Proxying economic activity with daytime satellite imagery: Filling data gaps across time and space

This paper develops a novel procedure for proxying economic activity with daytime satellite imagery across time periods and spatial units, for which reliable data on economic activity are otherwise not available. In developing this unique proxy, we apply machine-learning techniques to a historical time series of daytime satellite imagery dating back to 1984. Compared to satellite data on night light intensity, another common economic proxy, our proxy more precisely predicts economic activity at smaller regional levels and over longer time horizons. We demonstrate our measure’s usefulness for the example of Germany, where East German data on economic activity are unavailable for detailed regional levels and historical time series. Our procedure is generalizable to any region in the world, and it has great potential for analyzing historical economic developments, evaluating local policy reforms, and controlling for economic activity at highly disaggregated regional levels in econometric applications

Estimación de la fAPAR sobre la Península Ibérica a partir de la inversión del modelo de transferencia radiativa 4SAIL2

Revista oficial de la Asociación Española de Teledetección[EN] This work aims to the estimation of fAPAR over the Iberian Peninsula using MODIS data. First, the 4SAIL2 and PROSPECT radiative transfer models have been used to simulate a data set of reflectance and fAPAR. Second, an artificial neuronal network (ANN) has been trained using the simulated data and finally, it has been inverted to derive fAPAR estimates over the Iberian Peninsula from MODIS reflectances images. Moreover, the impact that the observation and illumination configuration have on the fAPAR estimates has been assessed. The fAPAR estimates from MODIS have been compared with other validated fAPAR products. The results confirm an overall error around the user requirements (0.1) when the fAPAR estimated from the (PROSPECT+4SAIL2+Nadir) combination is compared with the selected products. This combination is proposed as an alternative to estimate fAPAR over the Iberian Peninsula due to the ability to characterize different land cover types as well as the high intra-annual variability of particular canopies[ES] El objetivo de este trabajo consiste en la estimación de la fAPAR en la Península Ibérica a partir de datos MODIS. En primer lugar, se ha simulado un conjunto de datos de reflectividades y de fAPAR a partir de los modelos de transferencia radiativa de hoja (PROSPECT) y de cubiertas heterogéneas (4SAIL2). En segundo lugar, se ha entrenado un conjunto de redes neuronales artificiales (RNAs) para obtener mediante inversión la relación entre la fAPAR y las reflectividades simuladas y así calcular, por último, la fAPAR de la Península Ibérica a partir de imágenes de reflectivi-dad de MODIS. Además, se ha analizado la influencia de la configuración de observación e iluminación, nadir y oblicua. La fAPAR estimada se ha comparado con otros productos ya validados. Los resultados ponen de manifiesto que la fAPAR estimada a partir de la combinación (PROSPECT+4SAIL2+Nadir) proporciona, en general, diferencias alrededor del umbral requerido por los usuarios (0,1). Esta combinación se plantea como una alternativa para estimar la fAPAR en la Península Ibérica por su capacidad para caracterizar distintos tipos de cubiertas, así como por la alta variabilidad intra-anual observada en algunos casosEste trabajo ha sido financiado por los proyectos ARTEMIS (CGL2008–00381), RESET CLIMATE (CGL2012–35831) y LSA SAF de Eumetsat. Los autores agradecen los comentarios de los revisores que han ayudado a mejorar significativamente el trabajo. Los productos MCD43A1, MCD43A2 y MOD17A2 han sido proporcionadas por el centro de datos Data Pool at the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota.Martínez, B.; Albargues, E.; Camacho, F.; Moreno, A.; Gilabert, MA. (2014). fAPAR estimates over the Iberian Peninsula by the inversion of the 4SAIL 2 radiative transfer model. Revista de Teledetección. (42):61-78. https://doi.org/10.4995/raet.2014.3177SWORD61784

Land cover harmonization using Latent Dirichlet Allocation

Large-area land cover maps are produced to satisfy different information needs. Land cover maps having partial or complete spatial and/or temporal overlap, different legends, and varying accuracies for similar classes, are increasingly common. To address these concerns and combine two 30-m resolution land cover products, we implemented a harmonization procedure using a Latent Dirichlet Allocation (LDA) model. The LDA model used regionalized class co-occurrences from multiple maps to generate a harmonized class label for each pixel by statistically characterizing land attributes from the class co-occurrences. We evaluated multiple harmonization approaches: using the LDA model alone and in combination with more commonly used information sources for harmonization (i.e. error matrices and semantic affinity scores). The results were compared with the benchmark maps generated using simple legend crosswalks and showed that using LDA outputs with error matrices performed better and increased harmonized map overall accuracy by 6–19% for areas of disagreement between the source maps. Our results revealed the importance of error matrices to harmonization, since excluding error matrices reduced overall accuracy by 4–20%. The LDA-based harmonization approach demonstrated in this paper is quantitative, transparent, portable, and efficient at leveraging the strengths of multiple land cover maps over large areas

ACCURACIES, ERRORS, AND UNCERTAINTIES OF GLOBAL CROPLAND PRODUCTS

ABSTRACT ACCURACIES, ERRORS, AND UNCERTAINTIES OF GLOBAL CROPLAND PRODUCTS By Kamini Yadav University of New Hampshire, May 2019 Global cropland products are continuously being produced at different spatial resolutions using remotely sensed satellite imagery. Recently, with our increased accessibility to higher computing processing, three different cropland extent maps have been developed as a part of Global Food Security-Support Analysis Data (GFSAD) project at three spatial resolutions (i.e., GFSAD1km, GFSAD250m, and GFSAD30m). All cropland maps should be assessed for their accuracy, errors, and uncertainty for various agriculture monitoring applications. However, in previous assessment efforts appropriate assessment strategies have not always been applied and many have reported only a single accuracy measure for the entire world. This research was divided into four components to provide more attention and focus on the accuracy assessment of large area cropland products. First, a valid assessment of cropland extent maps was performed addressing different strategies, issues, and constraints depending upon various conditions related to the cropland distribution, proportion, and pattern present in each continent. This research focused on dealing with some specific issues encountered when assessing the cropland extent of North America (confined to the United States), Africa and Australia. Continent-specific sampling strategies and accuracy assessments were performed within homogenous regions (i.e., strata) of different continents to ensure that an appropriate reference data set was collected to generate rigorous and valid accuracy results indicative of the actual cropland proportion. Second, all the three different GFSAD cropland extent maps were assessed using appropriate sampling and collection of a cropland reference data based on the cropland distribution and proportion for different regions in the entire world. In addition to the accuracy assessment, the cropland extent maps developed at the three spatial resolutions were compared to investigate the differences among them and provide guidance for users to select the appropriate resolution given different agriculture field sizes. The comparison of three different GFSAD cropland extent maps was performed based on the similarity of the cropland area proportion (CAP) and landscape clumping at different spatial resolutions to provide specific recommendations for when to apply these maps in different agriculture field sizes. Third, an issue was discovered with the accuracy assessment of 30m global cropland extent map (i.e., GFSAD30m) in that insufficient samples were collected resulting in an ineffective assessment when the cropland map class was rare as occurred in some regions around the world. This research evaluated the sampling designs for different cropland regions to achieve sufficient samples and effective accuracy of rare cropland map class by comparing the distribution, allocation of samples and accuracy measures. The evaluation of sampling designs demonstrated that the cropland regions of \u3c15% CAP must be sampled with an appropriate stratified sampling combined with a predetermined minimum sample size for each map class. Finally, the accuracy assessment of all thematic maps (e.g., crop type maps) needs sufficient reference data to conduct a valid assessment. The availability of reference data is a severely limiting factor over large geographic region because of the time, effort, cost, and accessibility in different parts of the world. The objectives of this research were to augment and extend the limited availability of crop type reference data using non-ground-based sources of crop type information for creating and assessing large area crop type maps. There is the potential to either interpret the photographs available from Google Street View (GSV) or classify High Resolution Imagery (HRI) using a phenology-based classification approach to generate additional reference data within similar agriculture ecological zones (AEZs) based on the crop characteristics, their types, and growing season. These two methods of augmenting and extending crop type reference data were developed for the United States (US) where high-quality crop type reference data already exist so that the methods could be effectively and efficiently tested. This research described a tale of three continents providing recommendations to adapt accuracy assessment strategies and methodologies for assessing global cropland extent maps. Based on these results, the assessment and comparison of different resolution GFSAD cropland extent maps were performed to provide specific recommendations for when to apply each of the maps for agriculture monitoring based on the agriculture field sizes. When assessing the cropland extent maps, different sampling strategies perform differently in the various cropland proportion regions and therefore, must be selected according to the cropland extent maps to be assessed. Finally, this research concluded that the limited crop type reference data can be effectively extended using a phenology-based classification approach and is more efficient than the interpretation of photographs collected from GSV

Simulació de fluxos de carboni terrestres mitjançant teledetecció i modelització d'ecosistemes

The main goal of this thesis is the establishment of a framework to analyze the Spanish forest ecosystems in terms of their role in the carbon cycle. In particular, the carbon fluxes that they exchange with atmosphere are modeled to evaluate their potential as carbon sinks and biomass reservoirs. Gross fluxes are estimated by a production efficiency model relying on the Monteith’s approach. The emphasis is put in characterizing the water stress effects on the light use efficiency and, eventually, on the GPP. Six alternatives are evaluated. Among them, the ones using the ratio between the MODIS actual and potential evapotranspiration, and the soil moisture from SMOS demonstrate that it is possible to characterize the water stress on GPP using only remote sensing products. Daily images of GPP are calculated and used as a reference in the rest of the thesis. The reference GPP is then used to calibrate and validate a semi-empirical model for the estimation of annual GPP. This model is a simplification of the Monteith approach that relies on a linear relationship between GPP and a PAR-weighted vegetation index (VI). This semi-empirical model can be used to estimate the annual GPP from commonly available VI images and a representative PAR, which does not require actual meteorological data. Therefore, inputs and computing time are considerably reduced. NDVI and EVI are tested. EVI does not need a land cover map, reducing the number of inputs even more. NDVI allows the elaboration of climatic studies that require long time series. Ecosystem respirations are simulated through Biome-BGC. A methodology to calibrate the rooting depth parameter, critical to the simulation of the water balance, is developed. The optimal rooting depth is obtained by comparing the reference GPP with the one simulated by Biome-BGC. The methodology is first tested in 4 validation sites and then extended to the whole study area. As a result, daily GPP maps and an optimal rooting depth map are obtained. Reference GPP and optimized respirations are used to calculate net fluxes. However, both GPP and respiration must be previously corrected. The first one because it represents the contribution of all the vegetation present in the considered area, not only the one from the forests. The second one because Biome-BGC works on equilibrium conditions and does not represent the actual state of the ecosystem. To do so, the necessary information layer, a growing stock map, is produced by the combination of the Third Spanish National Forest Inventory data (more than 50000 plot along the 1997-2007 period) and Landsat-5 TM and Landsat-7 ETM+ imagery (more than 8000 scenes covering the whole study area during the inventory period). Finally, preliminary net fluxes resulting from the corrected GPP and respirations are presented and validated.The main goal of this thesis is the establishment of a framework to analyze the Spanish forest ecosystems in terms of their role in the carbon cycle. In particular, the carbon fluxes that they exchange with atmosphere are modeled to evaluate their potential as carbon sinks and biomass reservoirs. Gross fluxes are estimated by a production efficiency model relying on the Monteith’s approach. The emphasis is put in characterizing the water stress effects on the light use efficiency and, eventually, on the GPP. Six alternatives are evaluated. Among them, the ones using the ratio between the MODIS actual and potential evapotranspiration, and the soil moisture from SMOS demonstrate that it is possible to characterize the water stress on GPP using only remote sensing products. Daily images of GPP are calculated and used as a reference in the rest of the thesis. The reference GPP is then used to calibrate and validate a semi-empirical model for the estimation of annual GPP. This model is a simplification of the Monteith approach that relies on a linear relationship between GPP and a PAR-weighted vegetation index (VI). This semi-empirical model can be used to estimate the annual GPP from commonly available VI images and a representative PAR, which does not require actual meteorological data. Therefore, inputs and computing time are considerably reduced. NDVI and EVI are tested. EVI does not need a land cover map, reducing the number of inputs even more. NDVI allows the elaboration of climatic studies that require long time series. Ecosystem respirations are simulated through Biome-BGC. A methodology to calibrate the rooting depth parameter, critical to the simulation of the water balance, is developed. The optimal rooting depth is obtained by comparing the reference GPP with the one simulated by Biome-BGC. The methodology is first tested in 4 validation sites and then extended to the whole study area. As a result, daily GPP maps and an optimal rooting depth map are obtained. Reference GPP and optimized respirations are used to calculate net fluxes. However, both GPP and respiration must be previously corrected. The first one because it represents the contribution of all the vegetation present in the considered area, not only the one from the forests. The second one because Biome-BGC works on equilibrium conditions and does not represent the actual state of the ecosystem. To do so, the necessary information layer, a growing stock map, is produced by the combination of the Third Spanish National Forest Inventory data (more than 50000 plot along the 1997-2007 period) and Landsat-5 TM and Landsat-7 ETM+ imagery (more than 8000 scenes covering the whole study area during the inventory period). Finally, preliminary net fluxes resulting from the corrected GPP and respirations are presented and validated

Characterization of terrestrial ecosystems state based on interannual variations of RUE (Rain Use Efficiency)

[EN] Ecosystems degradation has increased in recent decades and climate change is expected to increase the risk of such processes in the coming years, especially in arid and semi-arid ecosystems. The purpose of this work is to characterize the state of the terrestrial ecosystems of the Spanish mainland and the Balearic Islands through the temporal analysis of the variable RUE (Rain Use Efficiency) during the period 2004-2018. Annual RUE images have been calculated as the quotient between annual gross primary production (GPP) and annual cumulative precipitation (PPT) in a 1 km spatial resolution, and the values have been later normalized. The annual GPP is derived from the daily GPP, obtained using an optimization of the Monteith model and the PPT from daily precipitation images, which are computed by applying a kriging to the data from AEMet network stations. Temporal analysis of the RUE has been made by calculating the slope from a Mann-Kendall test and Sen-Theil method. RUE has been analyzed at three levels of study: at regional level, by vegetation types and at pixel level. The results have shown a negative trend of the normalized RUE (between -0.05 and -0.25 year-1) for most of the area, for the 9 classes of vegetation (the forest classes being the ones that have presented the steepest slopes) and in 5 of the 8 ecosystems analyzed at pixel level. A decline in the RUE indicates some degree of degradation in vegetation cover. From the analysis of the results it has been extracted that the interannual variability of the RUE is largely mediated by precipitation, presenting a negative correlation. On the other hand, it has been observed that GPP has experienced a progressive increase in recent years known as greening process.[ES] La degradación de los ecosistemas se ha intensificado en las últimas décadas y se prevé que el cambio climático incremente su riesgo, sobre todo en los ecosistemas áridos y semiáridos. El objetivo de este trabajo es la caracterización del estado de los ecosistemas terrestres del territorio español peninsular y las Islas Baleares a través del análisis temporal de la variable RUE (Rain Use Efficiency) durante el periodo 2004-2018. Las imágenes de RUE anual se han calculado como el cociente entre la producción primaria bruta (GPP) anual y la precipitación acumulada (PPT) anual a una resolución espacial de 1 km, y posteriormente se han normalizado los valores. La GPP anual se deriva de la GPP diaria, obtenida por medio de datos satelitales (método de Monteith) y la PPT a partir de las imágenes de precipitación diaria, que proceden de aplicar una interpolación espacial kriging a los datos de las estaciones de la red de AEMet. El análisis temporal de la RUE se ha realizado calculando su pendiente con el test de Mann-Kendall y el método de Sen-Theil. La RUE se ha analizado a tres niveles de estudio: a nivel regional, por tipos de vegetación y a nivel de píxel. Los resultados han mostrado una tendencia negativa de la RUE normalizada (entre -0,05 y -0,25 año–1) para la mayoría del territorio, para las 9 clases de vegetación (siendo las clases forestales las que han presentado las pendientes más acusadas) y en 5 de los 8 ecosistemas analizados a nivel de píxel. Un declive en la RUE indica cierta degradación en la cubierta vegetal. Del análisis de los resultados se ha extraído que la variabilidad interanual de la RUE se encuentra mediada en gran parte por la precipitación (correlación negativa). Se ha observado que la GPP ha experimentado en los últimos años un incremento progresivo conocido como greening.El presente trabajo se ha realizado con una Ayuda de colaboración en la investigación para estudiantes de la Universitat de València durante el curso 2020-2021. 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