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1.
Land cover change analysis was undertaken in semi-arid southeastern Botswana. The aim was to determine how remotely sensed data could be applied over time and under different rainfall regimes to help assess the relative significance of biophysical and human factors in causing land cover change in a rapidly evolving developing world context. To this purpose, land cover changes were studied along an east (hardveld)-west (sandveld) gradient of decreasing rainfall and decreasing population density. Three years of Thematic Mapper imagery from 1984, 1994 and 1996, covering the period from the 1980s drought to the 1990s ‘normal’ rainfall regime were analysed using supervised classification techniques. Land cover change analysis revealed that over a large part of the study area the dry and more biophysically vulnerable western sandveld showed greater vegetation recovery than the eastern hardveld with its more productive soils and higher rainfall. Underlying causes behind this apparent reversal of trends are inferred to be mainly socioeconomic in nature and particularly related to higher population density due to the rise of salaried urban occupation opportunities in the hardveld. This work concludes that, while biophysical causes of change are important, the human dimension is regarded as being more significant especially where human factors negate otherwise positive biophysical effects in an agrarian developing country. 相似文献
2.
Start-of-season data are more and more used to qualify the land surface phenology trends in relation with climate variability and, more rarely, with human land management. In this paper, we compared the phenology of rangeland vs cropped land in the Sahel belt of Africa, using the only currently available global phenology product (MODIS MCD12Q2 – Land Cover Dynamics Yearly), and an enhanced crop mask of Mali. The differences in terms of start-of-season (SOS) are spatially (north south gradient), and temporally (10 years, 2001–2009) analyzed in bioclimatic terms. Our results show that globally the MODIS MCD12Q2 SOS dates of croplands and rangelands differ, and that these differences depend on the bioclimatic zone. In Sahelian and Guinean regions, cropland vegetation begins to grow earlier than rangeland vegetation (8-day and 4-day advance, respectively). Between, in the Sudanian and Sudano-Sahelian parts of Mali, rangeland vegetation greens about one week earlier than croplands. These results are discussed in the context of the land surface heterogeneity at MODIS scale, and in the context of the natural vegetation ecology. These results could help interpreting phenological trends in climate change analysis. 相似文献
3.
基于空间连续数据的小流域景观格局破碎化研究 总被引：1，自引：0，他引：1
基于空间连续数据，采用局部空间关联指标（LISA）——局部Moran指数（Local Moran Index, LMI），通过探测小流域内景观均质性和异质性的变化情况来反映景观格局破碎化的变化过程。作为一种空间明确的景观格局研究方法，LMI能够发现流域景观格局变化过程中的热点地区，并分析其与流域土地利用变化之间的联系，明确了土地利用变化是引起小流域景观格局变化的最主要的驱动因素。研究表明，基于空间连续数据的局部空间关联指标方法可以作为传统景观格局变化研究方法的有益补充。 相似文献
4.
Rapid urbanization threatens urban green spaces and vegetation, demonstrated by a decrease in connectivity and higher levels of fragmentation. Understanding historic spatial and temporal patterns of such fragmentation is important for habitat and biological conservation, ecosystem management and urban planning. Despite their potential value, Local Indicators of Spatial Autocorrelation (LISA) measures have not been sufficiently exploited in monitoring the spatial and temporal variability in clustering and fragmentation of vegetation patterns in urban areas. LISA statistics are an important structural measure that indicates the presence of outliers, zones of similarity (hot spots) and of dissimilarity (cold spots) at proximate locations, hence they could be used to explicitly capture spatial patterns that are clustered, dispersed or random. In this study, we applied landscape metrics, LISA indices to analyse the temporal variability in clustering and fragmentation patterns of vegetation patches in Harare metropolitan city, Zimbabwe using Landsat series data for 1994, 2001 and 2017. Analysis of landscape metrics showed an increase in the fragmentation of vegetation patches between 1994–2017 as shown by the decrease in mean patch size, an increase in number of patches, edge density and shape complexity of vegetation patches. The study further demonstrates the utility of LISA indices in identifying key hot spot and cold spots. Comparatively, the highly vegetated northern parts of the city were characterised by significantly high positive spatial autocorrelation (p < 0.05) of vegetation patches. Conversely, more dispersed vegetation patches were found in the highly and densely urbanized western, eastern and southern parts of the city. This suggest that with increasing vegetation fragmentation, small and isolated vegetation patches do not spatially cluster but are dispersed geographically. The findings of the study underline the potential of LISA measures as a valuable spatially explicit method for the assessment of spatial clustering and fragmentation of urban vegetation patterns. 相似文献
5.
Tugba Memisoglu Baykal 《Transactions in GIS》2023,27(5):1289-1317
Forests are essential in contributing to the continuity of the natural balance. Therefore, their protection and sustainability are vital. However, all over the world, forest fires occur, and forests are destroyed due to both human factors and unknown causes. It is necessary to carry out studies to prevent this destruction. At this point, GIS-based location–time relationship-based hot spot clustering analysis can provide significant advantages in detecting risky spots of forest fires. In this study, GIS-based emerging hot spot clustering analysis was carried out to determine the risky areas where forest fires will occur and to carry out preventive studies in the relevant areas. Turkey was chosen as the pilot region, and analyses were carried out using the data obtained from the official statistics of the Ministry of Agriculture and Forestry General Directorate of Forestry according to the causes of the fires (negligence, intentional, accidental, unknown cause and natural) between the years 2010 and 2020. Spatial autocorrelation analysis was conducted for each fire type, and threshold distances were determined {with a number of distance bands = 20,000, distant increment = 10,000}. Emerging hot spot analyses were then conducted, and the results were presented as maps and statistical outputs. According to all fire types, 15 new hot spots, 14 persistent hot spots, 33 sporadic hot spots, 9 consecutive hot spots, 15 intensifying, and 2 diminishing hot spot regions were obtained throughout the country. 相似文献
6.
Kuntal Ganguly Rajiv Kumar K. Mruthyunjaya Reddy P. Jagadeeswara Rao Manoj Raj Saxena G. Ravi Shankar 《国际地球制图》2017,32(7):777-796
This study investigated land use/land cover change (LULCC) dynamics using temporal satellite images and spatial statistical cluster analysis approaches in order to identify potential LULCC hot spots in the Pune region. LULCC hot spot classes defined as new, progressive and non-progressive were derived from Gi* scores. Results indicate that progressive hot spots have experienced high growth in terms of urban built-up areas (20.67% in 1972–1992 and 19.44% in 1992–2012), industrial areas (0.73% in 1972–1992 and 3.46% in 1992–2012) and fallow lands (4.35% in 1972–1992 and ?6.38% in 1992–2012). It was also noticed that about 28.26% of areas near the city were identified as new hot spots after 1992. Hence, non-significant change areas were identified as non-progressive after 1992. The study demonstrated that LULCC hot spot mapping through the integrated spatial statistical approach was an effective approach for analysing the direction, rate, spatial pattern and spatial relationship of LULCC. 相似文献
7.
The 1980 eruptions of Mount St. Helens provided an excellent opportunity for scientists to investigate the recovery of vegetation communities following a major geologic disturbance. An important and often overlooked aspect in these studies is the human factor in recovery processes, and specifically, the different management approaches taken towards re-establishment of vegetation on lands under the control of various owners. This study examines vegetation changes throughout the 1980 blast zone using a time series of Landsat-derived Normalized Difference Vegetation Index (NDVI) images and change detection methods to assess the changes over 25 years, from 1980 to 2005, as a function of human management combined with ecological factors. This long-term tracking of change indicates that differences in the speed of vegetation re-establishment and consequent rates of change substantially reflect human involvement and varying management strategies. 相似文献
8.
基于空间分析的徐州市居民点分布模式研究 总被引：8，自引：1，他引：7
居民点空间分布的研究是聚落地理学的主要内容之一,运用空间分析的方法研究居民点的分布能更准确地刻画出其空间分布的本质规律。本文根据2004年TM遥感图像和城市地图得到徐州市城乡居民点空间分布的信息,继而运用样方分析(QA)法、最近邻距离指数(NNI)、K(d)函数、热点探测技术(NNH)研究了徐州市居民点空间分布格局与模式。结果显示:徐州市居民点的空间分布具有明显的空间依赖性,总体上呈现出集聚分布的特点;随着研究尺度的变大,居民点空间分布的集聚性指数也增大;居民点空间分布的热点区域在微观尺度上具有空间随机性、在中观尺度上具有轴带延伸性、宏观尺度上具有面状集中性的特点。 相似文献
9.
A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (http://bis.iirs.gov.in). 相似文献
10.
Iraq contains the Great Mesopotamian alluvial plain of the Euphrates and Tigris rivers. Its regional vegetation phenological patterns are worthy of investigation because relatively little is known about the phenology of semi-arid environments, and because their inter-annual variation is expected to be driven by uncertain rainfall and varied topography. The aim of this research was to assess and map the spatial variation in key land surface phenology (LSP) parameters over the last decade and their relation with elevation. It is the first study mapping land surface phenology during last decade over the whole of Iraq, and one of only a few studies on vegetation phenology in a semi-arid environment. Time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) normalised difference vegetation index (NDVI) data at 250 m spatial resolution and 8 day temporal resolution, were employed to map the spatial variation in three LSP parameters for the major vegetation types in Iraq during 2001–2012. LSP parameters were defined by inflection points after smoothing the vegetation phenological signals using the Fourier technique. The estimated key LSP parameters indicated that the relatively shorter length of season (LOS) in the north of Iraq resulted from a delayed start of season (SOS). Greater spatial variation occurred in the SOS than end of season (EOS), which may be due to the spatial distribution of rainfall and temperature as a function of elevation. A positive correlation was observed for SOS and EOS with elevation for all major land cover types with EOS producing the largest positive correlation (R2 = 0.685, R2 = 0.638 and R2 = 0.588, p < 0.05 in shrubland, cropland and grassland, respectively). The magnitude of delay in SOS and EOS increased in all land cover types along a rising elevation gradient where for each 500 m increase, SOS was delayed by around 25 or more days and EOS delayed by around 22 or more days, except for grassland. The SOS and EOS also varied temporally during the last decade, particularly the SOS in the lowland, north of the country where the standard deviation was around 80 to 120 days, due mainly to the practice of crop rotation and the traditional biennial cropping system. Thus, the results of this research emphasize the effect of elevation on key LSP parameters over Iraq, for all major vegetation types. 相似文献
11.
Mazlan Hashim Syarifuddin Misbari Amin Beiranvand Pour 《Journal of the Indian Society of Remote Sensing》2018,46(2):233-248
Integration of satellite remote sensing data and GIS techniques is an applicable approach for landslide mapping and assessment in highly vegetated regions with a tropical climate. In recent years, there have been many severe flooding and landslide events with significant damage to livestock, agricultural crop, homes, and businesses in the Kelantan river basin, Peninsular Malaysia. In this investigation, Landsat-8 and phased array type L-band synthetic aperture radar-2 (PALSAR-2) datasets and analytical hierarchy process (AHP) approach were used to map landslide in Kelantan river basin, Peninsular Malaysia. Landslides were determined by tracking changes in vegetation pixel data using Landsat-8 images that acquired before and after flooding. The PALSAR-2 data were used for comprehensive analysis of major geological structures and detailed characterizations of lineaments in the state of Kelantan. AHP approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index, land cover, distance to drainage, precipitation, distance to fault, and distance to the road were extracted from remotely sensed data and fieldwork to apply AHP approach. The excessive rainfall during the flood episode is a paramount factor for numerous landslide occurrences at various magnitudes, therefore, rainfall analysis was carried out based on daily precipitation before and during flood episode in the Kelantan state. The main triggering factors for landslides are mainly due to the extreme precipitation rate during the flooding period, apart from the favorable environmental factors such as removal of vegetation within slope areas, and also landscape development near slopes. Two main outputs of this study were landslide inventory occurrences map during 2014 flooding episode and landslide susceptibility map for entire Kelantan state. Modeled/predicted landslides with a susceptible map generated prior and post-flood episode, confirmed that intense rainfall throughout Kelantan has contributed to produce numerous landslides with various sizes. It is concluded that precipitation is the most influential factor for landslide event. According to the landslide susceptibility map, 65% of the river basin of Kelantan is found to be under the category of low landslide susceptibility zone, while 35% class in a high-altitude segment of the south and south-western part of the Kelantan state located within high susceptibility zone. Further actions and caution need to be remarked by the local related authority of the Kelantan state in very high susceptibility zone to avoid further wealth and people loss in the future. Geo-hazard mitigation programs must be conducted in the landslide recurrence regions for reducing natural catastrophes leading to loss of financial investments and death in the Kelantan river basin. This investigation indicates that integration of Landsat-8 and PALSAR-2 remotely sensed data and GIS techniques is an applicable tool for Landslide mapping and assessment in tropical environments. 相似文献
12.
Changes in natural vegetation cover comprising the Kalahari rangeland were undertaken using Landsat MSS imagery over a period of above average rainfall (1972–1982) and a period of drought (1982–1986). This and ancillary data were collected to determine whether changes in the range were related primarily to rainfall events or to man‐induced effects. Data from different orbits were made compatible digitally. Dark area subtraction was a problem because deep shadow and water were lacking in the Kalahari landscape. Eleven land‐use/land cover classes were derived for the 1984 base year. Additional signatures had to be obtained for the later drought years because of extreme increases in brightness. Broadly the south‐eastern Kalahari was divided into an interior, relatively uninhabited homogeneous area and a more diverse area containing fossil valleys and pans. Changes in vegetation cover in the interior appeared to be more related to rainfall events than anthropogenic factors. Changes in the fossil valley vegetation cover appeared to be more related to rainfall events during the period of above average rainfall and more related to cattle and smallstock densities during the drought period. 相似文献
13.
In the past 50 years, the Sahel has experienced significant tree- and land cover changes accelerated by human expansion and prolonged droughts during the 1970s and 1980s. This study uses remote sensing techniques, supplemented by ground-truth data to compare pre-drought woody vegetation and land cover with the situation in 2011. High resolution panchromatic Corona imagery of 1967 and multi-spectral RapidEye imagery of 2011 form the basis of this regional scaled study, which is focused on the Dogon Plateau and the Seno Plain in the Sahel zone of Mali. Object-based feature extraction and classifications are used to analyze the datasets and map land cover and woody vegetation changes over 44 years. Interviews add information about changes in species compositions. Results show a significant increase of cultivated land, a reduction of dense natural vegetation as well as an increase of trees on farmer's fields. Mean woody cover decreased in the plains (−4%) but is stable on the plateau (+1%) although stark spatial discrepancies exist. Species decline and encroachment of degraded land are observed. However, the direction of change is not always negative and a variety of spatial variations are shown. Although the impact of climate is obvious, we demonstrate that anthropogenic activities have been the main drivers of change. 相似文献
14.
Climate variation and land transformations related to exploitative land uses are among the main drivers of vegetation productivity decline and ongoing land degradation in East Africa. We combined analysis of vegetation trends and cumulative rain use efficiency differences (CRD), calculated from 250-m MODIS NDVI time-series data, to map vegetation productivity loss over eastern Africa between 2001 and 2011. The CRD index values were furthermore used to discern areas of particular severe vegetation productivity loss over the observation period. Monthly 25-km Tropical Rainfall Measuring Mission (TRMM) data metrics were used to mask areas of rainfall declines not related to human-induced land productivity loss. To provide insights on the productivity decline, we linked the MODIS-based vegetation productivity map to land transformation processes using very high resolution (VHR) imagery in Google Earth (GE) and a Landsat-based land-cover change map. In total, 3.8 million ha experienced significant vegetation loss over the monitoring period. An overall agreement of 68% was found between the rainfall-corrected MODIS productivity decline map and all reference pixels discernable from GE and the Landsat map. The CRD index showed a good potential to discern areas with ‘severe’ vegetation productivity losses under high land-use intensities. 相似文献
15.
This paper investigated spatiotemporal dynamic pattern of vegetation, climate factor, and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS data-sets. First, most vegetation canopies demonstrated obvious seasonality, increasing with latitudinal gradient. Second, obvious dynamic trends were observed in both vegetation and climate change, especially the positive trends. Over 70% areas were observed with obvious vegetation greening up, with vegetation degradation principally in the Pearl River Delta, Yangtze River Delta, and desert. Overall warming trend was observed across the whole country (>98% area), stronger in Northern China. Although over half of area (58.2%) obtained increasing rainfall trend, around a quarter of area (24.5%), especially the Central China and most northern portion of China, exhibited significantly negative rainfall trend. Third, significantly positive normalized difference vegetation index (NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions, corresponding to their synchronous stronger seasonal pattern. Finally, at inter-annual level, the NDVI–climate relationship differed with climatic regions and their long-term trends: in humid regions, positive coefficients were observed except in regions with vegetation degradation; in arid, semiarid, and semihumid regions, positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing temperature. This study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process. 相似文献
16.
Investigation of rainfall–run-off modelling is an important subject to develop any available means to water supply, which maintains human life such as run-off harvesting method. This study aims to analyse and understand the rainfall–run-off relationship in a part of Babil city, Iraq. Curve number which is a function of land use, soil texture, soil moisture and land slope is used in this study. Remote sensing and GIS are used to analyse the data and to produce the run-off depth map for the study area. Then, the run-off depth is used with rainfall to investigate the relationship between them using linear correlation. This study showed a strong linear relationship between rainfall and run-off (R2 = 0.992). It indicates that in the absence of rainfall data, run-off data can be used to estimate rainfall amount. Also, the study revealed through water balance analysis that there is an average monthly change in storage. 相似文献
17.
Poverty at the national and sub-national level is commonly mapped on the basis of household surveys. Typical poverty metrics like the head count index are not able to identify its underlaying factors, particularly in rural economies based on subsistence agriculture. This paper relates agro-ecological marginality identified from regional and global datasets including remote sensing products like the normalized difference vegetation index (NDVI) and rainfall to rural agricultural production and food consumption in Burkina Faso. The objective is to analyze poverty patterns and to generate a fine resolution poverty map at the national scale. We compose a new indicator from a range of welfare indicators quantified from Georeferenced household surveys, indicating a spatially varying set of welfare and poverty states of rural communities. Next, a local spatial regression is used to relate each welfare and poverty state to the agro-ecological marginality. Our results show strong spatial dependency of welfare and poverty states over agro-ecological marginality in heterogeneous regions, indicating that environmental factors affect living conditions in rural communities. The agro-ecological stress and related marginality vary locally between rural communities within each region. About 58% variance in the welfare indicator is explained by the factors of rural agricultural production and 42% is explained by the factor of food consumption. We found that the spatially explicit approach based on multi-temporal remote sensing products effectively summarizes information on poverty and facilitates further interpretation of the newly developed welfare indicator. The proposed method was validated with poverty incidence obtained from national surveys. 相似文献
18.
Abstract Environmental data are often utilized to guide interpretation of spectral information based on context, however, these are also important in deriving vegetation maps themselves, especially where ecological information can be mapped spatially. A vegetation classification procedure is presented which combines a classification of spectral data from Landsat‐5 Thematic Mapper (TM) and environmental data based on topography and fire history. These data were combined utilizing fuzzy logic where assignment of each pixel to a single vegetation category was derived comparing the partial membership of each vegetation category within spectral and environmental classes. Partial membership was assigned from canopy cover for forest types measured from field sampling. Initial classification of spectral and ecological data produced map accuracies of less than 50% due to overlap between spectrally similar vegetation and limited spatial precision for predicting local vegetation types solely from the ecological information. Combination of environmental data through fuzzy logic increased overall mapping accuracy (70%) in coniferous forest communities of northwestern Montana, USA. 相似文献
19.
研究城市设施的热点分布对把握当前城市形态具有重要意义。传统的设施热点识别方法容易忽略设施的特征尺度且多以区域识别为主,缺少精准化提取设施热点的方法体系。针对上述问题,本文提出了一种顾及属性特征的设施热点识别方法,并以北京市住宅设施为例进行了试验分析。首先将设施的属性值作为权重,进行加权核密度估计生成密度值表面,利用极值点探测模型提取极值点;然后采用Getis-Ord Gi*统计进行空间自相关分析,生成具有显著统计学意义的热点区域,筛选极值点得到热点。结果表明,该方法能够准确有效地识别设施热点并进行合理的等级划分,为城市设施空间布局研究提供多样化视角。 相似文献
20.
In this study, we developed a prior-knowledge-based spectral mixture analysis (PKSMA) to map impervious surfaces by using endmembers derived separately for high- and low-density urban regions. First, an urban area was categorized into high- and low-density urban areas, using a multi-step classification method. Next, in high-density urban areas that were assumed to have only vegetation and impervious surfaces (ISs), the vegetation–impervious model (V–I) was used in a spectral mixture analysis (SMA) with three endmembers: vegetation, high albedo, and low albedo. In low-density urban areas, the vegetation–impervious–soil model (V–I–S) was used in an SMA analysis with four endmembers: high albedo, low albedo, soil, and vegetation. The fraction of IS with high and low albedo in each pixel was combined to produce the final IS map. The root mean-square error (RMSE) of the IS map produced using PKSMA was about 11.0%, compared to 14.52% only using four-endmember SMA. Particularly in high-density urban areas, PKSMA (RMSE = 6.47%) showed better performance than four-endmember (15.91%). The results indicate that PKSMA can improve IS mapping compared to traditional SMA by using appropriately selected endmembers and is particularly strong in high-density urban areas. 相似文献