Landcover and crop type classification with intra-annual times series of sentinel-2 and machine learning at central Portugal

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesLand cover and crop type mapping have benefited from a daily revisiting period of sensors such as MODIS, SPOT-VGT, NOAA-AVHRR that contains long time-series archive. However, they have low accuracy in an Area of Interest (ROI) due to their coarse spatial resolution (i.e., pixel size > 250m). The Copernicus Sentinel-2 mission from the European Spatial Agency (ESA) provides free data access for Sentinel 2-A(S2a) and B (S2b). This satellite constellation guarantees a high temporal (5-day revisit cycle) and high spatial resolution (10m), allowing frequent updates on land cover products through supervised classification. Nevertheless, this requires training samples that are traditionally collected manually via fieldwork or image interpretation. This thesis aims to implement an automatic workflow to classify land cover and crop types at 10m resolution in central Portugal using existing databases, intra-annual time series of S2a and S2b, and Random Forest, a supervised machine learning algorithm. The agricultural classes such as temporary and permanent crops as well as agricultural grasslands were extracted from the Portuguese Land Parcel Identification System (LPIS) of the Instituto de Financiamento da Agricultura e Pescas (IFAP); land cover classes like urban, forest and water were trained from the Carta de Ocupação do Solo (COS) that is the national Land Use and Land Cover (LULC) map of Portugal; and lastly, the burned areas are identified from the corresponding national map of the Instituto da Conservação da Natureza e das Florestas (ICNF). Also, a set of preprocessing steps were defined based on the implementation of ancillary data allowing to avoid the inclusion of mislabeled pixels to the classifier. Mislabeling of pixels can occur due to errors in digitalization, generalization, and differences in the Minimum Mapping Unit (MMU) between datasets. An inner buffer was applied to all datasets to reduce border overlap among classes; the mask from the ICNF was applied to remove burned areas, and NDVI rule based on Landsat 8 allowed to erase recent clear-cuts in the forest. Also, the Copernicus High-Resolution Layers (HRL) datasets from 2015 (latest available), namely Dominant Leaf Type (DLT) and Tree Cover Density (TCD) are used to distinguish between forest with more than 60% coverage (coniferous and broadleaf) such as Holm Oak and Stone Pine and between 10 and 60% (coniferous) for instance Open Maritime Pine. Next, temporal gap-filled monthly composites were created for the agricultural period in Portugal, ranging from October 2017 till September 2018. The composites provided data free of missing values in opposition to single date acquisition images. Finally, a pixel-based approach classification was carried out in the “Tejo and Sado” region of Portugal using Random Forest (RF). The resulting map achieves a 76% overall accuracy for 31 classes (17 land cover and 14 crop types). The RF algorithm captured the most relevant features for the classification from the cloud-free composites, mainly during the spring and summer and in the bands on the Red Edge, NIR and SWIR. Overall, the classification was more successful on the irrigated temporary crops whereas the grasslands presented the most complexity to classify as they were confused with other rainfed crops and burned areas

Commodity-based Freight Activity on Inland Waterways through the Fusion of Public Datasets for Multimodal Transportation Planning

Within the U.S., the 18.6 billion tons of goods currently moved along the multimodal transportation system are expected to grow 51% by 2045. Most of those goods are transported by roadways. However, several benefits can be realized by shippers and consumers by shifting freight to more efficient modes, such as inland waterways, or adopting a multimodal scheme. To support such freight growth sustainably and efficiently, federal legislation calls for the development of plans, methods, and tools to identify and prioritize future multimodal transportation infrastructure needs. However, given the historical mode-specific approach to freight data collection, analysis, and modeling, challenges remain to adopt a fully multimodal approach that integrates underrepresented modes, such as waterways, into multimodal forecasting tools to identify and prioritize transportation infrastructure needs. Examples of such challenges are data heterogeneity, confidentiality, limitations in terms of spatial and temporal coverage, high cost associated with data collection, subjectivity in surveys responses, etc. To overcome these challenges, this work fuses data across a variety of novel transportation sources to close existing gaps in freight data needed to support multimodal long-range freight planning. In particular, the objective of this work is to develop methods to allow integration of inland waterway transportation into commodity-based freight forecasting models, by leveraging Automatic Identification System (AIS) data. The following approaches are presented in this dissertation: i) Maritime Automatic Identification System (AIS) data is mapped to a detailed inland navigable waterway network, allowing for an improved representation of waterway modes into multimodal freight travel demand models which currently suffer from unbalanced representation of waterways. Validation results show the model correctly identifies 84% stops at inland waterway ports and 83.5% of trips crossing locks. ii) AIS and truck Global Positioning System (GPS) data are fused to a multimodal network to identify the area of impact of a freight investment, providing a single methodology and data source to compare and contrast diverse transportation infrastructure investments. This method identifies parallel truck and vessel flows indicating potential for modal shift. iii) Truck GPS and maritime Lock Performance Monitoring System (LPMS) data are fused via a multi-commodity assignment model to characterize and quantify annual commodity throughput at port terminals on inland waterways, generating new data from public datasets, to support estimation of commodity-based freight fluidity performance measures. Results show that 84% of ports had less than a 20% difference between estimated and observed truck volumes. iv) AIS, LPMS, and truck GPS datasets are fused to disaggregate estimated annual commodity port throughput to vessel trips on inland waterways. Vessel trips characterized by port of origin, destination, path, timestamp, and commodity carried, are mapped to a detailed inland waterway network, allowing for a detailed commodity flow analysis, previously unavailable in the public domain. The novel, repeatable, data-driven methods and models proposed in this work are applied to the 43 freight port terminals located on the Arkansas River. These models help to evaluate network performance, identify and prioritize multimodal freight transportation infrastructure needs, and introduce a unique focus on modal shift towards inland waterway transportation

Book of short Abstracts of the 11th International Symposium on Digital Earth

The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium

Feature Papers of Drones - Volume II

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 24–41 are focused on drone applications, but emphasize two types: firstly, those related to agriculture and forestry (articles 24–35) where the number of applications of drones dominates all other possible applications. These articles review the latest research and future directions for precision agriculture, vegetation monitoring, change monitoring, forestry management, and forest fires. Secondly, articles 36–41 addresses the water and marine application of drones for ecological and conservation-related applications with emphasis on the monitoring of water resources and habitat monitoring. Finally, articles 42–54 looks at just a few of the huge variety of potential applications of civil drones from different points of view, including the following: the social acceptance of drone operations in urban areas or their influential factors; 3D reconstruction applications; sensor technologies to either improve the performance of existing applications or to open up new working areas; and machine and deep learning development

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.The two-layer model of Shuttlerworth and Wallace (SW) was evaluated to estimate actual evapotranspiration (ETa) above a drip-irrigated Merlot vineyard, located in the Talca Valley, Region del Maule, Chile (35° 25' LS; 71° 32' LW ; 136m above the sea level). An automatic weather system was installed in the center of the vineyard to measure climatic variables (air temperature, relative humidity, and wind speed) and energy balance components (solar radiation, net radiation, latent heat flux, sensible heat flux, and soil heat flux) during November and December 2006. Values of ETa estimated by the SW model were tested with latent heat flux measurements obtained from an eddy-covariance system on a 30 minute time interval. Results indicated that SW model was able to predict ETa with a root mean square error (RMSE) of 0.44 mm d-1 and mean absolute error (MAE) of 0.36 mm d-1. Furthermore, SW model predicted latent heat flux with RMSE and MAE of 32 W m-2 and 19W m-1, respectively

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.A In order to promote irrigation sustainability through reporting by irrigation water managers around Australia, we have developed an adaptive framework and methodology for improved triple-bottom-line reporting. The Irrigation Sustainability Assessment Framework (ISAF) was developed to provide a comprehensive framework for irrigation sustainability assessment and integrated triple-bottom-line reporting, and is structured to promote voluntary application of this framework across the irrigation industry, with monitoring, assessment and feedback into future planning, in a continual learning process. Used in this manner the framework serves not only as a "reporting tool", but also as a "planning tool" for introducing innovative technology and as a "processes implementation tool" for enhanced adoption of new scientific research findings across the irrigation industry. The ISAF was applied in case studies to selected rural irrigation sector organisations, with modifications to meet their specific interests and future planning

USCID Fourth international conference on irrigation and drainage

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.Integrated regional water management -- Change of irrigation water quantity according to farm mechanization and land consolidation in Korea -- Local stakeholders participation for small scale water resources management in Bangladesh -- Water user participation in Egypt -- The man swimming against the stream knows the strength of it -- Roles and issues of Water Users' Associations for Sustainable Irrigation and Drainage in the Kyrgyz Republic and Uzbekistan in Central Asia -- Chartered Water User Associations of Afghanistan -- Updated procedures for calculating state-wide consumptive use in Idaho -- Measuring and estimating open water evaporation in Elephant Butte Reservoir in New Mexico -- Evapotranspiration of deficit irrigated sorghum and winter wheat -- Evaluation of a two-layer model to estimate actual evapotranspiration for vineyards -- Estimating pecan water use through remote sensing in Lower Rio Grande -- Estimating crop water use from remotely sensed NDVI, crop models, and reference ET -- Alfalfa production using saline drainage water -- Performance evaluation of subsurface drainage system under unsteady state flow conditions in coastal saline soils of Andhrapradesh, India -- Management strategies for the reuse of wastewater in Jordan -- Providing recycled water for crop irrigation and other uses in Gilroy, California -- Oakdale Irrigation District Water Resources Plan -- Use of information technology to support integrated water resources management implementation -- Decision-support systems for efficient irrigation in the Middle Rio Grande -- Salt management -- Ghazi Barotha Project on Indus River in Pakistan -- Field tests of OSIRI -- Water requirements, irrigation evaluation and efficiency in Tenerife's crops (Canary Islands, Spain) -- Using wireless technology to reduce water use in rice production -- Variability of crop coefficients in space and time -- Assessing the implementation of integrated water management approach in closed basins -- New strategies of donors in the irrigation sector of Africa -- Holistic perspective for investments in agricultural drainage in Egypt -- Mapping system and services for canal operation techniques -- An open channel network modernization with automated structures -- Canal control alternatives in the irrigation district 'Sector BXII del Bajo Guadalquivir,' Spain -- Hydrodynamic behavior of a canal network under simultaneous supply and demand based operations -- Simulation on the effect of microtopography spatial variability on basin irrigation performance -- Drip irrigation as a sustainable practice under saline shallow ground water conditions -- Water retention, compaction and bean yield in different soil managements under a center pivot system -- Precision mechanical move irrigation for smallholding farmers -- Wild flood to graded border irrigation for water and energy conservation in the Klamath basin -- A method describing precise water application intensity under a CPIS from a limited number of measurements -- An irrigation sustainability assessment framework for reporting across the environmental-economic-social spectrum -- Planning for future irrigation landscapes -- One size does not fit all -- Water information networks -- Improving water use efficiency -- Irrigation system modernization in the Middle Rio Grande Valley -- Relationship of operation stability and automatic operation control methods of open canal -- Responsive strategies of agricultural water sector in Taiwan -- Effect of network water distribution schedule and different on-farm water management practices on sugarbeet water use efficiency -- Variable Frequency Drive (VFD) considerations for irrigation -- Accuracy of radar water level measurements -- Transition submergence and hysteresis effects in three-foot Cutthroat flumes -- Practical irrigation flow measurement and control -- Linear anionic PAM as a canal water seepage reducing technology -- In-situ non-destructive monitoring of water flow in damaged agricultural pipeline by AE -- Reoptimizing global irrigation systems to restore floodplain ecosystems and human livelihoods -- Water management technologies for sustainable agriculture in Kenya -- Impacts of changing rice irrigation practices on the shallow aquifer of Nasunogahara basin, Japan -- Drought protection from an in-lieu groundwater banking program -- Development of agricultural drought evaluation system in Korea -- Bean yield and root development in different soil managements under a center pivot system -- Can frost damage impact water demand for crop production in the future? -- Real time water delivery management and planning in irrigation and drainage networks -- Growth response of palm trees to the frequency of irrigation by bubblers in Khuzestan, Iran -- Application of Backpropagation Neural Network to estimate evapotranspiration for ChiaNan irrigated area, Taiwan -- Increasing water and fertilizer use efficiency through rain gun sprinkler irrigation in sugar cane agriculture