DETAILED ACTION
Status of Claims
Claims 2, 6, 12-13 are canceled.
Claims 1, 3-5, 7-11, 14-15 are amended.
Claims 1, 3-5, 7-11, 14-15 are pending.
Priority
Applicant’s claim for the benefit of a prior-filed application filed in CN 202210980560.2 on 08/16/2022 under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-5, 7-11, 14-15 are rejected under 35 U.S.C. 101 the claimed invention is directed to an abstract idea.
Claims 1, 14-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites obtaining “a water storage sequence”.
The limitation of obtaining “a water storage sequence of the target reservoir according to a water level-water storage relationship curve”, as drafted, is an abstract idea grouping that, under its broadest reasonable interpretation, is a mathematical concept defined by mathematical equations. That is, a claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "obtaining" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims only recite calculations and variables to arrive at a mathematical concept – monitoring a reservoir water storage. Monitoring a reservoir water storage is recited at a high-level of generality (i.e., as a generic application for performing the calculations) such that it amounts no more than mere calculations to apply the exception by monitoring a reservoir water storage. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of monitoring a reservoir water storage to perform the mathematical calculations amounts to no more than mere equations without direct application to apply the exception. Mere equations without direct application to apply an exception by monitoring a reservoir water storage cannot provide an inventive concept. The claim is not patent eligible.
Claims 3-5, 7-11, are rejected 35 U.S.C. 101 due to their dependency on Claim 1.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3-5, 7-11, 14-15 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1, 14-15 recite the limitation “the classification algorithm comprising a random forest (RF) algorithm”. No written descriptive support is provided in the claims or instant specification teaching how this algorithm is implemented in order to determine a water area sequence. The instant specification points to where the information is obtained by citing “the above processes of classifying the SAR image sequence by the classification algorithm and determining the water area sequence of the target local waters are performed on the Google Earth Engine (GEE) cloud computing platform, so that local computational load can be greatly reduced.” No descriptive support is provided on how GEE is used to perform the classification algorithm. Further, water area data seems to be provided to GEE users without the methods/apparatus described in the claims.
Claims 3-5, 7-11 are rejected 35 U.S.C. 112(a) due to their dependency on Claim 1.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3-5, 7-11, 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Cheng (US 20220316876) in view of Schneider (US 20210319370).
Regarding Claims 1, 14-15, Cheng teaches the following limitations:
A system for monitoring a reservoir water storage, configured to perform: (Cheng - [0007] A method for continuous measurement of river flow based on satellite big data [0008] determining a river reach to conduct flow measurement: selecting a river reach of a river to conduct flow measurement, based on revisit positions, adjacent to each other, of various types of satellites; determining a cross section of a river channel where an echo point of an available high-precision altimetry satellite is located as a flow measurement section; and measuring by a three-dimensional (3D) surveying and mapping satellite, and determining a cross section with a gentle river bank as a flow measurement section, if there is no high-precision altimetry satellite available; and [0009] selecting, based on latest high-precision orthophoto/remote sensing image data, cross sections with a gentle river bank at a certain distance upstream and downstream from the flow measurement section as gradient sections, and measuring a distance L between upper and lower gradient sections; [0010] S2: reconstructing the cross section of the river channel based on satellite big data: coupling revisit times and observation elements of an altimetry satellite or a 3D surveying and mapping satellite and an orthophoto/remote sensing satellite available for the flow measurement section based on historical data thereof, and establishing water level and water surface breadth relationship curves of the flow measurement section and the gradient sections; [0011] S3: calculating real-time water levels by coupling data of the various types of satellites:)
(Claim 14) A computer device, comprising a memory and a processor, the memory having a computer program stored thereon, wherein, the processor, when executing the computer program, performs: (Cheng - [0008-0011], [0004] Due to the launch of surveying and mapping satellites such as the Resource series and the High-resolution series, and the implementation of programs such as the Surface Water and Ocean Topography Satellite (SWOT), the ability and accuracy to monitor the altitude and slope of surface water gradually improve. [0021] the various types of satellites include, but are not limited to, an altimetry satellite provided with a laser or radar altimeter, an orthophoto/remote sensing satellite, and a resource or surveying and mapping satellite configured for integrated 3D imaging.)
(Claim 15) A non-transitory computer-readable storage medium, having a computer program stored thereon, wherein the computer program, when executed by a processor, causes the processor to perform: (Cheng - [0004], [0008-0011], [0021])
acquiring a synthetic aperture radar (SAR) image sequence covering target local waters of a target reservoir; (Cheng - [0004], [0021])
the SAR image sequence comprising a plurality of SAR images acquired at different times; (Cheng - [0008-0011])
obtaining a feature vector of each of pixels in each SAR image according to the SAR image sequence, and the feature vector comprising a vertical-vertical (VV) backscattering coefficient, a vertical-horizontal (VH) backscattering coefficient, a VV backscattering coefficient processed by a moving average, a VH backscattering coefficient processed by the moving average, an elevation value, and a slope value; (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention as described in the instant specification.)
inputting the feature vector of each of the pixels into a classification algorithm to obtain a classification result of each of the pixels, (Cheng - [0004], [0008-0011], [0021])
the classification algorithm comprising a random forest (RF) algorithm; (Cheng - [0004], [0008-0011])
determining water pixels in the SAR image sequence according to classification results determining a water area sequence of the target local waters of the target reservoir according to each of the water pixels in the SAR image sequence, the water area sequence comprising water areas of the target local waters in the plurality of SAR images; (Cheng - [0004], [0008-0011], [0021])
acquiring an initial water level sequence of the target reservoir according to at least one of a laser altimetry satellite and a radar altimetry satellite, (Cheng - [0008-0011], [0021])
the initial water level sequence comprising water levels of the target reservoir changing with times; (Cheng - [0008-0011])
obtaining an initial partial water area sequence, corresponding to the initial water level sequence, from the water area sequence according to time information corresponding to the initial water level sequence; (Cheng - [0004], [0008-0011], [0021])
the initial partial water area sequence comprising water areas from the water area sequence corresponding to the same time as the water levels in the initial water level sequence; (Cheng - [0008-0011])
obtaining a first relationship between a water level of the target reservoir and a water area of the target local waters of the target reservoir based on the initial water level sequence of the target reservoir and the initial partial water area sequence of the target reservoir; converting the water area sequence into a target water level sequence according to the first relationship; the target water level sequence comprising a plurality of water levels of the target reservoir; and obtaining a water storage sequence of the target reservoir according to a water level-water storage relationship curve and the target water level sequence, (Cheng - [0004], [0008-0011], [0021])
the water storage sequence comprising a plurality of water storage values corresponding to the plurality of water levels in the target water level sequence. (Cheng - [0004], [0008-0011], [0021])
Cheng does not explicitly teach the following limitations, however Schneider, in the same field of endeavor, teaches:
Google Earth Engine data (Schneider – [0049] While FIG. 3 is sourced from the Google Earth Engine platform and API to pull the Landsat images and calculate the zonal statistics, there are numerous alternatives for all of the above steps including locating the necessary images on other cloud servers (e.g., Amazon S3, Microsoft Azure) or by purchasing the Landsat images directly from the USGS and NASA.)
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the satellite data of Cheng with the GEE data of Schneider in order to calculate statistics (Schneider – [0049]).
Cheng does not explicitly teach the following limitations, however Schneider, in the same field of endeavor, teaches:
random forest (RF) algorithm (Schneider – [0073] The precision of these estimates can improve when more complicated machine learning algorithms such as random forest and neural networks are employed.)
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the calculations of Cheng with the system of implementing a random forest algorithm of Schneider in order to conduct machine learning algorithms (Schneider – [0073]).
Regarding Claim 3, Cheng further teaches:
wherein the obtaining the first relationship between the water level of the target reservoir and the water area of the target local waters of the target reservoir based on the initial water level sequence of the target reservoir and the initial partial water area sequence of the target reservoir, comprises: (Cheng - [0004], [0008-0011], [0021])
processing the initial water level sequence of the target reservoir and the initial partial water area sequence of the target reservoir by a polynomial regression to obtain the first relationship between the water level of the target reservoir and the water area of the target local waters of the target reservoir. (Cheng - [0004], [0008-0011], [0021])
Regarding Claim 4, Cheng further teaches:
further configured to perform: acquiring a plurality of sample image pairs of the target local waters, each of the plurality of the sample image pairs comprising a sample optical image and a sample SAR image; determining a training region boundary according to the sample optical image, and the training region boundary being a boundary between water and land in the target local waters; (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
obtaining sample features according to the sample SAR images, and the sample features comprising a vertical-vertical (VV) backscattering coefficient, a vertical-horizontal (VH) backscattering coefficient, a VV backscattering coefficient processed by a moving average, a VH backscattering coefficient processed by the moving average, an elevation value, and a slope value; and selecting training samples from the sample SAR images according to the training region boundary, and inputting the sample features of the training samples into a RF classifier for training to obtain the classification algorithm. (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
Regarding Claim 5, Cheng further teaches:
wherein the determining the training region boundary according to the sample optical image comprises: (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
determining mixed water index (MWI) gray images of the sample optical image; converting the MWI gray images into binary images by using a maximum inter-class variance method, and the binary images comprising pixels representing a water portion and a land portion; and vectorizing the water portion in the binary images to obtain the training region boundary. (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
Regarding Claim 7, Cheng further teaches:
wherein before the obtaining the water storage sequence of the target reservoir according to the water level-water storage relationship curve and the target water level sequence, the system is configured to perform: (Cheng - [0004], [0008-0011], [0021])
acquiring laser point cloud elevation data higher than the highest water level of the target reservoir from a laser altimetry satellite; correcting a digital elevation model (DEM) according to the laser point cloud elevation data; (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellite, not the claimed invention.)
obtaining the elevation value of each grid point in a computation range from the corrected DEM, and the computation range being obtained according to a maximum water surface range of the target reservoir; and (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
determining the target water storage corresponding to the target water level according to the target water level, the number of the grid points in the computation range, and the elevation value of each of the grid points in the computation range, and obtaining the water level-water storage relationship curve of the target reservoir. (Cheng - [0004], [0008-0011], [0021])
Regarding Claim 8, Cheng further teaches:
wherein a time difference between time points, when the sample optical image and the sample SAR image in each of the plurality of sample image pairs are captured respectively, is less than five days. (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
Regarding Claim 9, Cheng further teaches:
wherein the target local waters refer to a region of the target reservoir with a flat terrain and wide open water surface. (Cheng - [0004], [0008-0011])
Regarding Claim 10, Cheng further teaches:
wherein the selecting the training samples from the sample SAR images according to the training region boundary, comprises: processing a buffer zone for the training region boundary by extending the training region boundary outwards by a certain distance; and selecting the training samples according to a ratio of the number of the water pixels to the number of land pixels being 1:3. (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
Regarding Claim 11, Cheng further teaches:
wherein the selecting training samples from the sample SAR images according to the training region boundary, and inputting the sample features of the training samples into the RF classifier for training to obtain the classification algorithm, comprise: (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
selecting 12 sets of training samples from the sample SAR images according to the training region boundary, and inputting the sample features of 11 sets of the selected training samples into the RF classifier for training to obtain the classification algorithm; and (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
after obtaining the classification algorithm, the system is further configured to perform: testing the classification algorithm by using a remaining set of the training samples. (Cheng - [0004], [0008-0011], [0021] Limitations depend on the satellites and GEE data, not the claimed invention.)
Response to Arguments
Applicant’s arguments, see Page 14, filed 12/11/2025, with respect to the objection to the claims and specification have been fully considered and are persuasive. The objection to the claims and specification has been withdrawn.
Applicant’s arguments, see Pages 20-21, filed 12/11/2025, with respect to the rejection under 35 U.S.C. § 112(b) have been fully considered and are persuasive. The rejection under 35 U.S.C. § 112(b) has been withdrawn.
Applicant’s arguments, see Pages 14-17, filed 12/11/2025, with respect to the rejection under 35 U.S.C. § 101 have been fully considered and are not persuasive. Applicant argues that the claims are not directed to an abstract idea and as a whole constitute an improvement in technology. The examiner disagrees, the claims simply mention “monitoring” (only in Claim 1) and then describe a mathematical process that can be fully conducted using GEE. This process does not improve any specific technology but merely points to the abstract idea that this information can be calculated using data (e.g. cloud services).
Applicant’s arguments, see Pages 17-20, filed 12/11/2025, with respect to the rejection under 35 U.S.C. § 112(a) have been fully considered and are not persuasive. Applicant argues that “the specification provides ample, detailed, and enabling disclosure that teaches one skilled in the art precisely how the classification algorithm is implemented to determine the water area sequence”. The examiner points out that this teaching is not what lacks descriptive support. Specifically, “the classification algorithm comprising a random forest (RF) algorithm” is what lacks descriptive support. Combining algorithms is a very complicated process and involves detailed steps to allow one algorithm to work with another.
Applicant’s arguments, see Pages 21-24, filed 12/11/2025, with respect to the rejection under 35 U.S.C. § 102 have been fully considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. The claims are now rejected under 35 U.S.C. § 103. Applicant argues for specific features that are already provided by satellite data and GEE and are well understood by PHOSITA. The amended claims are now rejected by the combination of Cheng and Schneider to show that through GEE the water level, water area, and water volume are obvious and provided measurements that can be obtained in any order without increasing computational complexity. Cheng’s flow measurements are further implementations of water level, slope, and water breadth. Under BRI, water level may include dead storage or dead storage in addition to water level would be an obvious calculation to arrive at a water storage sequence or water level-water storage relationship curve when considering the data provided by GEE.
Applicant’s arguments, see Pages 24-26, filed 12/11/2025, with respect to the rejection under 35 U.S.C. § 103 have been fully considered and are not persuasive. Applicant argues that the dependent claims are allowable due to the dependency on Claim 1. The examiner disagrees due to the above-mentioned rejections.
Applicant's remaining arguments amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims is understandable and distinguishable from other inventions.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's
disclosure or directed to the state of art is listed on the enclosed PTO-892.
The following is a brief description for relevant prior art that was cited but not applied:
Tian (US20220092306) describes a cloud platform-based method that includes Google Earth Engine for active and passive sensing.
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/BRANDON JAMES HENSON/Examiner, Art Unit 3645
/ROBERT W HODGE/Supervisory Patent Examiner, Art Unit 3645