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1.
The paper presents a geospatial modeling approach for the assessment of biological richness in Kuldiha wildlife sanctuary in Orissa located in the northern tip of the Eastern Ghats in India. Indian Remote Sensing satellite data of Resourcesat-1 LISS III and field sampling were used to model biological richness at 1:50,000 scale. It was found that the sanctuary is dominated by Sal mixed dry deciduous forest. The vegetation map prepared through visual interpretation of satellite imagery was subjected to landscape analysis and assessment of biotic disturbance using SPLAM software. The disturbance index together with species richness, ecosystem uniqueness, terrain complexity and total importance value was modeled to access the biological richness in the sanctuary. A total of 3.9 per cent area was found to posses very high plant richness followed by high (21.2%), medium (42.1%) and low (32.8%) in the sanctuary. The study demonstrated the geospatial technology in conjunction with landscape analysis, ground inventory and geospatial modeling seizes good potential for rapid assessment of biological richness. The fringe areas of the sanctuary having disturbance more because most of the small villages which are relocated from sanctuary, settled in those areas.  相似文献   

2.
Panna National Park is situated in the north-central part of Madhya Pradesh, India. Landscape parameters like fragmentation, porosity, patchiness and jaxtaposition have been analysed for disturbance gradient characterization. Disturbance on biodiversity due to human activities has been studied both qualitatively and quantitatively. The species richness is highest in northern mixed dry deciduous forest followed by dry deciduous open scrub and southern tropical dry deciduous teak forest. Species richness of the open thorny dry deciduous forest with grasses is found to be the lowest. Disturbance analysis indicates that 22.02% of the southern slightly moist teak forests are highly disturbed whereas Anogeissus forest and Riverine forest have 17.04% and 12.41% of the area under high disturbance, respectively. A total of 88 field sample plots were laid to enumerate trees, shrubs, herbs, climbers, etc. Biological richness parameters such as Shannon-Wiener biodiversity index, biodiversity value, ecosystem uniqueness were derived from field data. High biological richness is found in northern mixed dry deciduous forest and mixed dry deciduous forest with bamboo. More than 99% of such areas are falling under medium to high biological richness. Nearly 55% of the gentle and flat to gentle, slope categories were found to have low biological richness. Phytosociological analysis of sampled field data indicated that the number of trees per unit area is the lowest in the Savannah. In inaccessible areas, the species richness and number of trees per unit area is very high. Main forces causing disturbance are search for diamonds, dams on river Ken, settlements in and around the park, grazing and resource utilization by villagers for fodder, animal grazing, fuel-wood, timber, etc.  相似文献   

3.
Mangroves of the Marine National Park constitute the second largest patch of mangroves in Gujarat, extending up to 11,000 ha, comprising six species of mangroves. Earlier studies carried out using remote sensing data pertained to baseline data generation and mapping and monitoring the mangroves (density-wise) of the Park from 1975 to 1993. Using IRS IC/ID LISS III data (1998–2001) supported by ground data, the distribution of different mangrove communities in the Park has been attempted. Amongst various image-processing techniques, band ratioing followed by supervised classification gave the best result (classification accuracy was 92%).Avicennia community is the most dominant community accounting for more than 70% of the area. TheRhizophora community occupies the inward margins of the creeks and theCeriops community is present in the interior regions. The ecotone between the marsh and mangrove communities has been identified as the transitional mangroves (Avicennia alba, Sueada), representing the transition from the less saline mangrove to the highly saline marsh community. The zoning of the mangroves has also helped in assessing the diversity of the region. Based on the richness of species, three areas, namely Bhains Bid, North-east Dide Ka Bet and South-east Chhad Island have been identified as highly diverse (most suitable area for preservation).  相似文献   

4.
The present study highlights the application of satellite remote sensing in the assessment and monitoring of the mangrove forests along the coastline in Goa state of India. Based on onscreen visual interpretation techniques various land use and land cover classes have been mapped and classified. An attempt has been made to analyse changes in the mangrove forest cover from 1994 to 2001 using IRS-1B LISS-II and IRS-1D LISS-III data. An increase in the mangrove vegetation in the important estuaries has been found during 1994 and 2001. During this period, the mangrove forest increased by 44.90 per cent as a result of increased protection and consequent regeneration. Plantation of mangrove species has been raised in 876 ha (1985 to 1997) by the State Forest Department¨  相似文献   

5.
薛朝辉  钱思羽 《遥感学报》2022,26(6):1121-1142
科学准确地监测红树林是保护海陆过渡性生态系统的基础和前提,但红树林分布于潮间带,难以进行大规模人工监测。遥感技术能够对红树林进行长时间、大面积监测,但已有研究尚存不足。一方面,红树林分布于热带、亚热带区域,受到天气条件限制难以获得长时间覆盖的有效光学遥感数据;另一方面,红树林极易与其他陆生植被混淆,仅利用多波段数据的光谱信息难以精确识别。本文以恒河三角洲孙德尔本斯地区为例,基于谷歌地球引擎GEE（Google Earth Engine）获取2016年全年的Landsat 8 OLI和Sentinel-2 MSI数据,利用物候信息进行红树林提取研究。首先,基于最小二乘回归构建两个传感器在相同指数之间的关系,重建时间序列数据,之后根据可分性判据选取增强型植被指数EVI（Enhanced Vegetation Index）和陆地表面水分指数LSWI（Land Surface Water Index）。其次,对两个指数的时间序列数据进行Savitzky-Golay滤波处理,并分别提取生长期始期等13种物候信息。最后,将两个指数的物候信息进行特征级联,采用随机森林RF（Random Forest）方法进行分类,提取研究区红树林范围。实验结果表明：Landsat 8 OLI和Sentinel-2 MSI数据融合可有效提升时间序列质量,与基于单一传感器数据的分类结果相比,总体精度提高1.58%;物候信息可以显著增强红树林与其他植被的可分性,与直接使用时间序列数据的分类结果相比,总体精度提高1.92%;同时考虑EVI和LSWI指数可极大地提升分类效果,与采用单一指数相比,总体精度分别提高14.11%和9.69%。因此,本文通过数据融合、物候信息提取和指数特征级联可以更好地提取红树林,总体精度达到91.02%,Kappa系数为0.892。研究验证了物候信息在红树林遥感监测中的应用潜力,提出的方法对科学准确地监测全球或区域红树林具有一定参考价值。  相似文献   

6.
Abstract

The paper presents a geospatial modeling approach for the assessment of plant richness in Barsey Rhododendron Sanctuary in Sikkim, a Himalayan State of India located in the “Indo‐Burma” biodiversity hotspot. Remotely sensed data from Indian Remote Sensing Satellite IRS‐1C Linear Imaging Self‐Scanner (LISS‐III) and field‐based methods were synergistically used to model plant richness on 1:50,000 scale. It was found that the sanctuary is dominated by East Himalayan Moist Temperate Forest (55.50%), followed by Rhododendron Forest (23.77%), Degraded Forest (6.66%) and Hemlock Forest (0.78%). The vegetation map prepared through digital interpretation of satellite imagery was subjected to landscape analysis and assessment of biotic disturbance in terms of disturbance index. The disturbance index together with species richness, ecosystem uniqueness, total importance value and terrain complexity was modeled to assess the plant richness in this unique sanctuary. Out of the 120 km2 of the total geographical area of the sanctuary, 28.45 per cent was found to possess very high plant richness followed by high (50.84%), medium (6.96%) and low richness (13.75%). It was noted that plant richness assessment at ecosystem level presents a more realistic picture than at landscape level. The study demonstrated that remote sensing coupled with landscape analysis, ground inventory data and geospatial modeling holds good potential for rapid and operational assessment of plant richness.  相似文献   

7.
A study on land degradation in the upper catchment of river Tons, a tributary of Yamuna river, in Uttarkashi district of the Uttarakhand state, was carried out using on-screen visual interpretation of IRS LISS-III + PAN merged data. The study area, which is largely mountainous, includes Govind Wildlife Sanctuary and National Park. Vegetation cover, slope and erosion status were used as criteria for the delineation of four major land degradation categories viz., undegraded, moderately degraded, degraded and severely degraded. More than 50 per cent of the study area is reported to be covered with snow and grassland. The moderate to severely degraded area worked out to be 42.4 per cent of the total area. The 32.8 per cent of area was found to be moderately degraded, followed by degraded (6.63%) and severely degraded (2.88%) areas. The depletion of vegetation cover on mountainous terrain and subsequent cultivation without proper protection measures is the reason for severe soil erosion and land degradation. In view of the existing land degradation situation, the catchment requires immediate treatment on priority for the sustenance of agriculture and wild life. It is expected that these measures will reduce the silt load in the river Tons and eventually, in river Yamuna.  相似文献   

8.
Monthly time series, from 2001 to 2016, of the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) from MOD13Q1 products were analyzed with Seasonal Trend Analysis (STA), assessing seasonal and long-term changes in the mangrove canopy of the Teacapan-Agua Brava lagoon system, the largest mangrove ecosystem in the Mexican Pacific coast. Profiles from both vegetation indices described similar phenological trends, but the EVI was more sensitive in detecting intra-annual changes. We identified a seasonal cycle dominated by Laguncularia racemosa and Rhizophora mangle mixed patches, with the more closed canopy occurring in the early autumn, and the maximum opening in the dry season. Mangrove patches dominated by Avicennia germinans displayed seasonal peaks in the winter. Curves fitted for the seasonal vegetation indices were better correlated with accumulated precipitation and solar radiation among the assessed climate variables (Pearson’s correlation coefficients, estimated for most of the variables, were r ≥ 0.58 p < 0.0001), driving seasonality for tidal basins with mangroves dominated by L. racemosa and R. mangle. For tidal basins dominated by A. germinans, the maximum and minimum temperatures and monthly precipitation fit better seasonally with the vegetation indices (r ≥ 0.58, p < 0.0001). Significant mangrove canopy reductions were identified in all the analyzed tidal basins (z values for the Mann-Kendall test ≤ ?1.96), but positive change trends were recorded in four of the basins, while most of the mangrove canopy (approximately 87%) displayed only seasonal canopy changes or canopy recovery (z > ?1.96). The most resilient mangrove forests were distributed in tidal basins dominated by L. racemosa and R. mangle (Mann-Kendal Tau t ≥ 0.4, p ≤ 0.03), while basins dominated by A. germinans showed the most evidence of disturbance.  相似文献   

9.
In remote sensing the identification accuracy of mangroves is greatly influenced by terrestrial vegetation. This paper deals with the use of specific vegetation indices for extracting mangrove forests using Earth Observing-1 Hyperion image over a portion of Indian Sundarbans, followed by classification of mangroves into floristic composition classes. Five vegetation indices (three new and two published), namely Mangrove Probability Vegetation Index, Normalized Difference Wetland Vegetation Index, Shortwave Infrared Absorption Index, Normalized Difference Infrared Index and Atmospherically Corrected Vegetation Index were used in decision tree algorithm to develop the mangrove mask. Then, three full-pixel classifiers, namely Minimum Distance, Spectral Angle Mapper and Support Vector Machine (SVM) were evaluated on the data within the mask. SVM performed better than the other two classifiers with an overall precision of 99.08%. The methodology presented here may be applied in different mangrove areas for producing community zonation maps at finer levels.  相似文献   

10.
Vegetation cover classification in Sariska National Park and surroundings   总被引：2，自引：0，他引：2  
Appraisal of spatial distribution of vegetation types is an important aspect for wildlife habitat suitability and ecological studies. Remote sensing provides quick, accurate and cost and time effective methods for vegetation cover mapping. In the present study Landsat MSS data was digitally classified into various land use/forest type classes. Forested land was about 52 per cent of the study area. Four forest types, namelyAnogeissus pendula, Boswellia serra ta, mixedAnogeissus-Butea and mixed Acacia-Zizyphus occupied 28.47 percent, 6.60 percent, 18.60 percent and 9.70 percent of the forested land, respectively. The area under National Park was 51.28 percent of total study area. About 61 percent of the Park area was under tree-covered vegetation. Overall accuracies for classified and smoothened-classified images were 89.37 percent and 91.96 percent, respectively. The vegetation of the area is controlled by topography and edaphic factors.  相似文献   

11.
The study reported herein deals with the utility of satellite remote sensing techniques for land evaluation for agricultural land use planning. False colour composite of Landsat imagery in the scale of 1:250,000 was visually interpreted for physiography that formed the base for mapping soil and land resources in the field. The small-scale soil map thus prepared has thirteen map units with association of soil families. Soil and land resource units shown on these small-scale maps were evaluated for their suitability for growing sorghum crop by matching the relevant land qualities against the land requirements for sorghum. The land evaluation carried out for growing sorghum crop in the study area revealed that about 38.6 per cent is highly suitable (S1), 31.5 per cent moderately suitable (S2) and 24.5 per cent marginally suitable (S3). An area of about 5.4 per cent is not suitable, of which 3.0 per cent is currently not suitable (N1) and 2.4 per cent permanently not suitable for growing sorghum crop.  相似文献   

12.
The land use information collected for Dehlon block of Ludhiana district, Punjab from the analysis of the IRS-1B LISS-II data for the year 1993 and IRS PAN data for the year 1997 and SOI topographical maps for 1964 revealed a large change in the area of different land use categories during the period from 1964 to 1997. The agricultural land covering an area of about 94.14 per cent in 1964 reduced to 90.26 per cent in 1997. while the area under rural settlements increased from 312 ha in 1964 to 1162 ha in 1997. An extra area of about 169 ha under waste land was added during the period under study making total waste land area to about 400 ha in 1997. However, the block lacks the forest cover of the required limit. Considerable change in living environment was observed in the block. Number of persons per unit settlement area (ha) being 213.3 in 1964 reduced to 97.1 in 1991; it indicate that the living standard of the people of the block has improved with the changed cropping pattern and increased agricultural production during the period from 1964 to 1991.  相似文献   

13.
基于Sentinel-2的潮间红树林提取方法   总被引：1，自引：0，他引：1  
位于潮间带的红树林可能在高潮时被海水淹没的特点，使得传统的植被提取方法在红树林信息提取方面存在局限性。本文在对比分析了出露的红树林、高潮水位淹没的红树林、海水水体的光谱特征后，提出了一种利用归一化潮间红树林指数（NIMI）提取潮间带红树林的方法。该指数是由植被强吸收的红波段，强反射的两个红边波段和近红外波段组成的归一化表达式。利用该指数对福建省龙海九龙江口湿地的红树林进行了分类提取，提取结果与高分二号影像目视验证和现场调查结果进行了对照。结果显示，该方法提取红树林的用户精度达到93.98%，并显著优于利用归一化水体指数（NDWI）、归一化植被指数（NDVI）及随机森林的结果。  相似文献   

14.
氮素是植被整个生命周期的必要元素,红树林冠层氮素含量（CNC）遥感估算对红树林健康监测具有重要意义。以广东湛江高桥红树林保护区为研究区,本文旨在基于Sentinel-2影像超分辨率重建技术进行红树林CNC估算和空间制图。研究首先基于三次卷积重采样、Sen2Res和SupReMe算法实现Sentinel-2影像从20 m分辨率到10 m的重建;然后以重建后的影像和原始20 m影像为数据源构建40个相关植被指数,采用递归特征消除法（SVM-RFE）确定CNC估算的最优变量组合,进而构建CNC反演的核岭回归（KRR）模型;最后选取最优模型实现CNC制图。研究结果表明：基于Sen2Res和SupReMe超分辨率算法的重建影像不仅与原始影像具有很高的光谱一致性,且明显提高了影像的清晰度和空间细节。红树林CNC反演波段主要集中在红（B4）、红边（B5）、近红外波段（B8a）以及短波红外波段（B11和B12）,与“红边波段”相关的植被指数（RSSI和TCARIre1/OSAVI）也是红树林CNC反演的有效变量。基于3种方法重建后10 m的影像构建的模型反演精度（R2val>0.579）均优于原始20 m的影像（R2val=0.504）;基于Sen2Res算法重建影像构建的反演模型拟合精度（R2val=0.630,RMSE_val=5.133,RE_val=0.179）与基于三次卷积重采样重建影像的模型拟合精度（R2val=0.640,RMSE_val=5.064,RE_val=0.179）基本相当,前者模型验证精度（R2cv=0.497,RMSE_cv=5.985,RE_cv=0.214）较高且模型变量选择数量最为合理。综合重建影像光谱细节及模型精度,基于Sen2Res算法重建的Sentinel-2影像在红树林CNC估算中具有良好的应用潜力,能为区域尺度红树林冠层健康状况的精细监测提供有效的方法借鉴和数据支撑。  相似文献   

15.
The world’s largest mangrove ecosystem, the Sunderbans is experiencing multidimensional threats of degradation. The present study was aimed to understand these problems and search for proper remedies by applying suitable remote sensing technologies. South-western parts of Indian Sunderbans Biosphere Reserve had been chosen for assessment of land use/land cover changes in between 1975 and 2006 by using multitemporal Landsat data. Results indicated considerable reduction of open mangrove stands and associated biodiversity mainly in the forest-habitation interference zones of Sunderbans. On the contrary, increase in the coverage of dense mangroves in the reserved forests had been observed indicating the existence of proper centralized management regimes. Overall, a cumulative loss of approximately 0.42% of its original mangrove cover in between 1975 and 2006 had been estimated for this part of the Sunderbans which was at parity with the findings of other studies in the Sunderbans or similar mangrove ecosystems of the tropics. Expansion of non agricultural lands in the last two decades was found to be related with the growth of new settlements, tourism infrastructure, and facilities. This transformation was attributed to the shifting of local peoples’ interest from traditional forestry and subsistence farming towards alternative occupations like shrimp culture, coastal tourism, and commercial fishing although environmentally hazardous livelihood activities like collection of prawn seeds along the riverbanks were still persistent.  相似文献   

16.
Mangroves are one of the most productive ecosystems known for provisioning of various ecosystem goods and services. They help in sequestering large amounts of carbon, protecting coastline against erosion, and reducing impacts of natural disasters such as hurricanes. Bhitarkanika Wildlife Sanctuary in Odisha harbors the second largest mangrove ecosystem in India. This study used Terra, Landsat and Sentinel-1 satellite data for spatio-temporal monitoring of mangrove forest within Bhitarkanika Wildlife Sanctuary between 2000 and 2016. Three biophysical parameters were used to assess mangrove ecosystem health: leaf chlorophyll (CHL), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). A long-term analysis of meteorological data such as precipitation and temperature was performed to determine an association between these parameters and mangrove biophysical characteristics. The correlation between meteorological parameters and mangrove biophysical characteristics enabled forecasting of mangrove health and productivity for year 2050 by incorporating IPCC projected climate data. A historical analysis of land cover maps was also performed using Landsat 5 and 8 data to determine changes in mangrove area estimates in years 1995, 2004 and 2017. There was a decrease in dense mangrove extent with an increase in open mangroves and agricultural area. Despite conservation efforts, the current extent of dense mangrove is projected to decrease up to 10% by the year 2050. All three biophysical characteristics including GPP, LAI and CHL, are projected to experience a net decrease of 7.7%, 20.83% and 25.96% respectively by 2050 compared to the mean annual value in 2016. This study will help the Forest Department, Government of Odisha in managing and taking appropriate decisions for conserving and sustaining the remaining mangrove forest under the changing climate and developmental activities.  相似文献   

17.
Impact of raining Vindhyan Sandstone, at 3D centres spread over 617 sq kms, by Open cast method in Bijolia area, Rajasthan on the environment, both trataral and social, assessed ever a period of 20 years (1971-91), revealed that it had affected nearly 20 times the area of lease. The study was earried out using Multidate remote sensing date for 1984 and 1991 and topographical maps of 1971, for change detection in land use pattern with the increase in mining activity. Whereas area covered fey mining activity increased by 35.3 times in 20 years, the forest cover decreased by 46.3 per cent The dense forest decreased by 90 per cent and the land under agriculture decreased by 12 per cent Consequently the waste land increased by 67.4 per cent. Hydrologtcal regime was affected by way of blocking the channels and lowering of water table. Solid particulate matter (SPM) values in mining centres were found to be more than double the normal, leading to diseases related to tungs and liver such as Silieosis. Bronchitis, Asthama and T.B. Nearly 25 per cent of workers were found to suffer from one or the other disease. 50 per cent of mine workers suffer from malaria as a consequence of breeding mosquitoes in stagnant waters m mine pits and labour colonies Noise levels at the active zones like drilling, blasting and mine service stations range from 96 to 125 dB as against the permissible limit of 75 dB affecting health and mental facility of mine workers.  相似文献   

18.
农牧交错带土地沙化遥感监测   总被引：17，自引：1，他引：17  
以内蒙古多伦县为研究对象,作时隔5a的两次遥感调查,对内蒙古东南部农牧业交错带的土地沙化进行监测。建立了土地沙化分类体系,把土地沙化与土地利用紧密联系,依据植被指数概念,采用了一组比值组合,有效地将土地沙化类别分层分离。通过第一次遥感调查,了解到多伦县由于过度耕种和过度放牧,致使土地沙化十分严重。经第二次调查对比分析,退耕还林、退牧还草的治沙效果显著,土地沙化发展趋势得到遏制,遥感监测为地方政府的防沙治沙起了重要作用。  相似文献   

19.
ABSTRACT

Mangroves are critical in the ecological, economic and social development of coastal rural and urban communities. However, they are under threat by climate change and anthropogenic activities. The Sunda Banda Seascape (SBS), Indonesia, is among the world’s richest regions of mangrove biomass and biodiversity. To inform current and future management strategies, it is critical to provide estimates of how mangroves will respond to climate change in this region. Therefore, this paper utilized spatial analysis with model-based climatic indicators (temperature and precipitation) and mangrove distribution maps to estimate a benchmark for the mangrove biomass of the SBS in six scenarios, namely the Last Inter-glacial Period, the current scenario (1950–2000) and all four projected Representative Concentration Pathways in 2070 due to climate change. Despite mangroves gaining more biomass with climate change (the increase in CO2 concentration), this paper highlighted the great proportion of below-ground biomass in mangrove forests. It also showed that the changes in spatial distribution of mangrove biomass became more variable in the context of climate change. As mangroves have been proposed as an essential component of climate change strategies, this study can serve as a baseline for future studies and resource management strategies.  相似文献   

20.
Accurate and reliable information on the spatial distribution of mangrove species is needed for a wide variety of applications, including sustainable management of mangrove forests, conservation and reserve planning, ecological and biogeographical studies, and invasive species management. Remotely sensed data have been used for such purposes with mixed results. Our study employed an object-oriented approach with the use of a lacunarity technique to identify different mangrove species and their surrounding land use and land cover classes in a tsunami-affected area of Thailand using Landsat satellite data. Our results showed that the object-oriented approach with lacunarity-transformed bands is more accurate (over-all accuracy 94.2% kappa coefficient = 0.91) than traditional per-pixel classifiers (overall accuracy 62.8% and kappa coefficient = 0.57).  相似文献   

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