Data and knowledge of the spatial-temporal dynamics of surface water area (SWA) and terrestrial water storage (TWS) in China are critical for sustainable management of water resources but remain very ...limited. Here we report annual maps of surface water bodies in China during 1989-2016 at 30m spatial resolution. We find that SWA decreases in water-poor northern China but increases in water-rich southern China during 1989-2016. Our results also reveal the spatial-temporal divergence and consistency between TWS and SWA during 2002-2016. In North China, extensive and continued losses of TWS, together with small to moderate changes of SWA, indicate long-term water stress in the region. Approximately 569 million people live in those areas with deceasing SWA or TWS trends in 2015. Our data set and the findings from this study could be used to support the government and the public to address increasing challenges of water resources and security in China.
We consider the joint design of packet forwarding policies and controllers for wireless control loops where sensor measurements are sent to the controller over an unreliable and energy-constrained ...multi-hop wireless network. For fixed sampling rate of the sensor, the co-design problem separates into two well-defined and independent subproblems: transmission scheduling for maximizing the deadline-constrained reliability and optimal control under packet loss. We develop optimal and implementable solutions for these subproblems and show that the optimally co-designed system can be efficiently found. Numerical examples highlight the many trade-offs involved and demonstrate the power of our approach.
This paper studies online shortest path routing over multihop networks. Link costs or delays are time varying and modeled by independent and identically distributed random processes, whose parameters ...are initially unknown. The parameters, and hence the optimal path, can only be estimated by routing packets through the network and observing the realized delays. Our aim is to find a routing policy that minimizes the regret (the cumulative difference of expected delay) between the path chosen by the policy and the unknown optimal path. We formulate the problem as a combinatorial bandit optimization problem and consider several scenarios that differ in where routing decisions are made and in the information available when making the decisions. For each scenario, we derive a tight asymptotic lower bound on the regret that has to be satisfied by any online routing policy. Three algorithms, with a tradeoff between computational complexity and performance, are proposed. The regret upper bounds of these algorithms improve over those of the existing algorithms. We also assess numerically the performance of the proposed algorithms and compare it to that of existing algorithms.
Open surface water bodies play an important role in agricultural and industrial production, and are susceptible to climate change and human activities. Remote sensing data has been increasingly used ...to map open surface water bodies at local, regional, and global scales. In addition to image statistics-based supervised and unsupervised classifiers, spectral index- and threshold-based approaches have also been widely used. Many water indices have been proposed to identify surface water bodies; however, the differences in performances of these water indices as well as different sensors on water body mapping are not well documented. In this study, we reviewed and compared existing open surface water body mapping approaches based on six widely-used water indices, including the tasseled cap wetness index (TCW), normalized difference water index (NDWI), modified normalized difference water index (mNDWI), sum of near infrared and two shortwave infrared bands (Sum457), automated water extraction index (AWEI), land surface water index (LSWI), as well as three medium resolution sensors (Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-2 MSI). A case region in the Poyang Lake Basin, China, was selected to examine the accuracies of the open surface water body maps from the 27 combinations of different algorithms and sensors. The results showed that generally all the algorithms had reasonably high accuracies with Kappa Coefficients ranging from 0.77 to 0.92. The NDWI-based algorithms performed slightly better than the algorithms based on other water indices in the study area, which could be related to the pure water body dominance in the region, while the sensitivities of water indices could differ for various water body conditions. The resultant maps from Landsat 8 and Sentinel-2 data had higher overall accuracies than those from Landsat 7. Specifically, all three sensors had similar producer accuracies while Landsat 7 based results had a lower user accuracy. This study demonstrates the improved performance in Landsat 8 and Sentinel-2 for open surface water body mapping efforts.
Aberrant expression of HOXA9 is a prominent feature of acute leukemia driven by diverse oncogenes. Here we show that HOXA9 overexpression in myeloid and B progenitor cells leads to significant ...enhancer reorganizations with prominent emergence of leukemia-specific de novo enhancers. Alterations in the enhancer landscape lead to activation of an ectopic embryonic gene program. We show that HOXA9 functions as a pioneer factor at de novo enhancers and recruits CEBPα and the MLL3/MLL4 complex. Genetic deletion of MLL3/MLL4 blocks histone H3K4 methylation at de novo enhancers and inhibits HOXA9/MEIS1-mediated leukemogenesis in vivo. These results suggest that therapeutic targeting of HOXA9-dependent enhancer reorganization can be an effective therapeutic strategy in acute leukemia with HOXA9 overexpression.
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•Leukemogenesis driven by HOXA9 is accompanied by epigenome remodeling•HOXA9 mediates the establishment of de novo enhancers in leukemia cells•HOXA9 interacts with the MLL3/MLL4 histone methyltransferase complex•MLL3/MLL4 complex is required for HOXA9/MEIS1 leukemia in vitro and in vivo
Sun et al. show that HOXA9 overexpression in myeloid and B progenitor cells induces emergence of leukemia-specific enhancers by recruiting CEBPα and the MLL3/MLL4 complex, leading to activation of an ectopic embryonic gene program. Genetic deletion of MLL3/MLL4 inhibits HOXA9/MEIS1-mediated leukemogenesis.
South America has the largest tropical rainforests and the richest biodiversity in the world. It is challenging to map tropical forests and their spatio-temporal changes because forests are facing ...fragmentation from human activities (e.g., logging, deforestation), drought, and fire, as well as persistent clouds. Here we present a robust approach to map forests in South America during 2007–2010 and analyze the consistency and uncertainty among eight major forest maps in South America. Greenness-relevant MOD13Q1 NDVI and structure/biomass-relevant ALOS PALSAR time series data recorded 2007 through 2010 were coupled to identify and map forests at 50-m spatial resolution. Both area and spatial comparison were conducted to analyze the consistency and uncertainty of these eight forest maps. Annual 50-m PALSAR/MODIS forest maps were generated during 2007–2010 and the total forest area in South America was about 8.63×106km2 in 2010. Large differences in total forest area (8.2×106km2–12.7×106km2) existed among these forest products, especially in the forest edges, semi-humid tropical, and subtropical regions. Forest products generated under a similar forest definition had similar or even larger variation than those generated with contrasting forest definitions. We also find out that one needs to consider leaf area index as an adjusting factor and use much higher threshold values in the Vegetation Continuous Field (VCF) datasets to estimate forest cover areas. Analyses of PALSAR/MODIS forest maps in 2008/2009 showed a relatively small rate of loss (3.2×104km2year−1) in net forest cover, similar to that of FAO FRA (3.3×104km2year−1), but much higher annual rates of forest loss and gain. The rate of forest loss (0.195×106km2year−1) was higher than that of Global Forest Watch (0.081×106km2year−1). PALSAR/MODIS forest maps showed that more deforestation occurred in the unfragmented forest areas. Caution should be used when using the different forest maps to analyze forest loss and make policies regarding forest ecosystem services and biodiversity conservation. The integration of PALSAR and MODIS images during 2007–2010 provides annual maps of forests in South America with improved accuracy and reduced uncertainty.
•Annual 50-m PALSAR/MODIS forest maps in South America during 2007–2010.•PALSAR/MODIS forest maps report small net forest loss, close to that of FAO FRA.•PALSAR/MODIS forest maps report much larger forest changes (gain, loss) than GFW did.•Much higher threshold values in VCF datasets should be used to estimate forest cover.•Microwave/optical imagery combination is essential for accurately mapping of forests.
We develop optimal sleeping and harvesting policies for radio frequency (RF) energy harvesting devices, formalizing the following intuition: when the ambient RF energy is low, devices consume more ...energy being awake than what can be harvested and should enter sleep mode; when the ambient RF energy is high, on the other hand, it is essential to wake up and harvest. Toward this end, we consider a scenario with intermittent energy arrivals described by a two-state Gilbert-Elliott Markov chain model. The challenge is that the state of the Markov chain can only be observed during the harvesting action, and not while in sleep mode. Two scenarios are studied under this model. In the first scenario, we assume that the transition probabilities of the Markov chain are known and formulate the problem as a partially observable Markov decision process (POMDP). We prove that the optimal policy has a threshold structure and derive the optimal decision parameters. In the practical scenario where the ratio between the reward and the penalty is neither too large nor too small, the POMDP framework and the threshold-based optimal policies are very useful for finding non-trivial optimal sleeping times. In the second scenario, we assume that the Markov chain parameters are unknown and formulate the problem as a Bayesian adaptive POMDP and propose a heuristic posterior sampling algorithm to reduce the computational complexity. The performance of our approaches is demonstrated via numerical examples.
Post-disaster recovery plans and policies can be better made after understanding which households are in the greatest need of help and support in post-disaster life recovery. In this study, we ...analyzed influencing factors of households with a disadvantaged status of life recovery, which could then be used as indicators for detecting households in urgent need of help at the beginning of post-disaster recovery. Based on life recovery field survey data from the 2008 Wenchuan earthquake, we found 81 disadvantaged households, identified by the fact that they lagged behind in the post-earthquake life recovery process. Using logit regression, we analyzed the influencing factors of disadvantaged households that may distinguish them from more prosperous ones. The results showed that the lower economic status, longer duration of unemployment, loss of loved ones and the less education are the significant influencing factors of disadvantaged households. Therefore, the poor and unemployed households who are less educated and suffered the trauma of losing loved ones should be made a priority in post-disaster recovery planning and policy making in consideration of their disadvantaged status in life recovery.
The Delmarva Peninsula in the eastern United States is partially characterized by thousands of small, forested, depressional wetlands that are highly sensitive to weather variability and climate ...change, but provide critical ecosystem services. Due to the relatively small size of these depressional wetlands and their occurrence under forest canopy cover, it is very challenging to map their inundation status based on existing remote sensing data and traditional classification approaches. In this study, we applied a state-of-the-art U-Net semantic segmentation network to map forested wetland inundation in the Delmarva area by integrating leaf-off WorldView-3 (WV3) multispectral data with fine spatial resolution light detection and ranging (lidar) intensity and topographic data, including a digital elevation model (DEM) and topographic wetness index (TWI). Wetland inundation labels generated from lidar intensity were used for model training and validation. The wetland inundation map results were also validated using field data, and compared to the U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) geospatial dataset and a random forest output from a previous study. Our results demonstrate that our deep learning model can accurately determine inundation status with an overall accuracy of 95% (Kappa = 0.90) compared to field data and high overlap (IoU = 70%) with lidar intensity-derived inundation labels. The integration of topographic metrics in deep learning models can improve the classification accuracy for depressional wetlands. This study highlights the great potential of deep learning models to improve the accuracy of wetland inundation maps through use of high-resolution optical and lidar remote sensing datasets.
Quantifying the spatial pattern of large-scale forest biomass can provide a general picture of the carbon stocks within a region and is of great scientific and political importance. The combination ...of the advantages of remote sensing data and field survey data can reduce uncertainty as well as demonstrate the spatial distribution of forest biomass. In this study, the seventh national forest inventory statistics (for the period 2004–2008) and the spatially explicit MODIS Land Cover Type product (MCD12C1) were used together to quantitatively estimate the spatially-explicit distribution of forest biomass in China (with a resolution of 0.05°, ~5600 m). Our study demonstrated that the calibrated forest cover proportion maps allow proportionate downscaling of regional forest biomass statistics to forest cover pixels to produce a relatively fine-resolution biomass map. The total stock of forest biomass in China was 11.9 Pg with an average of 76.3 Mg ha−1 during the study period; the high values were located in mountain ranges in northeast, southwest and southeast China and were strongly correlated with forest age and forest density.
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