Dynamic Change of Landscape Pattern at Jilin Province from 1980 to 2000

By using remote sensing images from three periods (1980, 1995, 2000) and with the support of GIS and RS, the spatial information of landscape elements of Jilin Province from 1980 to 2000 was interpreted and extracted. Using models of landscape indices such as diversity, fragmentation, and mean patch fractal dimension, dynamic spatio-temporal changes of landscape patterns of the province were analyzed. The results: ① cropland and forestland were the main landscape types, and forestland became a landscape matrix; ② in the study area, landscapes were distributed unevenly, and there was low heterogeneity, a simple ecosystem structure and a tendency of irrational landscape patterns. There were also simple spatial shapes of patches and strong self-similarities, and in terms of dynamic change analysis, patch shapes tended to be more simple; ③ from 1980 to 2000, holistic landscape fragmentation was low and changed slightly. As far as landscape elements were concerned, the fragmentation of grassland, water area, land for residential area and factory facilities was relatively low; land distribution for residential areas and factory facilities was dispersed; and cropland and forestland were most concentrated-an indication that the trend will continue. Comprehensive effects among human activity, local policy, regional climate and environmental change led to the results.     

1990—2019年石漠化区耕地时空特征及成因分析——以富源县为例

针对石漠化区耕地变化研究存在时间、空间尺度有限的问题,本文以富源县为例,基于1990、2000、2010和2019年4期的Landsat遥感数据,应用多特征与随机森林相结合的分类方法提取耕地,运用耕地覆盖度、耕地类型转化、坡度分区统计分析了近30年(1990—2019年)耕地时空变化特征,并讨论了耕地变化的原因。结果表明,1990—2019年富源县耕地面积呈先增加(1990—2010年)后减少(2010—2019年)的态势;耕地面积主要来源和转化类型均以林地和草地为主,林地最多;主要分布在北部5个石漠化面积较少的乡镇,以缓坡区为主;耕地覆盖度呈现低-高-低的过程,陡坡区耕地变化率在不同时段差异明显。近30年富源县耕地变化是在石漠化独特的地理环境下,由人口、经济、政策、交通等因素共同作用而形成的。本文的结论可为评估石漠化区域生态安全和粮食安全提供数据支撑。     

眉山市东坡区景观生态信息初步分析

利用景观生态学格局分析方法,将东坡区景观分成耕地、林地、草地、水体、建筑用地和裸地景观六大类。通过遥感影像判读解译,得到上述六类景观基本形状数据。通过计算得到各景观的斑块总面积指数、景观类型所占景观面积的比例指数、斑块数指数、最大斑块指数、平均斑块面积指数、景观破碎化指数、景观优势度指数和多样性指数等景观格局数,初步分析2000年和2007年该区景观格局变化,为经济开发和环境保护提供科学依据和决策支持。     

Spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015

China has experienced unprecedented urbanization in the past decades, resulting in dramatic changes in the physical, limnological, and hydrological characteristics of lakes in urban landscapes. However, the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly understood. Here, we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape metrics. The results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 years. The total surface area of the urban lakes has decreased by 17,620.02?ha, a decrease of 24.22%, with a significant increase in the landscape fragmentation and a reduction in shape complexity. We defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern, followed by edge-shrinkage and tunneling in terms of lake area. Moreover, we also found that urban sprawl was the dominant driver of the lake shrinkage, accounting for 67.89% of the total area loss, and the transition from lakes to cropland was also an important factor (19.86%). This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design.     

近30年巴音布鲁克遗产地景观格局遥感监测与分析

本文以巴音布鲁克世界自然遗产地为研究对象,基于卫星遥感影像、气象站点观测信息、地面调查资料等多源数据,完成了1992年—2020年遗产地突出普遍价值OUVs（Outstanding Universal Values）关键要素空间制图,并从景观尺度分析OUVs关键要素及景观格局的时空变化特征,讨论影响其变化特征的主要驱动因子。结果表明：遗产地从中心向边缘呈水体—沼泽—高覆盖度草地—中覆盖度草地/滩地/沙地—低覆盖度草地/耕地—裸地/建设用地逐渐过渡的景观特征。1992年—2020年遗产地以沼泽和中覆盖度草地为主要OUVs表征要素,其年平均面积分别占遗产地总面积的29.51%和29.75%。整个遗产地景观则呈散布且复杂化分布特征,斑块密度（PD）、形状指数（LSI）由1992年的2.05个/km²、43.01分别增加到2020年的2.37个/km²、52.02,蔓延度指数（CONTAG）则由58.44降低为56.54。研究发现遗产地水体和沼泽受平均降水量影响最大,r绝对值为0.884、0.929,低覆盖度草地受平均相对湿度影响最大,r绝对值为0.931,说明自然因素是遗产地高寒湿地和高寒草地面积变化的主要因子。人口密度、土壤类型和高程为影响遗产地OUVs关键要素空间分异特征的主要因子,解释力在30%—45%;各因子的交互作用均高于单因子的影响,人口密度与土壤类型组合的解释力最大达47.8%;驱动因子对遗产地OUVs关键要素动态度的影响程度则均不高（最大q值仅为0.106）。巴音布鲁克自然遗产地景观格局变化及其驱动因素研究结果对高山湿地类自然遗产地保护、生态修复及可持续发展等具有重要意义。     

基于GIS的丘陵区耕地景观格局时空演变特征分析

以四川省绵阳市涪城区为例,运用景观格局原理与GIS空间分析方法,分析1996--2009年期间耕地景观时空格局及其演变机理（驱动力）。结果表明：13年间,研究区耕地面积呈急剧减少的趋势,变化率明显高于省内丘陵区平均水平;耕地景观空间格局稳定性逐步降低,格局时空变化的地形分异特征显著;变化趋势受坡度、新增建设用地、人口密度、高程、城镇化水平、GDP、起伏度等负向驱动力与灌溉条件、等级公路水平、土地整理程度等正向驱动力因子共同影响。     

Application of landscape ecology and remote sensing for assessment,monitoring and conservation of biodiversity

Landscape ecology, inter alia, addresses the question as to how altered landscape patterns affect the distribution, persistence, and abundance of a species. Landscape ecology plays an important role in integrating the different scales of biodiversity from habitat patch to biome level. Satellite remote sensing technology with multi-sensor capabilities offers multi-scale information on landscape composition and configuration. Advances in geospatial analytical tools and spatial statistics have improved the capability to quantify spatial heterogeneity. Globally, landscape level characterization of biodiversity has become an important discipline of science. Considering the vast extent, heterogeneity, and ecological and economic importance of forest landscapes, significant efforts have been made in India during the past decade to strengthen landscape level biodiversity characterization. The generic frame work of studies comprises preparation of national databases providing information on composition and configuration of different landscapes using multi-scale remote sensing techniques, understanding the landscape patterns using geospatial models to elicit disturbance and diversity patterns and application of this information for bioprospecting and conservation purposes. Studies on hierarchical linkage of multi-scale information to study the processes of change, landscape function, dynamics of habitat fragmentation, invasion, development of network of conservation areas based on the understanding of multi-species responses to landscape mosaics, macro-ecological studies to understand environment and species richness, habitat and species transitions and losses, landscape level solutions to adaptation and mitigation strategies to climate change are a few of the future challenges. The paper presents the current experiences and, analyses in conjunction with international scenario and identifies future challenges of Indian landscape level biodiversity studies.     

Quantifying spatiotemporal dynamics of agricultural landscapes using remotely sensed data and landscape metrics

This study focuses on the spatiotemporal dynamics of agricultural lands and differences in rapidly developing urban and declining rural counties in Iowa, USA between 1984 and 2000. The study presents an analysis of land-cover maps derived from Landsat TM and ETM+ satellite imagery and different landscape metrics using FRAGSTATS and IDRISI software. The study provides evidence of both loss of croplands and change in fragmentation between 1984 and 2000. Fragmentation in agriculture-dominated areas increased with the development of urban centres and diversification of land uses. Fragmentation of landscapes, including agricultural land, was found to be higher in the urbanized counties, but was stable or even declined over time in these counties. In contrast, in the context of remote rural areas, agricultural landscapes experienced rapid increase in fragmentation and farmland loss. The urban–rural gradient analysis used in this study showed that the highest fragmentation occurred on the city edges. These findings suggest that farmland fragmentation is a complex process associated with socio-economic trends at regional and local scales. In addition, socio-economic determinants of landscape fragmentation differ between areas with diverging development trajectories. Intensive cropland fragmentation in remote agricultural regions, detected by this research, should be further studied and its possible effects on both agricultural productivity and biodiversity should be carefully considered.     

Use of multi-temporal Landsat images for analyzing forest transition in relation to socioeconomic factors and the environment

Recently there have been reports of forest regrowth occurring in different regions across the world. There is also a growing recognition of the potential beneficial impact that secondary forests may have on the global environment: providing crucial ecosystem services such as soil conservation, stabilization of hydrological cycles, carbon sequestration, and support for forest dependent communities. Consequently, there is a growing awareness of the need to recognize that landscapes are complex shifting mosaics wherein forest clearing and reforestation take place. In this study, the rates of reforestation, deforestation, forest regrowth and degradation were measured using multi-temporal Landsat images of Danjiangkou, China. Landsat data from 1990, 1999 and 2007 were (1) classified as dense forest, open forest and non-forest areas and (2) compared between years to identify forest cutting, regeneration and degradation. The results showed that there was a net gain of 29,315 ha of forest area (including dense and open forest) from 1990 to 2007, showing a clear trend of reforestation in the study area. Forest modification (degradation and regrowth) and change categories (deforestation and reforestation) occurred simultaneously during the observation time period. Socioeconomic data from public statistics and environmental attributes allowed the assessment of the socioeconomic factors and the environmental conditions that caused these changes using non-metric multidimensional scaling (NMDS). The research showed that the socioeconomic factors due to different policies were major driving forces of forest transition, whereas environmental attributes of the underlying landscape constrained forest cover changes. These findings have led to a better understanding of forest transition at a local scale in our study region. Comprehensive knowledge of these relationships may be useful to reconstruct past forest transitions and predict future changes, and may help to enhance sustainable management practices aimed at preserving essential ecological functions.     

Urban expansion patterns of 291 Chinese cities, 1990–2015

China has experienced rapid and massive urban expansion in recent decades. To address the opportunities and challenges posed by urbanization, it is important to investigate this process. Although many studies have characterized China’s urbanization, mainly based on individual cities or urban agglomerations, few studies have compared the urban expansion patterns among cities of different regions and sizes at a national scale. Additionally, the source of the newly developed urban land has largely been ignored in previous research. To fill these gaps, we provide a comprehensive view of the growth patterns of 291 Chinese cities during 1990–2015, quantifying the rates, spatial forms, and corresponding landscape characteristics of the urban expansion. More importantly, we further investigate what their new urban land is converted from. Key findings include: (1) the annual expansion (AE) and annual growth rate (AGR) of all 291 cities were 1869.81?km² and 4.81% during 1990–2015; (2) cropland and rural settlements were the predominant source, accounting for 65.22% and 17.49% of the new urban land during 1990–2015; (3) edge-expansion was the dominant growth form for most cities, followed by infilling and leapfrogging growth; and (4) the landscape characteristics of the occupied cropland differed across various cities.     

Diurnal and seasonal impacts of urbanization on the urban thermal environment: A case study of Beijing using MODIS data

Beijing has experienced rapid urbanization and associated urban heat island effects and air pollution. In this study, a contribution index was proposed to explore the effect of urbanization on land surface temperature (LST) using Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived data with high temporal resolution. The analysis indicated that different zones and landscapes make diurnally and seasonally different contributions to the regional thermal environment. The differences in contributions by the three main functional zones resulted from differences in their landscape compositions. The roles of landscapes in this process varied diurnally and seasonally. Urban land was the most important contributor to increases in regional LSTs. The contributions of cropland and forest varied distinctly between daytime and nighttime owing to differences in their thermal inertias. Vegetation had a notable cooling effect as the normalized vegetation difference index (NDVI) increased during summer. However, when the NDVI reached a certain value, the nighttime LST shifted markedly in other seasons. The results suggest that urban design based on vegetation partitions would be effective for regulating the thermal environment.     

Changing landscape in the Three Gorges Reservoir Area of Yangtze River from 1977 to 2005: Land use/land cover,vegetation cover changes estimated using multi-source satellite data

The eco-environment in the Three Gorges Reservoir Area (TGRA) in China has received much attention due to the construction of the Three Gorges Hydropower Station. Land use/land cover changes (LUCC) are a major cause of ecological environmental changes. In this paper, the spatial landscape dynamics from 1978 to 2005 in this area are monitored and recent changes are analyzed, using the Landsat TM (MSS) images of 1978, 1988, 1995, 2000 and 2005. Vegetation cover fractions for a vegetation cover analysis are retrieved from MODIS/Terra imagery from 2000 to 2006, being the period before and after the rising water level of the reservoir. Several analytical indices have been used to analyze spatial and temporal changes. Results indicate that cropland, woodland, and grassland areas reduced continuously over the past 30 years, while river and built-up area increased by 2.79% and 4.45% from 2000 to 2005, respectively. The built-up area increased at the cost of decreased cropland, woodland and grassland. The vegetation cover fraction increased slightly. We conclude that significant changes in land use/land cover have occurred in the Three Gorges Reservoir Area. The main cause is a continuous economic and urban/rural development, followed by environmental management policies after construction of the Three Gorges Dam.     

哈尔滨市景观生态风险时空变化驱动力及分布预测

本文以哈尔滨市为研究对象,首先构建了景观生态风险及预测模型;然后对1998—2018年景观生态风险时空变化驱动力进行分析;最后对研究区域2023年景观生态风险空间分布进行预测。结果表明：①研究区域近20年景观生态风险先降低后升高,空间格局变化较为显著。②道路距离、第二产业、农业、高程为景观生态风险变化主要驱动力。1998—2008年,主城区周围道路距离系数逐年减小,南部地区逐年增高,其他时间内未见明显变化;农业和高程对区域景观生态风险的总体影响显著,存在空间差异;第二产业对区域景观生态风险影响程度呈现先增后降的变化。③预测所得的2023年景观生态风险空间差别不明显,降低区域比升高区域面积大。     

黑河下游土地利用与景观格局时空特征分析

基于研究区1986年LandSat TM和2003年LandSat ETM 遥感影像资料,综合运用遥感与GIS技术手段,结合FRAGSTATS景观格局分析软件,就近17 a来黑河下游额济纳流域土地利用与景观格局变化进行了分析,并探讨了引起变化的驱动因素。结果表明:研究区草地、林地、水域及耕地面积减少,居民工矿建设用地和未利用土地面积显著增加;景观破碎化程度降低,多样性及异质性程度减小,稳定性降低;气候的暖干化趋势、黑河下泄水量的持续减少以及人类不合理的经济活动是黑河下游土地利用和景观格局变化的主要原因。     

Agricultural cropland mapping using black-and-white aerial photography,Object-Based Image Analysis and Random Forests

Land-use and land-cover (LULC) conversions have an important impact on land degradation, erosion and water availability. Information on historical land cover (change) is crucial for studying and modelling land- and ecosystem degradation. During the past decades major LULC conversions occurred in Africa, Southeast Asia and South America as a consequence of a growing population and economy. Most distinct is the conversion of natural vegetation into cropland. Historical LULC information can be derived from satellite imagery, but these only date back until approximately 1972. Before the emergence of satellite imagery, landscapes were monitored by black-and-white (B&W) aerial photography. This photography is often visually interpreted, which is a very time-consuming approach. This study presents an innovative, semi-automated method to map cropland acreage from B&W photography. Cropland acreage was mapped on two study sites in Ethiopia and in The Netherlands. For this purpose we used Geographic Object-Based Image Analysis (GEOBIA) and a Random Forest classification on a set of variables comprising texture, shape, slope, neighbour and spectral information. Overall mapping accuracies attained are 90% and 96% for the two study areas respectively. This mapping method increases the timeline at which historical cropland expansion can be mapped purely from brightness information in B&W photography up to the 1930s, which is beneficial for regions where historical land-use statistics are mostly absent.     

Assessment of carbon in woody plants and soil across a vineyard-woodland landscape

Background

Quantification of ecosystem services, such as carbon (C) storage, can demonstrate the benefits of managing for both production and habitat conservation in agricultural landscapes. In this study, we evaluated C stocks and woody plant diversity across vineyard blocks and adjoining woodland ecosystems (wildlands) for an organic vineyard in northern California. Carbon was measured in soil from 44 one m deep pits, and in aboveground woody biomass from 93 vegetation plots. These data were combined with physical landscape variables to model C stocks using a geographic information system and multivariate linear regression.

Results

Field data showed wildlands to be heterogeneous in both C stocks and woody tree diversity, reflecting the mosaic of several different vegetation types, and storing on average 36.8 Mg C/ha in aboveground woody biomass and 89.3 Mg C/ha in soil. Not surprisingly, vineyard blocks showed less variation in above- and belowground C, with an average of 3.0 and 84.1 Mg C/ha, respectively.

Conclusions

This research demonstrates that vineyards managed with practices that conserve some fraction of adjoining wildlands yield benefits for increasing overall C stocks and species and habitat diversity in integrated agricultural landscapes. For such complex landscapes, high resolution spatial modeling is challenging and requires accurate characterization of the landscape by vegetation type, physical structure, sufficient sampling, and allometric equations that relate tree species to each landscape. Geographic information systems and remote sensing techniques are useful for integrating the above variables into an analysis platform to estimate C stocks in these working landscapes, thereby helping land managers qualify for greenhouse gas mitigation credits. Carbon policy in California, however, shows a lack of focus on C stocks compared to emissions, and on agriculture compared to other sectors. Correcting these policy shortcomings could create incentives for ecosystem service provision, including C storage, as well as encourage better farm stewardship and habitat conservation.

     

Assessment of the image misregistration effects on object-based change detection

High-spatial resolution remote sensing imagery provides unique opportunities for detailed characterization and monitoring of landscape dynamics. To better handle such data sets, change detection using the object-based paradigm, i.e., object-based change detection (OBCD), have demonstrated improved performances over the classic pixel-based paradigm. However, image registration remains a critical pre-process, with new challenges arising, because objects in OBCD are of various sizes and shapes. In this study, we quantified the effects of misregistration on OBCD using high-spatial resolution SPOT 5 imagery (5 m) for three types of landscapes dominated by urban, suburban and rural features, representing diverse geographic objects. The experiments were conducted in four steps: (i) Images were purposely shifted to simulate the misregistration effect. (ii) Image differencing change detection was employed to generate difference images with all the image-objects projected to a feature space consisting of both spectral and texture variables. (iii) The changes were extracted using the Mahalanobis distance and a change ratio. (iv) The results were compared to the ‘real’ changes from the image pairs that contained no purposely introduced registration error. A pixel-based change detection method using similar steps was also developed for comparisons. Results indicate that misregistration had a relatively low impact on object size and shape for most areas. When the landscape is comprised of small mean object sizes (e.g., in urban and suburban areas), the mean size of ‘change’ objects was smaller than the mean of all objects and their size discrepancy became larger with the decrease in object size. Compared to the results using the pixel-based paradigm, OBCD was less sensitive to the misregistration effect, and the sensitivity further decreased with an increase in local mean object size. However, high-spatial resolution images typically have higher spectral variability within neighboring pixels than the relatively low resolution datasets. As a result, accurate image registration remains crucial to change detection even if an object-based approach is used.     

基于多源国产高分卫星时空信息的米级分辨率耕地提取

及时准确地获取耕地空间分布数据对于农业生产管理、产量估算、种植结构调整等具有重要意义。目前的耕地提取多基于多时相中低分辨率影像或单时相高分辨率影像,难以满足耕地破碎,农作物种植模式复杂的区域精度需求。基于此,本研究通过协同国产高分一号（GF-1）、高分二号（GF-2）和高分六号（GF-6）卫星影像,探索米级分辨率尺度下的耕地高精度提取方法。该方法以深度神经网络UNet为基础,通过协同GF-1/6的多时相优势和GF-2影像的高空间分辨率构建了CEUNet（Cropland Extraction UNet）模型,以充分挖掘耕地的时相特征和空间几何特征。同时,将基于CEUNet模型提取的米级耕地结果分别与基于UNet和多源不同分辨率遥感影像的语义分割（UNet_m）、基于UNet和单时相高分辨率影像的语义分割（UNet_s）、基于对象的随机森林分类（OBIA）、基于像元的随机森林分类（RF）提取的耕地结果展开对比,分析所提出的方法在不同区域的适宜性。结果表明,基于CEUNet模型提取的米级耕地总体精度达到92.92%,且基于CEUNet提取的耕地的逐像元验证结果在平均F1-Score值上相较于基于对象和基于像元的随机森林分类分别提升了0.21和0.21,相较于UNet_m和UNet_s分别提升了0.04和0.11,其中针对地块破碎,景观异质性高等区域,CEUNet相较于UNet_m和UNet_s提升了0.09和0.26。本研究提出的CEUNet模型能够充分发挥多源国产高分卫星数据的空间和时间优势,两者结合能够快速、高效地提取不同农业景观及不同种植模式的耕地空间分布信息。     

Assessing the ecological vulnerability of forest landscape to agricultural frontier expansion in the Central Highlands of Vietnam

Forest conservation in human-dominated tropical landscapes ensures provision of major ecosystem services. However, conservation goals are threatened by growing demands for agricultural products. As the expansion of agricultural frontiers continues to exert increasing pressure on forest cover, it is crucial to provide indicators on forest vulnerability to improve our understanding of forest dynamics and prioritize management actions by local decision-makers. The purpose of this study is to develop a rigorous methodological framework to assess forest ecological vulnerability. We aim at evaluating the potential of remote sensing to characterize forest landscape dynamics in spatial and temporal dimensions. We present an innovative method that spatially integrates current landscape mosaic mapping with 45 years of landscape trajectories using Sentinel-2 and Landsat imagery. We derive indicators of exposure to cropland expansion, sensitivity linked with forest degradation and fragmentation, and forest capacity to respond based on forest landscape composition in Di Linh district in the Central Highlands of Vietnam. We map current forest-agricultural mosaics with high accuracy to assess landscape intensification (kappa index = 0.78). We also map the expansion of the agricultural frontier and highlighted heterogeneous agricultural encroachment on forested areas (kappa index = 0.72-0.93). Finally, we identify degradation and fragmentation trajectories that affect forest cover at different rates and intensity. Combined, these indicators pinpoint hotspots of forest vulnerability. This study provides tailored management responses and levers for action by local decision makers. The accessibility of multi-dimensional remote sensing data and the developed landscape approach open promising perspectives for continuously monitoring agricultural frontiers.     

Studying Changes in Land Use Within the Poyang Lake Region

Poyang Lake is the largest freshwater lake in China. Because the lake is faced with a series of ecological and environmental problems, it is important and necessary to study the land use changes in the Poyang Lake region. In this study, Landsat images from 1976, 1989, 1999 and 2009, were used along with other evaluation methods (quantitative analysis of changes in land use, land use dynamic, degree and transfer matrix analyses) to investigate the changes in land use within the Poyang Lake region from 1976 to 2009. Land use was classified into seven types: cropland, woodland, grassland, the water body, construction land, bottomland and unused land. Areas of cropland, bottomland and the water body were decreasing although the area of the water body decreased relatively slowly. However, areas of construction land, grassland, woodland and unused land increased to a certain extent, with unused land increasing the most rapidly given its smaller proportion compared to the other types. All land types in the study region had different levels of conversion between other types of land. As a whole, the decrease in cropland and the increase in construction land, woodland and grassland were caused by human activities and the conservation policies such as Grain-for-Green and “returning farm to lake”. However, the decrease in the water body area was mainly influenced by natural factors and human activities. Changes in the area of bottomland were mainly influenced by water levels and human farming activities.