi-xin, et al(扶卿华, 倪绍祥, 王世新, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2007，23(1)： 48. [15] LI Shu-gang, WANG Zhou-qiong(李述刚，王周琼). Desert Alkaline Soil(荒漠碱土). Urumqi: Xinjiang People Press(乌鲁木齐： 新疆人民出版社), 1988. [16] CHEN Nan-xiang(陈南祥). Geotechnical Investigation & Surveying(工程勘察)，1999，(3)： 35. [17] YANG Zhong-ping, LU Wen-xi, LI Ping(杨忠平, 卢文喜, 李 平). Journal of Hydraulic Engineering(水利学报), 2005，36(12)： 1475. [18] Agricultural Bureau of Uygur Autonomous Region of Xinjiang, Soil Survey Office of Uygur Autonomous Region of Xinjiang(新疆农业厅，新疆土壤普查办公室). Soil in Xinjiang(新疆土壤). Beijing: Science Press(北京： 科学出版社), 1996. [19] LIANG Shun-lin(梁顺林). Quantitative Remote Sensing(定量遥感). Beijing: Science Press(北京： 科学出版社), 2009.
