Crop monitoring and detection of anomalous crop development at the parcel-level with multispectral and synthetic aperture radar satellite data

Crop monitoring will become a major challenge in the coming years. Under the pressure of climate change on the one hand, and the increase of the world population on the other hand, food supply chains are likely to be strongly constrained, impacting food security in many areas of the planet. In this context, using remote sensing to acquire information on vegetation status will be a key asset. One of the areas directly concerned is precision agriculture, which consists in optimizing yields and agricultural practices. With the arrival of the Copernicus mission satellites, Sentinel-1 (synthetic aperture radar) and Sentinel-2 (multispectral imagery), the possibilities of applications in this area have increased drastically. Indeed, Sentinel data are freely available, with a temporal and spatial resolution adapted to crop monitoring at the parcel level. The main objective of this thesis is to propose a strategy to automatically detect agricultural parcels with abnormal agronomic development. Special attention was given to the joint use of Sentinel-1 and Sentinel-2 data. Moreover, in order to be easily deployed in an operational context, a constraint is to have a method able to analyzing a single growth cycle (or a part of it). To meet the objectives of the thesis, we first propose a processing chain allowing the extraction of agronomic indicators at the parcel-level. These indicators are calculated in two steps: 1) calculation of agronomic indicators at the pixel level and 2) calculation of spatial statistics at the plot level. Then, these indicators are used to detect parcels with abnormal phenological behavior. The detection is unsupervised and performed using an anomaly detection algorithm. A comparison of several approaches was made to find the most suitable method for our problem. Among the different algorithms tested, the most efficient method is the isolation forest, which also has the advantage of being fast and not very sensitive to the choice of its parameters. Thanks to the proposed method, it is possible to detect plots with abnormal behavior with a high accuracy. The results obtained were validated on two different types of crops, wheat and rapeseed. In a second step, we addressed the problem of anomaly detection in the presence of missing data. This problem is fundamental in remote sensing, in particular for multispectral data because they are sensitive to cloud cover. To solve this problem, we propose to reconstruct the missing data (at the parcel-level) using Gaussian mixture models. This approach has been found to be significantly better than the other tested approaches for reconstructing missing data and for detecting anomalies on parcels with incomplete time series. In addition, we also have proposed a method for estimating Gaussian mixture models that are robust to the presence of outliers in the data. This method is particularly useful in the presence of strong outlier values, for example in the presence of parcels coming from a different crop type than the one analyzed. Finally, we explore in this thesis anomaly detection approaches that take into account the temporal structure of the data. In particular, we propose a method based on an ensemble of hidden Markov models. One of the interests of this approach is to be able to localize the anomalies in time

A Review of Vegetation Phenological Metrics Extraction Using Time-Series, Multispectral Satellite Data

Vegetation dynamics and phenology play an important role in inter-annual vegetation changes in terrestrial ecosystems and are key indicators of climate-vegetation interactions, land use/land cover changes, and variation in year-to-year vegetation productivity. Satellite remote sensing data have been widely used for vegetation phenology monitoring over large geographic domains using various types of observations and methods over the past several decades. The goal of this paper is to present a detailed review of existing methods for phenology detection and emerging new techniques based on the analysis of time-series, multispectral remote sensing imagery. This paper summarizes the objective and applications of detecting general vegetation phenology stages (e.g., green onset, time or peak greenness, and growing season length) often termed “land surface phenology,” as well as more advanced methods that estimate species-specific phenological stages (e.g., silking stage of maize). Common data-processing methods, such as data smoothing, applied to prepare the time-series remote sensing observations to be applied to phenological detection methods are presented. Specific land surface phenology detection methods as well as species-specific phenology detection methods based on multispectral satellite data are then discussed. The impact of different error sources in the data on remote-sensing based phenology detection are also discussed in detail, as well as ways to reduce these uncertainties and errors. Joint analysis of multiscale observations ranging from satellite to more recent ground-based sensors is helpful for us to understand satellite-based phenology detection mechanism and extent phenology detection to regional scale in the future. Finally, emerging opportunities to further advance remote sensing of phenology is presented that includes observations from Cubesats, near-surface observations such as PhenoCams, and image data fusion techniques to improve the spatial resolution of time-series image data sets needed for phenological characterization

Earth resources: A continuing bibliography with indexes (issue 47)

This bibliography lists 524 reports, articles and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1985. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Earth resources: A continuing bibliography, issue 46

This bibliography lists 467 reports, articles and other documents introdcued into the NASA scientific and technical information system between April 1 and June 30, 1985. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental cultural resources geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Earth Resources, A Continuing Bibliography with Indexes

This bibliography lists 460 reports, articles and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1984. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Earth Resources: A continuing bibliography with indexes (Issue 37)

This bibliography lists 512 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1983. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Remote Sensing in Agriculture: State-of-the-Art

The Special Issue on “Remote Sensing in Agriculture: State-of-the-Art” gives an exhaustive overview of the ongoing remote sensing technology transfer into the agricultural sector. It consists of 10 high-quality papers focusing on a wide range of remote sensing models and techniques to forecast crop production and yield, to map agricultural landscape and to evaluate plant and soil biophysical features. Satellite, RPAS, and SAR data were involved. This preface describes shortly each contribution published in such Special Issue

Earth Resources: A continuing bibliography with indexes

This bibliography lists 475 reports, articles and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1984. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis