基于遥感在土地利用与土地覆盖中的应用研究

介绍了遥感技术的发展以及土地利用与土地覆盖遥感信息的获取和应用,为我国土地保护和合理利用提供了新的技术支持。     

基于高分卫星遥感的天然草地牧草营养含量季节动态反演的研究

本试验选取了青海省海北地区的海晏县作为研究区域，按照返青期（4-6月）、盛草期（7-9月）、枯黄期（10-12月）和枯草期（1-3月）4个阶段，试图通过实地测量、实验室分析与高分遥感影像相结合，分别筛选与草地各营养指标含量相关性最优的植被指数，建立草地营养含量月际动态估测模型，旨在将高分卫星影像与地面高光谱数据相结合，初步探寻天然草地各营养指标含量的月际动态规律，对指导冷季补饲及实现草地资源最优配置具有重要意义。结果表明：结合高分遥感数据，针对不同月份分别筛选最佳反演模型，对各营养指标含量进行反演，以此分析草场各营养含量月际动态变化规律是可行的；牧草干物质、粗蛋白、钙和磷含量随着返青期-盛草期-枯黄期-枯草期的变化趋势，基本呈现先增后减型变化。4个阶段中，草场干物质和磷含量最大相差约6倍，粗蛋白含量最大相差约7倍，钙含量最大相差约17倍。     

遥感影像判读技术在林地变更调查中的应用探讨

指出了遥感技术在森林资源调查中应用广泛,研究林地变更调查中的遥感影像判读技术,能够有效提高变更调查结果的精度,确保森林资源管理“一张图”的真实性和准确性。结合2017年度广西都安县林地变更调查项目,利用高分辨率遥感影像,参考林业经营管理档案,对变化图斑进行修正和判读,并对判读结果进行了分析。提出了影响遥感影像判读的主要影响因素,为森林资源调查中的影像判读提供参考。     

Satellite remote sensing of breeding habitat for an African weaver-bird

Data derived from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA series of operational, polar orbiting, meteorological satellites have previously been shown to be quite useful for monitoring vegetation dynamics at scales ranging from regional (10⁴ km²) to global. In this report, we demonstrate that these same data can be used to monitor potential breeding habitat for a highly mobile, granivorous African weaver-bird, the red-billed quelea (Quelea quelea). This species is often considered to be an agricultural pest, affecting cereal production throughout sub-Saharan Africa. The temporal resolution and very large (continental) spatial coverage provided by these data can provide a unique context within which to examine species distribution and abundance patterns.     

专业户荟萃

专业户荟萃龙南县南亨乡夹水村中拖驾驶员张石成，选准治理荒山水土流失，发展果业致富这条路，从１９８３年起，全家苦战４个春秋，按水土保持技术要求，高标准种植柑桔１０００株。１９８７年以来，年平均产桔１．５万公斤，纯收入１万余元。与此同时，张石成积极开展多...     

我国温带草地草畜平衡动态监测系统的研究

本文讨论了我国温带草地放牧系统草畜平衡动态监测的原理与方法，设计了动态监测的数据库与技术系统以及遥感测产和动态监测的有关模型，以期建立可运行的大范围草地资源动态监测系统，为草地管理决策提供依据。     

建立人工草地是维护陕北黄土高原生态平衡和发展畜牧业的战略措施

本文通过陕北草地资源的遥感调查,并结合该地区的生态变迁及畜牧业发展的历史与现状的资料分析研究认为,各种优良牧草具有分蘖力强,地面郁闭度大;根量大,在土层内能积聚大量有机物质;产量高,质量好等特点。因而在这里建立人工草地是保持水土,恢复生态平衡和发展畜牧业的战略措施。与此同时,还要处理好保护资源与开发利用、经济效益与生态效益和农牧林业之间的三个关系。     

卫星遥感影像图在国家公益林核查工作中的应用

通过国家公益林核查工作中对遥感卫星影像图的实际应用，介绍了从遥感数据准备、影像图使用、解译效果等全部工作过程。阐明了数据选取的原则，数据合成依据，分析了应用效果，指出了存在的问题。为其他类似的资源调查提供了参考和借鉴。     

The Classification of Grassland Types Based on Object-Based Image Analysis with Multisource Data

The spatial distribution of different grassland types is important for effectively analyzing spatial patterns, obtaining key vegetation parameters using remote sensing (e.g., biomass, leaf area index, net primary production), and using and protecting grasslands. Existing classifications of grasslands by remote sensing are mostly divided according to the fractional vegetation cover or biomass, but classifications according to grassland types are scarce. In this study, we focused on the classification of different grassland types using remote sensing based on object-based image analysis (OBIA) with multitemporal images in combination with a 30-m digital elevation model (DEM) and the normalized difference vegetation index (NDVI). The grasslands were located in Hulunber, Inner Mongolia, and an autonomous region of China. The support vector machine (SVM) and random forest (RF) machine learning classifiers were selected for the classification. The results revealed the following: 1) It is feasible to generally extract different grassland types on the basis of OBIA with multisource data; the overall classification accuracy and Kappa value exceeded 90% and 0.9, respectively, using the SVM and RF machine learning classifiers, and the classification accuracy of the different grassland types ranged from 61.64% to 98.71%; 2) Multitemporal images and auxiliary data (DEM and NDVI) improved the separability of different grassland types. The information in the growing season was conducive for distinguishing temperate meadow steppe from temperate steppe and was favorable for extracting lowland meadow and swamp in the nongrowing season. The DEM and NDVI also effectively reduced the number of image segmentation objects and improved the segmentation effects; 3) Spectral and textural features were more important than geometric features in this study. A few main variables played a major role in the classification, while a large number of variables had either no significant effect or a negative effect on the classification results when the optimal feature subset was determined. This study provides a scientific basis and reference for the classification of various grassland types by remote sensing, including the data selection, image segmentation, feature selection, classifier selection, and parameter settings.     

沙漠化环境信息管理系统的设计框架研究--以于田县为例

研究从建立于田县沙漠化孕灾环境的多层次、多学科、综合性的区域性环境信息系统入手，技术路线是供助于遥感和GIS技术，以遥感卫星图像为系统数据库重要信息源，将参数控空间分布特点，输入计算机系统，建立沙漠化环境综合数据库，实现信息计算机化的动态存储管理、检索和综合理论分析，以便为沙漠化防治的综合治理、全面规划、管理决策及动态监测等提供丰富的信息，最终实现沙漠化环境监测各项地学指标的定量化和模式化。