Canadian Landsat studies for monitoring agricultural intensification and urbanization: A summary

This report summarizes a major paper reviewing the progression of work using Landsat for land use and agricultural monitoring in Canada since 1973. From the launch of Landsat to the present, the focus has moved from using simple visual techniques for interpretation of photographic products to the use of conceptually simple methods which now employ the power of special-purpose image analysis hardware and the standard geometrically corrected products available in Canada. Outlined in the major paper are studies on urban growth, large area land use mapping, crop studies (related to both crop area estimates and erosion potential), assessment of changes in vegetation vigour and clearing of land in areas which were devoted to both dry land farming and forestry. This report emphasizes developments in land use studies.     

Canadian landsat studies for monitoring hydrologic conditions and coastal environments: A summary

This report summarizes a major paper reviewing Canadian work using Landsat imagery for studying changes in lakes and in coastal environments. The nature of environmental change is discussed. For lakes and coastal environments, it is suggested that change is either seasonal, long term, short term or constant; examples of each are given. There is also an important distinction between natural and man-induced change. Outlined in the paper are studies of the filling of the LG2 Reservoir, water level and vegetation changes in the Peace-Athabasca Delta, possible vegetation changes due to the construction of Roberts Bank Port near Vancouver and measurement of surface suspended sediment concentration in the Bay of Fundy using chromaticity analysis.     

A strategy for mineral and energy resource independence

Data acquired by Landsats 1, 2, and 3, are beginning to provide the information on which an improved mineral and energy resource exploration strategy can be based. Landsat 4 is expected to augment this capability with its higher resolution (30 m) and additional spectral bands in the Thematic Mapper (TM) designed specifically to discriminate clay minerals associated with mineral alteration. In addition, a new global magnetic anomaly map, derived from the recent Magsat mission, has recently been compiled by the National Aeronautics and Space Administration (NASA), the U.S. Geological Survey (USGS), and others. Preliminary, extremely small-scale renditions of this map indicate that global coverage is nearly complete and that the map will improve upon a previous one derived from Polar Orbiting Geophysical Observatory (POGO) data. Digital processing of the Landsat image data and Magsat geophysical data can be used to create three-dimensional stereoscopic models for which Landsat images provide surface reference to deep structural anomalies.Comparative studies of national Landsat lineament maps, Magsat stereoscopic models, and metallogenic information derived from the Computerized Resources Information Bank (CRIB) inventory of U.S. mineral resources, provide a way of identifying and selecting exploration areas that have mineral resource potential. Landsat images and computer-compatible tapes can provide new and better mosaics and also provide the capability for a closer look at promising sites.     

Satellite data as a basis for planning studies of infrastructure and related rural development in Atacora Province,Benin, West Africa

Landsat satellite data has been used to provide information for integrated land resources, agriculture and rural access road planning in Atacora Province, Benin, to ensure that correct decisions are made on the location of feeder roads and best use is made of the terrain. A significant aspect of the interpretation programme involved using a method of terrain evaluation and land classification to provide a framework for planning and assessing all subsequent development projects and highway engineering activities within the Province. Use of this terrain classification, in conjunction with further sequential satellite coverage, is considered as a basis for monitoring and subsequently analysing the rleationship between feeder road construction and induced benefits within the rural agricultural development sector, and for the establishment of a system of data storage. The value of a data storage system is evaluated as a means of preventing wasteful repetition of survey effort and facilitating the transfer of relevant data on rural development to similar areas within Benin and throughout West Africa.     

Main results and perspectives of some Chilean experiences developed with low cost and accurate spatial remote sensing technology

This paper intends to summarize the main results and perspectives of several Chilean Programs developed by using low cost but accurate remote sensing techniques. Due to paper restrictions, three main applications will be shown : use of satellite data collection systems to measure meteorological data in Ant arctic Peninsula; study of geothermal resources in Los Andes Range by using multispectral and multitemporal Landsat images; and snowmelt runoff forecasting for Andean watersheds by using Landsat data. All these applications have allowed to obtain important and useful results and low cost, reliable and accurate methodologies have been obtained for these studies.     

Selection of classification techniques for land use/land cover change investigation

The concerns over land use/land cover (LULC) change have emerged on the global stage due to the realisation that changes occurring on the land surface also influence climate, ecosystem and its services. As a result, the importance of accurate mapping of LULC and its changes over time is on the increase. Landsat satellite is a major data source for regional to global LULC analysis. The main objective of this study focuses on the comparison of three classification tools for Landsat images, which are maximum likelihood classification (MLC), support vector machine and artificial neural network (ANN), in order to select the best method among them. The classifiers algorithms are well optimized for the gamma, penalty, degree of polynomial in case of SVM, while for ANN minimum output activation threshold and RMSE are taken into account. The overall analysis shows that the ANN is superior to the kernel based SVM (linear, radial based, sigmoid and polynomial) and MLC. The best tool (ANN) is then applied on detecting the LULC change over part of Walnut Creek, Iowa. The change analysis of the multi temporal images indicates an increase in urban areas and a major shift in the agricultural practices.     

Land use/land cover classification using time series Landsat 8 images in a heavily urbanized area

It is of great significance to timely, accurately, and effectively monitor land use/cover in city regions for the reasonable development and utilization of urban land resources. The remotely sensed dynamic monitoring of Land use/land cover (LULC) in rapidly developing city regions has increasingly depended on remote-sensing data at high temporal and spatial resolutions. However, due to the influence of revisiting periods and weather, it is difficult to acquire enough time-series images with high quality at both high temporal and spatial resolution from the same sensor. In this paper we used the temporal-spatial fusion model ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) to blend Landsat8 and MODIS data and obtain time-series Landsat8 images. Then, land cover information is extracted using an object-based classification method. In this study, the proposed method is validated by a case study of the Changsha City. The results show that the overall accuracy and Kappa coefficient were 94.38% and 0.88, respectively, and the user/producer accuracies of vegetation types were all over 85%. Our approach provides an accurate and efficient technical method for the effective extraction of land use/cover information in the highly heterogeneous regions.     

Monitoring the changing aereal extent of irrigated lands of the gefara plain,libya

The inventory of large often non-homogeneous tracts of land by resource agencies has led to the development of estimation methods and sampling strategies that produce estimates of the aereal extent of various features from ‘limited’ observations of the universe of interest. Landsat data has furnished a tool that allows for potential improvement in estimates of resource parameters over extensive areas. This paper examines the methodology and results of a procedure which uses an economical sampling procedure allied with the large area covering qualities of the satellite imaging system to make improved estimates of irrigated land in a more timely, efficient and ‘accurate’ manner.     

Space platform albedo measurements as indicators of change in arid lands

The change in albedo of arid lands is an indicator of changes in their condition and quality, including density of vegetative cover, erosion, deposition, surficial soil moisture, and man-made change. In general, darkening of an arid land surface indicates an increase in land quality while brightening indicates a decrease in quality, primarily owing to changes in vegetation.Landsat multiband images taken on different dates can be converted to black-and-white albedo images. Subtraction of one image from another, pixel by pixel, results in an albedo change map that can be density sliced to show areas that have brightened or darkened by selected percentages. These maps are then checked in the field to determine the reasons for the changes and to evaluate the changes in land condition and quality.The albedo change mapping technique has been successfully used in the arid lands of western Utah and northern Arizona and has recently been used for detection of coal strip mining activities in northern Alabama.     

Temporal analysis of suspended solid in Tokyo Bay by Landsat data

The amount of suspended solid (S.S.) discharged from Tokyo metropolitan area is estimated by use of multi-temporal Landsat data from 1979 to 1980. The method to estimate S.S. was verified with sea truth data which was observed with Landsat passes covering Tokyo Bay. The radiometric information is normalized against seasonal change of sun illuminations and atmospheric conditions. Path radiance estimation methods were discussed, because its effects are very sensitive to the estimation of S.S. concentration by Landsat MSS data. Temporal changes of S.S. distribution was also interpreted.     

Integration of Landsat-8 and Sentinel-1 dataset to extract geological lineaments in complex formations of Tepal mountain area,Shahrood, north Iran

Recently, the detection and extraction of geological lineaments have become an essential analytical technique to find relationships between the characteristics and occurrence of hydrogeology, and tectonic studies. The use of remote sensing, with the progressive development of image enhancement techniques, provides an opportunity to produce more reliable and comprehensive lineament maps. In this paper, semi-automatic approach based on Landsat 8 and Sentinel 1 radar data is proposed for lineaments extraction and validation. The combined method of linear filtering and automatic line module ensures a high degree of accuracy resulting in a lineament map. Based on identified lineaments, Sentinel1 is more capable of detecting edges than Landsat8, but the primary orientation lineaments extracted from Landsat8 and Sentinel1 were different. So, by combining band6 of Landsat8, and VV and VH polarization of Sentinel1, the area lineaments were extracted with high accuracy. Rose diagram showed the extracted lineaments' orientation is in good compliance with the region's existing faults. Also, the formations' lineament length density has good consistent with the density of the faults in the geological map.     

An ensemble deep learning based shoreline segmentation approach (WaterNet) from Landsat 8 OLI images

Shorelines constantly vary due to natural, urbanization and anthropogenic effects such as global warming, population growth, and environmental pollution. Sustainable monitoring of coastal changes is vital in terms of coastal resource management, environmental preservation and planning. Publicly available Landsat 8 OLI (Operational Land Manager) images provide accurate, reliable, temporal and up-to-date information about coastal areas. Recently, the use of machine learning and deep learning algorithms have become widespread. In this study, we used our public Landsat 8 OLI satellite image dataset to create a majority voting method which is an ensemble automatic shoreline segmentation system (WaterNet) to obtain shorelines automatically. For this purpose, different deep learning architectures have been utilized namely as Standard U-Net, Dilated U-Net, Fractal U-Net, FC-DenseNet, and Pix2Pix. Also, we have suggested a novel framework to create labeling data from OpenStreetMap service to create a unique dataset called YTU-WaterNet. According to the results, IoU and F1 scores have been calculated as 99.59% and 99.79% for the WaterNet. The results indicate that the WaterNet method outperforms other methods in terms of shoreline extraction from Landsat 8 OLI satellite images.     

基于光学图像的撞击坑识别研究综述

当前,随着深空探测研究工作的需要,将信息科学的图像处理、模式识别技术应用到空间探测领域成为必然。基于光学图像的撞击坑自主检测技术就是将信息科学的图像处理技术应用到空间科学研究中的一个很好例证,近年来得到了各国学者的重视。本文针对这一领域的相关研究进行了介绍与分析。首先,对这一技术的研究意义从地质学、天体表面结构和特征数据库建设、探测器导航三个角度加以说明;其次,详细阐述了该技术的研究现状,简要介绍了其中一些经典算法,并将相关算法分为三类:全自主检测算法、半自主检测算法和组合检测算法;最后,提出了该技术研究所面临的难点和未来研究方向与应用空间,以及介绍了作者在这一方面的研究进展。     

CRESDA APPLICATION SYSTEM OF CBERS-1, RESULTS AND TYPICAL EXAMPLES OF APPLICATIONS

CRESDA Application System of CBERS-1 was established in 1999. During the operation of the system for more than two years, about 240 000 scenes of CBERS-1 Level 0 data have been archived and more than 13 000 scenes of Level 2 products have been ordered by end users from different application fields.In this paper, the typical examples of applications in crop yield estimation,calamity alleviation, resources survey and protection, environment monitoring and continuable development, and urban planning are mainly described.     

Experiment for mapping land cover and it’s change in southeastern Sri Lanka utilizing 250 m resolution MODIS imageries

Utilizing freely available MODIS NDVI and Natural color imageries of 250 m spatial resolution produced by NASA, an experiment was made to map land-cover and its change with an emphasis on vegetation cover in southeastern Sri Lanka, which plays a vital role for control of green house gas. For the change detection purpose, 1987 land cover map made by present authors from Landsat MSS image and extensive ground truth survey data was used as the base map. The result of the experiment shows that MODIS data are useful to make a land cover map of 250 m spatial resolution for tropical areas with high cloud coverage like Sri Lanka. It was found that the forest cover decrease amounted as large as 21% in 19 years time span in southeastern Sri Lanka, the prominent forest region of the country. On the other hand homestead/vegetation and mixed vegetation/scrub dominant categories increased by 13.7% and 7.1%, respectively. These changes are considered due to a large clearance of forest areas for agriculture and building houses to accommodate increasing inhabitants.     

Object-based rice mapping using time-series and phenological data

Remote sensing techniques are often used in mapping rice, but high quality time-series remote sensing data are difficult to obtain due to the cloudy weather of rice growing areas and long satellite revisit interval. As such, rice mapping is usually based on mono-temporal Landsat TM/ETM+ data, which have large uncertainties due to the spectral similarity of different vegetation types. Moreover, conventional pixel-based classification method is unable to meet the required accuracy for rice mapping. Therefore, this study proposes a new strategy for mapping rice in cloud-prone areas using fused data of Landsat-8 OLI time-series and phenological parameters, based on the object-based method. We determine the critical growth stages of paddy rice from observed phenological data and MODIS-NDVI time-series data. The spatial and temporal adaptive reflectance fusion model (STARFM) is used to blend the MODIS and Landsat data to obtain a multi-temporal Landsat-like dataset for classification. Finally, an object-oriented algorithm is used to extract rice paddies from the Landsat-like, time-series dataset. The validation experiments show that the proposed method can provide high accuracy rice mapping, with an overall accuracy of 92.38% and a kappa coefficient of 0.85.     

Mapping recent agricultural developments in China from satellite data

Landsat data have been employed to study and map agricultural developments in three regions of China: 1) Pearl River delta; 2) Nen River basin; and 3) Xinjiang Autonomous Region. Manual interpretation procedures used in conjunction with multi-date Landsat images and collateral information permitted rice yields to be estimated for the Pearl River delta in 1978. A combination of manual and computer-assisted analyses of Landsat data of Northeast China revealed that more than 15,000 km² of agricultural land in a 184,500 km² study area had been reclaimed from rangeland and marshland. These analyses also indicated a shift in cropping practices, with the foodcrops wheat and corn replacing cash crops such as soybeans. In the arid west, Landsat image data provided valuable input to a geographic information system (GIS). It appears the GIS approach will prove useful for evaluating agricultural land potential in the remote areas of China.     

Responses to satellite remote sensing opportunities in East and Southern Africa

Since 1978 the U.S. Agency for International Development (USAID) has funded a regional remote sensing project for East and Southern Africa. The project, hosted by the Regional Centre for Services in Surveying Mapping and Remote Sensing, has provided a programme of training courses, user services and project support. This included the equipping and establishment of a photo-laboratory complex for processing Landsat images and the provision of advice and support for agencies undertaking natural resources analysis.Response to the training programme has been very good. Courses are usually over subscribed and there is a continued demand for training. Assessments of the courses by participants are highly positive and the courses have featured consultants of international calibre. Requests for follow-up courses, and for specialist group training indicate a strong response to this training activity. User services are active, consultations with staff, use of the browse file and interpretation equipment and the purchase of data for project work all produce an average demand of 12 active enquiries per working week. The photo-laboratory is particularly active and demand for products exceeds available capacity.Project work is now being supported but limited resources restrict the range and amount of project activity. Response to the opportunities offered for projects has been favourable and this activity is ripe for expansion. The difficulty in expanding to meet the expressed demand is primarily financial. The east and southern Africa region is not economically strong and has a great need for natural resources data for development work and planning. The responses to satellite remote sensing opportunities will be limited by these financial constraints which effectively means by the level of international aid directed to this activity. For such aid to be effective it must be coordinated and firmly attached to the region. Such coordinated aid programmes would avoid fragmentation of distribution and applications work. Fragmentation could seriously disrupt the present growth in natural resources activity based on remote sensing data from satellites. The lack of financing for a regional ground receiving station is also a significant limiting factor.     

Application of space sciences to hydrology and water resources: The potential and practical use as reflected by WMO experience

Observations from spacecraft have already proved their worth in a number of fields and much work has been undertaken to develop their use in studies of hydrology and water resources. The ability to obtain areal estimates of parameters over large areas as opposed to only point values and the inherent computer-compatibility of the data obtained are only two of the many advantages which may be stressed. However, any new technology requires the expenditure of scarce financial resources, not only on the system itself but also on associated activities. A full use of space observations in hydrology and water resources will require major changes in existing data collection, storage and processing systems. The net benefits to be gained from such changes must first be demonstrated to those responsible for these systems. A dialogue should therefore be established between those supplying the data and investigating their potential uses, and those actually engaged in the assessment and management of water resources. Examples are offered of projects in which space observations are being used and information is given on requirements for work in hydrology and water resources for data acquired by space observation.