A major application of satellite remote sensing is the estimation of the acreage of agricultural crops. The potential for crop yield estimation using satellite remote sensing exists, but research in this area is still in its early stages. In this paper we survey the methodology for using remotely sensed data in agricultural surveys, based primarily on research conducted during the Large Area Crop Inventory Experiment (LACIE) and the follow-on program Agricultural Research and Inventory Surveys Through Aerospace Remote Sensing (AgRISTARS). The data obtained from multispectral scanner (MSS) and thematic mapper (TM) sensors onboard the Landsat series of satellites are described. Approaches for preprocessing, transferring, and modeling these data for understanding the relationship between their temporal behavior and crop growth cycles are discussed. Finally, techniques for crop identification and area and yield estimation are briefly described 相似文献
Satellite data used in combination with a stochastic production function method reveal an inefficient formal economy in rural Rostov Oblast 2013–2015 embedded in an overall (formal and informal) relatively efficient economy with the measurement of both important to better understand non-economic impacts of sanctions. Increased military activity may have insulated the formal economy of the border area from poor economic performance and the deindustrialization that characterizes adjacent areas. The current Oblast Administration’s grant program to localities does not reward relatively efficient economic performance with a model suggested here to change the policy. The region’s economy has the ability to absorb many Ukrainian refugees though non-economic issues support the current assistance from other Russian regions in helping relocate refugees beyond Rostov region. Like other conflict zones, urban areas experience less of an impact relative to rural areas. 相似文献
Background: The etiology of benign prostatic hyperplasia (BPH) has not been well established. The preferred medical treatment for many men with symptomatic benign prostatic hyperplasia is either an α-adrenergic receptor antagonist (α-blocker), or a 5α-reductase inhibitor. Single nucleotide polymorphism (SNP) is a powerful tool for successful implementation of individualized treatment.Methods: Eighteen SNPs associated with drug efficacy in a Chinese population were genotyped in 790 BPH cases (330 aggressive and 460 non-aggressive BPH cases) and 1008 controls. All BPH patients were treated with α-adrenergic blockers for at least 9 months. We tested the associations between tagging single nucleotide polymorphism and BPH risk/aggressiveness, clinical characteristics at baseline, including the International Prostate Symptom Score (IPSS) and total prostate volume, and changes in clinical characteristics after treatment.Results: There were nine SNPs associated with BPH risk, clinical progression and therapeutic effect. (1) There were nine tSNPs been chosen in CYP3A4, CYP3A5 and RANBP3L genes. (2) The SNP, rs16902947 in RANBP3L at 5p13.2 (p?=?.01), was significantly associated with BPH. (3) We found two SNPs, rs16902947 in RANBP3L at 5p13.2 (p?=?.0388) and rs4646437 in CYP3A4 at 7q21.1 (p?=?.0325), associated with drug effect. (4) Allele “G” for rs16902947 was found to be risk alleles for BPH risk (OR=?2.357, 95%CI 1.01–1.48). The “A” allele of rs4646437 was associated with lower IPSS at baseline (β=??0.4232, p=?.03255).Conclusions: rs16902947, rs16902947 and rs4646437 single nucleotide polymorphisms are significantly associated with the clinical characteristics of benign prostatic hyperplasia and the efficacy of benign prostatic hyperplasia treatment. 相似文献
Remote sensing is a helpful tool for crop monitoring or vegetation-growth estimation at a country or regional scale. However, satellite images generally have to cope with a compromise between the time frequency of observations and their resolution (i.e. pixel size). When concerned with high temporal resolution, we have to work with information on the basis of kilometric pixels, named mixed pixels, that represent aggregated responses of multiple land cover. Disaggreggation or unmixing is then necessary to downscale from the square kilometer to the local dynamic of each theme (crop, wood, meadows, etc.).
Assuming the land use is known, that is to say the proportion of each theme within each mixed pixel, we propose to address the downscaling issue through the generalization of varying-time regression models for longitudinal data and/or functional data by introducing random individual effects. The estimators are built by expanding the mixed pixels trajectories with B-splines functions and maximizing the log-likelihood with a backfitting-ECME algorithm. A BLUP formula allows then to get the ‘best possible’ estimations of the local temporal responses of each crop when observing mixed pixels trajectories. We show that this model has many potential applications in remote sensing, and an interesting one consists of coupling high and low spatial resolution images in order to perform temporal interpolation of high spatial resolution images (20 m), increasing the knowledge on particular crops in very precise locations.
The unmixing and temporal high-resolution interpolation approaches are illustrated on remote-sensing data obtained on the South-Western France during the year 2002. 相似文献