Land use/land cover mapping and change detection in part of eastern ghats of tamil nadu using remote sensing and GIS

In the present study an attempt has been made to map land use/land cover and change detection analysis in Kolli hill, part of Eastern Ghats of Tamil Nadu, using remote sensing and GIS. About 467 ha increase has been observed in single crop category and about 434 ha decrease has been observed in land with or without scrub category. Majority of the area (13639 ha) is under scrubland. Lesser changes could be noticed in double crop, plantation and barren/rocky categories. Necessary measures should be taken to utilize the scrubland and to prevent the conversion of cropland into scrubland. The identified wastelands, which are suitable for agriculture, have to be utilized optimally to improve the economy of the people.     

Modeling the spatial distribution of above-ground carbon in Mexican coniferous forests using remote sensing and a geostatistical approach

Forest conservation is considered an option for mitigating the effect of greenhouse gases on global climate, hence monitoring forest carbon pools at global and local levels is important. The present study explores the capability of remote-sensing variables (vegetation indices and textures derived from SPOT-5; backscattering coefficient and interferometric coherence of ALOS PALSAR images) for modeling the spatial distribution of above-ground biomass in the Environmental Conservation Zone of Mexico City. Correlation and spatial autocorrelation coefficients were used to select significant explanatory variables in fir and pine forests. The correlation for interferometric coherence in HV polarization was negative, with correlations coefficients r = −0.83 for the fir and r = −0.75 for the pine forests. Regression-kriging showed the least root mean square error among the spatial interpolation methods used, with 37.75 tC/ha for fir forests and 29.15 tC/ha for pine forests. The results showed that a hybrid geospatial method, based on interferometric coherence data and a regression-kriging interpolator, has good potential for estimating above-ground biomass carbon.     

Identification of understory invasive exotic plants with remote sensing in urban forests

Invasive exotic plants (IEP) pose a significant threat to many ecosystems. To effectively manage IEP, it is important to efficiently detect their presences and determine their distribution patterns. Remote sensing has been a useful tool to map IEP but its application is limited in urban forests, which are often the sources and sinks for IEP. In this study, we examined the feasibility and tradeoffs of species level IEP mapping using multiple remote sensing techniques in a highly complex urban forest setting. Bush honeysuckle (Lonicera maackii), a pervasive IEP in eastern North America, was used as our modeling species. Both medium spatial resolution (MSR) and high spatial resolution (HSR) imagery were employed in bush honeysuckle mapping. The importance of spatial scale was also examined using an up-scaling simulation from the HSR object based classification. Analysis using both MSR and HSR imagery provided viable results for IEP distribution mapping in urban forests. Overall mapping accuracy ranged from 89.8% to 94.9% for HSR techniques and from 74.6% to 79.7% for MSR techniques. As anticipated, classification accuracy reduces as pixel size increases. HSR based techniques produced the most desirable results, therefore is preferred for precise management of IEP in heterogeneous environment. However, the use of MSR techniques should not be ruled out given their wide availability and moderate accuracy.     

松辽盆地西部斜坡区烃渗漏蚀变信息遥感探测

使用陆地卫星ETM+7图像对松辽盆地西部斜坡区进行稠油探测,图像增强方法有主成分分析、波段比值和假彩色合成等.主成分因子1,3,4,5-PC3(1,3,4,5主成分分析的第3主成分),1,3,5,7-PC3,2,3,5,7-PC3和3,4,5,7-PC4与波段比值3/1,4/3,7/5和(4/3)-(2/3)等用丁假彩色合成,在合成影像上圈定烃渗漏蚀变区域.结果表明烃渗漏蚀变区域与地质背景密切相关,与下伏油藏的分布大致相符.     

Mapping of wastelands through remote sensing techniques and their reclamation—A case study

Wasteland map (1∶100,000) of Rewasa catchment (Sikar district) has been prepared using aerial photographs and Landsat TM imagery. Thematic Mapper data were helpful in identifying the types of wastelands and details could be derived from the aerial photographs. The types of wastelands identified are sands, gullied land, salt affected areas, and barren rocky area. Depending upon the nature of wasteland, suitable rehabilitation measures like plantations, afforestation have been proposed.     

Assessment and monitoring of estuarine mangrove forests of Goa using satellite remote sensing

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¨     

DT-CWT结合MRF的遥感图像变化检测

为了解决多尺度遥感图像变化检测在降噪时丢失大量高频信息及单一像素孤立性的问题,提出了一种双树复小波变换DT-CWT(Dual-tree Complex Wavelet Transform)和马尔可夫随机场MRF(Markov Random Field)相结合的非监督遥感图像变化检测算法,首先采用DT-CWT对差异图像进行多尺度分解,并根据MRF模型分割算法提取高频区域的变化特征,然后进行相应层的高、低频重构,再对重构后的各层建立MRF模型并根据贝叶斯最大后验概率准则MAP(Maximum A Posterior)进行最终分割,最后对各层分割结果进行求交融合,得到最终的变化检测结果掩膜图。对比实验结果表明,该方法在去除杂点和噪声的同时能够较好地保留高频信息,并且边缘检测更加平滑,具有较高的变化检测精度和很好的鲁棒性。     

Potential application of remote sensing in monitoring ecosystem services of forests,mangroves and urban areas

The application of remote sensing (RS) techniques to monitor ecosystem services has increased in recent years. Nevertheless, the potential application of RS to monitor some of ecosystem services is still challenging. The paper reviews the applications of RS to monitor ecosystem services of forests, mangroves and urban areas. Satellite data provide substantial information about dynamics of environmental changes over time from local to global scale. These information are useful data sources for the people who are involved in the on-going evaluation and decision-making process to manage ecosystem. Many recent research papers on the topic were reviewed to find new applications and limitations of RS for monitoring ecosystem services. Advanced RS techniques have high potential to monitor ecosystem services with the advancement of sensors ranging from aerial photography to high and medium resolution optical RS and from hyperspectral RS to microwave RS.     

粤港澳大湾区红树林长时间序列遥感监测

随着遥感数据量的爆发式增长,对变化过程分析的精细化要求与本地算力不足之间的矛盾日益突出。GEE（Google Earth Engine）地理云平台的出现,解决了用户算力紧张的行业痛点。本文以粤港澳大湾区为研究区,在GEE的支持下,构建1987年—2020年年度湿地分类数据集,分析大湾区红树林的时间阶段性特征和空间扩张过程,结合连续长历时分析对变化时间点的准确识别,揭示了保护区设立与滩涂造林等工程在红树林保护与修复中的积极成效。主要结论有：（1）截止到2020年,大湾区共有红树林2174 ha,81%的红树林集中在深圳湾、淇澳岛和镇海湾;（2）大湾区的红树林经历了由平稳发展（1987年—2003年）到快速增长（2003年—2020年）的变化过程,其主要增量来源于镇海湾（40%）和淇澳岛（28%）;（3）淇澳岛和镇海湾的红树林仍处于快速增长期,但淇澳岛增速最快,从2002年至今面积翻了30倍,深圳湾则在早期的快速增长（1987年—2009年）后进入平稳期（2009年—2020年）;（4）由于保护区设立时间较早,深圳湾成为大湾区唯一一个形成稳定核心区的红树林分布区,镇海湾虽然拥有最大的红树林面积,但林道狭窄,景观破碎,生态系统反而更加脆弱;（5）设立自然保护区和滩涂造林都对红树林面积增长起到了积极作用。本研究为大湾区海岸带湿地生态系统保护与修复提供科学的证据支持,对沿海生态屏障建设具有一定的指导作用。     

油松毛虫灾害遥感监测及其影响因子分析

辽宁西部大面积的油松(Pinus tabulaeformis)人工林长期受到油松毛虫(Dendrolimus tabulaeformis)的危害,通过遥感技术,可以及时、高效、精准地对此大面积灾害进行监测,并获知地形、气象因子对其的影响。本文利用遥感和地理信息系统(GIS)技术,使用TM、ETM+数据,通过近红外与红光波段反射率的比值RVI,对油松的受灾程度进行了有效监测。前人的研究发现:油松毛虫易在干燥、温暖的环境爆发,本文将监测分类结果与地形、气象数据叠加后,分析发现结果亦与油松毛虫的生物学特性相吻合,由此逆向证明了监测结果的可靠性。通过对影像灰度直方图的分析,发现近红外波段对轻度的虫害敏感;红光波段对重度的虫害敏感。对影响因子的分析发现:油松毛虫在阳坡,坡度缓的地区危害更剧烈;在日照时数长、降雨少、积温低的地区,油松的受灾程度更重。此结论为预测虫害爆发的概率提供了依据。本研究表明:在森林灾害的遥感工作中,利用监测对象的生物生态学特性,可以在实地调查数据不足,难以直接对监测结果进行评价的情况下,判断结果的可靠性。利用此方法,一定程度上可以减少调查的工作量,降低外业的难度。     

Landuse/Landcover change detection through remote sensing and its climatic implications in the godavari delta region

Interpretation of multi-date satellite imagery has revealed changes in land use/land cover pattern in the Godavari deltaic region during the past 26 years. The area under intensive agriculture has increased from 1459 to 3500 km² and the extent of wetland from 368 to 648 km² during the period 1973-1999, while the seasonal fallow has decreased by 2321 km². Analysis of the climatic data of 1970-1998 from different stations covering the entire 5100 km² area of the delta indicated that the day time temperatures have decreased by 0.2° C to 0.7° C, while the night time temperatures have increased by 0.5° C to 0.6° C during the past three decades. At the same time the rainfall has increased by about 75 to 479 mm. These trends in the climatic parameters arc attributed to the increased vegetation cover and wetland extent in the Godavari deltaic region.     

条件随机场框架下基于随机森林的城市土地利用/覆盖遥感分类

针对"基于像素的条件随机场(conditional random fields,CRFs)模型能否在m级分辨率的多光谱遥感图像分类中表现良好"的问题,提出了集成图像的光谱、方向梯度直方图和多尺度多方向Texton纹理等多种线索的CRFs模型定义方法。利用上述特征,选择随机森林(random forests,RF)定义CRFs关联势函数;利用特征对比度加权的Potts函数定义CRFs交互势函数,并且建立了多标签的RF-CRFs模型;对该模型进行分项参数训练以及基于图割的α-膨胀算法推理;利用典型城区的Quick Bird多光谱图像进行模型的验证与精度评价。结果表明RF-CRFs模型的分类精度可达82.52%以上,比RF分类器的分类精度提高了3.35%。     

Mapping and management of flood-affected areas through remote sensing a case study of Sirsa district,Haryana

The flood-affected areas in Siras district, Haryana, was mapped during 1993 using IRS-1A LISS-II data. Two categories of flood-affected areas viz. (i) standing water, and (ii) wet areas were identified. The flood water was standing in an area of 19676.25 ha, while wet areas covered 16773.75 ha., Silting of Ottu reservoir, mismanagement of river banks and bunds and lack of drainage system were identified, as major causes of floods. Three management practices including (i) desilting of Ottu reservoir, (ii) proper management of river banks and bands, and (iii) constructions of drains to flush out flood water have been suggested to contain the fury of floods. This study will be useful to the planners and administrators in the planning of flood-affected areas.     

Monitoring of forest cover type and landuse classes through remote sensing techniques

Ranikhet tahsil being situated in mountaineous region of the Himalaya has been influenced by fast changes in forest cover and landuse during the recent past. Remote sensing technique has been employed to monitor the changes in forest cover and imporant landuse classes. Landsat MSS (FCC) and Landsat TM (FCC) of 1972 and 1986 respectively has been visually interpreted. The study highlights the potential of remote sensing techniques for monitoring the changes in forest cover and land use classes.     

森林扰动遥感监测研究进展

作为陆地生态系统的主体,森林的碳循环与碳蓄积对研究陆地生态系统起着重要作用,但目前森林扰动资料的缺乏在很大程度上影响着区域森林碳通量的估算精度。在对森林扰动监测方法和监测指数进行总结的基础上,对几种森林扰动监测指数进行了比较研究。鉴于当前基于长时间序列的森林扰动研究主要集中在北美国家,国内鲜有系统报道,因此,针对我国森林变化特点,结合长时间序列扰动分析方法和适宜的扰动监测指数,研究适用于我国森林的扰动监测模型具有重要的理论意义和应用价值。     

浒苔遥感监测方法的研究进展

综述了目前国内外浒苔遥感监测方法,阐述了单波段阈值分割法、多波段比值法和辐射传输模型法的优缺点,指出多波段比值法是应用最广和有效的方法,主要有双波段比值法、归一化植被指数法、浮游植物指数法和归一化藻类指数法4种.辐射传输模型法主要用于水下悬浮浒苔的监测,目前应用较少,还处于起步阶段.而研究浒苔与其他浮游植物的差异,深入研究水下悬浮浒苔的遥感监测方法,发展解决现有监测能力不足与监测信息使用者需求之间矛盾的手段和方法是未来浒苔遥感监测的主要研究方向.     

Mapping of soil degradation hazards by remote sensing in Hanumangarh district (western Rajasthan)

In the present study, efforts have been made to identify and map areas affected by various soil degradation processes in Hanumangarh district of western Rajasthan. Soil degradation processes were identified by using IRS-1B satellite image of the year 1998, SOI toposheets, ground truth verification and soil studies. The kind, extent and degree of soil degradation have been mapped in an area of 9703 km². The study reveals that the soil degradation problems were mainly due to wind erosion/deposition and water-logging, followed by salinity/alkalinity, water erosion and wind and water erosion combinedly. Nearly 38.7% area is subjected to slight and moderate degradation, which can easily be combated by adopting the suggested techniques and 17.1% area is free of hazard. Soil degradation processes have resulted in the loss of organic carbon, available Phosphorus and Potassium. Soil degradation due to water logging/salinization has also shown a significant increase in electrical conductivity and available potassium content of soil.     

深度神经网络条件随机场高分辨率遥感图像建筑物分割

高分辨率遥感图像建筑物分割的实质是构建一个输入图像到分割结果之间的高维强非线性映射模型。然而,建筑物可能遍布整幅遥感图像,则在语义分割过程中,当前像素点可能与非邻域的像素点存在直接关系。为了更加精确地逼近建筑物分割的真实映射模型,克服道路、建筑物错层和阴影的影响,提高分割精度,本文以深度残差神经网络为基础,构建Encoder-Decoder的深度学习架构,自动提取建筑物的特征,学习建立高维强非线性分割模型;同时,通过条件随机场的成对势函数调节当前像素点与其他像素点之间的关联关系,从而构成全连接条件随机场对Encoder-Decoder的分割结果进行调节,提升分割精度。在全连接条件随机场的计算过程中,采用循环神经网络的运行机制来完成均值场的计算,这将条件随机场与深度神经网络有机融合,实现了Encoder-Decoder和全连接条件随机场参数的同步训练。实验结果表明,本文采用的深度神经网络条件随机场方法能有效克服道路、建筑物错层和阴影的影响,提升高分辨率遥感图像中建筑物的分割精度;同时,在一定范围内对多分辨率遥感图像具有较好的泛化能力。     

被动微波遥感积雪参数反演方法进展

雪深(snow depth,SD)和雪水当量(snow water equivalent,SWE)是气候水文研究中的重要参数,在雪灾监测中尤为重要。首先,简要介绍了被动微波遥感SD和SWE反演算法的物理基础——积雪微波辐射传输模型,分析了不同微波频段、不同特点的积雪微波辐射和散射特性。然后,根据前人的研究从数学角度将反演算法分为线性亮温梯度法和基于先验知识法,总结了2类算法的优势和局限性:线性亮温梯度法相对简单、速度快,一般只适用于特定的研究区;先验知识法需要获取研究区的样本数据,并反复训练才能达到较好的精度,但对样本的独立性及其均值差异显著性的要求较高。最后,重点介绍了我国风云三号微波成像仪(FY-3 MWRI)的全球SD和SWE反演算法和针对中国区域的改进算法,并对未来的研究热点进行了展望。