Glacier mapping in the Cordillera Blanca,Peru, tropical Andes,using Sentinel‐2 and Landsat data

Sentinel‐2 images were used for mapping debris‐free glaciers for the first time in Cordillera Blanca. Landsat‐8 and Sentinel‐2 data were compared for glacier area estimation in 2016, obtaining comparable results. It was observed that normalized difference snow index method for glacier mapping using MSI data is less sensitive to cast shadows and steep terrain compared with Landsat data. Estimated total glacier areas in 1975, 1994, and 2016 were 726 ± 20.3 km², 576.9 ± 15.1 km² and 482.8 ± 7.4 km², respectively. Glacier area in 2016 using Landsat was slightly lower (475.7 ± 16.8 km²) compared to the area estimated using MSI data. Observed glacier shrinkage between 1975 and 2016 was 33.5 per cent, which is lower compared to observed glacier area loss in the eastern cordilleras of Peru. Glacier shrinkage was higher at northern and northeastern slopes (47.9 per cent and 48.1 per cent, respectively) compared to the south‐western slopes (11.1 per cent).     

若尔盖县弯曲河流精细提取研究

利用Google Earth Engine遥感大数据云平台,以若尔盖县的弯曲河流为研究对象,以空间分辨率为10 m的Sentinel-2多光谱卫星遥感影像为数据源,选用归一化差分水体指数(NDWI)、改进型归一化差分水体指数(MNDWI)和自动水体提取指数(AWEI)相组合的方式,建立支持向量机模型,进行弯曲河流信息的提取;利用归一化差分水体指数、改进型归一化差分水体指数和自动水体提取指数,提取出弯曲河流信息,并与支持向量机模型提取的结果进行了比较。研究结果表明,利用归一化差分水体指数提取的弯曲河流的整体性和连续性最优;利用改进型归一化差分水体指数提取的地势复杂区域细小河流的精度较高;利用支持向量机模型提取的弯曲河流更为准确,并消除了山体和植物阴影对弯曲河流提取的影响;与利用3种指数提取的结果相比,支持向量机模型提取的弯曲河流的总体精度和用户精度都相对最高。     

Thematic land-cover map assimilation and synthesis: the case of locating potential bioenergy feedstock in eastern Ontario,Canada

Insufficient spatial coverage of existing land-cover data is a common limitation to timely and effective spatial analysis. Achieving spatial completeness of land-cover data is the most challenging for large study areas which straddle ecological or administrative boundaries, and where individuals and agencies lack access to, and the means to process, raw data from which to derive spatially complete land-cover maps. In many cases, various sources of secondary data are available, so that land-cover map assimilation and synthesis can resolve this research problem. The following paper develops a reliable and repeatable framework for assimilating and synthesizing pre-classified data sets. Assimilation is achieved through data reformatting and map legend reconciliation in the context of a specific application. Individual maps are assessed for accuracy at various geographic scales and levels of thematic precision, with an emphasis on the ‘area of overlap’, in order to extract information that guides the synthesis process. The quality of the synthesized land-cover data set is evaluated using advanced accuracy assessment methods, including a measure describing the ‘magnitude of disagreement’. This method is applied to derive a seamless thematic map of the land cover of eastern Ontario from two disparate map series. The importance of assessing data quality throughout the process using multiple reference data sets is highlighted, and limitations of the method are discussed.     

A review of historical reconstruction methods of land use/land cover

Understanding long-term human-environment interactions requires historical reconstruction of past land-use and land-cover changes. Most reconstructions have been based primarily on consistently available and relatively standardized information from historical sources. Based on available data sources and a retrospective research, in this paper we review the approaches and methods of the digital reconstruction and analyze their advantages and possible constraints in the following aspects: (1) Historical documents contain qualitative or semi-quantitative information about past land use, which also usually include land-cover data, but preparation of archival documents is very time-consuming. (2) Historical maps and pictures offer visual and spatial quantitative land-cover information. (3) Natural archive has significant advantages as a method for reconstructing past vegetation and has its unique possibilities especially when historical records are missing or lacking, but it has great limits of rebuilding certain land-cover types. (4) Historical reconstruction models have been gradually developed from empirical models to mechanistic ones. The method does not only reconstruct the quantity of land use/cover in historical periods, but it also reproduces the spatial distribution. Yet there are still few historical land-cover datasets with high spatial resolution. (5) Reconstruction method based on multiple-source data and multidisciplinary research could build historical land-cover from multiple perspectives, complement the missing data, verify reconstruction results and thus improve reconstruction accuracy. However, there are challenges that make the method still in the exploratory stage. This method can be a long-term development goal for the historical land-cover reconstruction. Researchers should focus on rebuilding historical land-cover dataset with high spatial resolution by developing new models so that the study results could be effectively applied in simulations of climatic and ecological effects.     

基于RapidEye卫星和面向对象方法的南方山区居民地提取（英文）

在中国快速城市化进程中,农村居住人口减少的同时居住用地却呈增加趋势,这一现象在南方山区尤为明显。利用遥感技术进行农村居民地信息的提取与分析具有重要意义。本研究选取江西省泰和县为典型研究区,基于RapidEye卫星影像,利用面向对象的分类方法进行居民地的分类提取。构建的分类规则集包括归一化植被指数NDVI、归一化水体指数NDWI、亮度以及长/宽比。通过多次实验,图像的最佳分割尺度设置为200。通过设置不同的分类规则参数,提取了研究区的居民地及其他土地利用类型,并进行分类结果验证和精度评价。研究区的居民地分类总体精度为78.40%,生产者精度和用户精度分别为68.75%和77.33%。结果表明通过利用面向对象的分类方法,Rapid Eye卫星影像为农村居民地信息提取提供了适宜数据源。与第二次全国土地调查结果相比,存在93.67公顷的分类差异,主要分布在居民地与其他土地利用类型的毗邻地区。     

土地利用/覆被历史重建方法(英文)

Understanding long-term human-environment interactions requires historical reconstruction of past land-use and land-cover changes. Most reconstructions have been based primarily on consistently available and relatively standardized information from historical sources. Based on available data sources and a retrospective research, in this paper we review the approaches and methods of the digital reconstruction and analyze their advantages and possible constraints in the following aspects:(1) Historical documents contain qualitative or semi-quantitative information about past land use, which also usually include land-cover data, but preparation of archival documents is very time-consuming.(2) Historical maps and pictures offer visual and spatial quantitative land-cover information.(3) Natural archive has significant advantages as a method for reconstructing past vegetation and has its unique possibilities especially when historical records are missing or lacking, but it has great limits of rebuilding certain land-cover types.(4) Historical reconstruction models have been gradually developed from empirical models to mechanistic ones. The method does not only reconstruct the quantity of land use/cover in historical periods, but it also reproduces the spatial distribution. Yet there are still few historical land-cover datasets with high spatial resolution.(5) Reconstruction method based on multiple-source data and multidisciplinary research could build historical land-cover from multiple perspectives, complement the missing data, verify reconstruction results and thus improve reconstruction accuracy. However, there are challenges that make the method still in the exploratory stage. This method can be a long-term development goal for the historical land-cover reconstruction. Researchers should focus on rebuilding historical land-cover dataset with high spatial resolution by developing new models so that the study results could be effectively applied in simulations of climatic and ecological effects.     

Integrating land-cover data with different ontologies: identifying change from inconsistency

Spatially coincident land-cover information frequently varies due to technological and political variations. This is especially problematic for time-series analyses. We present an approach using expert expressions of how the semantics of different datasets relate to integrating temporal time series land-cover information where the classification classes have fundamentally changed. We use land-cover mapping in the UK (LCMGB and LCM2000) as example data sets because of the extensive object-based meta-data in the LCM2000. Inconsistencies between the two datasets can arise from random, gross and systematic error and from an actual change in land cover. Locales of possible land-cover change are inferred by comparing characterizations derived from the semantic relations and meta-data. Field visits showed errors of omission to be 21% and errors of commission to be 28%, despite the accuracy limitations of the land-cover information when compared with the field survey component of the Countryside Survey 2000.     

THE N-FACTOR AS A TOOL IN GEOCRYOLOGICAL MAPPING: SEASONAL THAW IN THE KUPARUK RIVER BASIN,ALASKA

Although maps of active-layer thickness have useful roles in geocryology, polar ecology, and hydrology, a lack of geographically distributed data at appropriate scales has prevented their widespread implementation. The n-factor (ratio of temperature at the soil surface to that in the air) has considerable potential as a tool for mapping active-layer thickness and other geocryological parameters by providing refinements to relatively simple analytic solutions for the depth of thaw. Although temperature data from the soil surface under representative land-cover units have rarely been collected historically, recent advancements in data-logger technology allow the variability of soil-surface temperature regimes to be assessed inexpensively over small temporal and spatial intervals. Temperature data collected in the air at 2 m height and at the soil surface within 10 representative land-cover units in the Kuparuk River region of north-central Alaska were used to compute seasonal n-factor values for specific vegetation-soil associations. The resulting values were used with degree-day sums, a digital elevation model, and a digital map of vegetation to compute a modified Stefan estimate of thaw depth over a 26,278 km² area. Comparisons between maps based on the n-factor and an empirical, data-intensive method show similar performance. Given sufficient ancillary data, the n-factor provides a useful tool for mapping active-layer thickness over large areas without intensive in situ data collection. [Key words: Alaska, permafrost, active-layer thickness, frozen ground, mapping, temperature.]     

SPECTRAL AND TEXTURAL FEATURES TO CLASSIFY ELUSIVE LAND COVER AT THE URBAN FRINGE

Land-cover classification using only remotely sensed spectral features does not provide accurate information on all urban-fringe classes. Four texture measures used in conjunction with LANDSAT spectral features were empirically evaluated to determine their utility in Level II and III land-cover mapping. The contrast and high-frequency measures improved land-cover classification at the urban fringe. However, the decision to use texture measures should be weighed carefully because they yield only a small, yet important, increment in absolute classification accuracy and entail additional expense for data preprocessing.     

1990 年以来广州市土地覆被景观的时空梯度分异

取1990 年、1995 年、2000 年和2005 年4 个时相覆盖广州市的TM 遥感影像为数据源, 经非监督分类及人工目视解译, 获得研究区各时相土地覆被类型图。以高速公路为轴线 应用缓冲区技术, 形成南北和东西两条样带, 同时以城市中心区域向外等距扩展而形成辐射状梯度圈。通过样带和梯度圈剪裁形成土地覆被类型图, 计算土地覆被类型图的景观指数, 分析广州市15 年间土地覆被动态过程, 揭示区域景观动态的方向和梯度分异特征。数量结构与样带研究结果表明: 广州市因经济发展而使土地覆被景观恶化的趋势已得到一定程度的遏制, 城市发展逐步进入理性控制阶段, 但是存在方向分异, 东西样带上的土地覆被景观的多样性持续下降, 斑块破碎化程度加剧; 辐射梯度圈研究结果显示, 向外围扩展的城市化过程使广州市呈现出多个次级中心的格局, 对城市土地覆被景观的干扰强度自中心城区向郊区递减, 方向分异不显著; 东南方向的辐射梯度圈内土地覆被景观的分维数和多样性指数变化特征表明, 自2000 年始, 经济发展已开始侵占南部海域。     

SPECTRAL AND TEXTURAL FEATURES TO CLASSIFY ELUSIVE LAND COVER AT THE URBAN FRINGE

Land-cover classification using only remotely sensed spectral features does not provide accurate information on all urban-fringe classes. Four texture measures used in conjunction with LANDSAT spectral features were empirically evaluated to determine their utility in Level II and III land-cover mapping. The contrast and high-frequency measures improved land-cover classification at the urban fringe. However, the decision to use texture measures should be weighed carefully because they yield only a small, yet important, increment in absolute classification accuracy and entail additional expense for data preprocessing.     

基于3S技术的金沙江干热河谷区LUCC研究——以云南省元谋县为例

以云南省元谋县为例,集成3S技术,对多期Landsat-TM数据进行土地利用/土地覆被信息提取及建立数据库,采用单一土地利用/土地覆被动态度和综合土地利用/土地覆被动态度指标,分析金沙江干热河谷区土地利用/土地覆被结构变化规律,提出基于生态环境建设的金沙江干热河谷区土地利用优化对策。并结合DEM数据分析分析金沙江干热河谷区土地利用/土地覆被垂直分异及其变化规律,结果表明：1.草地和林地是土地利用/土地覆被的主体,但林地以疏林地为主,草地以低、中覆盖度草地为主,具有相当大的敏感性和脆弱性;2.土地利用较为粗放,如水浇地占耕地、人工草地占草地及城乡建设用地占总用地面积的比例等相对较低;3.土地利用/土地覆被结构发生了较快的变化,耕地、草地、水域、未利用土地面积有所减少,而林地、城乡建设用地面积增长较快;4.低山区和中低山区为以林草地为主、耕地亦有一定比例的类农林牧交错带,是干热河谷区生态环境最脆弱的地带。     

黄土高原地区土地覆盖变化对气候的反馈作用数值模拟

区域尺度土地覆盖变化是自然变化和人类活动共同驱动的结果,同时又对区域气候环境产生反馈。利用欧洲中值数值预报中心（ECMWF） ERA-Interim再分析资料,驱动RegCM4.5区域气候模式,进行了两个时间段（1980-2014、2005-2014）的数值模拟试验。以1：250 000土地利用图为基础,结合植被图、土壤图制作具有高精度、极强现势性的土地覆盖资料,区域模式中陆面过程模式采用BATS,模拟了现实的土地覆盖改变对气候要素的影响,分析了黄土高原地区土地覆盖变化对气候的反馈作用。结果表明：（1） RegCM4.5不但能够较好描述黄土高原气温、降水的时间空间分布特征,也能够模拟土地覆盖变化对黄土高原局地气候变化的反馈。（2）不同土地覆盖变化特征对气候反馈作用不同,荒漠化会引起局部地区气温升高和降水减少,并通过正反馈机制,致使自然植被生长发育受阻;水域旱化会导致夏季气温升高和降水增加,从而加剧干旱洪涝灾害风险;草地覆盖增加会导致春夏季降水量与气温的降低,秋冬季降水量与气温升高。（3）土地覆盖变化对气温与降水的影响在夏季较强。该研究可促进对黄土高原生态治理环境效应的理解,也能深化对土地利用-气候变化之间互馈作用的过程认识,并为区域生态建设对策选择提供参考。     

Image data fusion for the remote sensing of freshwater environments

Remote sensing based mapping of diverse and heterogeneous freshwater environments requires high-resolution images. Data fusion is a useful technique for producing a high-resolution multispectral image from the merging of a high-resolution panchromatic image with a low-resolution multispectral image. Given the increasing availability of images from different satellite sensors that have different spectral and spatial resolutions, data fusion techniques that combine the strengths of different images will be increasingly important to Geography for land-cover mapping. Different data fusion methods however, add spectral and spatial distortions to the resultant data depending on the geographical context; therefore a careful selection of the fusion method is required. This paper compares a technique called subtractive resolution merge, which has not previously been formally tested, with conventional techniques such as Brovey transformation, principal component substitution, local mean and variance matching, and optimised high pass filter addition. Data fusion techniques are grouped into spectral and spatial centric methods. Subtractive resolution merge belongs to a new class of data fusion techniques that uses a mix of both spatial and spectral centric approaches. The different data fusion techniques were applied to a QuickBird image of a semi-aquatic freshwater environment in New Zealand. The results were compared both qualitatively and quantitatively using spectral and spatial error metrics. This research concludes that subtractive resolution merge performed better than all the other techniques and will be a valuable technique for enhancing images for freshwater land-cover mapping.     

Conflation and aggregation of spatial data improve predictive models for species with limited habitats: A case of the threatened yellow-billed cuckoo in Arizona,USA

Riparian vegetation provides important wildlife habitat in the southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.     

NDVI prediction over Mongolian grassland using GSMaP precipitation data and JRA-25/JCDAS temperature data

An algorithm to predict the NDVI (Normalized Difference Vegetation Index) distribution over Mongolia, which is based on a stepwise multiple linear regression analysis, has been developed using global precipitation data obtained from satellites and global surface air temperature data obtained from the reanalysis data during the period 1998–2005. This algorithm can predict the NDVI value up to 1–3 months in advance for a grid with a spatial resolution of 0.25° × 0.25°.In order to validate the algorithm, the NDVI distribution was predicted for the period from May to November 2006 using 1 to 3-month prediction algorithms. The distributions of the predicted normalized anomalies agreed well with those of the observed normalized anomalies. It was found that these algorithms were effective for arid and semi-arid regions, despite its low accuracy for August and regions with high vegetation activity.     

Forest-Cover Change from Labor- and Capital-Intensive Commercial Logging in the Southern Chocó Rainforests*

Abstract

This article examines two key aspects of land-cover change in the south of the Chocó region. First, it assesses and compares the local impact on forest condition of labor-intensive and capital-intensive commercial logging. Second, it assesses the regional significance and permanency of these changes. Studies of land-cover change associated with commercial logging have focused almost exclusively on capital-intensive extraction and have assumed that after logging, degraded forests are transformed into agricultural cover. This study shows that both capital- and labor-intensive logging result in similar land-cover changes (i.e., forest degradation) if the timber sought is the same. However, labor-intensive loggers also seek timber species not sought by capital-intensive loggers, and this impact is statistically different from the impact of the extraction of the first group of species. Results also show that only a small fraction (20–30 percent) of the area logged is later converted to agricultural cover types. The persistence of logged forests means that up to 20 percent of the remaining forest cover could correspond to forests with significant and lasting levels of degradation. Furthermore, the different production requirements for each group of species also mean that there is a spatial differentiation in the impact of logging in the region. Logged forests are arranged into two consecutive corridors on each side of access routes (e.g., rivers). The first corridor corresponds to a narrow (approximately 1-km) band of high-intensity degradation. The second, broader (approximately 2-km) forest band, with lower levels of degradation, extends inland along first-tier corridors. A key factor determining the permanency of this land-cover pattern is the strong control local communities have over the land in the region. This limits the spread of patterns observed in other frontier areas, especially the conversion of logged forests into agricultural cover.     

基于地理模拟方法的昆明市空间拓展情景分析

改革开放以来,西部高原湖滨城市经历的快速城镇化进程给湖泊流域带来了较为严重的生态环境问题,未来城市空间发展政策的调整需要关注城市空间拓展对区域生态环境的影响。以位于滇池湖滨地区的昆明市为例,设定6种不用的城市空间拓展政策情景,应用SLEUTH模型预测了6种情景下未来20年的城市空间格局,采用空间指数和空间分析方法对预测结果进行了分析评价。结果表明：昆明市城市建成区具有典型的摊大饼式空间拓展模式,城市道路网对城市形态具有重要的影响。6种情景模式下未来昆明市建成区空间格局既有相似性,也表现出显著的差异。城市建设用地空间格局总体上呈集约、紧凑型的发展趋势。生态保护与城市发展管制相结合的政策情景对滇池湖滨地区的景观影响最小。多中心城市发展格局和城市发展管制相结合的政策情景对城市总体空间规模的控制具有明显的效果,但不宜在湖滨地区实施。滇池湖滨地区需要划定景观或生态保护区,严格禁止城市建设用地对湖滨用地景观的占用与分割。滇池湖滨以外的区域,适宜执行生态保护与城市发展管制相结合的多中心发展模式。     

Multi-faceted land cover and land use change analyses in the Yellow River Basin based on dense Landsat time series: Exemplary analysis in mining,agriculture, forest,and urban areas

The Yellow River Basin is one of China's most dynamic regions, where past and recent anthropogenic land use activities and polices have had a remarkably impact on the basin's surface. Over the past decades, the rapid socio-economic development has increased the pressure on the prevailing water and land resources with various repercussions on the environment and society. Counteracting ecological degradation in the basin, large-scale conservation and restoration plans have been initiated to expand vegetation coverage on deteriorated land, simultaneously fostering rural sustainable agriculture production. In this context, we derived precise spatial thematic products from long-term satellite time-series about high-frequency temporal dynamics. This information, available in a consistent and repeatable fashion is rare and relevant for many regional and local stakeholders and must be monitored annually to capture the rapid rate of change. Such information serves as a valuable base for decision-making processes. In this study, we used all the archived Landsat images between 2000 and 2015 (4520 scenes) to computed annually the spatially continuous spectral-temporal and textual metrics based on dense Landsat time-series to derive annual maps showing the most prominent land-cover change types related to mining, agriculture, forestry, and urbanization in four sub-regions spread over the Yellow River Basin. These novel land cover/use products provide new insights into recent regional and local dynamics. For final classification, we employed random forest classifiers for each thematic focus-region, trained and tested based on a stable-pixels data set. The resulting maps achieved high accuracies and show afforestation on the Loess Plateau and urbanization as the most prominent drivers of land use/cover dynamics. Agricultural land remained stable, showing local small-scale dynamics. Our study highlights the great potential of using consistent spectral-temporal metrics derived from dense Landsat time-series data together with a stable pixels reference set, allowing for local and regional land surface dynamics mapping at high spatial resolution and the prediction of implications of future change for effective and sustainable basin management.