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  • 1
    UID:
    edochu_18452_27622
    Format: 1 Online-Ressource (17 Seiten)
    Content: Long-term monitoring of the extent and intensity of irrigation systems is needed to track crop water consumption and to adapt land use to a changing climate. We mapped the expansion and changes in the intensity of irrigated dry season cropping in Turkey´s Southeastern Anatolia Project annually from 1990 to 2018 using Landsat time series. Irrigated dry season cropping covered 5,779 km² (± 479 km²) in 2018, which represents an increase of 617% over the study period. Dry season cropping was practiced on average every second year, but spatial variability was pronounced. Increases in dry season cropping frequency were observed on 40% of the studied croplands. The presented maps enable the identification of land use intensity hotspots at 30 m spatial resolution, and can thus aid in assessments of water consumption and environmental degradation. All maps are openly available for further use at https://doi.org/10.5281/zenodo.4287661.
    Content: Peer Reviewed
    In: London [u.a.] : Taylor & Francis, 2021, 16,1, Seiten 94-110
    Language: English
    URL: Volltext  (kostenfrei)
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  • 2
    UID:
    edochu_18452_25005
    Format: 1 Online-Ressource (27 Seiten)
    Content: Open and analysis-ready data, as well as methodological and technical advancements have resulted in an unprecedented capability for observing the Earth’s land surfaces. Over 10 years ago, Landsat time series analyses were inevitably limited to a few expensive images from carefully selected acquisition dates. Yet, such a static selection may have introduced uncertainties when spatial or inter-annual variability in seasonal vegetation growth were large. As seminal pre-open-data-era papers are still heavily cited, variations of their workflows are still widely used, too. Thus, here we quantitatively assessed the level of agreement between an approach using carefully selected images and a state-of-the-art analysis that uses all available images. We reproduced a representative case study from the year 2003 that for the first time used annual Landsat time series to assess long-term vegetation dynamics in a semi-arid Mediterranean ecosystem in Crete, Greece. We replicated this assessment using all available data paired with a time series method based on land surface phenology metrics. Results differed fundamentally because the volatile timing of statically selected images relative to the phenological cycle introduced systematic uncertainty. We further applied lessons learned to arrive at a more nuanced and information-enriched vegetation dynamics description by decomposing vegetation cover into woody and herbaceous components, followed by a syndrome-based classification of change and trend parameters. This allowed for a more reliable interpretation of vegetation changes and even permitted us to disentangle certain land-use change processes with opposite trajectories in the vegetation components that were not observable when solely analyzing total vegetation cover. The long-term budget of net cover change revealed that vegetation cover of both components has increased at large and that this process was mainly driven by gradual processes. We conclude that study designs based on static image selection strategies should be critically evaluated in the light of current data availability, analytical capabilities, and with regards to the ecosystem under investigation. We recommend using all available data and taking advantage of phenology-based approaches that remove the selection bias and hence reduce uncertainties in results.
    Content: Peer Reviewed
    Note: This article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.
    In: Basel : MDPI, 14,3
    Language: English
    URL: Volltext  (kostenfrei)
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  • 3
    UID:
    edochu_18452_24522
    Format: 1 Online-Ressource (20 Seiten)
    Content: Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration, and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereby the rainfall effect on those increasingly dry conditions was subtler than just annual and seasonal declines and greater annual variation of rainfall, which requires further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action.
    Content: Peer Reviewed
    In: Basel : MDPI, 13,24
    Language: English
    URL: Volltext  (kostenfrei)
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  • 4
    UID:
    edochu_18452_20125
    Format: 1 Online-Ressource (8 Seiten)
    ISSN: 0264-8377 , 0264-8377
    Content: Brazil’s Soy Moratorium solidified the world’s largest traders’ commitment to stop soybean purchases from production areas deforested after July 2006. The aim was to remove deforestation from the soybean supply-chain and halt one of the main drivers of forest loss in the Amazon biome. In this study, we investigated changes in deforestation at the property-level for the period 2004 to 2014. The objective was to examine direct and indirect deforestation, defined as on-property displacement and cross-parcel displacement deforestation for soybean expansion in the Amazon region of Mato Grosso, the leading soy-producing state of the Brazilian Amazon. We used publicly available property and land use data to quantify deforestation associated with cropland expansion. Similar to previous studies, we found that direct deforestation for soybean expansion declined following the implementation of the Soy Moratorium. Moreover, our analysis suggest that indirect deforestation occurred already before the implementation of the Soy Moratorium, and decreased following the first period of analyses. However, slight increases of indirect deforestation in the more recent periods, combined with decreasing direct deforestations rendered indirect deforestation to be responsible for more than half of the deforestation associated with soybean expansion. While we acknowledge the overall reduction of deforestation for soybean, our results suggest, given the increasing trends of deforestation in the Brazilian Amazon since 2013, to address indirect deforestation within the Soy Moratorium. This may be achieved by zero-property-deforestation commitments and by strengthening the integration between supply-chain actors, the soybean and beef purchasing companies and the federal policies aiming to control deforestation.
    Content: Peer Reviewed
    Note: Nachgenutzt gemäß den CC-Bestimmungen des Lizenzgebers bzw. einer im Dokument selbst enthaltenen CC-Lizenz.
    In: Amsterdam [u.a.] : Elsevier Science, 78,November 2018, Seiten 377-385, 0264-8377
    Language: English
    URL: Volltext  (kostenfrei)
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  • 5
    UID:
    edochu_18452_21384
    Format: 1 Online-Ressource (26 Seiten)
    Content: Spatially explicit information on cropland use intensity is vital for monitoring land and water resource demands in agricultural systems. Cropping practices underlie substantial spatial and temporal variability, which can be captured through the analysis of image time series. Temporal binning helps to overcome limitations concerning operability and repeatability for mapping large areas and can improve the thematic detail and consistency of maps in agricultural systems. We here assessed the use of annual, quarterly, and eight-day temporal features for mapping five cropping practices on annual croplands across Turkey. We used 2403 atmospherically corrected and topographically normalized Landsat Collection 1 L1TP images of 2015 to compute quarterly best-pixel composites, quarterly and annual spectral-temporal metrics, as well as gap-filled eight-day time series of Tasseled Cap components. We tested 22 feature sets for binary cropland mapping, and subsequent discrimination of five cropping practices: Spring and winter cropping, summer cropping, semi-aquatic cropping, double cropping, and greenhouse cultivation. We evaluated area-adjusted accuracies and compared cropland area estimates at the province-level with official statistics. We achieved overall accuracies above 90%, when using either all quarterly features or the eight-day Tasseled Cap time series, indicating that temporal binning of intra-annual image time-series into multiple temporal features improves representations of cropping practices. Class accuracies of winter and spring, summer, and double cropping were robust, while omission errors for semi-aquatic cropping and greenhouse cultivation were high. Our mapped cropland extent was in good agreement with province-level statistics (r2 = 0.85, RMSE = 7.2%). Our results indicate that 71.3% (±2.3%) of Turkey’s annual croplands were cultivated during winter and spring, 15.8% (±2.2%) during summer, while 8.5% (±1.6%) were double-cropped, 4% (±1.9%) were cultivated under semi-aquatic conditions, and 0.32% (±0.2%) was greenhouse cultivation. Our study presents an open and readily available framework for detailed cropland mapping over large areas, which bears the potential to inform assessments of land use intensity, as well as land and water resource demands.
    Content: Peer Reviewed
    Note: This article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.
    In: Basel : MDPI, 11,3
    Language: English
    URL: Volltext  (kostenfrei)
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  • 6
    UID:
    edochu_18452_26032
    Format: 1 Online-Ressource (11 Seiten)
    Content: Water withdrawals for irrigated crop production constitute the largest source of freshwater consumption on Earth. Monitoring the dynamics of irrigated crop cultivation is crucial for tracking crop water consumption, particularly in water-scarce areas. We analyzed changes in water-dependent crop cultivation for 650 000 km2 of Central Asian drylands, including the entire basin of the Amu Darya river, once the largest tributary to the Aral Sea before large-scale irrigation projects grossly reduced the amount of water reaching the river delta. We used Landsat time series to map overall cropland extent, dry season cropping, and cropping frequency in irrigated croplands annually from 1987 to 2019. We scrutinized the emblematic change processes of six localities to discern the underlying causes of these changes. Our unbiased area estimates reveal that between 1988 and 2019, irrigated dry season cropping declined by 1.34 million hectares (Mha), while wet season and double cropping increased by 0.64 Mha and 0.83 Mha, respectively. These results show that the overall extent of cropland in the region remained stable, while higher cropping frequency increased harvested area. The observed changes’ overall effect on water resource use remains elusive: Following the collapse of the Soviet Union, declining dry season cultivation reduced crop water demand while, more recently, increasing cropping frequency raised water consumption. Our analysis provides the first fine-scale analysis of post-Soviet changes in cropping practices of the irrigated areas of Central Asia. Our maps are openly available and can support future assessments of land-system trajectories and, coupled with evapotranspiration estimates, changes in crop water consumption.
    Content: Peer Reviewed
    In: Bristol : IOP Publ., 17,9
    Language: English
    URL: Volltext  (kostenfrei)
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  • 7
    UID:
    almahu_BV046269487
    Format: xviii, 185 Seiten : , Illustrationen, Diagramme, Karten (überwiegend farbig).
    Note: Dissertation Humboldt-Universität zu Berlin 2019
    Additional Edition: Erscheint auch als Online-Ausgabe Rufin, Philippe A global to regional scale assessment of dam-induced agricultural change by means of remote sensing urn:nbn:de:kobv:11-110-18452/20933-9
    Language: English
    Subjects: Geography
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    Keywords: Landwirtschaft ; Staudamm ; Bewässerungswirtschaft ; Landnutzung ; Fernerkundung ; Hochschulschrift
    URL: Volltext  (kostenfrei)
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  • 8
    UID:
    almahu_BV045417847
    Format: 1 Online-Ressource.
    Language: English
    URL: Volltext  (kostenfrei)
    Author information: Hostert, Patrick, 1967-
    Author information: Ernst, Stefan, 19XX-
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  • 9
    UID:
    almahu_BV046054089
    Format: 1 Online-Ressource (xviii, 185 Seiten) : , Illustrationen, Diagramme, Karten.
    Note: Dissertation Humboldt-Universität zu Berlin 2019
    Additional Edition: Erscheint auch als Druck-Ausgabe Rufin, Philippe A global to regional scale assessment of dam-induced agricultural change by means of remote sensing
    Language: English
    Keywords: Landwirtschaft ; Staudamm ; Bewässerungswirtschaft ; Landnutzung ; Fernerkundung ; Hochschulschrift
    URL: Volltext  (kostenfrei)
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  • 10
    UID:
    edochu_18452_24186
    Format: 1 Online-Ressource (24 Seiten)
    Content: Reliable crop type maps from satellite data are an essential prerequisite for quantifying crop growth, health, and yields. However, such maps do not exist for most parts of Africa, where smallholder farming is the dominant system. Prevalent cloud cover, small farm sizes, and mixed cropping systems pose substantial challenges when creating crop type maps for sub-Saharan Africa. In this study, we provide a mapping scheme based on freely available Sentinel-2A/B (S2) time series and very high-resolution SkySat data to map the main crops—maize and potato—and intercropping systems including these two crops on the Jos Plateau, Nigeria. We analyzed the spectral-temporal behavior of mixed crop classes to improve our understanding of inter-class spectral mixing. Building on the Framework for Operational Radiometric Correction for Environmental monitoring (FORCE), we preprocessed S2 time series and derived spectral-temporal metrics from S2 spectral bands for the main temporal cropping windows. These STMs were used as input features in a hierarchical random forest classification. Our results provide the first wall-to-wall crop type map for this key agricultural region of Nigeria. Our cropland identification had an overall accuracy of 84%, while the crop type map achieved an average accuracy of 72% for the five relevant crop classes. Our crop type map shows distinctive regional variations in the distribution of crop types. Maize is the dominant crop, followed by mixed cropping systems, including maize–cereals and potato–maize cropping; potato was found to be the least prevalent class. Plot analyses based on a sample of 1166 fields revealed largely homogeneous mapping patterns, demonstrating the effectiveness of our classification system also for intercropped classes, which are temporally and spatially highly heterogeneous. Moreover, we found that small field sizes were dominant in all crop types, regardless of whether or not intercropping was used. Maize–legume and maize exhibited the largest plots, with an area of up to 3 ha and slightly more than 10 ha, respectively; potato was mainly cultivated on fields smaller than 0.5 ha and only a few plots were larger than 1 ha. Besides providing the first spatially explicit map of cropping practices in the core production area of the Jos Plateau, Nigeria, the study also offers guidance for the creation of crop type maps for smallholder-dominated systems with intercropping. Critical temporal windows for crop type differentiation will enable the creation of mapping approaches in support of future smart agricultural practices for aspects such as food security, early warning systems, policies, and extension services.
    Content: Peer Reviewed
    Note: This article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.
    In: Basel : MDPI, 13,17
    Language: English
    URL: Volltext  (kostenfrei)
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