T. Bennouna, A. Nejmeddine, M. Lefèvre, M. Kaemmerer, J. Lacombe, J. Revel
{"title":"Innovative Evaluation of Field and Spatial Remote Sensing Data for Analysis of Vegetation Bio-types in Arid Rangelands, Taznakht, Moroccan Anti-Atlas","authors":"T. Bennouna, A. Nejmeddine, M. Lefèvre, M. Kaemmerer, J. Lacombe, J. Revel","doi":"10.1080/089030600263184","DOIUrl":null,"url":null,"abstract":"In Morocco, as in many other regions of north Africa, desertification is affecting the most sensitive environments such as the rangelands. Demographic expansion, cereal growing, and overgrazing constitute the principal factors of degradation in such regions. The use of satellite data provides an efficient tool for observation and continuous measurement of the biosphere. Our objective is to propose a method for the characterization and mapping of rangelands in arid and desert areas, based on the biophysical reality of the environment (field data). A highly detailed study based on field surveys of the Taznakht basin (Moroccan Anti-Atlas) was carried out to determine rangeland typology. Close relationships were demonstrated between the abiotic environment and the vegetation. The relevant bio-pedo-morphological classes at each site, corresponding to the different types of rangeland, were identified. The cartographic accuracy of these classes was considerably increased by combining the stratification obtained by Visual Interpretation Assisted by Computer of the photofacies of a Satellite Pour l'Observation de la Tene (SPOT) image obtained during the dry period, with a supervised classification of each stratum based on maximum likelihood. This methodological approach was used to develop a simple, robust, and generally applicable model for the efficient correlation of field and remote sensing data.","PeriodicalId":174966,"journal":{"name":"Arid Soil Research and Rehabilitation","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Arid Soil Research and Rehabilitation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/089030600263184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In Morocco, as in many other regions of north Africa, desertification is affecting the most sensitive environments such as the rangelands. Demographic expansion, cereal growing, and overgrazing constitute the principal factors of degradation in such regions. The use of satellite data provides an efficient tool for observation and continuous measurement of the biosphere. Our objective is to propose a method for the characterization and mapping of rangelands in arid and desert areas, based on the biophysical reality of the environment (field data). A highly detailed study based on field surveys of the Taznakht basin (Moroccan Anti-Atlas) was carried out to determine rangeland typology. Close relationships were demonstrated between the abiotic environment and the vegetation. The relevant bio-pedo-morphological classes at each site, corresponding to the different types of rangeland, were identified. The cartographic accuracy of these classes was considerably increased by combining the stratification obtained by Visual Interpretation Assisted by Computer of the photofacies of a Satellite Pour l'Observation de la Tene (SPOT) image obtained during the dry period, with a supervised classification of each stratum based on maximum likelihood. This methodological approach was used to develop a simple, robust, and generally applicable model for the efficient correlation of field and remote sensing data.
在摩洛哥,象在北非许多其他地区一样,沙漠化正在影响最敏感的环境,例如牧场。人口膨胀、谷物种植和过度放牧是这些地区退化的主要因素。卫星数据的使用为观测和连续测量生物圈提供了一种有效的工具。我们的目标是根据环境的生物物理现实(实地数据),提出一种描述干旱和沙漠地区牧场特征和绘制地图的方法。根据对Taznakht盆地(摩洛哥Anti-Atlas)的实地调查,进行了一项非常详细的研究,以确定牧场类型。非生物环境与植被有着密切的关系。每个样地对应不同类型的草地,确定了相应的生物土壤形态分类。这些类别的制图精度通过结合在干旱期间获得的卫星Pour l'Observation de la Tene (SPOT)图像的计算机辅助视觉解译获得的分层,以及基于最大似然的每个地层的监督分类,大大提高了。该方法方法用于开发一个简单、稳健且普遍适用的模型,以有效地将野外数据与遥感数据相关联。