Characterization of biophysical land units using remote sensing and gis

In the present study, an attempt has been made to characterize the biophysical land units in Kanholi bara river basin of sub-humid tropical ecosystem of central India using remotely sensed data, field surveys and GIS based multi-criteria overlay analysis. The geo-spatial database on elevation, slope, landforms, soil depth, soil erosion, land use/land cover and hydrogeomorphological parameters has been generated using IRS-ID LISS-III satellite data coupled with soil survey data in GIS. The methodology followed in characterization of biophysical land units in GIS includes assigning scores for different classes of the layers and weighatges for different layers based on their characteristics and degree of influence on desired output. GIS based ‘multi criteria overlay’ analysis reveals seventeen distinct biophysical land units in the river basin. Severe (50.5-59.5) to very severe (59.5) biophysical stress units are found in plateau spurs, isolated mounds, linear ridges, dissected plateau and escarpments. These zones are associated with severe to very severe erosion, steep to very steep, extremely shallow soils, poor to very poor groundwater prospects, wastelands and scrublands. The characterization of biophysical land units helps in analysis of their potentials, problems and stress environment to plan and execute site-specific landscape management practices and maximize the productivity from each biophysical land unit. The present study demonstrates that generation of geo-spatial database based on remotely sensed data and field surveys in GIS and their analysis helps great extent in characterization of biophysical land units and analysis of their stress environment for management.     

茅尾海入海河口池塘养殖污染状况遥感调查

针对广西茅尾海入海河口池塘养殖污染问题,本文利用无人机多光谱遥感影像和实测水质数据,建立了反映水体营养状态的叶绿素a (Chl-a)、化学需氧量(COD)、悬浮物(SS)、总氮(TN)、总磷(TP)5种水质参数,反演光谱特征及遥感反演模型,并利用湖泊综合营养指数法对水体富营养化状态进行评价。研究结果表明:①Chl-a与蓝、近红外波段相关性显著,COD与红、红边波段相关性显著,SS与红边波段相关性显著,TN与近红外波段相关性显著,TP与蓝、绿波段相关性显著;②在建立的几种水质参数反演模型中,二次多项式函数反演模型综合效果最佳;③池塘养殖区水体富营养指数多集中在60～80,属于中度和重度富营养化程度,且近岸水体富营养化程度大多低于远岸。     

1995—2019年北莉岛人工水产养殖遥感监测

有效监测人工水产养殖水面的分布变化对于海洋资源管理、生态环境保护、防灾减灾具有重要意义。本文以Landsat 5、SPOT 5和GF-1卫星影像为数据源,选择广东省北莉岛为研究区,使用线性光谱解混方法获取中等空间分辨率卫星影像的人工水产养殖水面面积,通过面向对象多尺度分割的方法结合支持向量机分类算法提取高空间分辨率卫星影像的人工水产养殖水面分布。研究结果表明,与单一卫星影像相比,综合多源中高空间分辨率卫星数据延长了人工水产养殖水面变化分析可追溯的时间跨度,提高了监测精度;联合光谱解混和面向对象分类方法开展人工水产养殖长时序遥感监测是可行的。近20多年来,北莉岛人工水产养殖水面的面积经历了先增加后缓慢减少的变化过程,1995—2000年平均增速为23.39 hm²/a,2000—2006年平均增速为23.95 hm²/a,2006—2019年平均减少速度为1.96 hm²/a。     

Modelling of non-point source pollution in a watershed using remote sensing and gis

Assessment of the environmental impact of Non Point Source (NPS) pollutants on a global, regional and localized scale is the key component for achieving sustainability of agriculture as well as preserving the environment. The knowledge and information required to address the problem of assessing the impact of NPS pollutants like Nitrogen (N), Phosphorus (P), etc., on the environment crosses several sub-disciplines like remote sensing, Geographical Information System (GIS), hydrology and soil science. The remote sensing data, by virtue of its potential like synopticity, multi-spectral and multi-temporal capability, computer compatibility, besides providing almost real time information, has enhanced the scope of automation of mapping dynamic elements, such as land use/land cover, degradation profile and computing the priority categorisation of sub-watersheds. The present study demonstrates the application of remote sensing, GIS and distributed parameter model Agricultural Non-Point Source Pollution Model (AGNPS) in the assessment of hazardous non-point source pollution in a watershed. The ARC-INFO GIS and remote sensing provided the input data to support modelling, while the AGNPS model predicted runoff, sediment and pollutant (N and P) transport within a watershed. The integrated system is used to evaluate the sediment pollution in about 2700 ha Karso watershed located in Hazaribagh area of Jharkhand State, India. The predicted values of runoff and sediment yield copared reasonably well with the measured values. It is important to emphasize that this study is not intended to characterise, in an exhaustive manner. Instead, the goal is to illustrate the implications and potential advantages of GIS and remote sensing based Hydrology and Water quality (H/WQ) modelling framework.     

太原市黑臭水体遥感识别与地面验证

城市黑臭水体整治是城市水环境治理的一项重要工作。本文通过构建黑臭水体遥感识别模型,解决城市黑臭水体整治过程中黑臭水体的识别问题,实现城市黑臭水体空间分布快速定位与排查。通过分析黑臭水体形成机理和试验数据,从光谱特征上构建反映水体清洁程度的光谱指数（WCI）,从图像特征上构建水体颜色、次生环境、河道淤塞、岸边带垃圾堆放等解译标志,综合光谱指数和解译标志共同进行黑臭水体遥感识别。利用该方法对太原市建成区内黑臭水体空间分布进行排查识别,共得到疑似黑臭河段14条,长度为52.530 km。经验证,除去断流影响外,遥感识别黑臭水体点位精度为92.86%,遥感识别黑臭河段长度精度为78.19%。在精度验证基础之上,进一步分析了黑臭水体遥感识别光谱指数和各项解译标志在黑臭识别中所占的权重,其中光谱指数和水体颜色二者权重最大,分别占29.60%和27.10%,是构成遥感识别黑臭水体的主要特征标志。通过两时相影像识别结果比对表明,WCI指数能够明显反应黑臭水体变化特征。因此,利用本文方法进行城市黑臭水体遥感识别具有很高的精度,在城市水环境整治过程中具有重要的应用价值。     

Habitat analysis for sambar in corbett national park using remote sensing and gis

Habitat analysis for sambar in terms of food, cover, water, space and extent of edge in Corbett National Park using remote sensing and GIS has been attempted. Other physical parameters include climate, topography, fire history, disturbance regimes, weeds etc. IRS-IB LISS II data (FCC, hardcopy) on 1:50.000 scale was interpreted to generate vegetation cover and density map. Other maps showing drainage, water bodies, roads, human habitations and contours were prepared using Survey of India topographical maps. During evaluation of sambar habitat information regarding habitat parameters and their tolerance was collected from existing literature as well as during field observations. Twenty-two transects of one km. length were laid down in all the strata randomly to collect information regarding the structure and composition of the forest and also habitat use (direct and indirect evidences) by sambar. This was then integrated using condition-based equations in the GIS domain to generate suitability maps. Actual sightings on the ground to a large extent supported the results.     

An assessment of biodiversity hotspots using remote sensing and GIS

This study focuses on the assessment of the status of world’s remaining closed forests (WRCF), population distribution, and protected areas in global biodiversity hotspots using remote sensing and Geographic Information System (GIS). Conservation International (CI) has identified 25 eco-regions, called biodiversity hotspots that are especially rich in endemic species and are particularly threatened by human activities. This study uses globally consistent and comprehensive geo-spatial data sets generated using rerriote sensing and other sources, and the application of GIS layering methods. The consistent data set has made it possible to identify and quantify relationships between the WRCF, human population, and protected areas in biodiversity hotspots. It is expected that such information will provide a scientific basis for biodiversity hotspots management and assist in policy formulations at the national and international levels.     

Remote sensing and geophysical survey applications for delineating near-surface palaeochannels and shallow aquifer in the United Arab Emirates

This study integrates remote sensing data and geoelectrical dipole–dipole resistivity to delineate near-surface palaeochannels and shallow aquifer in the northern part of Abu Dhabi Emirate, United Arab Emirates. The shuttle imaging radar images and shuttle radar topographic mission DEM were used to delineate near-surface palaeochannels visually based on the contrast between bright and dark tone and automatically using the eight-direction flow model. The delineated palaeochannels were validated by comparing the textural features evident from advanced land observing satellite-phased array type L-band synthetic aperture radar images and determining whether these patterns were different. Field observation and geoelectrical dipole–dipole resistivity method was used to define the depth of palaeochannels and lithology of the shallow aquifer. The remote sensing and geophysical investigations in the UAE, including the study area, indicate the presence of buried palaeochannels with south-west and north-west flow directions from Oman Mountain. The study area can be of economic importance to the local population.     

Remote sensing applications in the study of landuse and soils of aeolian cover op the western part of Haryana State

Multispectral and multitemporal landsat-FCC of 1:250,000 and transparancies on 1:1000,000 scales of bands 4, 5, 6 and 7 were interepreted to identify and delineate the areas under varying intensities of dunal activity in the western part of Haryana State comprising an area of 12610 sq. km. CCTs of some representative areas were also interpreted on the Multispectral Interactive Data Analysis System. Field checks were made to correlate the laboratory interpretation and the ground truth. The study areas were differentiated into the following units: (1) Sandy desert zone: No cultivation on dune tops except some shrubs, (2) Aeolian cover with sandy hummocks: low intensity cultivation, (3) Plain with aeolian cover: moderately cultivated, (4) Plain: Moderately to intensively cultivated. The major soils in association were Typic Torripsamments/Ustipsamments/Ustorthents/Ustifluvents/Calciorthids and Natric Camborthids.     

Remote sensing and GIS in identification of soil constraints for sustainable development in Bhilwara district,Rajasthan

Soil is an integral part of ecosystem nurturing the biological system. Sustainable management of soil resources based on the consideration of constraints is the key to check land degradation and maintain productivity of biological system. To meet the objective remote sensing and GIS technology has been employed for identification of soil constraints in resource potential Bhilwara district. IRS LISS-III FCC images were interpreted for soil constraints using physiography soil approach, verified through field checking and laboratory analysis. On IRS LISS-III FCC images the salt affected soils of Kotri and Taswaria appeared in bright white to light grey tone, smooth texture with white mottles. These were also verified during ground truth and soil analysis for salinity (EC 2.90–3.32 dS m⁻¹) and sodicity (pH 9.50–9.86 and ESP 17.60–19.05). Similarly on the LISS III FCC, constraints due to water erosion near Bir, Sareri and Vijaypura soil series were apparent in light grey to whitish tone, intercepted by medium grey streaks indicating streams and exposed sub-soil. The constraints due to shallow depth associated with rock out crops and hilly areas of Balda and Delwara series appeared in greenish grey tone and coarse texture. There was close relationship between image characteristics, field observation and analytical data.     

Morphotectonic analysis in Anandpur Sahib area,Punjab (India) using remote sensing and gis approach

Anandpur Sahib area of Rupnagar district (Punjab) was investigated using an integrated multi-disciplinary approach of geomorphological, structural, drainage and morphotectonic analysis through satellite data and GIS. Most commonly used geomorphic indices viz., channel sinuosity, drainage basin asymmetry, basin elongation ratio, mountain front sinuosity and valley floor to valley width ratio index have been used to identify the geomorphic indicators of active tectonics in the area. Existence of fluvial anomalies viz., abrupt changes in flow direction, flow against gradient, beheaded streams and river terraces reflect the strong structural control on the fluvial features. Asymmetric nature of drainage basin, elongated nature of the sub-watersheds, straight to curvilinear mountain fronts and narrow incised valley floors further substantiate the role of active tectonics in the region.     

青藏高原纳木错湖冰物候变化遥感监测与模拟

湖冰物候是反映区域气候变化的直观指标.由于青藏高原湖冰物候的地面观测不足,遥感与模拟成为动态监测湖冰物候变化并揭示其变化机理的重要途径.本文以纳木错为例,通过不同遥感方法获取了纳木错2000年-2015年湖冰物候的动态变化.在此基础上,将遥感与物理基础清晰的湖泊过程模型相结合,重建了纳木错1963年-2018年的湖冰物...     

Morphometric analysis of sub-watersheds in the pavagada area of Tumkur district,South India using remote sensing and gis techniques

The study area covers 570 km² comprising of 9 sub-watersheds (Dalavayihalli, Maddalenahalli, Talamaradahalli, Puluvalli tank, Nagalamadike, Gowdatimmanahalli, Naliganahalli, Devadabetta and Byadanur) range from 49 to 75 km² forming part of Pennar river basin around Pavagada. The drainage network of 9 sub-watersheds was delineated using remote sensing data - Geocoded FCC of bands - 2 3 4 of IRS 1 C and 1 D (LISS III+PAN merged) on 1:50,000 scale and SOI topomaps were used as reference. The morphometric analysis of 9 sub-watersheds has been carried out using GIS softwares - Arclnfo and Are View. The drainage network shows that the terrain exhibits dendritic to sub-dendritic drainage pattern. Stream orders ranges from fourth to fifth order. Drainage density varies between 1.55 and 2.16 km/ km² and has very coarse to coarse drainage texture. The relief ratio range from 0.006 to 0.021. The mean bifurcation ratio varies from 3.21 to 4.88 and falls under normal basin category. The elongation ratio shows that Devedabetta sub-watershed possesses circular shape while remaining sub-watersheds mark elongated pattern. Hence from the study it can be concluded that remote sensing techniques proved to be a competent tool in morphometric analysis.     

高分二号的沈阳市黑臭水体遥感识别

中国城市黑臭水体情况严重,基于遥感监测黑臭水体刚刚起步,很多问题待解决。以沈阳市城市建成区内主要河流为研究区,于2015年—2016年开展地面调查,获取了浑河和蒲河46个一般水体的样点,和辉山明渠、满堂河、细河以及微山湖路附近、丁香湖北部50个黑臭水体的样点数据,包括水面光谱和主要水质参数。分析了黑臭水体与一般水体的光谱特征,发现城市黑臭水体反射率光谱在绿光—红光波段变化比一般水体平缓,基于这一特点提出了一种基于反射率光谱指数BOI(Black and Odorous water Index)的黑臭水体识别模型,并将其与红绿波段比值指数进行对比,具有更好的识别精度。结果表明:(1)基于遥感反射率(Rrs)计算的BOI小于0.065时,可判为黑臭水体。(2)由于GF2水体图像精确大气校正存在困难,可以利用瑞利散射校正反射率(Rrc)替代R_(rs),BOI小于阈值0.05时,可判别为黑臭水体;同时模拟证明,当气溶胶光学厚度逐渐增大时,黑臭水体与一般水体的光谱差异将逐渐减小,因此这种方法主要适用于比较清晰的图像、气溶胶光学厚度比较小(如AOT(550)≤0.5时)。(3)基于R_(rc)的BOI模型可以较好的应用于GF2图像上,具有较好的识别精度。对2015年—2016年3景GF-2影像提取的结果显示,满堂河和新开河黑臭现象得到逐步改善,辉山明渠黑臭现象依然严峻。本文发展的黑臭水体遥感识别算法主要是基于沈阳黑臭水体的光谱特征,仅在沈阳市进行了验证,将来还需在其他城市进一步验证,并且需要更多地考虑多种因素对水体反射率的影响。     

Remote sensing classification approach to large-scale crop cultivation identification: A case study of the Aral Sea Basin

Since the collapse of the Soviet Union, the crop cultivation structure in the Aral Sea Basin has changed dramatically, and these changes are worth studying. However, historical crop remote sensing mapping at the watershed scale remains challenging, especially crop misclassification at the cropland edge due to mixed pixels. Therefore, we proposed a field segmentation approach to constrain field edges based on time-series Sentinel-2 remote sensing images and the Google Earth Engine platform and then employed the random forest algorithm to perform crop classification based on time series Landsat/Sentinel-2 images and crop phenology information to produce historical crop maps in the Aral Sea Basin from the 1990s onward. The results showed that the intersection over union between the extracted field edges and in situ-measured field size data was 0.65. The overall accuracy of crop mapping was 95.2% in 2019. Then, we extended our method to historical mapping over the 1991–2015 period with accuracies ranging from 82.8% to 91.3%. Moreover, our method applied to historical mapping works well in terms of accuracy and policy matching. These findings indicate that our method can accurately distinguish cropland edges to reduce classification errors due to mixed pixels. This method is promising for solving the cropland edge problem for historical crop mapping in the Aral Sea Basin and can potentially provide a reference for historical crop classification in other watersheds of the world.     

基于高分遥感的金沙江流域滑坡识别——以巴塘县王大龙村为例

金沙江流域因两岸地势陡峭、软弱岩层发育、降雨集中等,使得流域内滑坡灾害分布密集。高分辨率遥感是滑坡识别的重要手段,但通过目视解译法开展的大范围滑坡灾害识别,具有工作量大、效率低的特点。针对此问题,本文采用基于面向对象的分类方法,提出了利用滑坡灾害的光谱、形状、空间等特征进行区域内滑坡灾害的快速识别。同时,选取金沙江流域巴塘县王大龙村区段进行了滑坡识别提取试验,区域内利用面向对象分类方法识别出滑坡18处,其中12处与目视解译结果相同,一致性为75%;发现3处目视解译未识别出的隐蔽性滑坡。结果表明,该方法识别效果较好,可为后续的金沙江流域乃至川藏铁路沿线的大范围滑坡识别提取及滑坡编目工作提供参考。