DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1, 3-4, 6-7, 9, 13-15 and 17-24 are pending in the application. Claims 1, 3, 15 and 17-22 have been amended, claims 2, 5, 8, 10-12 and 16 have been canceled, and claims 23-24 have been added.
Response to Arguments
Applicant’s arguments filed 7/29/26 have been fully considered. The arguments with respect to “temporally spaced points of time” in view of amended limitation “wherein each of the plurality of first images of the target area is substantially of a common geographic area”, are persuasive. A new search has been conducted and rejection to pending claims has been updated.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 4, 7, 15, 19-21 and 23-24 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by ISHIDA et al. (JP2021006017A, published 2021-01-21, hereafter ISHIDA).
As per claim 1, ISHIDA teaches a data acquisition apparatus (FIG. 1), comprising at least one processor (FIG. 1 #101 “CPU”; para. [0025]), wherein:
the at least one processor acquires a plurality of first image data including a plurality of first images of a target area from a satellite at a plurality of temporally spaced points of time, wherein each of the plurality of first images of the target area is substantially of a common geographic area (FIG. 1 #110; para. [0030] “The satellite image data 110 is time-series image data, and is, for example, a color still image taken by an earth observation satellite 140 or the like. The photographing range of the satellite image data 110 includes an area (hereinafter referred to as “target area”) in which a field to be grasped for grasping the growth state of crops exists”; para. [0036] “The satellite image data 110 is an image obtained by continuously and regularly photographing the target area by, for example, the earth observation satellite 140”; FIG. 2);
the at least one processor individually calculates vegetation indexes at the plurality of temporally spaced points of time of the target area by using the plurality of first image data (See below);
the at least one processor determines whether statistics of the vegetation indexes at the plurality of temporally spaced points of time of the target area satisfies a predetermined evaluation criterion (As shown in FIG. 5, S502 , S503 and S504 represents “reference date estimation process”, “growth prediction process” and “shooting optimum time determination process” respectively. Specifically, ISHIDA first estimates a reference date, which is a date used for predicting the growth status of crops based on a first image data, then predicts the growth condition of the crop after the reference date is predicted based on the meteorological data which is the time series data, and lastly estimates the time when the crop reaches a specific growth stage, such as an optimum shooting time (FIG. 5 S502-S504; para. [0012]). In the step S502 for estimating a reference date, the vegetation index value in each target field area is calculated based on each of the read satellite images (FIG. 6 S604). The reference date for grasping the growth status of the target crop is estimated from the time change of the vegetation index value obtained in each target field area (FIG. 6 S605) (para. [0060]; para. [0062]-[0063]). That is to say ISHIDA uses the time change of the vegetation index value obtained in each target field area (i.e., statistics) to determine the growth status of the target crop, and based on the growth status to determine the reference date; para. [0065] “In general, the growth status and yield of agricultural products cultivated in fields such as paddy rice, wheat, and soybean are estimated and predicted using the date of sowing, planting, and transplantation, or the date of heading as the reference date”; That says the date of sowing, planting, and transplantation, or the date of heading is estimated using the change of vegetation index. Therefore the time change of the vegetation index value should/should not satisfy a predetermined evaluation criterion in order to distinguish the reference date.); and
the at least one processor acquires second image data including a second image obtained by photographing the target area at a higher resolution than a resolution of the plurality of first images if the statistics of the vegetation indexes at the plurality of temporally spaced points of time of the target area do not satisfy the predetermined evaluation criterion, wherein the second image is within at least a portion of the common geographic area as each of the plurality of first images (para. [0054], [0056], [0055] “Since the (second) remote sensing image taken by the earth observation satellite 140 affects the accuracy obtained by the growth situation analysis, it was used in the reference date estimation process S502 when the analysis was desired to be performed with high accuracy (first). It is desirable to have higher definition than the remote sensing image”; FIG. 5 S505).
As per claim 4, dependent upon claim 1, ISHIDA teaches wherein the at least one processor outputs the second image data (ISHIDA FIG. 5 S505, S506).
As per claim 7, dependent upon claim 1, ISHIDA teaches wherein: the at least one processor analyzes the second image data to generate analysis; and the at least one processor outputs a result of the analysis (ISHIDA FIG. 5 S506; para. [0077]).
As per claim 15, dependent upon claim 1, ISHIDA teaches wherein the at least one processor designates a resolution of the second image in accordance with the vegetation indexes at the plurality of temporally spaced points of time (ISHIDA para. [0055] “Since the (second) remote sensing image taken by the earth observation satellite 140 affects the accuracy obtained by the growth situation analysis, it was used in the reference date estimation process S502 when the analysis was desired to be performed with high accuracy (first). It is desirable to have higher definition than the remote sensing image”; para. [0063] “In S605, the growth status of the target crop is analyzed from the time change of the vegetation index value calculated in S604, and the reference date for grasping the growth status is estimated”).
Claim 19, an independent method claim, recites steps corresponding to the steps recited in claim 1. Therefore, the recited elements of this claim are mapped to ISHIDA in the same manner as the corresponding steps in its corresponding apparatus claim, claim 1.
Claim 20, an independent medium claim, recites steps corresponding to the steps recited in claim 1. Claim 20 further recites medium and computer. Therefore, the recited elements of this claim are mapped to ISHIDA in the same manner as the corresponding steps and computer components in its corresponding apparatus claim, claim 1.
As per claim 21, dependent upon claim 1, ISHIDA teaches wherein the at least one processor sets the predetermined evaluation criterion based on a track record of the vegetation indexes at the plurality of temporally spaced points of time (ISHIDA para. [0060] “The reference date for grasping the growth status of the target crop is estimated from the time change of the vegetation index value obtained in each target field area (S605)”; para. [0063] “In S605, the growth status of the target crop is analyzed from the time change of the vegetation index value calculated in S604, and the reference date for grasping the growth status is estimated”).
As per claim 23, dependent upon claim 1, ISHIDA teaches wherein the second image is acquired from at least one of an airplane or a drone (ISHIDA para. [0081] “Since the resolution or capture range of images varies depending on the specifications of equipment such as artificial satellites used when acquiring remote sensing images, when using aerial photographs or high-resolution satellite images acquired by aircraft or drones, it is necessary to use field units”).
As per claim 24, dependent upon claim 1, ISHIDA teaches wherein: the satellite is a first satellite; and the second image is acquired from at least one of the first satellite or a second satellite (para. [0054] “In the remote sensing image capturing process S505, the earth observation satellite 140 captures a remote sensing image of the target area. An operator of the earth observation satellite 140 (hereinafter referred to as "observation satellite operator") separately gives an instruction for photographing the earth observation satellite 140”; para. [0056] “The (second) remote sensing image may be acquired by the same equipment as the equipment that acquired the (first) remote sensing image, or may be acquired by a different equipment. For example, the (first) remote sensing image is an image acquired by the first earth observation satellite 140-1, and the (second) remote sensing image is a second image different from the first earth observation satellite 140-1. It may be an image acquired by the earth observation satellite 140-2”).
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 3, 6, 9, 17 and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over ISHIDA et al. (JP2021006017A, published 2021-01-21, hereafter ISHIDA), in view of Wheeler et al. (US 11,308,595 B1, hereafter Wheeler).
As per claim 3, ISHIDA teaches using the statistics of the vegetation indexes at the plurality of temporally spaced points of time of the target area (para. [0060], [0063]), but does not teach the statistics of the vegetation indexes is a maximum value of the vegetation indexes.
Wheeler in an analogous field discloses a method of detecting thermal anomaly in satellite imagery (Abstract; FIG. 8A; col. 17 ln 44-54). The method includes generating a composite image of an area using data associated with each of the “best” pixels from a sequence of images covering the area. The “best” pixel can be considered the one in a set (e.g., a time series) for which given spectral information associated with that pixel was least obscured by atmospheric obstruction. For example, NDVI value associated with a pixel can be used to select the best pixel in a time series (col. 17 ln 54-col. 18 ln 8). Specifically, Wheeler teaches the statistics of the vegetation indexes is a maximum value of the vegetation indexes at the plurality of temporally spaced points of time of the target area (Wheeler FIG. 10; col. 19 ln 36-63).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of ISHIDA to incorporate the teaching of Wheeler to use the maximum value of the vegetation indexes at the plurality of temporally spaced points of time of the target area as a statistics. Doing so would allow the best pixel in a time series for which given spectral information associated with that pixel was least obscured by atmospheric obstruction to be selected as recognized by Wheeler (col. 3 ln 50 -col. 4 ln 9).
Claim 6, dependent upon claim 3, is rejected as applied to claim 4 above.
Claim 9, dependent upon claim 3, is rejected as applied to claim 7 above.
Claim 17, dependent upon claim 3, is rejected as applied to claim 15 above.
Claim 22, dependent upon claim 3, is rejected as applied to claim 21 above.
Claims 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over ISHIDA et al. (JP2021006017A, published 2021-01-21, hereafter ISHIDA), as applied above to claim 1, in view of Kelly et al. (US Publication 2024/0407288 A1, hereafter Kelly).
As per claim 13, ISHIDA does not teach the recited limitations.
Kelly in an analogous field discloses a system for monitoring vegetation health in a garden (Abstract). Specifically, vegetation index, such as NDVI, is calculated using captured image data (para. [0004]). The vegetation index is compared with a threshold to determine if a pruning activity should be performed. The threshold can be determined by various methods. For example, it is conceivable that the specific threshold value for the vegetation index for carrying out the pruning activity is determined by means of the machine learning method and/or the machine learning system (para. [0061]). Kelly further discloses environmental data acquisition unit (FIG. 1; para. [0012]) for acquiring environmental data associated with a garden area in which image data is acquired, such as a temperature, an air pressure, a humidity, a brightness, a light intensity, an irradiated energy etc. (FIG. 1; para. [0007]). Kelly further teaches training the machine learning system by using a plurality of values of the vegetation index from a plurality of different garden areas and/or from a plurality of different gardens, as well as a plurality of values for each environmental parameter (para. [0135]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of ISHIDA to incorporate the teaching of Kelly to set the evaluation criterion by using the environmental data. Doing so would allow measures to maintain the vegetation's health can be adapted precisely and specifically to the environment as recognized by Kelly (para.[0020]).
Claim 14, dependent upon claim 13, ISHIDA in view of Kelly teaches setting the evaluation criterion by using a learning model that is machine-learned such that the evaluation criterion is output in response to inputting the environmental data (Kelly in an analogous field discloses a system for monitoring vegetation health in a garden (Abstract). Specifically, vegetation index, such as NDVI, is calculated using captured image data (para. [0004]). The vegetation index is compared with a threshold to determine if a pruning activity should be performed. The threshold can be determined by various methods. For example, it is conceivable that the specific threshold value for the vegetation index for carrying out the pruning activity is determined by means of the machine learning method and/or the machine learning system (para. [0061]). Kelly further discloses environmental data acquisition unit (FIG. 1; para. [0012]) for acquiring environmental data associated with a garden area in which image data is acquired, such as a temperature, an air pressure, a humidity, a brightness, a light intensity, an irradiated energy etc. (FIG. 1; para. [0007]). Kelly further teaches training the machine learning system by using a plurality of values of the vegetation index from a plurality of different garden areas and/or from a plurality of different gardens, as well as a plurality of values for each environmental parameter (para. [0135])).
Claim 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over ISHIDA et al. (JP2021006017A, published 2021-01-21, hereafter ISHIDA), as applied above to claim 15, in view of DVIR et al. (US 20190073534 A1, hereafter DVIR).
As per claim 18, ISHIDA does not teach the recited limitation.
DVIR in an analogous field discloses a method for multi-spectral imagery acquisition and analysis. The method including capturing preliminary multi-spectral aerial images according to pre-defined survey parameters at a pre-selected resolution, automatically performing preliminary analysis on site or location in the field using large scale blob partitioning of the captured images in real or near real time, detecting irregularities within the pre-defined survey parameters and providing an output corresponding thereto, and determining, from the preliminary analysis output, whether to perform a second stage of image acquisition and analysis at a higher resolution than the pre-selected resolution (Abstract). Specifically, DVIR teaches automatically directing the same aerial vehicle or another vehicle with an image capturing device to these areas of interest, directing it to take detailed (higher resolution) imagery according to the survey type. Typically, the criteria directing the platform to perform high resolution acquisition will be the presence of blobs that are associated with NDVI values 10% or 20% lower than the optimal NDVI value—i.e., an indication of “vegetation stress”. See para. [0066].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of ISHIDA to incorporate the teaching of DVIR to designate a resolution of the second image based on a difference between the vegetation indexes at the plurality of temporally spaced points of time and the predetermined evaluation criterion. Doing so would allow performing fast and practical scanning of the environment/fields where possible in real time or near real time, while “focusing” in high resolution imagery on blobs of interest and identifying, as accurately as possible, as recognized by DVIR (para.[0043]).
Conclusion
Prior art searched but not cited is recorded in PTO-892.
Additional prior art NAKAGAWA et al. (US 20210174080 A1) discloses an apparatus for image processing (Abstract). Crop image acquisition unit acquires an image of a crop region shot by drone. Index calculation unit calculates an index indicating growth conditions of a crop shot in the image based on the acquired image of the crop region. Flight instruction unit instructs, if a portion (low index region) regarding which the calculated index is less than a predetermined index threshold is present in the crop region, drone to shoot the low index region while increasing the resolution of the image. Specifically, flight instruction unit makes an instruction to shoot the portion while performing a low-altitude flight at an altitude lower than that when the image regarding which the index of the low index region has been calculated has been shot. See Abstract; FIG. 4-5, 10-17; para. [0092]-[0097].
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to XUEMEI G CHEN whose telephone number is (571)270-3480. The examiner can normally be reached Monday-Friday 9am-6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John M Villecco can be reached at (571) 272-7319. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/XUEMEI G CHEN/Primary Examiner, Art Unit 2661
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