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1.
The changes in the land use and land cover (LULC), above ground biomass (AGB) and the associated above ground carbon (AGC) stocks were assessed in Lidder Valley, Kashmir Himalaya using satellite data (1980–2013), allometric equations and phytosociological data. Change detection analysis of LULC, comprising of eight vegetation and five non-vegetation types, indicated that 6% (74.5 km2) of the dense evergreen forest has degraded. Degraded forest and settlement increased by 20 and 52.8 km2, respectively. Normalized difference vegetation index was assessed and correlated with the field-based biomass estimates to arrive at best-fit models for remotely sensed AGB estimates for 2005 and 2013. Total loss of 1.018 Megatons of AGB and 0.5 Megatons of AGC was estimated from the area during 33-year period which would have an adverse effect on the carbon sequestration potential of the area which is already facing the brunt of climate change.  相似文献   

2.
This paper investigates statistical relationships between land use/land cover (LULC), Landsat-7 ETM+ imagery and landscape mosaic structure in southern Cameroon where the conversion of tropical rain forest to shifting cultivation leads to dynamic processes, acting on the spatial aggregation of various LULC types. A Global Positioning System (GPS) was used in the field to identify a total of 171 shifting cultivation patches representing eight LULC types in two sub-areas. Because of the lack of a cloud-free image for the date of field sampling, the ETM+ imagery was acquired 2 months after field survey, during which it was assumed that no significant changes in LULC occurred (all dry season). Per pixel correlations were developed between spectral reflectance data, vegetation indices and LULC. As an exploratory study, several statistical methods (analysis of variance, means separations (Tukey HSD), principal component analysis (PCA), geo-statistical analysis, image classification and landscape metrics) were applied on point data and sensor images for evaluating the spatial variability within the landscape. Most variables explained 30–72% of LULC variation in the whole dataset. Those variables with high information content of LULC (infrared bands 4, 5, 7 and derived indices and PC1) also showed long ranges (6 km) spatial dependence as compared to those varying only within 1 km range. The results of these statistical analyses suggested the need to group some LULC types and the application of the Maximum Likelihood Classifier (MLC) for supervised classification provided a LULC map with the highest accuracy (81%) after consolidation of perennial LULC types, such as bush fallow, forest fallow and cocoa plantations. Landscape metrics computed from this map showed a high level of patch diversity and connectivity within the landscape and provided input data that can further be used to simulate predictive maps as substitute to cloud-covered sensor imageries. Landsat-7 ETM+ imagery proved to be useful in discriminating (with about 80% accuracy) the most dynamic LULC types such cropped plots and young fallow patches (shifting every season) and the extension front of the agricultural landscape.  相似文献   

3.
In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km2 in 1990 to 3 794.9 km2 in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of “returning farmland to transportation and huge expansion in military camps” was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time. Supported by the Al-Basrah University, Iraq, the Geo-information Science and Technology Program (No. IRT 0438)China).  相似文献   

4.
Understanding rates, patterns and types of land use and land cover (LULC) changes are essential for various decision-making processes. This study quantified LULC changes and the effect of urban expansion in three Saudi Arabian cities: Riyadh, Jeddah and Makkah using Landsat images of 1985, 2000 and 2014. Seasonal change of vegetation cover was conducted using normalised difference vegetation index, and object-based image analysis was used to classify the LULC changes. The overall accuracies of the classified maps ranged from 84 to 95%, which indicated sufficiently robust results. Urban area was the most changed land cover, and most of the converted land to urban was from bare soil. The seasonal analysis showed that the change of vegetation cover was not constant due to climatic conditions in these areas. The agricultural lands were significantly decreased between 1985 and 2014, and most of these lands were changed to bare soil due to dwindling groundwater resources.  相似文献   

5.
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6.
Expansion and heterogeneous clustering of commercial horticulture within the central highlands of Kenya after the mid-1990s impact watersheds and the sustainable resource management. This is distressing since climate conditions for world horticultural regions are projected to change, making such farming extremely difficult and costly to the environment. To understand the scope of impact on vegetation, the study evaluated (1) interannual variability in averaged normalized difference vegetation index (NDVI); (2) trends in average annual NDVI before and after 1990 – the presumed onset of rapid horticulture; and (3) relationship between the average annual NDVI and large-scale commercial farms, population density, and mean annual rainfall in subwatersheds. Time-series analysis of long-term Global Inventory Modeling and Mapping Studies NDVI data were analyzed as indicator of vegetation condition. NDVI trends before 1990s (1982–1989) and after 1990s (1990–2006) were evaluated to determine the slope (sign), and the Spearman’s correlation coefficient (strength). Overall, results show considerable variations in vegetation condition due largely to mixed factors including intensive farming activities, drought, and rainfall variation. Statistical analysis shows significant differences in slopes before 1990 and after 1990 (p < 0.05 and p < 0.1 respectively). Negative (decline) trends were common after 1990, linked to increased commercial horticulture and related anthropogenic disturbances on land cover. There was decline in vegetation over densely populated subwatersheds, though low NDVI values in 1984 and 2000 were the effect of severe droughts. Understanding the linkage between vegetation responses to the effects of human-induced pressure at the subwatershed scale can help natural resource managers approach conservation measures more effectively.  相似文献   

7.
针对现有植被净初级生产力研究对城市圈、城市带尺度缺乏关注的问题,基于MODIS遥感数据、地面气象资料等,利用改进的CASA模型,结合回归分析、相关分析等方法探究了2000—2013年皖江城市带植被NPP的时空变化及其对气候因子的响应,为区域生态环境质量评价提供参考。结果表明:近14年来,皖江城市带植被NPP总体呈增加趋势;不同土地利用类型NPP差异显著,林地草地耕地建设用地未利用土地水体;年NPP均值呈现由南部向西北部减少的空间分布特征;植被NPP年际变化率较小,介于±10gC·m-2·a-1范围内;温度是影响研究区植被NPP时空变化的主要气候因子。  相似文献   

8.
Sri Lanka is one of the biodiversity hotspots of the world. This study has utilized satellite remote sensing and GIS techniques to generate a nation-wide database on forests, forest types and land use/land cover of Sri Lanka. Spatial assessment of forest cover changes was carried out for the periods 1976–1985, 1985–1994, 1994–2005 and 2005–2014. The landscape fragmentation analysis has carried out to calculate the spatial and temporal patterns of forest. Land use/land cover map was prepared representing seven classes in 2014. The plantations occupy a large area (34.2%) followed by forests (33.4%) and agriculture (26.1%) in 2014. During the period of 1976–2014, the forest has been decreased by 5.5%. From 1976 to 1985 forest recorded a loss at an annual rate of 0.49%. This annual rate decreased to 0.01% during 2005–2014 indicates declining trend of deforestation and effective conservation measures. The study found deforestation hotspots in south east and northern most parts of the Sri Lanka. Total number of patches estimated has increased from 15193 in 1976 to 16136 in 2014. The study has found that main causes of deforestation in Sri Lanka were due to expansion of agriculture and plantations. The extent of change detected in the study through geospatial techniques has significance to the forest ecology and management of natural landscapes in Sri Lanka.  相似文献   

9.
In this study, we explored the capacity of vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products to characterize global savannas in Australia, Africa and South America. The savannas were spatially defined and subdivided using the World Wildlife Fund (WWF) global ecoregions and MODIS land cover classes. Average annual profiles of Normalized Difference Vegetation Index, shortwave infrared ratio (SWIR32), White Sky Albedo (WSA) and the Structural Scattering Index (SSI) were created. Metrics derived from average annual profiles of vegetation indices were used to classify savanna ecoregions. The response spaces between vegetation indices were used to examine the potential to derive structural and fractional cover measures. The ecoregions showed distinct temporal profiles and formed groups with similar structural properties, including higher levels of woody vegetation, similar forest–savanna mixtures and similar grassland predominance. The potential benefits from the use of combinations of indices to characterize savannas are discussed.  相似文献   

10.
Coastal zones are most vulnerable for landuse changes in this rapid industrialization and urbanization epoch. It is necessary to evaluate land use — land cover (LULC) changes to develop efficient management strategies. The main objective of this paper is to evaluate and quantity Abu Dhabi coastal zone LULC changes from 1972 to 2000 using multi-temporal LANDSAT satellite data and digital change detection techniques. Supervised classification coupled with expert visual interpretation techniques were used to produce LULC classified images with an accuracy of 88%. Change detection process was achieved by applying post-classification comparison techniques in ENVI software. From this study it has been observed that the important coastal landuse types of Abu Dhabi coast .i.e. wetlands and woody Vegetation (Mangrove, represented by a single species,Avicennia marina) have been reduced drastically in their extent due to reclamation, dredging, tipping and other anthropogenic activities along the coastal zone. However, it has been observed that there is rapid increase in the man-made plantation and managed vegetation from 1990 to 2000 due to the Abu Dhabi government initiation. This study has given good insight into Abu Dhabi coastal zone changes during last 3 decades.  相似文献   

11.
Land-cover change may affect water and carbon cycles when transitioning from one land-cover category to another (land-cover conversion, LCC) or when the characteristics of the land-cover type are altered without changing its overall category (land-cover modification, LCM). Given the increasing availability of time-series remotely sensed data for earth monitoring, there has been increased recognition of the importance of accounting for both LCC and LCM to study annual land-cover changes. In this study, we integrated 1,513 time-series Landsat images and a change-updating method to identify annual LCC and LCM during 1986–2015 in the coastal area of Zhejiang Province, China. The purpose was to quantify their contributions to land-cover changes and impacts on the amount of vegetation. The results show that LCC and LCM can be successfully distinguished with an overall accuracy of 90.0%. LCM accounted for 22% and 40.5% of the detected land-cover changes in reclaimed and inland areas, respectively, during 1986–2015. In the reclaimed area, LCC occurred mostly in muddy tidal flats, construction land, aquaculture ponds, and freshwater herbaceous land, whereas LCM occurred mostly in freshwater herbaceous land, Spartina alterniflora, and muddy tidal flats. In the inland area, both LCC and LCM were concentrated in forest and dryland. Overall, LCC had a mean magnitude of normalized difference vegetation index (NDVI) change similar to that of LCM. However, LCC had a positive effect and LCM had a negative effect on NDVI change in the reclaimed area. Both LCC and LCM in the inland area had negative impacts on vegetation greenness, but LCC resulted in larger NDVI change magnitude. Impacts of LCC and LCM on vegetation greenness were quantified for each land-cover type. This study provided a methodological framework to take both LCC and LCM into account when analyzing land-cover changes and quantified their effects on coastal ecosystem vegetation.  相似文献   

12.
Urbanization effects on vegetation cover (VC) have been analyzed in many regions. However, little attention has been paid to Africa, which has undergone rapid urbanization in recent decades. In this study, MODIS land cover and enhanced vegetation index (EVI) data were used to examine urbanization effects on VC in 59 large cities in Africa during 2001–2017. The ΔEVI (urban EVI minus rural EVI) was used to represent urbanization effects on VC. Major findings include: (1) for 59 cities averaged, annual ΔEVI averaged from 2015 to 2017 was -0.116. Negative annual ΔEVI (i.e. urban EVI lower than rural) were observed in 56 of 59 cities. (2) For 59 cities averaged, urban area increased 17.9% from 2001 (262.8 km2) to 2016 (309.8 km2). (3) Annual ΔEVI decreased significantly (p<0.05) in 44 of 59 cities for the period 2001–2017, and annual average area of urbanization effects on VC increased significantly in 40 of 59 cities. For 59 cities averaged, the percentage of urban area with significant decreasing trends of annual ΔEVI was 60.0%. Spatially, cities near the Gulf of Guinea showed more significant decreasing ΔEVI than cities in other regions. In addition, the trends and spatial distributions of urbanization effects on VC differed little by seasons. These results suggested that urbanization and its effects on VC in Africa should arouse more attentions.  相似文献   

13.
Accurate estimation of ecosystem carbon fluxes is crucial for understanding the feedbacks between the terrestrial biosphere and the atmosphere and for making climate-policy decisions. A statistical model is developed to estimate the gross primary production (GPP) of coniferous forests of northeastern USA using remotely sensed (RS) radiation (land surface temperature and near-infra red albedo) and ecosystem variables (enhanced vegetation index and global vegetation moisture index) acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. This GPP model (called R-GPP-Coni), based only on remotely sensed data, was first calibrated with GPP estimates derived from the eddy covariance flux tower of the Howland forest main tower site and then successfully transferred and validated at three other coniferous sites: the Howland forest west tower site, Duke pine forest and North Carolina loblolly pine site, which demonstrate its transferability to other coniferous ecoregions of northeastern USA. The proposed model captured the seasonal dynamics of the observed 8-day GPP successfully by explaining 84–94% of the observed variations with a root mean squared error (RMSE) ranging from 1.10 to 1.64 g C/m2/day over the 4 study sites and outperformed the primary RS-based GPP algorithm of MODIS.  相似文献   

14.
Abstract

High-latitude ecosystems are exposed to more pronounced warming effects than other parts of the globe. We develop a technique to monitor ecological changes in a way that distinguishes climate influences from disturbances. In this study, we account for climatic influences on Alaskan boreal forest performance with a data-driven model. We defined ecosystem performance anomalies (EPA) using the residuals of the model and made annual maps of EPA. Most areas (88%) did not have anomalous ecosystem performance for at least 6 of 8 years between 1996 and 2004. Areas with underperforming EPA (10%) often indicate areas associated with recent fires and areas of possible insect infestation or drying soil related to permafrost degradation. Overperforming areas (2%) occurred in older fire recovery areas where increased deciduous vegetation components are expected. The EPA measure was validated with composite burn index data and Landsat vegetation indices near and within burned areas.  相似文献   

15.
Abstract

Large areas in the Czech Republic were used for open casts of brown coal mining. Many of them have been already closed. Reclamation of them and of their dumps is the next step intheir development. It is possible to divide used reclamations into the forest, hydrologic, agricultural and other ones – roads, etc. Their age varies from 45 years to as yet unfinished. Reclaimed areas are documented in reclamation projects. Information about age and land use determined groups of these areas to be evaluated by vegetation indices. 100 areas with forest type were evaluated. Eight vegetation indices (NDVI, DVI, RVI, PVI, SAVI, MSAVI, TSAVI and EVI) were calculated and their average value in each area in 1988, 1992 and 1998 Thematic Mapper data were compared. Changes over years showed close relation to precipitations of previous periods. This relation was confirmed by evaluation of forest areas situated near reclamation areas. Positive/negative changes of vegetation indices were different for different groups and different vegetation indices. An overview of results of vegetation indices is presented for individual areas whose land use comprised at least partly forest stand. Results in a 4-year period (1988–1992) were in many areas by many indices negative, changes in 10 years were in most areas by most vegetation indices positive. Changes, minimum values and maximum values in groups were compared. Evaluation of vegetation indices brought again various results. One vegetation index is not sufficient to prove improvement/deterioration of vegetation changes. Precipitation state before measurement should be controlled. Temporary shortage of precipitation can cause vegetation cover deterioration, which is also only temporary. The best development derived from vegetation indices evaluation was found at forest reclamation with mixed tree stand that was 10–20 years old. The method was derived as a tool for post-finishing control of vegetation development of reclamations performed in several year periods.  相似文献   

16.
ABSTRACT

East Rennell of Solomon Island is the first natural site under customary law to be inscribed on UNESCO’s World Heritage List. Potential threats due to logging, mining and agriculture led to the site being declared a World Heritage in Danger in 2013. For East Rennell World Heritage Site (ERWHS) to ‘shed’ its ‘Danger’ status the management must monitor forest cover both within and outside of ERWHS. We used satellite data from multiple sources to track forest cover changes for the entire East Rennell island since 1998. 95% of the island is still covered by undisturbed forests; annual average normalized difference vegetation index (NDVI) for the whole island was above 0.91 in 2015. However, vegetation cover in the island has been slowly decreasing, at a rate of –0.0011 NDVI per year between 2000 and 2015. This decrease less pronounced inside ERWHS compared to areas outside. While potential threats due to forest clearing outside ERWHS remain the forest cover change from 2000 to 2015 has been below 15%. We suggest ways in which the Government of Solomon Islands could use our data as well as unmanned air vehicles and field surveys to monitor forest cover change and ensure the future conservation of ERWHS.  相似文献   

17.
地理国情普查数据在林地监测中的应用研究   总被引：1，自引：0，他引：1  
以黑龙江省穆棱市为研究区,利用2005年的基础地理信息数据和2015年全国地理国情普查数据成果作为基础数据,并结合SPOT-5、ZY-3卫星遥感影像数据,对穆棱市林地进行监测。本文从数据的收集与整理、影像处理和变化监测数据提取及处理方法等进行应用研究,准确快速获取变化信息的光谱、纹理、植被指数及面积等信息,通过特定运算得到每期研究区内植被的覆盖率、保有量以及蓄积量,实现林地覆盖率、保有量及蓄积量的动态变化监测。最后,通过对监测数据的统计分析得出穆棱市林地变化监测成果。  相似文献   

18.
Pasture land occupies extensive areas and is increasingly of interest for sustainable intensification, land use diversification, greenhouse gas emission mitigation, and bioenergy expansion. Accurate maps of pasture and other managed land covers are needed for monitoring, intercomparison, assessing potential uses, and planning. Yet, land maps can be generated from different types of classification datasets – i.e. as a land use or land cover type – as well as different sources. In this study our aim was to assess and compare land use and land cover definitions for pasture, and examine variability in the resulting pasture land classification maps. First, we conducted a review of pasture definitions in commonly used mapping databases. We then performed a case study involving Brazil, a dominant global producer of pasture-based livestock. Six geospatial databases were harmonized and compared to each other and to MODIS land cover for Brazil including the Cerrado and Amazon biomes, which are internationally recognized for their ecological value. Total pasture area estimates for Brazil ranged by a factor greater than four, from about 430,000 km2 to over 1.7 million km2. Our analysis showed high variability in pasture land maps depending on the definitions, methods and underlying datasets used to generate them. The results are illustrative of a symptomatic problem for all manage land datasets, demonstrating the need for land categories studies and geospatial data resources that fully define land terms and describe measurable management attributes. Additionally, the suitability of individual geospatial datasets for different types of land mapping must be better described and reported. These recommendations would help bring more consistency in the consideration of managed lands in research, reporting, and policy development, as demonstrated here for pasture land using six case study datasets from multiple sources.  相似文献   

19.
Abstract

Land use/land cover (LULC) classification with high accuracy is necessary, especially in eco-environment research, urban planning, vegetation condition study and soil management. Over the last decade a number of classification algorithms have been developed for the analysis of remotely sensed data. The most notable algorithms are the object-oriented K-Nearest Neighbour (K-NN), Support Vector Machines (SVMs) and the Decision Trees (DTs) amongst many others. In this study, LULC types of Selangor area were analyzed on the basis of the classification results acquired using the pixel-based and object-based image analysis approaches. SPOT 5 satellite images with four spectral bands from 2003 and 2010 were used to carry out the image classification and ground truth data were collected from Google Earth and field trips. In pixel-based image analysis, a supervised classification was performed using the DT classifier. On the other hand, object-oriented (K-NN) image analysis was evaluated using standard nearest neighbour as classifier. Subsequently SVM object-based classification was performed. Five LULC categories were extracted and the results were compared between them. The overall classification accuracies for 2003 and 2010 showed that the object-oriented (K-NN) (90.5% and 91%) performed better results than the pixel-based DT (68.6% and 68.4%) and object-based SVM (80.6% and 78.15%). In general, the object-oriented (K-NN) performed better than both DTs and SVMs. The obtained LULC classification maps can be used to improve various applications such as change detection, urban design, environmental management and zooning.  相似文献   

20.
Predicting land surface energy budgets requires precise information of land surface emissivity (LSE) and land surface temperature (LST). LST is one of the essential climate variables as well as an important parameter in the physics of land surface processes at local and global scales, while LSE is an indicator of the material composition. Despite the fact that there are numerous publications on methods and algorithms for computing LST and LSE using remotely sensed data, accurate prediction of these variables is still a challenging task. Among the existing approaches for calculating LSE and LST, particular attention has been paid to the normalised difference vegetation index threshold method (NDVITHM), especially for agriculture and forest ecosystems. To apply NDVITHM, knowledge of the proportion of vegetation cover (PV) is essential. The objective of this study is to investigate the effect of the prediction accuracy of the PV on the estimation of LSE and LST when using NDVITHM. In August 2015, a field campaign was carried out in mixed temperate forest of the Bavarian Forest National Park, in southeastern Germany, coinciding with a Landsat-8 overpass. The PV was measured in the field for 37 plots. Four different vegetation indices, as well as artificial neural network approaches, were used to estimate PV and to compute LSE and LST. The results showed that the prediction accuracy of PV improved using an artificial neural network (R2CV = 0.64, RMSECV = 0.05) over classic vegetation indices (R2CV = 0.42, RMSECV = 0.06). The results of this study also revealed that variation in the accuracy of the estimated PV affected calculation results of the LSE. In addition, our findings revealed that, though LST depends on LSE, other parameters should also be taken into account when predicting LST, as more accurate LSE results did not increase the prediction accuracy of LST.  相似文献   

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