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1.
Land-use and land-cover (LULC) conversions have an important impact on land degradation, erosion and water availability. Information on historical land cover (change) is crucial for studying and modelling land- and ecosystem degradation. During the past decades major LULC conversions occurred in Africa, Southeast Asia and South America as a consequence of a growing population and economy. Most distinct is the conversion of natural vegetation into cropland. Historical LULC information can be derived from satellite imagery, but these only date back until approximately 1972. Before the emergence of satellite imagery, landscapes were monitored by black-and-white (B&W) aerial photography. This photography is often visually interpreted, which is a very time-consuming approach. This study presents an innovative, semi-automated method to map cropland acreage from B&W photography. Cropland acreage was mapped on two study sites in Ethiopia and in The Netherlands. For this purpose we used Geographic Object-Based Image Analysis (GEOBIA) and a Random Forest classification on a set of variables comprising texture, shape, slope, neighbour and spectral information. Overall mapping accuracies attained are 90% and 96% for the two study areas respectively. This mapping method increases the timeline at which historical cropland expansion can be mapped purely from brightness information in B&W photography up to the 1930s, which is beneficial for regions where historical land-use statistics are mostly absent.  相似文献   

2.
Many African countries are facing increasing risks of food insecurity due to rising populations. Accurate and timely information on the spatial distribution of cropland is critical for the effective management of crop production and yield forecast. Most recent cropland products (2015 and 2016) derived from multi-source remote sensing data are available for public use. However, discrepancies exist among these cropland products, and the level of discrepancy is particularly high in several Africa regions. The overall goal of this study was to identify and assess the driving factors contributing to the spatial discrepancies among four cropland products derived from remotely sensed data. A novel approach was proposed to evaluate the spatial agreement of these cropland products and assess the impact of environmental factors such as elevation dispersion, field size, land-cover richness and frequency of cloud cover on these spatial differences. Results from this study show that the overall accuracies of the four cropland products are below 65%. In particular, large disagreements are seen on datasets covering Sahel zone and along the West African coasts. This study has identified land-cover richness as the driving factor with the largest contribution to the spatial disagreement among cropland products over Africa, followed by the high frequency of cloud cover, small and fragmented field size, and elevation complexity. To improve the accuracy of future cropland products for African regions, the data producers are encouraged to take a multi-classification approach and incorporate multi-sensors into their cropland mapping processes.  相似文献   

3.
Irrigation infrastructure development for smallholder farmers in developing countries increasingly gains attention in the light of domestic food security and poverty alleviation. However, these complex landscapes with small cultivated plots pose a challenge with regard to mapping and monitoring irrigated agriculture. This study presents an object-based approach to map irrigated agriculture in an area in the Central Rift Valley in Ethiopia using SPOT6 imagery. The study is a proof-of-concept that the use of shape, texture, neighbour and location information next to spectral information is beneficial for the classification of irrigated agriculture. The underlying assumption is that the application of irrigation has a positive effect on crop growth throughout the field, following the field's borders, which is detectable in an object-based approach. The type of agricultural system was also mapped, distinguishing smallholder farming and modern large-scale agriculture. Irrigated agriculture was mapped with an overall accuracy of 94% and a kappa coefficient of 0.85. Producer's and user's accuracies were on average 90.6% and 84.2% respectively. The distinction between smallholder farming and large-scale agriculture was identified with an overall accuracy of 95% and a kappa coefficient of 0.88. The classifications were performed at the field level, since the segmentation was able to adequately delineate individual fields. The additional use of object features proved essential for the identification of cropland plots, irrigation period and type of agricultural system. This method is independent of expert knowledge on crop phenology and absolute spectral values. The proposed method is useful for the assessment of spatio-temporal dynamics of irrigated (smallholder) agriculture in complex landscapes and yields a basis for land and water managers on agricultural water use.  相似文献   

4.
Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.  相似文献   

5.
This paper describes an operational application of AVHRR satellite imagery in combination with the satellite-based land cover database CORINE Land Cover (CLC) for the comprehensive observation and follow-up of 10000 fire outbreaks and of their consequences in Greece during summer 2000. In the first stage, we acquired and processed satellite images on a daily basis with the aim of smoke-plume tracking and fire-core detection at the national level. Imagery was acquired eight times per day and derived from all AVHRR spectral channels. In the second stage, we assessed the consequences of fire on vegetation by producing a burnt-area map on the basis of multi-annual normalised vegetation indices using AVHRR data in combination with CLC. In the third stage we used again CLC to assess the land cover of burnt areas in the entire country. The results compared successfully to available inventories for that year. Burnt area was estimated with an accuracy ranging from 88% to 95%, depending on the predominant land cover type. These results, along with the low cost and high temporal resolution of AVHRR satellite imagery, suggest that the combination of low-resolution satellite data with harmonised CLC data can be applied operationally for forest fire and post-fire assessments at the national and at a pan-European level.  相似文献   

6.
LiDAR data are becoming increasingly available, which has opened up many new applications. One such application is crop type mapping. Accurate crop type maps are critical for monitoring water use, estimating harvests and in precision agriculture. The traditional approach to obtaining maps of cultivated fields is by manually digitizing the fields from satellite or aerial imagery and then assigning crop type labels to each field - often informed by data collected during ground and aerial surveys. However, manual digitizing and labeling is time-consuming, expensive and subject to human error. Automated remote sensing methods is a cost-effective alternative, with machine learning gaining popularity for classifying crop types. This study evaluated the use of LiDAR data, Sentinel-2 imagery, aerial imagery and machine learning for differentiating five crop types in an intensively cultivated area. Different combinations of the three datasets were evaluated along with ten machine learning. The classification results were interpreted by comparing overall accuracies, kappa, standard deviation and f-score. It was found that LiDAR data successfully differentiated between different crop types, with XGBoost providing the highest overall accuracy of 87.8％. Furthermore, the crop type maps produced using the LiDAR data were in general agreement with those obtained by using Sentinel-2 data, with LiDAR obtaining a mean overall accuracy of 84.3％ and Sentinel-2 a mean overall accuracy of 83.6％. However, the combination of all three datasets proved to be the most effective at differentiating between the crop types, with RF providing the highest overall accuracy of 94.4％. These findings provide a foundation for selecting the appropriate combination of remotely sensed data sources and machine learning algorithms for operational crop type mapping.  相似文献   

7.
Interpretation of IRS LISS II and LISS III imagery has revealed the various landforms as well as land use/land cover features in a part of the Godavari delta coastal belt. A comparative analysis of geomorphological vs. land use/land cover maps suggested that the landforms exert a certain degree of control over human land use activities even in this monotonously plain area. Further, an analysis of the sequential imagery pertaining to 1992 and 2001 aimed at detecting the land use/land cover change has indicated that the aquaculture has phenomenally increased by 9,293.5 ha during the 9-year period. At the same time, the cropland which occupied about 29,104 ha in 1992 has been reduced to 19,153.9 ha by 2001 mainly due to the encroachment of aquaculture. Village level data on temporal variation in land use/land cover extracted through GIS analysis revealed that in 14 out of the total 39 villages in the area, the conversion of cropland into aquaculture ponds was more than 30% with the highest conversion rate of 89.8% in Gondi village. These fourteen villages, which are designated as ‘aquaculture hotspots’ are grouped into 4 priority classes based on the intensity of conversion.  相似文献   

8.
Land cover dynamics at the African continental scale is of great importance for global change studies. Actually, four satellite-derived land cover maps of Africa now available, e.g. ECOCLIMAP, GLC2000, MODIS and GLOBCOVER, are based on images acquired in the 2000s. This study aims at stressing the compliances and the discrepancies between these four land cover classifications systems. Each of them used different mapping initiatives and relies on different mapping standards, which supports the present investigation. In order to do a relative comparison of the four maps, a preamble was to reconcile their thematic legends into more aggregated categories after a projection into the same spatial resolution. Results show that the agreement between the four land cover products is between 56 and 69%. While all these land cover datasets show a reasonable agreement in terms of surface types and spatial distribution patterns, mapping of heterogeneous landscapes in the four products is not very successful. Land cover products based on remote sensing imagery can indeed significantly be improved by using smarter algorithms, better timing of image acquisition, improved class definitions. Either will help to improve the accuracy of future land cover maps at the African continental scale. Data producers may use the areas of spatial agreement for training area selection while users might need to verify the information in the areas of disagreement using additional data sources.  相似文献   

9.
Topographic information from maps and geographical information systems (GIS) has been combined with satellite data (SPOT Panchromatic, SPOT Multispectral and Landsat Thematic Mapper) to derive a product that may be valuable in preliminary route location studies. The objectives of this study were to evaluate the classification accuracy of this combined product, to compare levels of ground detail obtainable from different types of satellite imagery against aerial photography, and to present an example application on the use of the combined product.
The classification accuracy of the combined product was dependent on the type of land cover and was 83 to 100 per cent successful, with accuracy exceeding 95 per cent for most land cover types. The overall accuracy of the product was almost 95 per cent, with accuracy based on KHAT statistics of 92 per cent. Varying levels of ground detail were attainable from different types of satellite imagery. This detail may be adequate for preliminary route selection, especially in the absence of aerial photographs and GIS. The combined product presented in this study was applied successfully in selecting the optimal route for the Greater Amman ring road.  相似文献   

10.
With the availability of very high resolution multispectral imagery, it is possible to identify small features in urban environment. Because of the multiscale feature and diverse composition of land cover types found within the urban environment, the production of accurate urban land cover maps from high resolution satellite imagery is a difficult task. This paper demonstrates the potential of 8 bands capability of World View 2 satellite for better automated feature extraction and discrimination studies. Multiresolution segmentation and object based classification techniques were then applied for discrimination of urban and vegetation features in a part of Dehradun, Uttarakhand, India. The study demonstrates that scale, colour, shape, compactness and smoothness have a significant influence on the quality of image objects achieved, which in turn governs the classified result. The object oriented analysis is a valid approach for analyzing high spatial and spectral resolution images. World View 2 imagery with its rich spatial and spectral information content has very high potential for discrimination of the less varied varieties of vegetation.  相似文献   

11.
Abstract

The paper discusses the potential of very high resolution (VHR) satellite imagery for post-earthquake damage assessment in comparison with the role of aerial photographs. Post-disaster optical and radar satellite data are assessed for their ability to resolve collapsed buildings, destroyed transportation infrastructure, and specific land cover changes. Optical VHR imagery has shown to be effective in quantifying building stock and for assessing damage at the building level. High-resolution synthetic aperture radar (SAR) imagery requires further research to identify optimum information extraction procedures for rapid assessment of affected buildings. Based on current technical and operational capabilities increasing efforts should be devoted to the generation of spatial datasets for disaster preparedness.  相似文献   

12.
Land cover roughness coefficients (LCRs) have been used in multivariate spatial models to test the mitigation potential of coastal vegetation to reduce impacts of the 2004 tsunami in Aceh, Indonesia. Previously, a Landsat 2002 satellite imagery was employed to derive land cover maps, which were then combined with vegetation characteristics, i.e., stand height, stem diameter and planting density to obtain LCRs. The present study tested LCRs extracted from 2003 and 2004 Landsat (30 m) images as well as a combination of 2003 and 2004 higher spatial resolution SPOT (10 m) imagery, while keeping the previous vegetation characteristics. Transects along the coast were used to extract land cover, whenever availability and visibility allowed. These new LCRs applied in previously developed tsunami impact models on wave outreach, casualties and damages confirmed previous findings regarding distance to the shoreline as a main factor reducing tsunami impacts. Nevertheless, the models using the new LCRs did not perform better than the original one. Particularly casualties models using 2002 LCRs performed better (δAIC > 2) than the more recent Landsat and SPOT counterparts. Cloud cover at image acquisition for Landsat and low area coverage for SPOT images decreased statistical predictive power (fewer observations). Due to the large spatial heterogeneity of tsunami characteristics as well as topographic and land-use features, it was more important to cover a larger area. Nevertheless, if more land cover classes would be referenced and high resolution imagery with low cloud cover would be available, the full benefits of higher spatial resolution imagery used to extract more precise land use roughness coefficients could be exploited.  相似文献   

13.
Remotely-sensed data products have got unique advantage over conventional data-gathering techniques in the study of urban morphology. The physical parameters like built-up area density, street pattern, population density, urban structure as well as functional characteristics which can be derived from land use/land cover map, are clearly visible on aerial data products. This technique provides synoptic view of the area which makes the study comprehensive and uniform. Sequential aerial photographs and satellite imagery help in studying the growth of urban area and temporal changes in urban structure. These informations are very useful in the planning of city extension. Here an attempt has been made to study the urban morphology of Saharanpur city by using panchromatic aerial photographs on scale 1∶10,000, IRS-1B LISS II geocoded imagery on 1∶50,000 scale and photo-maps on 1∶4000 scale, and the results are very encouraging.  相似文献   

14.
Availability of remote sensing data from earth observation satellites has made it convenient to map and monitor land use/land cover at regional to local scales. A land cover map is very critical for a various planning activities including watershed planning. The spectral and spatial resolutions are major constraints for mapping the crop resources at microlevel. The cropping pattern zones have been mapped using the false color composite, physiography, irrigation and toposheets. The IRS LISS-III data is classified into various categories depending on spectral reflectance from crop canopy and are overlaid on cropping zones map. The re-classified resultant map provides land use/land cover information including dominant cropping systems. The canopy cover is estimated monthly considering the crop calendar for the area.  相似文献   

15.
高精度作物分布图制作   总被引：5，自引：3，他引：5  
中国自然条件复杂 ,农业种植结构多样 ,地块小而分散 ,利用遥感影像制作作物分布图的精度很难满足农业遥感估产的需求。该文利用目前最高分辨率的商用遥感卫星 (QuickBird)影像 ,采用面向对象的影像分析方法提取耕地种植地块图 ,结合详细的地面调查制作高精度的作物分布图 ,为农业遥感估产服务。  相似文献   

16.
Over the last two decades, China has introduced a series of agricultural and forestland use reforms, aiming to feed the largest population in the world and maintain ecological services locally and nationally. This paper studies the impacts of local government-driven reforestation on land use and land cover change, as well as its further impacts on livelihoods of upland farmers in Xizhuang watershed. An analysis of aerial photographs and ASTER satellite imagery from 1987 to 2002, respectively, showed that the forest has significantly increased at the expense of decreasing farmland. However, the monoculture reforestation of pine has caused both biophysical and socio-economic consequences. This case study also shows forestry decentralization in China remains incomplete. Land use and land cover change is also a political economic issue. Some of the reforms designed to protect forest resources have had a negative impact on rural livelihoods.  相似文献   

17.
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.  相似文献   

18.
Jerdon’s courser (Cursorius bitorquatus) considered as lost bird is found in Sri Lankamalleswaram Sanctuary, Cuddapah District, Andhra Pradesh. It is listed in Red data book as endangered bird. Analysis of satellite imagery of 1989, 1996, 1998 and ground information have revealed an improvement of Jerdon courser’s habitat after declaration of area as sanctuary in 1988. Large open grounds show a decrease, white small open grounds surrounded by scrub plants offering protection and food cover increase. Analysis of satellite imagery shows core niche covering 4 x 3 km area and larger area of sanctuary (7.3 x 13.1 km) having various land cover classes. Comparison of satellite imagery from 1989 to 1998 shows degradation of larger area of sanctuary where birds are not seen.  相似文献   

19.
In recent years, special attention has been given to the long-term effects of biochar on the performance of agro-ecosystems owing to its potential for improving soil fertility, harvested crop yields, and aboveground biomass production. The present experiment was set up to identify the effects on soil-plant systems of biochar produced more than 150 years ago in charcoal mound kiln sites in Wallonia (Belgium). Although the impacts of biochar on soil-plant systems are being increasingly discussed, a detailed monitoring of the crop dynamics throughout the growing season has not yet been well addressed. At present there is considerable interest in applying remote sensing for crop growth monitoring in order to improve sustainable agricultural practices. However, studies using high-resolution remote sensing data to focus on century-old biochar effects are not yet available. For the first time, the impacts of century-old biochar on crop growth were investigated at canopy level using high-resolution airborne remote sensing data over a cultivated field. High-resolution RGB, multispectral and thermal sensors mounted on unmanned aerial vehicles (UAVs) were used to generate high frequency remote sensing information on the crop dynamics. UAVs were flown over 11 century-old charcoal-enriched soil patches and the adjacent reference soils of a chicory field. We retrieved crucial crop parameters such as canopy cover, vegetation indices and crop water stress from the UAV imageries. In addition, our study also provides in-situ measurements of soil properties and crop traits. Both UAV-based RGB imagery and in-situ measurements demonstrated that the presence of century-old biochar significantly improved chicory canopy cover, with greater leaf lengths in biochar patches. Weighted difference vegetation index imagery showed a negative influence of biochar presence on plant greenness at the end of the growing season. Chicory crop stress was significantly increased by biochar presence, whereas the harvested crop yield was not affected. The main significant variations observed between reference and century-old biochar patches using in situ measurements of crop traits concerned leaf length. Hence, the output from the present study will be of great interest to help developing climate-smart agriculture practices allowing for adaptation and mitigation to climate.  相似文献   

20.
Remote sensing data utilize valuable information via various satellite sensors that have different specifications. Image fusion allows the user to combine different spatial and spectral resolutions to improve the information for purposes such as forest monitoring and land cover mapping. In this study, I assessed the contribution of dual-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar data to multispectral Landsat imagery. The research investigated the separability of forested areas using different image fusion techniques. Quality analysis of the fused images was conducted using qualitative and quantitative analyses. I applied the support vector machine image classification method for land cover mapping. Among all methods examined, the à trous wavelet transform method best differentiated the forested area with an overall accuracy (OA) of 94.316%, while Landsat had an OA of 92.626%. The findings of this study indicated that optical-SAR-fused images improve land cover classification, which results in higher quality forest inventory data and mapping.  相似文献   

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