Impacts of land use and fire on the loss and degradation of lowland forest in 1983–2000 in East Kutai District, East Kalimantan, Indonesia

Deforestation and forest degradation are proceeding rapidly in the lowland forests of Indonesian Borneo. Time series analysis of satellite imagery provides an ideal means of quantifying landscape change and identifying the pathways which lead to the changes. This study investigates the forest and land cover changes by classifying Landsat MSS (Multispectral Scanner), TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) images over three time periods (1983–90, 1990–98, and 1998–2000), creating land cover maps for each year and change trajectories for each year-pair. The study area chosen covers an area of 2160 km² of undulating topography and alluvial plains in the East Kutai District of East Kalimantan Province, which in the 1980s was covered mostly with lowland dipterocarp forest; today the landscape is a patchwork dominated by oil palm and timber plantations and degraded forest. We relate land cover change data to land use allocation and to fire impacts based on fire hotspot distribution and fire damage information. The multidate land cover change trajectories provide an insight into the forest loss and degradation pathways over the 17-year period spanning the first entry of commercial logging concessionaires, followed by a government-sponsored transmigration scheme, government-licensed timber and oil palm plantations and, finally, the devastating fires of 1998. The results show a mean deforestation rate of 42 km² or 6 per cent per year for 1983–2000, rising to 10 per cent per year for 1990–98; by 2000, 70 per cent of forest initially damaged by fire and drought during the 1982–83 El Niño event was classified as non-forest. Although our study area is perhaps a worst-case scenario in terms of land use planning outcomes, the lessons from this research are directly applicable to scenario prediction for informed forest and land use planning and monitoring.     

SPATIO-TEMPORAL ASPECTS OF LAND USE AND LAND COVER CHANGES IN THE NIAH CATCHMENT, SARAWAK, MALAYSIA

This paper focuses on the large‐scale land use and land cover changes that have taken place in Sarawak state, East Malaysia over the three decades of 1972‐2002. Results are presented from a detailed land use and cover change (LUCC) study in the Niah River catchment using satellite imagery, questionnaire surveys and interviews. Successive waves of land cover changes have taken place. Large forest areas have been logged and gradually replaced by oil palm plantations, which now occupy more than 40 per cent of the total land area in the catchment. Concurrently, small‐scale farming systems have also changed. Formerly dominant Iban shifting cultivation practices are increasingly being replaced by cash crop production on permanent fields and impacted by off‐farm activities involving many ethnic groups. It is argued that land cover changes are continuous and complex processes involving a large number of variables which can be analysed for different time periods at various scales.     

Utility of Landsat 7 satellite data for continued monitoring of forest cover change in protected areas in Southeast Asia

Satellite instruments, particularly the Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) series of sensors, are important tools in the interdisciplinary study of tropical forests that are increasingly integrated into studies that monitor changes in vegetation cover within tropical forests and tropical protected areas, and also applied with other types of data to investigate the drivers of land cover change. However, further advances in the use of Landsat to study and monitor tropical forests and protected areas are threatened by the scan line corrector failure on the ETM+ sensor, as well as uncertainty about the continuity of the Landsat mission. Given these problems, this paper illustrates how ETM+ data were used in an interdisciplinary study that effectively monitored forest cover change in Gunung Palung National Park in West Kalimantan, Indonesian Borneo. Following 31 May 2003, when the ETM+ sensor's scan line corrector failed, we analysed how this failure impedes our ability to perform a similar study from this date onwards. This analysis uses six simulated post-scan line corrector failure (SLC-off) images and reveals that data gaps caused by SLC-off introduce maximum errors of 1.47 per cent and 4.04 per cent in estimates of forest cover and rates of forest loss, respectively. The analysis also demonstrates how SLC-off has transformed ETM+ data from a complete inventory dataset to a statistical sample with variable sample fraction, and notes how this data loss will confound the use of Landsat data to model land cover change in a spatially explicit manner. We discuss potential limited uses of SLC-off data and suggest alternative sensors that may provide essential remotely sensed data for monitoring tropical forests in Southeast Asia.     

基于越南遥感时间序列数据的湄公河三角洲土地利用及河岸变化检测研究

通过采用先进的遥感技术,基于光学和雷达时间序列卫星影像（陆地卫星,SPOT和雷达卫星）,本文对金瓯半岛（位于湄公河三角洲南部）土地覆被变化及湄公河河岸侵蚀情况进行了检测研究。鉴于金瓯半岛典型的土地覆被类型为红树林,通过对1973-2008年红树林遥感影像分析发现,近年来红树林林地面积急剧下降,超过一半的红树林已经转变为虾养殖场。与此同时,检测发现湄公河河岸已经被严重侵蚀,且侵蚀趋势正加速恶化。具体而言,田河和口河的左右两岸被认为是遭受严重侵蚀的热点区域。本文以1966-1968年地形图作为基准线数据,与1989-2009年卫星影像数据进行比照分析,此外采用数字海岸线分析系统（DSAS）模型对未来变化趋势进行了预测。     

基于MODIS 数据的长江三角洲地区土地覆盖分类

长江三角洲地区是我国经济最发达的地区之一, 人类活动对自然环境产生了很大影响。为了研究该地区人类活动与生态环境的相互作用, 利用250 m 分辨率MODIS 数据进行土地 覆盖制图研究, 采用的主要数据为增强型植被指数EVI 数据、反射率数据和DEM 数据。通过基于时间序列的滤波方法消除EVI 的噪声, 通过PCA 变换压缩数据量, 并计算均质度来表征空间维的纹理信息, 构造了一个综合性的分类数据矩阵, 依据高分辨率影像选取了训练区, 采用最大似然法进行分类, 并采用缓冲区分析技术进行分类修正, 得到长江三角洲地区的土地覆盖分类结果。利用高分辨率影像解译信息对分类结果进行了精度评价, 并将分类结果与 MODIS 土地覆盖产品进行了对比, 精度分析表明分类结果很好的反映了研究区的土地覆盖信息, 显示了本研究分类方法与技术处理在实践中的可行性及250 m 分辨率EVI 时间序列数据在区域尺度土地覆盖分类方面的优势与潜力。     

Trends of tropical deforestation in Southeast Mexico

We assessed deforestation in Southeast Mexico (a surface area of 29 000 km² in seven states) through the comparison of land use/land cover maps at a scale of 1:250 000. This facilitated mapping of the land use/land cover change (LULCC) processes and calculation of the rates of change and the change matrix for the period 1978–2000. An original method was used to assess the accuracy of the LULCC map. The verification sites were selected through a stratified random sampling and were corroborated with aerial photographs for 1978 and 2000. Error matrices were elaborated using both hard and fuzzy set approaches in order to take into account the errors related to generalization of the map in fragmented landscapes. The results showed an average annual deforestation rate of 1.1 per cent which represents an average annual loss of 190 000 ha of forest, or an estimated total reduction of 4.2 million ha over 22 years. Furthermore, deforestation processes are concentrated in some areas such as Yucatan and Chiapas states, which registered major forest conversions to grassland and slash‐burning. The overall accuracy of the LULCC map, assessed with hard and fuzzy set approaches, was 72 per cent and 88 per cent respectively.     

基于Landsat 8 OLI数据与面向对象分类的昆嵛山地区土地覆盖信息提取

利用2015年Landsat 8 OLI遥感影像和DEM作为分类数据源,结合野外调查数据,采用面向对象的分类方法对昆嵛山地区土地覆盖信息进行提取,并对分类结果进行精度评价与比较分析。研究表明：面向对象分类方法提取的各地类连续且边界清晰,分类效果与实际情况基本吻合。昆嵛山地区占主导地位的土地覆盖类型是针叶林,面积为1 546.81 km²。研究区土地覆盖分类的总体精度和Kappa系数分别为91.5%和0.88,其中针叶林、草地、水体和建设用地的生产者精度均达到87%以上。相对于监督分类方法,本研究提出的土地覆盖信息提取方法的总体分类精度和Kappa系数分别提高14.7%和0.17。基于面向对象的中分辨率遥感影像,能够获取较高精度的土地覆盖信息,为大范围土地覆盖分类研究提供方法参考。     

Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization

This study evaluates land use/cover changes and urban expansion in Greater Dhaka, Bangladesh, between 1975 and 2003 using satellite images and socio-economic data. Spatial and temporal dynamics of land use/cover changes were quantified using three Landsat images, a supervised classification algorithm and the post-classification change detection technique in GIS. Accuracy of the Landsat-derived land use/cover maps ranged from 85 to 90%. The analysis revealed that substantial growth of built-up areas in Greater Dhaka over the study period resulted significant decrease in the area of water bodies, cultivated land, vegetation and wetlands. Urban land expansion has been largely driven by elevation, population growth and economic development. Rapid urban expansion through infilling of low-lying areas and clearing of vegetation resulted in a wide range of environmental impacts, including habitat quality. As reliable and current data are lacking for Bangladesh, the land use maps produced in this study will contribute to both the development of sustainable urban land use planning decisions and also for forecasting possible future changes in growth patterns.     

Carbon stock of oil palm plantations and tropical forests in Malaysia: A review

In Malaysia, the main land change process is the establishment of oil palm plantations on logged‐over forests and areas used for shifting cultivation, which is the traditional farming system. While standing carbon stocks of old‐growth forest have been the focus of many studies, this is less the case for Malaysian fallow systems and oil palm plantations. Here, we collate and analyse Malaysian datasets on total carbon stocks for both above‐ and below‐ground biomass. We review the current knowledge on standing carbon stocks of 1) different forest ecosystems, 2) areas subject to shifting cultivation (fallow forests) and 3) oil palm plantations. The forest ecosystems are classified by successional stage and edaphic conditions and represent samples along a forest succession continuum spanning pioneer species in shifting cultivation fallows to climax vegetation in old‐growth forests. Total carbon stocks in tropical forests range from 4 to 384 Mg C/ha, significantly wider than the range of total carbon stocks of oil palm plantations, 2 to 60 Mg C/ha. Conversion of old‐growth forest areas to oil palm plantations leads to substantial reduction in carbon storage, while conversion of forest fallows to oil palm plantations may sustain or even increase the standing carbon stock.     

Accuracy assessment of the Mexican National Forest Inventory map: A study in four ecogeographical areas

The accuracy of the Mexican National Forest Inventory (NFI) map is derived in four distinct ecogeographical areas, using an assessment design tailored for the project. A main achievement of the design was to integrate the high diversity of classes encompassed at the most detailed subcommunity level of the classification scheme within a cost‐controlled statistically sound assessment. A hybrid double sampling strategy was applied to the 2.5 million‐ha study area. A total of 5955 reference sites were verified against their NFI map label. The availability of detailed quasi‐synchronous reference data for the 2000 Landsat‐derived NFI and the high diversity of mapped classes allowed a careful thematic analysis on the selected regions, relevant for national extrapolation. Global accuracy estimates of 64–78 per cent were registered among the four ecogeographical areas (two with mainly temperate climate and the other two with mainly tropical climate), with the lower accuracy levels found in areas more densely covered with forests. According to the estimates, the NFI map tends to underestimate the presence of temperate forest (especially oak) and overestimate the presence of tropical forest in the areas investigated. The analysis of confusions reveals difficulties in unambiguously interpreting or labelling forests with secondary vegetation, herbaceous and/or shrub‐like vegetation as well as distinguishing between aquatic vegetation types. The design proved useful from the perspective of accuracy assessments of regional maps in biodiverse regions.     

Evaluation of forest cover change using remote sensing techniques and landscape metrics in Moncayo Natural Park (Spain)

Monitoring the change in land cover in natural places, such as ecotones, has become an important tool for forest management, especially in protected areas. The present work analyses the spatial and temporal changes in forest cover in Moncayo Natural Park (Spain) from 1987 to 2010 using remote sensing techniques, geographical information systems (GIS) and quantitative indices of landscape ecology. Four Landsat images were used to map nine representative land cover categories in this preserved area in both years. The overall classification accuracies in land cover cartographies in 1987 and 2010 were 87.65% and 84.56%, respectively. Landscape metrics obtained at the landscape level show an increase in fragmentation and, as a result, an increase in landscape spatial diversity. Focusing on the class level, the results show a forest expansion of sessile oaks (Quercus petraea) and beech forest (Fagus sylvatica), two important bioclimatic indicators in this natural park, because they are the southernmost locations for these species in Europe. The decrease of mainly introduced pine forest and the transformation of mixed shrub areas into natural forested areas explain the aforementioned increase in fragmentation. These results are in agreement with the strategies for nature conservation designed by forest managers during the period evaluated.     

博格达峰地区冰川和积雪变化遥感监测及影响因素分析

20世纪以来,随着全球气候变暖加剧,冰川和积雪普遍退缩,严重影响到人类的生存和社会经济的可持续发展,这一问题在我国西北干旱区的博格达峰地区及其周边地区尤为突出。以博格达峰地区为例,利用1990—2016年Landsat 5与Landsat 8遥感影像,对比分析归一化积雪指数（NDSI）、归一化冰雪指数（NDSII）、归一化主成分雪指数（NDPCSI）和缨帽转换湿度指数（WET）在博格达峰地区监测冰川和积雪的能力,同时结合研究区周边气温、降水数据和研究区地形数据,探讨博格达峰地区冰川和积雪面积变化与区域地形、气候间的响应关系。结果表明：（1） WET相对于NDSII、NDSI和NDPCSI精度值更高,可以替代NDSI、NDSII监测博格达峰地区冰川和积雪面积。（2） 博格达峰地区冰川和积雪面积呈持续退缩的趋势。1990—2016年,冰川和积雪面积减少率约20.07%,且年退缩率不断增加。（3） 高程、坡度和坡向对冰川和积雪面积变化的影响较显著,山地阴影对其影响较弱,气温的升高是冰雪面积减少的主要因素。     

Land Cover Changes on Ambergris Caye,Belize: A Case Study of Unregulated Tourism Development

Measuring land-use, land-cover change in biodiverse, tropical countries is critical for conservation management and sustainable planning because it provides quantifiable data regarding broad environmental changes. This project uses Landsat satellite imagery to document vegetation cover change on Ambergris Caye, Belize, from 2000 to 2017. The close proximity of the Belize Barrier Reef Reserve System has made Ambergris Caye the most popular tourist destination and economic hub in Belize. As a result, the region has undergone intense commercial and residential development coupled with rapid population growth over the past two decades. Understanding general trends in landscape dynamics is critical for the natural resource–based tourism industry of Belize to continue to thrive. Unsupervised classification methods and a per pixel postclassification comparison were used with Landsat imagery to estimate loss in vegetation cover and increases in urban and barren land. The results indicate a 10.85 percent decrease in vegetation and a 39 percent increase in urban and barren land during the seventeen-year study period with an annual forest loss rate of 0.67 percent per year using a compound interest rate formula. The results of this analysis represent a baseline study of vegetation change on Ambergris Caye to inform management and conservation efforts.     

Large-scale land cover mapping with the integration of multi-source information based on the Dempster–Shafer theory

Land cover type is a crucial parameter that is required for various land surface models that simulate water and carbon cycles, ecosystem dynamics, and climate change. Many land use/land cover maps used in recent years have been derived from field investigations and remote-sensing observations. However, no land cover map that is derived from a single source (such as satellite observation) properly meets the needs of land surface simulation in China. This article presents a decision-fuse method to produce a higher-accuracy land cover map by combining multi-source local data based on the Dempster–Shafer (D–S) evidence theory. A practical evidence generation scheme was used to integrate multi-source land cover classification information. The basic probability values of the input data were obtained from literature reviews and expert knowledge. A Multi-source Integrated Chinese Land Cover (MICLCover) map was generated by combining multi-source land cover/land use classification maps including a 1:1,000,000 vegetation map, a 1:100,000 land use map for the year 2000, a 1:1,000,000 swamp-wetland map, a glacier map, and a Moderate-Resolution Imaging Spectroradiometer land cover map for China in 2001 (MODIS2001). The merit of this new map is that it uses a common classification system (the International Geosphere-Biosphere Programme (IGBP) land cover classification system), and it has a unified 1 km resolution. The accuracy of the new map was validated by a hybrid procedure. The validation results show great improvement in accuracy for the MICLCover map. The local-scale visual comparison validations for three regions show that the MICLCover map provides more spatial details on land cover at the local scale compared with other popular land cover products. The improvement in accuracy is true for all classes but particularly for cropland, urban, glacier, wetland, and water body classes. Validation by comparison with the China Forestry Scientific Data Center (CFSDC)–Forest Inventory Data (FID) data shows that overall forest accuracies in five provinces increased to between 42.19% and 88.65% for our MICLCover map, while those of the MODIS2001 map increased between 27.77% and 77.89%. The validation all over China shows that the overall accuracy of the MICLCover map is 71%, which is higher than the accuracies of other land cover maps. This map therefore can be used as an important input for land surface models of China. It has the potential to improve the modeling accuracy of land surface processes as well as to support other aspects of scientific land surface investigations in China.     

Assessment of spatial and temporal dynamics of tropical forest cover: A case study in Malkangiri district of Orissa, India

Tropical forests have been recognized as having global conservation importance. However, they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa, India, during 1973–2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973), Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest, open forest, scrub land, agriculture, barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation, shifting cultivation, dam and road construction, unregulated management actions, and social pressure. A significant increase of 1222.8 km2 agriculture area (1973–2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences, including decline in forest cover, soil erosion, and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests, which are rapidly being deforested.     

Assessing and monitoring forest health using a forest fragmentation approach in Sariska Tiger Reserve,India

The relationship between trajectories of forest cover change and fragmentation due to physical and anthropogenic activities in Sariska Tiger Reserve is addressed in the article. The authors conducted a field visit to the reserve to collect groundtruth data and perform a village survey. Thereafter, their main method consisted of using Landsat TM images for three days, one in each of the years 1989, 1994, and 2014, to assess spatial-temporal variation in forest cover. A fragmentation model was used to examine the extent and pattern of forest degradation. The results showed an overall increase in forest cover in Sariska Tiger Reserve from 53% in 1989 to 55% in 2014. However, the fragmentation statistics revealed a deterioration in forest health. There was an increase in the fragmentation categories perforated, edge, and patch in their respective areas, while the core areas decreased at the expense of other fragmentation classes. The existence of villages, roads, and pilgrimage sites had increased the pace of degradation and fragmentation of forest in the reserve. The authors conclude that the fragmentation model was effective for analysing forest degradation and identifying the priority areas for strategic planning of nature conservation.     

From land cover-graphs to urban structure types

Urban structure types (UST) are an initial interest and basic instrument for monitoring, controlling and modeling tasks of urban planners and decision makers during ongoing urbanization processes. This study focuses on a method to classify UST from land cover (LC) objects, which were derived from high resolution satellite images. The topology of urban LC objects is analyzed by implementing neighborhood LC-graphs. Various graph measures are examined by their potential to distinguish between different UST, using the machine learning classifier random forest. Additionally the influence of different parameter settings of the random forest model, the reduction of training samples, and the graph measure importance is analyzed. An independent test set is classified and validated, achieving an overall accuracy of 87%. It was found that the height of the building with the highest node degree has a strong impact on the classification result.     

Using geographical information system and satellite imagery within a numerical simulation of regional urban growth

This paper represents an attempt to combine a geographical information system (GIS) and satellite imagery within a numerical model for the simulation of regional urban growth. The area under study is located in the southeast of France, between the cities of La Ciotat and Toulon. It covers 1600 km². The spatial resolution of the GIS as well as of the remote sensing data is better than one hectare (80 × 80 m²). Two Landsat MSS satellite images were analysed by a supervised maximum likelihood classifier to provide two maps of land use and urban domain for 1976 and 1981. A numerical model for the growth of the density of the population is applied to the urban domain. It takes into account some constraints that are due to the environment as well as the changes of population per city and per year. Seven environmental parameters are defined by pixel and originate from the content of the database, namely, land use, topography, road network, forest properties and forest fire characteristics. The global change in population is given by observations for the first years and by scenarios for the predicted years. The numerical simulation gives maps of the urban domain per year and per scenario. The initial state (year 1976) and the simulated states Tor the years 2000 and 2025 are compared and the differences are discussed briefly.     

Urban mapping,accuracy, & image classification: A comparison of multiple approaches in Tsukuba City,Japan

The rapid growth of urban space and its environmental challenges require precise mapping techniques to represent complex earth surface features more accurately. In this study, we examined four mapping approaches (unsupervised, supervised, fuzzy supervised and GIS post-processing) using Advanced Land Observing Satellite images to predict urban land use and land cover of Tsukuba city in Japan. Intensive fieldwork was conducted to collect ground truth data. A random stratified sampling method was chosen to generate geographic reference data for each map to assess the accuracy. The accuracies of the maps were measured, producing error matrices and Kappa indices. The GIS post-processing approach proposed in this research improved the mapping results, showing the highest overall accuracy of 89.33% as compared to other approaches. The fuzzy supervised approach yielded a better accuracy (87.67%) than the supervised and unsupervised approaches. The fuzzy supervised approach effectively dealt with the heterogeneous surface features in residential areas. This paper presents the strengths of the mapping approaches and the potentials of the sensor for mapping urban areas, which may help urban planners monitor and interpret complex urban characteristics.     

热带森林覆被的时空动态评价——以印度Malkangiri district of Orissa为例

Tropical forests have been recognized as having global conservation importance. However,they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa,India,during 1973-2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973),Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest,open forest,scrub land,agriculture,barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation,shifting cultivation,dam and road construction,unregulated management actions,and social pressure. A significant increase of 1222.8 km2 agriculture area (1973-2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences,including decline in forest cover,soil erosion,and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests,which are rapidly being deforested.