Characterizing the complexity of landscape boundaries by remote sensing

This paper presents a method for characterizing the complexity of landscape boundaries by remote sensing. This characterization is supported by a new boundary typology, that takes into account points where three or more landcovers converge (i.e., convergency points or coverts). Landscape boundary richness and diversity indices were proposed and calculated over 19 landscapes in South-East Brazil. Results showed that landscape boundaries, especially convergency points, provided an enrichment in landscape pattern analysis. Landcover boundary diversities were significantly related to landcover shape: elongated riparian units had the highest values for boundary diversity and coverts proportion indices. On the other hand, landscape analysis showed that indices of shape, richness, diversity and coverts proportion provided an additional evaluation of landcover spatial distribution within the landscape.     

青海杂多县冬虫夏草的生态调查

对青海省杂多县冬虫夏草及其寄主的自然生境进行调查研究发现,该县虫草主要分布于海拔4 000～4700m的高寒草甸或高寒灌丛中。因海拔、植被、地形和水热条件的不同,虫草及其寄主具有明显的垂直地带性分布特征。在青藏高原长期的进化过程中,虫草寄主形成耐寒、耐涝、耐饥的生态习性。水、热、光是完成虫草有性世代的主要因子。     

Applying Local Measures of Spatial Heterogeneity to Landsat-TM Images for Predicting Wildfire Occurrence in Mediterranean Landscapes

In mountainous Mediterranean regions, land abandonment processes in past decades are hypothesized to trigger secondary vegetal succession and homogenization, which in recent years has increased the size of burned areas. We conducted an analysis of temporal changes in landscape vegetal spatial pattern over a 15-year period (1984–1998) in a rural area of 672.3 km² in Eastern Spain to investigate the relationship between local landscape heterogeneity and wildfire occurrence. Heterogeneity was analyzed from textural metrics derived from non-classified remote sensing data at several periods, and was related to wildfire history in the study area. Several neural network models found significant relationships between local spatial pattern and future fire occurrence. In this study, sensitivity analysis of the texture variables suggested that fire occurrence, estimated as probability of burning in the near future, increased where local homogeneity was higher.     

地面高光谱和低空遥感监测小麦白粉病初探

利用手持式高光谱仪和基于数字技术的低空遥感系统，对不同严重度小麦白粉病冠层光谱反射率进行了测定，同时调查病情指数，分析不同时期地面平台光谱反射率与病情指数及低空遥感平台反射率与病情指数（disease index，DI）、归一化植被指数（normalized difference vegetable index，NDVI）相关性。结果表明，地面光谱测量冠层光谱反射率和低空遥感数字图像反射率与小麦白粉病病情指数在灌浆期有显著的相关关系，就地面测量结果而言，近红外波段的相关性高于绿光波段，相关系数分别为0．79和0．54；低空遥感数字图像红、绿、蓝三波段中，相关性依次降低，相关系数分别为0．79、0．75和0．62；而且低空遥感图像与归一化植被指数也存在较好的相关关系，蓝、红、绿波段，相关系数依次为0．70、0．68和0．54。这表明利用遥感非破坏性监测小麦白粉痛有着良好的应用前景，对于小麦白粉病发生面积监测有重要意义。     

Land Use – Land Cover Conversion, Regeneration and Degradation in the High Elevation Bolivian Andes

Regional land-cover change affects biodiversity, hydrology, and biogeochemical cycles at local, watershed, and landscape scales. Developing countries are experiencing rapid land cover change, but assessment is often restricted by limited financial resources, accessibility, and historical data. The assessment of regional land cover patterns is often the first step in developing conservation and management plans. This study used remotely sensed land cover and topographic data (Landsat and Shuttle Radar Topography Mission), supervised classification techniques, and spectral mixture analysis to characterize current landscape patterns and quantify land cover change from 1985 to 2003 in the Altiplano (2535–4671 m) and Intermediate Valley (Mountain) (1491–4623 m) physiographic zones in the Southeastern Bolivian Andes. Current land cover was mapped into six classes with an overall accuracy of 88% using traditional classification techniques and limited field data. The land cover change analysis showed that extensive deforestation, desertification, and agricultural expansion at a regional scale occurred in the last 20 years (17.3% of the Mountain Zone and 7.2% of the Altiplano). Spectral mixture analysis (SMA) indicated that communal rangeland degradation has also occurred, with increases in soil and non-photosynthetic vegetation fractions in most cover classes. SMA also identified local areas with intensive management activities that are changing differently from the overall region (e.g., localized areas of increased green vegetation). This indicates that actions of local communities, governments, and environmental managers can moderate the potentially severe future changes implied by the results of this study.     

利用遥感技术监测锡林郭勒天然草原利用强度方法初探

利用多时相的遥感数据，对2005年锡林郭勒天然草原生长期放牧利用强度进行了信息提取、监测和制图。结果表明：在牧草生长季节，天然草原各旬度的利用强度与植被指数旬度变动系数成反比，并与降雨和植被长势时空分布格局相一致；放牧初期旬度变动系数下降4％左右，利用强度较轻，处于轻度过牧状态；6月中旬以后，旬度变动系数下降12％～20％之间，利用强度加重，处于中度超载过牧状态；8月下旬后植物生长停止，旬度变动系数下降27％左右，利用强度最重，处于重度超载过牧状态。遥感监测结果经过地面同步采集数据验证，监测精度达到79．6％。     

山东省小规模养鸡场沙门氏菌流行病学调查分析

对近年来山东省内鸡沙门氏菌病进行了调查,并对典型的沙门氏菌做了生化鉴定和药物敏感试验。调查表明沙门氏菌病在小规模养殖场的发生呈上升趋势,常与大肠杆菌病、新城疫和鸡球虫病混合感染。对所分离的沙门氏菌株鉴定表明,70%为副伤寒沙门氏菌,也有鸡白痢沙门氏菌的存在。药敏试验结果表明沙门氏菌对传统的防治细菌性药物产生了多重耐药性,这说明细菌耐药性的产生和发展与抗生素长期反复使用和盲目使用有密切的关系。本文为更有效地防控细菌性疫病提供科学依据。     

Geospatial methods provide timely and comprehensive urban forest information

Urban forests are unique and highly valued resources. However, trees in urban forests are often under greater stress than those in rural or undeveloped areas due to soil compaction, restricted growing spaces, high temperatures, and exposure to air and water pollution. In addition, conditions change more quickly in urban as opposed to rural and undeveloped settings. Subsequently, proactive management of urban forests can be challenging and requires the availability of current and comprehensive information. Geospatial tools, such as, geographic information systems (GIS), global positioning systems (GPS) and remote sensing, work extremely well together for gathering, analyzing, and reporting information. Many urban forest management questions could be quickly and effectively addressed using geospatial methods and tools. The geospatial tools can provide timely and extensive spatial data from which urban forest attributes can be derived, such as land cover, forest structure, species composition and condition, heat island effects, and carbon storage. Emerging geospatial tools that could be adapted for urban forest applications include data fusion, virtual reality, three-dimensional visualization, Internet delivery, modeling, and emergency response.     

草地植被盖度的近距离遥感测定

盖度或者覆盖度是植物群落结构的一个重要数量指标。通常的目视估测植物群落盖度方法不仅精度低,而且因人而异。本研究采用近距离遥感方法测定草地植物群落盖度,该方法主要包括数据获取、图像处理、像元数量提取和盖度计算4个部分。精度评价表明,该方法测定的绿色植被盖度误差很小,与目视估测方法比较,它具有客观、一致和精度高的优点。     

Use of airborne multispectral imagery to discriminate and map weed infestations in a citrus orchard

Reliable information on weed abundance and distribution within fields is essential for weed management in agricultural systems. Such information is necessary to adopt localized and variable rates of herbicide spraying, thus reducing chemical waste, crop damage, and environmental pollution. This paper examined the potential of airborne multispectral imagery to discriminate and map weed infestations in an experimental citrus orchard in Japan. Using an airborne digital sensor, multispectral imagery was acquired over the study site on 10 April 2003. The obtained reflectance imagery was analyzed using an image object-based approach in eCognition. After creating image objects on the image, the spectral information for weeds and citrus, represented by corresponding selected sample image objects, was extracted. Significant differences in the spectral characteristics between weeds and citrus were observed in each of the red, green, and blue wavebands. The simple average values of these wavebands were used to classify image objects with the nearest neighbor algorithm. Maps were generated with different classes or levels of class groups. A subsequent accuracy assessment demonstrated that the weeds were successfully discriminated from other image objects with a classification accuracy of 99.07%. Therefore, maps generated based on the classification result could provide valuable information for developing a site-specific weed management program for the study orchard.