1990~2015年吉林省西部耕地变化与“旱改水”时空特征研究

以Landsat遥感影像为数据源，利用面向对象和决策树方法获得多期土地覆被数据；以此为基础，分析了1990~2015年吉林省西部耕地变化与旱田水田转化特征及驱动因素。结果表明：1990~2015年期间，吉林省西部耕地面积增加了2159.33 km²，增速逐渐变缓。旱田面积在1990~2000和2000~2010年期间有小幅增加，但在2010~2015年期间呈减少趋势。水田面积持续扩张，25年间增加了1139.39 km²（51.7%），旱田净转化为水田的面积不断增加，1990~2000年为69.13 km²，2000~2010年为156.19 km²，2010~2015年为288.27 km²。人口和经济的增长是导致耕地面积迅速增长的主要原因，影响水田面积扩张和旱田向水田转化的驱动因素有：科技进步、水利设施建设、政策倾向和利益驱动。最后提出了吉林省西部地区耕地保护的建议，为区域农业生产和生态建设提供科学借鉴。     

1990~2015年吉林省西部耕地变化与“旱改水”时空特征研究

以Landsat遥感影像为数据源,利用面向对象和决策树方法获得多期土地覆被数据;以此为基础,分析了1990~2015年吉林省西部耕地变化与旱田水田转化特征及驱动因素。结果表明：1990~2015年期间,吉林省西部耕地面积增加了2159.33 km²,增速逐渐变缓。旱田面积在1990~2000和2000~2010年期间有小幅增加,但在2010~2015年期间呈减少趋势。水田面积持续扩张,25年间增加了1139.39 km²（51.7%）,旱田净转化为水田的面积不断增加,1990~2000年为69.13 km²,2000~2010年为156.19 km²,2010~2015年为288.27 km²。人口和经济的增长是导致耕地面积迅速增长的主要原因,影响水田面积扩张和旱田向水田转化的驱动因素有：科技进步、水利设施建设、政策倾向和利益驱动。最后提出了吉林省西部地区耕地保护的建议,为区域农业生产和生态建设提供科学借鉴。     

Validation and comparison of 1 km global land cover products in China

Four 1 km global land cover products are currently available to the scientific community: the University of Maryland (UMD) global land cover product, the International Geosphere–Biosphere Programme Data and Information System Cover (IGBP‐DISCover), the MODerate resolution Imaging Spectrometer (MODIS) global land cover product and Global Land Cover 2000 (GLC2000). Because of differences in data sources, temporal scales, classification systems and methodologies, it is important to compare and validate these global maps before using them for a variety of studies at regional to global scales. This study aimed to perform the validation and comparison of the four global land cover datasets, and to examine the suitability and accuracy of different coarse spatial resolution datasets in mapping and monitoring cropland across China. To meet this objective, we compared the four global land cover products with the National Land Cover Dataset 2000 (NLCD‐2000) at three scales to evaluate the accuracy of estimates of aggregated cropland areas in China. This was followed by a spatial comparison to assess the accuracies of the four products in estimating the spatial distribution of cropland across China. A comparative analysis showed that there are varying levels of apparent discrepancies in estimating the cropland of China between these four global land cover datasets, and that both area totals and spatial (dis)agreement between them vary from region to region. Among these, the MODIS dataset has the best fit in depicting China's croplands. The coarse spatial resolution and the per pixel classification approach, as well as landscape heterogeneity, are the main reasons for the large discrepancies between the global land cover datasets tested and the reference data.     

Agricultural land-use change in Brazilian Amazônia between 1980 and 1995: Evidence from integrated satellite and census data

As cropland and pasture have replaced forest and cerrado in Brazilian Amazônia, concern has mounted over the effects of changing the biogeochemical and hydrological properties of one of the world's great storehouses of biomass and biodiversity. Although much recent effort has focused on the location, effects, and causes of deforestation and cerrado conversion, much less is known about the basin-wide spatial distribution and density of the land use following conversion for crops or pasture.In this paper, we use census and satellite records to develop maps of the distribution and abundance of major agricultural land uses across 4.5×10⁸ ha of Brazilian Amazônia in 1980 and 1995. Results indicate an overall expansion of 7.0×10⁶ ha in total agricultural area in Brazilian Amazônia between 1980 and 1995. The net change during this period is estimated for three different land-use types: croplands (an increase of 0.8×10⁶ ha), natural pastures (a decrease of 8.4×10⁶ ha), and planted pastures (an increase of 14.7×10⁶ ha). These estimates, the first spatially explicit quantifications of agricultural land-use activities in 1980 and 1995 across Brazilian Amazônia, are shown to be consistent with the results of applying a land use change and secondary regrowth model to published deforestation rates for the period.The resulting time slices, presented for each land-use category at 5-min (∼9 km) spatial resolution, allow for the quantification of land-use changes in this region for biogeochemical, demographic and economic models. Several foci of agricultural change existed within Brazilian Amazônia during this period: in the state of Pará, cropland was lost and planted pasture increased markedly; in Mato Grosso, both cropland and planted pasture increased; in Rondônia, planted pasture replacing forest was the primary route to agricultural expansion.     

基于RS和GIS的黄河下游沿岸县域土地利用与景观格局演变的驱动力研究 ——以河南省封丘县为例

以位于黄河下游沿岸的河南省封丘县为研究区域,通过遥感影像解译、地理信息系统和景观格局计算软件,分析了该区域1990、2000年土地利用和景观格局的变化特征,运用典型相关分析方法,找出土地利用和景观格局变化的驱动因子,结果如下：研究期间居民点与建设用地增加2 934.87 hm2,其它类型用地减少,尤其是旱地、水体分别减少1 084.81 hm2、1 717.92 hm2;以种植业用地为基质（旱地、水田用地比例之和近80%）的农业景观较为稳定,但农业结构单一、景观多样性较低;人口数量、粮食生产、对优越生活条件的追求等农业社会经济条件的变化是研究区土地利用与景观格局演变的驱动因子。     

Land-use change analysis in Yulin prefecture,northwestern China using remote sensing and GIS

Rapid land-use change has taken place in many arid and semi-arid regions of China such as Yulin prefecture over the last decade due to rehabilitation measures. In this paper, land-use change dynamics were investigated by the combined use of satellite remote sensing and geographical information systems (GIS). Our objectives were to determine land-use transition rates among land-use types in Yulin prefecture over 14 years from 1986-2000 and to quantify the changes of various landscape metrics using FRAGSTATS, the spatial pattern analysis program for Categorical Maps. Using 30-m resolution Landsat Thematic Mapper (TM) data from the Institute of Remote Sensing Application (IRSA) in China, we classified images into six land-use types: cropland, forestland, grassland, water, urban and/or built-up land, and barren land. Significant changes in land-use occurred within the area over the study period. The results show the significant decrease in barren land was mainly due to conversion to grassland. Cropland increased by 3.39%, associated with conversions from grassland and barren land. The landscape has become more continuous, clumped and more homogeneous. The study demonstrates that the integration of satellite remote sensing and GIS was an effective approach for analysing the direction, rate and spatial pattern of land-use change.     

Landscape evolution in the Yellow River Basin using satellite remote sensing and GIS during the past decade

Over the past decade, rapid landscape pattern change has taken place in many arid and semi-arid regions of China, such as the Yellow River Basin. In this paper, landscape evolution was investigated by the combined use of satellite remote sensing, geographic information system (GIS) and landscape modelling technologies. The aim was to improve our understanding of landscape changes so that sustainable land use could be established. First, the changes in various landscape metrics were analysed using the landscape structure analysis programme. Second, the mathematical methodology was explored and developed for landscape pattern change, which included: the status and trends change model for individual landscape types, the 1-km² area percentage data model and the transition matrix of landscape types. The results show that the area of the Yellow River Basin was about 794 000 km² during the period from 1990 to 2000; cropland, built-up land and unused land expanded significantly whereas woodland, grassland and water bodies contracted substantially. The area of cropland increased dramatically by 2817 km², and the areas of grassland and woodland decreased by 4669 and 33 km², respectively. Meanwhile, the landscape pattern in the study area also experienced numerous changes over the past decade. The major factors that caused the landscape changes in this area over the past decade were found to be governmental policies for environmental protection, population growth, and meteorological and environmental conditions.     

Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security,determined using MODIS 250 m time-series data and spectral matching techniques,in the Krishna River basin (India)

The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km² (26 575 200 ha), comparing a water-surplus year (2000–2001) and a water-deficit year (2002–2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61–100% for various land‐use classes and 61–81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R ²-values between 0.82 and 0.86.

The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002–2003) when compared with the water-surplus year (2000–2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.     

Land surface phenology dynamics and climate variations in the North East China Transect (NECT), 1982–2000

Land surface phenology dynamics reflect the response of the Earth's biosphere to inter‐ and intra‐annual dynamics of the Earth's climate and hydrologic regimes. Investigations of land surface phenology dynamics and its relation to long‐term climate variation could help us to detect the response of regional vegetation to climate variation. The present study developed a new algorithm for detecting regional land surface phenology dynamics (ARLSPD) and demonstrated it in detecting the vegetation response to inter‐annual climate variability in the North East China Transect (NECT), a mid‐latitude semi‐arid terrestrial transect with strong gradients in environmental conditions and vegetation formations. The spatial–temporal patterns of greenup‐onset date, maturity date, and senescence date during the period of 1982–2000 are presented. The resultant spatial–temporal patterns of land surface phenology were quite consistent with the land‐cover characteristics, moisture, and temperature gradients. The relations between inter‐annual variations in phenology and seasonal climate were investigated. It was found that besides human disturbance, land surface phenology depended primarily on the combined effects of preseason temperature and precipitation. The relative influence of preseason temperature and precipitation on land surface phenology was changing, which led to the different responses of land surface dynamics to climate variation along the moisture gradient in the NECT. In the arid and semi‐arid region of NECT, the dates of onset for phonological events in temperate typical grassland were most significantly related to the precipitation during the preceding 2–4 months. Temperature‐induced drought stress during the preceding months could delay greenup onset in cropland/grassland mosaic, and advance senescence in temporal typical grassland, and in cropland/grassland mosaic. The regional phenology algorithm, theoretically also applicable for complex ecosystems characterized by annual multiple growth cycles, is expected to couple with large‐scale biogeochemical models to regulate dynamically land surface phenology.     

Scene selection and the use of NASA's global orthorectified Landsat dataset for land cover and land use change monitoring

This study examines the utility of NASA's circa 1990 and circa 2000 global orthorectified Landsat dataset for land cover and land use change mapping and monitoring across Africa. This is achieved by comparing the temporal and spatial variation of NDVI, measured independently by the NOAA-AVHRR at the time of Landsat scene acquisition, against the seasonal mean for each Landsat scene extent. Decadal sequences of drift-corrected NOAA-AVHRR imagery were used to calculate NDVI means and standard deviations for the periods covered by the scenes composing the c.1990 and c.2000 Landsat datasets. The specific NOAA-AVHRR NDVI values at the acquisition date of each individual Landsat scene were also calculated and the differences, both from the mean and scaled by standard deviation, were mapped for the Landsat scene footprints in the c.1990 and c.2000 datasets. The resulting maps show the temporal position of each Landsat scene within the seasonal NDVI cycle, and provide a valuable guide to assist in quantifying uncertainty and interpreting land cover and land use changes inferred from these Landsat data.     

Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data

A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI VGT =(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI VGT ) and NDWI VGT . The NDWI VGT temporal dynamics were sensitive enough to capture the substantial increases of surface water due to flooding and rice transplanting at paddy rice fields. A land use thematic map for the timing and location of flooding and rice transplanting was generated for the study area. Our results indicate that NDWI and NDVI temporal anomalies may provide a simple and effective tool for detection of flooding and rice transplanting across the landscape.     

基于遥感与GIS的黄土丘陵半干旱区土地利用定量化研究-以中国定西县为例

研究区域为典型的黄土丘陵沟壑半干旱区,以中国定西县为例。从1990年和2000年的Landsat TM影像图中提取两个时段的土地利用图,包括9种土地利用类型。从1∶10万的等高线数据中提取坡度数据。参考景观生态指标,我们选择或修改了10个指标实现定量化土地利用特征,动态监测土地利用变化,并分析地形与土地利用和土地利用变化的关系及土地利用变化与政府政策之间的关系。结果表明:①所选择的指标可以量化中国典型的黄土丘陵半干旱区土地利用及其变化特征,当转移矩阵采用不同的基数,可以体现不同的转换的量的特征;②土地利用与土地利用变化在不同坡度的空间分布上有很好的规律性;③政府政策是土地利用变化的主要驱动力因素,包括梯田改造、集雨工程和退耕还林还草。     

The change of land cover and land use and its impact factors in upriver key regions of the Yellow River

Owing to the influence of global change, land cover and land use have changed significantly over the last decade in the cold and arid regions of China, such as Madoi County which is located in the source area of the Yellow River. In this paper, land‐use/cover change and landscape dynamics are investigated using satellite remote sensing (RS) and a geographical information system (GIS). The objectives of this paper are to determine land‐use/cover transition rates between different cover types in the Madoi County over 10 years e.g., from 1990 to 2000. Second, the changes of landscape metrics using various indices and models are quantified. The impact factors of LUCC (Land‐Use land cover Change) are systematically identified by integrating remote sensing as well as statistical data, including climate, frozen soil, hydrological data and the socio‐economic data. Using 30 m×30 m spatial resolution Landsat (Enhanced) Thematic Mapper (TM/ETM+) data in our study area, nine land cover classes can be discriminated. Our results show that Grassland, Marshes and Water Bodies decrease notably, while oppositely, Sands ‐ Gobi and Barren land increase significantly. The number of lakes with an acreage larger than six hectares decreased from 405 in 1990 to 261 in 2000. Numerous small lakes dried out. The area of grassland with a high cover fraction decreased as well, while the surface area of grassland with a medium level of cover fraction increased. The medium cover fraction grassland mainly originates from high cover fraction grassland. The desertification of land is a serious issue. (ii) The inter‐transformations between Grasslands, Barren Land, Sands, Gobi, Water Bodies and Marshes are remarkable. The Shannon–Weaver Diversity Index (SWDI), the Evenness Index (EI) and the extent of Landscape Heterogeneity (LH) has improved. Marshes have become more fragmented hence, with less connected patches. (iii) In the recent 30 years, average annual temperature, the power of evaporation and the index of dryness did increase significantly. Moreover, soil moisture content (SMC) decreased and the drought trend accelerated. The degradation of frozen soil has impacted on the decrease of surface water area and induced a drop in groundwater levels. Monitoring LUCC in sensitive regions would not only benefit from a study of vulnerable ecosystems in cold and high altitude regions, but would provide scientifically based decision‐making tools for local governments as well.     

缅甸土地覆被遥感制图和空间格局分析

在“一带一路”倡议框架下,中缅经济走廊逐步从概念转入实质规划建设阶段,了解和掌握缅甸土地覆被的空间格局和分布特征对于合理开发利用资源、制定务实的经济廊道建设规划具有重要的战略意义。利用Landsat-8 OLI遥感影像数据,基于多分类器集成的面向对象迭代分类方法（OIC-MCE）,生产了缅甸2015年30 m分辨率土地覆被产品（MyanmarLC-2015）。采用Google Earth高分辨率影像获取验证样本用于产品精度验证,验证结果表明：MyanmarLC-2015产品的总体分类精度为89.05%,Kappa系数为0.87,各类别的用户精度和制图精度均超过72%,能够准确地反映缅甸土地覆被类型的空间格局。根据产品统计,林地是缅甸面积最大的土地覆被类型,占国土面积56.15%,以常绿阔叶林为主,占林地面积83.57%。耕地面积次之,占国土面积27.01%。地形因子对缅甸土地覆被类型空间分布格局有显著的影响,随着海拔升高,呈现出按如下顺序的垂直地带性特征：森林湿地、水田、旱地、落叶灌木林、落叶阔叶林、常绿灌木林、常绿阔叶林、常绿针叶林。从植被生产力的角度来看,缅甸东部、东北部和东南部植...     

三江平原洪河自然保护区及周边地区湿地景观变化过程研究

选取我国东北地区三江平原腹地洪河国家级自然保护区及周边的3个农场作为研究区,选取1975年、1989年和2006年3个不同历史时段的研究区遥感影像,通过高精度影像的支持,应用遥感目视解译方法,提取出研究区沼泽、河流泡沼、林地、水田、旱地及其它地物类型共6种地类景观30 a来的历史变化信息。在地理信息系统方法支持下,定量分析了研究区从20世纪70年代中期单一的沼泽湿地景观随着当地农业发展逐步成为当前以农田景观为主的过程。研究表明,研究区湿地景观变化过程明显,在此过程中还伴随着水田与旱田景观结构剧烈变化,并且呈现出不同的区域内部景观变化发展过程。其中,开发最早、受人类活动影响最明显的前锋农场,沼泽湿地面积减少最多;鸭绿河农场的沼泽湿地面积减少速度最快;而洪河自然保护区由于生境栖息地狭小,尽管受到严格保护,在周边农场外部影响下还是出现了一定程度的沼泽湿地萎缩现象。     

Modeling different urban change trajectories and their trade-offs with food production in Jiangsu Province,China

Urban areas in China have expanded rapidly in recent decades, which mainly resulted in the conversion of fertile cropland. As the growth of urban areas is likely to continue in the next decades, there is a need for detailed assessments of urbanization impacts on food production. However, most land use models cannot simulate different types of urban change trajectories, such as expansion and densification, which constrains their capacity to inform such assessments with sufficient detail on the patterns of urbanization. In this paper, we present a land use model that represents multiple types of settlements, which allows to simulate multiple different urban change trajectories. We applied this model to Jiangsu Province, China, and assess the impact of projected urban development between 2015 and 2030 on cropland area and crop production. Results show that population growth is accommodated by different urban change trajectories, depending on the absence or presence of land use policies to maintain food security. In the absence of policies, population growth mainly leads to urban expansion, yielding losses in both cropland area and crop production. Implementing strict cropland protection policies leads to more urban densification and all population can be accommodated without a net loss of cropland. Yet, crop production decreases in this scenario as the most productive croplands are still converted and compensated by less productive areas. Protecting crop production instead leads to a small loss in cropland area combined with cropland intensification and different types of urban change, but maintains the total crop production. These results show the relevance of more nuanced representation of urban development in land use models in order to inform land use policies.     

Scene selection and the use of NASA's global orthorectified Landsat dataset for land cover and land use change monitoring

This study examines the utility of NASA's circa 1990 and circa 2000 global orthorectified Landsat dataset for land cover and land use change mapping and monitoring across Africa. This is achieved by comparing the temporal and spatial variation of NDVI, measured independently by the NOAA‐AVHRR at the time of Landsat scene acquisition, against the seasonal mean for each Landsat scene extent. Decadal sequences of drift‐corrected NOAA‐AVHRR imagery were used to calculate NDVI means and standard deviations for the periods covered by the scenes composing the c.1990 and c.2000 Landsat datasets. The specific NOAA‐AVHRR NDVI values at the acquisition date of each individual Landsat scene were also calculated and the differences, both from the mean and scaled by standard deviation, were mapped for the Landsat scene footprints in the c.1990 and c.2000 datasets. The resulting maps show the temporal position of each Landsat scene within the seasonal NDVI cycle, and provide a valuable guide to assist in quantifying uncertainty and interpreting land cover and land use changes inferred from these Landsat data.     

基于遥感和GIS的东亚土地覆盖年际变化研究

土地覆盖的年际变化是以土地覆盖的宏观分布模式为基准，在外界驱动因子的作用下发生的年与年之间的变化，因此，为揭示东亚地区土地覆盖的年际变化特征，首先选取东亚地区时相一致的不同空间分辨率（1km和8km)的NDVI影像进行了非监督分类，并总结了东亚土地覆盖的宏观分布模式，然后以时间序列的8kmAVHRRNDVI数字影像为基础，应用跨平百分率分析方法生成每年5-9月距平百分率分级影像，并以该影像为基础分析总结了东亚土地覆盖的年际变化特征，结果显示，该方法及其揭示的现象比较客观地反映了东亚土地覆盖年际变化特征。     

基于遥感与GIS的北京市土地利用动态演化模式研究

将土地利用动态变化模型与景观生态学景观格局模型相结合，在1988－2000年北京市遥感数据的基础上，分析了北京市土地利用动态变化模式。研究表明，地形条件对北京市土地利用类型的形成及土寺利用动态变化具有重要影响。在平原地区，农田、城乡居民点及独立工矿用地居于主导地位，土地利用动态变化主要表现为城乡居民点扩展占用耕地及生态退耕。在台地、丘陵和山地地区，林地、草地等自然景观居于主导地位，土地利用动态变化主要表现为生态退耕。北京市土寺利用格局的动态变化表现了城市化、工业化高速发展与退耕还林等生态建设政策实施对土地利用空间格局产生的影响。自然景观增加，景观多样性半加。在自然景观中，林地面积增加，破碎度减小，斑块边界趋于平滑；草地面积减少，趋于破碎。在人文景观中，城镇、农村居民点斑块增大，趋于紧凑，有利于用地节约。农田受到城镇农村居民点扩展及退耕还林政策的双重影响，面积大量减少，破碎度增加。     

An analysis of land use/cover change in Indonesia

The phenomena of land use/ change were evaluated by using a remote sensing approach in a case study in Yogyakarta, Indonesia. The index of changes, which was calculated by the superimposition of land use/ images of 1972, 1984, and land use maps of 1990, were introduced to analyse the pattern of change in the area. The results demonstrated that the pattern of land use/ change in the study area was that of paddy coverage to open/ land to settlement. The annual growth ratios of new settlements to absorb paddy coverage, mixed vegetation, and open/ land were 16 per cent, 20 per cent, and 64 per cent respectively. The larger the percentage of the paddy coverage, the higher the tendency for settlement growth to absorb the paddy coverage, and the larger the percentage of open/ land, the higher the tendency for settlement growth to absorb open/ land. Settlement growth had a high correlation with road accessibility. The highest settlement growth was distributed mostly in suburban areas between 200 and 400 m from secondary roads. Without intelligent intervention by the government and public awareness, the loss of these agricultural land cannot be stopped and will jeopardize the local and regional economy.